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  1. 4 points
    geemap is a Python package for interactive mapping with Google Earth Engine (GEE), which is a cloud computing platform with a multi-petabyte catalog of satellite imagery and geospatial datasets. During the past few years, GEE has become very popular in the geospatial community and it has empowered numerous environmental applications at local, regional, and global scales. GEE provides both JavaScript and Python APIs for making computational requests to the Earth Engine servers. Compared with the comprehensive documentation and interactive IDE (i.e., GEE JavaScript Code Editor) of the GEE JavaScript API, the GEE Python API lacks good documentation and functionality for visualizing results interactively. The geemap Python package is created to fill this gap. It is built upon ipyleaflet and ipywidgets, enabling GEE users to analyze and visualize Earth Engine datasets interactively with Jupyter notebooks. geemap is intended for students and researchers, who would like to utilize the Python ecosystem of diverse libraries and tools to explore Google Earth Engine. It is also designed for existing GEE users who would like to transition from the GEE JavaScript API to Python API. The automated JavaScript-to-Python conversion module of the geemap package can greatly reduce the time needed to convert existing GEE JavaScripts to Python scripts and Jupyter notebooks. For video tutorials and notebook examples, please visit https://github.com/giswqs/geemap/tree/master/examples. For complete documentation on geemap modules and methods, please visit https://geemap.readthedocs.io/en/latest/source/geemap.html. Features Below is a partial list of features available for the geemap package. Please check the examples page for notebook examples, GIF animations, and video tutorials. Automated conversion from Earth Engine JavaScripts to Python scripts and Jupyter notebooks. Displaying Earth Engine data layers for interactive mapping. Supporting Earth Engine JavaScript API-styled functions in Python, such as Map.addLayer(), Map.setCenter(), Map.centerObject(), Map.setOptions(). Creating split-panel maps with Earth Engine data. Retrieving Earth Engine data interactively using the Inspector Tool. Interactive plotting of Earth Engine data by simply clicking on the map. Converting data format between GeoJSON and Earth Engine. Using drawing tools to interact with Earth Engine data. Using shapefiles with Earth Engine without having to upload data to one's GEE account. Exporting Earth Engine FeatureCollection to other formats (i.e., shp, csv, json, kml, kmz) using only one line of code. Exporting Earth Engine Image and ImageCollection as GeoTIFF. Extracting pixels from an Earth Engine Image into a 3D numpy array. Calculating zonal statistics by group (e.g., calculating land over composition of each state/country). Adding a customized legend for Earth Engine data. Converting Earth Engine JavaScripts to Python code directly within Jupyter notebook. Adding animated text to GIF images generated from Earth Engine data. Adding colorbar and images to GIF animations generated from Earth Engine data. Creating Landsat timelapse animations with animated text using Earth Engine. Searching places and datasets from Earth Engine Data Catalog. Using timeseries inspector to visualize landscape changes over time. Exporting Earth Engine maps as HTML files and PNG images. Searching Earth Engine API documentation within Jupyter notebooks. Installation To use geemap, you must first sign up for a Google Earth Engine account. geemap is available on PyPI. To install geemap, run this command in your terminal: pip install geemap geemap is also available on conda-forge. If you have Anaconda or Miniconda installed on your computer, you can create a conda Python environment to install geemap: conda create -n gee python conda activate gee conda install -c conda-forge geemap If you have installed geemap before and want to upgrade to the latest version, you can run the following command in your terminal: pip install -U geemap If you use conda, you can update geemap to the latest version by running the following command in your terminal: conda update -c conda-forge geemap Usage Important note: A key difference between ipyleaflet and folium is that ipyleaflet is built upon ipywidgets and allows bidirectional communication between the front-end and the backend enabling the use of the map to capture user input, while folium is meant for displaying static data only (source). Note that Google Colab currently does not support ipyleaflet (source). Therefore, if you are using geemap with Google Colab, you should use import geemap.eefolium. If you are using geemap with binder or a local Jupyter notebook server, you can use import geemap, which provides more functionalities for capturing user input (e.g., mouse-clicking and moving). Youtube tutorial videos GitHub page of geemap Documentation While working on a small project I found this. This is a quite new library, some features shown in the tutorial may not work as intended but overall a very good package. The tools make the code much cleaner and readable. Searching EE docs from notebook is not yet implemented. Check out the youtube channel, it's great.
  2. 3 points
    It was just announced that June was the 3rd hottest on record, Johns Hopkins put the number of COVID-19 cases at 13-million, and over 300,000 sq km of protected areas were created last month. These are all indicators of the planet’s vitality, but traditionally you’d need to bookmark three different websites to keep track of these and other metrics. In partnership with Microsoft, National Geographic, and the United Nations Sustainable Development Solutions Network, Esri is gathering these and other topics into the ArcGIS Living Atlas Indicators of the Planet (Beta). Leveraging the near real-time information already contributed to Living Atlas by organizations such as NOAA, UN Environment Programme, and US Geological Survey, ArcGIS Living Atlas Indicators of the Planet draws upon authoritative sources for the latest updates on 18 topics, with more being developed. In addition to the summary statistics provided by the GeoCards, there are a series of maps and resources to better understand each issue and learn how to integrate timely data into decision making, along with stories on progress towards building a sustainable planet. ArcGIS Living Atlas Indicators of the Planet was developed using ArcGIS Experience Builder and is in its Beta release while additional capabilities are being implemented. This Experience Builder template can be customized for your own topics of interest. All of the underlying layers, maps, and apps are available from this Content Group. link: https://experience.arcgis.com/experience/003f05cc447b46dc8818640c38b69b83
  3. 3 points
    A Long March-2D carrier rocket, carrying the Gaofen-9 04 satellite, is launched from the Jiuquan Satellite Launch Center in northwest China, Aug. 6, 2020. China successfully launched a new optical remote-sensing satellite from the Jiuquan Satellite Launch Center at 12:01 p.m. Thursday (Beijing Time). (Photo by Wang Jiangbo/Xinhua) JIUQUAN, Aug. 6 (Xinhua) -- China successfully launched a new optical remote-sensing satellite from the Jiuquan Satellite Launch Center in northwest China at 12:01 p.m. Thursday (Beijing Time). The satellite, Gaofen-9 04, was sent into orbit by a Long March-2D carrier rocket. It has a resolution up to the sub-meter level. The satellite will be mainly used for land surveys, city planning, land right confirmation, road network design, crop yield estimation and disaster prevention and mitigation. It will also provide information for the development of the Belt and Road Initiative. The same carrier rocket also sent the Gravity & Atmosphere Scientific Satellite (Q-SAT) into space. The Q-SAT satellite, developed by Tsinghua University, will help with the satellite system design approach and orbital atmospheric density measurement, among others. Thursday's launch was the 342nd mission of the Long March rocket series. source: http://www.xinhuanet.com/english/2020-08/06/c_139269788.htm
  4. 3 points
    Our objective is to provide the scientific and civil communities with a state-of-the-art global digital elevation model (DEM) derived from a combination of Shuttle Radar Topography Mission (SRTM) processing improvements, elevation control, void-filling and merging with data unavailable at the time of the original SRTM production: NASA SRTM DEMs created with processing improvements at full resolution NASA's Ice, Cloud,and land Elevation Satellite (ICESat)/Geoscience Laser Altimeter (GLAS) surface elevation measurements DEM cells derived from stereo optical methods using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data from the Terra satellite Global DEM (GDEM) ASTER products developed for NASA and the Ministry of Economy, Trade and Industry of Japan by Sensor Information Laboratory Corp National Elevation Data for US and Mexico produced by the USGS Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010) developed by the USGS and the National Geospatial-Intelligence Agency (NGA) Canadian Digital Elevation Data produced by Natural Resources Canada We propose a significant modernization of the publicly- and freely-available DEM data. Accurate surface elevation information is a critical component in scientific research and commercial and military applications. The current SRTM DEM product is the most intensely downloaded dataset in NASA history. However, the original Memorandum of Understanding (MOU) between NASA and NGA has a number of restrictions and limitations; the original full resolution, one-arcsecond data are currently only available over the US and the error, backscatter and coherence layers were not released to the public. With the recent expiration of the MOU, we propose to reprocess the original SRTM raw radar data using improved algorithms and incorporating ancillary data that were unavailable during the original SRTM processing, and to produce and publicly release a void-free global one-arcsecond (~30m) DEM and error map, with the spacing supported by the full-resolution SRTM data. We will reprocess the entire SRTM dataset from raw sensor measurements with validated improvements to the original processing algorithms. We will incorporate GLAS data to remove artifacts at the optimal step in the SRTM processing chain. We will merge the improved SRTM strip DEMs, refined ASTER and GDEM V2 DEMs, and GLAS data using the SRTM mosaic software to create a seamless, void-filled NASADEM. In addition, we will provide several new data layers not publicly available from the original SRTM processing: interferometric coherence, radar backscatter, radar incidence angle to enable radiometric correction, and a radar backscatter image mosaic to be used as a layer for global classification of land cover and land use. This work leverages an FY12 $1M investment from NASA to make several improvements to the original algorithms. We validated our results with the original SRTM products and ancillary elevation information at a few study sites. Our approach will merge the reprocessed SRTM data with the DEM void-filling strategy developed during NASA's Making Earth System Data Records for Use in Research Environments (MEaSUREs) 2006 project, "The Definitive Merged Global Digital Topographic Data Set" of Co-Investigator Kobrick. NASADEM is a significant improvement over the available three-arcsecond SRTM DEM primarily because it will provide a global DEM and associated products at one-arcsecond spacing. ASTER GDEM is available at one-arcsecond spacing but has true spatial resolution generally inferior to SRTM one-arcsecond data and has much greater noise problems that are particularly severe in tropical (cloudy) areas. At one-arcsecond, NASADEM will be superior to GDEM across almost all SRTM coverage areas, but will integrate GDEM and other data to extend the coverage. Meanwhile, DEMs from the Deutsches Zentrum für Luft- und Raumfahrt Tandem-X mission are being developed as part of a public-private partnership. However, these data must be purchased and are not redistributable. NASADEM will be the finest resolution, global, freely-available DEM products for the foreseeable future. data page: https://lpdaac.usgs.gov/products/nasadem_hgtv001/ news links: https://earthdata.nasa.gov/esds/competitive-programs/measures/nasadem
  5. 3 points
    A new set of 10 ArcGIS Pro lessons empowers GIS practitioners, instructors, and students with essential skills to find, acquire, format, and analyze public domain spatial data to make decisions. Described in this video, this set was created for 3 reasons: (1) to provide a set of analytical lessons that can be immediately used, (2) to update the original 10 lessons created by my colleague Jill Clark and I to provide a practical component to our Esri Press book The GIS Guide to Public Domain Data, and (3) to demonstrate how ArcGIS Desktop (ArcMap) lessons can be converted to Pro and to reflect upon that process. The activities can be found here. This essay is mirrored on the Esri GeoNet education blog and the reflections are below and in this video. Summary of Lessons: Can be used in full, in part, or modified to suit your own needs. 10 lessons. 64 work packages. A “work package” is a set of tasks focused on solving a specific problem. 370 guided steps. 29 to 42 hours of hands-on immersion. Over 600 pages of content. 100 skills are fostered, covering GIS tools and methods, working with data, and communication. 40 data sources are used, covering 85 different data layers. Themes covered: climate, business, population, fire, floods, hurricanes, land use, sustainability, ecotourism, invasive species, oil spills, volcanoes, earthquakes, agriculture. Areas covered: The Globe, and also: Brazil, New Zealand, the Great Lakes of the USA, Canada, the Gulf of Mexico, Iceland, the Caribbean Sea, Kenya, Orange County California, Nebraska, Colorado, and Texas USA. Aimed at university-level graduate and university or community college undergraduate student. Some GIS experience is very helpful, though not absolutely required. Still, my advice is not to use these lessons for students’ first exposure to GIS, but rather, in an intermediate or advanced setting. How to access the lessons: The ideal way to work through the lessons is in a Learn Path which bundle the readings of the book’s chapters, selected blog essays, and the hands-on activities.. The Learn Path is split into 3 parts, as follows: Solving Problems with GIS and public domain geospatial data 1 of 3: Learn how to find, evaluate, and analyze data to solve location-based problems through this set of 10 chapters and short essay readings, and 10 hands-on lessons: https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path/ Solving Problems with GIS and public domain geospatial data 2 of 3: https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path-2/ Solving Problems with GIS and public domain geospatial data 3 of 3: https://learn.arcgis.com/en/paths/the-gis-guide-to-public-domain-data-learn-path-3/ The Learn Paths allow for content to be worked through in sequence, as shown below: You can also access the lessons by accessing this gallery in ArcGIS Online, shown below. If you would like to modify the lessons for your own use, feel free! This is why the lessons have been provided in a zipped bundle as PDF files here and as MS Word DOCX files here. This video provides an overview. source: https://spatialreserves.wordpress.com/2020/05/14/10-new-arcgis-pro-lesson-activities-learn-paths-and-migration-reflections/
  6. 3 points
    the satellites from planet can now take imagery at 50cm, they changed their orbit in order to achieve better GSD SKYSAT IMAGERY NOW AVAILABLE Bring agility to your organization with the latest advancements in high-resolution SkySat imagery, available today. Make targeted decisions in ever-changing operational contexts with improved 50 cm spatial resolution and more transparency in the ordering process with the new Tasking Dashboard.
  7. 3 points
    Interesting application of WebGIS to plot Dinosaur database, and you can search how is your place in the past on the interactive globe Map. Welcome to the internet's largest dinosaur database. Check out a random dinosaur, search for one below, or look at our interactive globe of ancient Earth! Whether you are a kid, student, or teacher, you'll find a rich set of dinosaur names, pictures, and facts here. This site is built with PaleoDB, a scientific database assembled by hundreds of paleontologists over the past two decades. check this interactive webgis apps: https://dinosaurpictures.org/ancient-earth#170 official link: https://dinosaurpictures.org/
  8. 3 points
    link: https://press.anu.edu.au/publications/new-releases
  9. 3 points
    Interesting video on How Tos: WebOpenDroneMap is a friendly Graphical User Interfase (GUI) of OpenDroneMap. It enhances the capabilities of OpenDroneMap by providing a easy tool for processing drone imagery with bottoms, process status bars, and a new way to store images. WebODM allows to work by projects, so the user can create different projects and process the related images. As a whole, WebODM in Windows is a implementation of PostgresSQL, Node, Django and OpenDroneMap and Docker. The software instalation requires 6gb of disk space plus Docker. It seem huge but it is the only way to process drone imagery in Windows using just open source software. We definitely see a huge potential of WebODM for the image processing, therefore we have done this tutorial for the installation and we will post more tutorial for the application of WebODM with drone images. For this tutorial you need Docker Toolbox installed on your computer. You can follow this tutorial to get Docker on your pc: https://www.hatarilabs.com/ih-en/tutorial-installing-docker You can visit the WebODM site on GitHub: https://github.com/OpenDroneMap/WebODM Videos The tutorial was split in three short videos. Part 1 https://www.youtube.com/watch?v=AsMSoWAToxE Part 2 https://www.youtube.com/watch?v=8GKx3fz0qgE Part 3 https://www.youtube.com/watch?v=eCZFzaXyMmA
  10. 3 points
    7th International Conference on Computer Science and Information Technology (CoSIT 2020) January 25 ~ 26, 2020, Zurich, Switzerland https://cosit2020.org/ Scope & Topics 7th International Conference on Computer Science and Information Technology (CoSIT 2020) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Conference looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe · Geographical Information Systems/ Global Navigation Satellite Systems (GIS/GNSS) Paper Submission Authors are invited to submit papers through the conference Submission system. Here’s where you can reach us : [email protected] or [email protected]
  11. 3 points
    Details geological-geophysical aspects of groundwater treatment Discusses regulatory legislations regarding groundwater utilization Serves as a reference material for scientists in geology, geophysics and environmental studies
  12. 2 points
    hello everyone, I'm a long time user of arcmap and already two years ago on my computer I installed arcgis pro... now I don't know for you but I'm postponing for years the real switch between versions and I'm still on arcmap... this because it seems to me that even if the expectations were very high, arcgis pro still doesn't seem to have that much declaimed performance. In particular, I'm concerned about the fact that for every little thing, it starts a geoprocessing that lasts between seconds and minutes, then for each function is a maze of menus and submenus where at the end I don't know where they are anymore. and I don't know for you, but it seems to me that "pro" is just an advertising program to convince even those who are not professionals to make maps, this even if they don't understand technically what they did.
  13. 2 points
    Tracing is better in ArcGIS Pro, but Cut Polygon cannot be done in ArcGIS Pro, only in ArcMap Dekstop
  14. 2 points
    what's really frustrating it's that esri still has his "standard response" every time I try to address an issue : - do you have the last version? (and of course in a big company you simply don't get the last last last patch at +1minute after the release > so this will be for them the solution nr. one. > and of course it will never change anything) .. then... The following question will be "can you send me a copy of your system configuration ?" (and of course they will find a way to say that your hardware it's "old" even if it does comply to all the requirements) - I'm pretty sure you have an installation issue.. please reinstall (so you have to get another problem with your IT department) VERY FRUSTRATING I'm in business since a while and every time those guys comes with the best solution for you I have an alarm bell going on.. * it will be a 64 bit solution (can you remember those bull****?), so better then arcmap and as always it doesnt make a little difference.. * it's 2D and 3D in one only software (but did they mention to you that you will need some extra licences? not to me). so basically.. I LOVE QGIS ! 😍😍😍
  15. 2 points
    until they fix the performance issue, i dont see any advantages on ArcGIS Pro.... I still can use ArcGIS desktop for the daily task, no need to use fancy latest product
  16. 2 points
    A joint NASA-USGS initiative has created the first worldwide map of the causes of change in mangrove habitats between 2000 and 2016. Mangrove trees can be found growing in the salty mud along the Earth’s tropical and subtropical coastlines. Mangroves are vital to aquatic ecosystems due to their ability to prevent soil erosion and store carbon. Mangroves also provide critical habitat to multiple marine species such as algae, barnacles, oysters, sponges, shrimp, crabs, and lobsters. Mangroves are threatened by both human and natural causes. Human activities in the form of farming and aquaculture and natural stressors such as erosion and extreme weather have both driven mangrove habitat loss. The joint study analyzed over one million Landsat images captured between 2000 and 2016 to create the first-ever global map visualizing the drivers of mangrove loss. Causes of mangrove loss were mapped at a resolution of 30 meters. Researchers found that 62% of mangrove loss during the time period studied was due to land use changes, mostly from conversion to aquaculture and agriculture. Roughly 80% of the loss was concentrated in six Southeast Asian nations: Indonesia, Myanmar, Malaysia, the Philippines, Thailand, and Vietnam. Mangrove loss due to human activities did decline 73% between 2000 and 2016. Mangrove loss due to natural events also decreased but at a lessor rate than human-led activities. Map and graphs showing global distribution of mangrove loss and its drivers. From the study: “(a) The longitudinal distribution of total mangrove loss and the relative contribution of its primary drivers. Different colors represent unique drivers of mangrove loss. (b) The latitudinal distribution of total mangrove loss and the relative contribution of its primary drivers. (c‐g) Global distribution of mangrove loss and associated drivers from 2000 to 2016 at 1°×1° resolution, with the relative contribution (percentage) of primary drivers per continent: (c) North America, (d) South America, (e) Africa, (f) Asia, (g) Australia together with Oceania.” links: https://www.mangrovelossdrivers.app/
  17. 2 points
    The St. Patrick Bay ice caps on the Hazen Plateau of northeastern Ellesmere Island in Nunavut, Canada, have disappeared, according to NASA satellite imagery. National Snow and Ice Data Center (NSIDC) scientists and colleagues predicted via a 2017 paper in The Cryosphere that the ice caps would melt out completely within the next five years, and recent images from NASA's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) have confirmed that this prediction was accurate. Mark Serreze, director of NSIDC, Distinguished Professor of Geography at the University of Colorado Boulder, and lead author on the paper, first set foot on the St. Patrick Bay ice caps in 1982 as a young graduate student. He visited the ice caps with his advisor, Ray Bradley, of the University of Massachusetts. "When I first visited those ice caps, they seemed like such a permanent fixture of the landscape," said Serreze. "To watch them die in less than 40 years just blows me away." In 2017, scientists compared ASTER satellite data from July 2015 to vertical aerial photographs taken in August of 1959. They found that between 1959 and 2015, the ice caps had been reduced to only five percent of their former area, and shrank noticeably between 2014 and 2015 in response to the especially warm summer in 2015. The ice caps are absent from ASTER images taken on July 14, 2020. The St. Patrick Bay ice caps were one-half of a group of small ice caps on the Hazen Plateau, which formed and likely attained their maximum extents during the Little Ice Age, perhaps several centuries ago. The Murray and Simmons ice caps, which make up the second half of the Hazen Plateau ice caps, are located at a higher elevation and are therefore faring better, though scientists predict that their demise is imminent as well. "We've long known that as climate change takes hold, the effects would be especially pronounced in the Arctic," said Serreze. "But the death of those two little caps that I once knew so well has made climate change very personal. All that's left are some photographs and a lot of memories." source: https://phys.org/news/2020-07-canadian-ice-caps-scientific.html
  18. 2 points
    Scientists have discovered new evidence for active volcanism next door to some of the most densely populated areas of Europe. The study crowdsourced GPS monitoring data from antennae across western Europe to track subtle movements in the Earth’s surface, thought to be caused by a rising subsurface mantle plume. The Eifel region lies roughly between the cities of Aachen, Trier and Koblenz, in west-central Germany. It is home to many ancient volcanic features, including the circular lakes known as maars. Maars are the remnants of violent volcanic eruptions, such as the one that created Laacher See, the largest lake in the area. The explosion that created the lake is thought to have occurred around 13,000 years ago. The mantle plume that fed this ancient activity is thought to still be present, extending up to 400 kilometers (km) into the earth. However, whether or not it is still active is unknown. “Most scientists had assumed that volcanic activity in the Eifel was a thing of the past,” said Corné Kreemer, lead author of the new study. “But connecting the dots, it seems clear that something is brewing underneath the heart of northwest Europe.” In the new study, the team — based at the University of Nevada, Reno and the University of California, Los Angeles — used data from thousands of commercial and state-owned GPS stations all over western Europe. The research revealed that the region’s land surface is moving upward and outward over a large area centered on the Eifel, and including Luxembourg, eastern Belgium and the southernmost province of the Netherlands, Limburg. “The Eifel area is the only region in the study where the ground motion appeared significantly greater than expected,” said Kreemer. “The results indicate that a rising plume could explain the observed patterns and rate of ground movement.” The new results complement those of a previous study in Geophysical Journal International that found seismic evidence of magma moving underneath the Laacher See. Both studies point towards the Eifel being an active volcanic system. The implication of this study is that there may not only be an increased volcanic risk, but also a long-term seismic risk in this part of Europe. The researchers urge caution, however. “This does not mean that an explosion or earthquake is imminent, or even possible again in this area. We and other scientists plan to continue monitoring the area using a variety of geophysical and geochemical techniques, to better understand and quantify any potential risks.” source: https://doi.org/10.1093/gji/ggaa227
  19. 2 points
    Hi Everyone, July 13–16, 2020 | The world’s largest, virtual GIS event (FREE this year) The 2020 Esri User Conference (Esri UC) is a completely virtual event designed to give users and students an interactive, online experience with Esri and the GIS community. Participate in sessions and view presentations that offer geospatial solutions, browse the online Map Gallery, watch the Plenary Session, and much more. Registration here : https://www.esri.com/en-us/about/events/uc/overview Enjoy
  20. 2 points
    for those like me who are not English mother tongue I recommend this site for translations (English - French - German - Italian - Spanish - Portuguese - Russian - Chinese - Japanese etc.)... fantastic and intuitive that is based on artificial intelligence https://www.deepl.com/ another interesting website https://www.linguee.com/
  21. 2 points
    Stop me if you’ve heard this before. DJI has introduced its latest enterprise powerhouse drone, the DJI Matrice 300 RTK. We learned a lot about the drone earlier this week due to a few huge leaks of specs, features, photos, and videos. But it’s worth looking at the drone again now that it’s official – and an incredible intro video. Also called the M300 RTK, this drone is an upgrade in every way over its predecessor, the M200 V2. That includes a very long flight time of 55 minutes, six-direction obstacle avoidance, and a doubled (6 pound) payload capability. That allows it to carry a range of powerful cameras, which we’ll get to in a bit. The drone is also built for weather extremes. IP45 weather sealing keeps out rain and dust. And a self-heating battery helps the drone to run in a broad range of temperatures, from -4 to 122 Fahrenheit. The DJI Matrice 300 RTK can fly up to 15 kilometers (9.3 miles) from its controller and still stream 1080p video back home. That video and other data can be protected using AES-256 encryption. The drone can also be flown by two co-pilots, with one able to take over for the other if any problem arises or a handoff scenario. A workhorse inspection drone All these capabilities are targeted to the DJI Matrice 300 RTK’s purpose as a drone for heavy-duty visual inspection and data collection work, such as surveys of power lines or railways. In fact, it incorporates many advanced camera features for the purpose. Smart inspection is a new set of features to optimize data collection. It includes live mission recording, which allows the drone to record every aspect of a flight, even camera settings. This allows workers to train a drone on an inspection mission that it will repeat again and again. With AI spot check, operators can mark the specific part of the photo, such as a transformer, that is the subject of inspection. AI algorithms compare that to what the camera sees on a future flight, so that it can frame the subject identically on every flight. An inspection drone is only as good as its cameras, and the M300 RTK offers some powerful options from DJI’s Zenmuse H20 series. The first option is a triple-camera setup. It includes a 20-megapixel, 23x zoom camera; a 12MP wide-angle camera; and a laser rangefinder that measures out to 1,200 meters (3,937 feet). The second option adds a radiometric thermal camera. TO make things simpler for operators, the drone provides a one-click capture feature that grabs videos or photos from three cameras at once, without requiring the operator to switch back and forth. Eyes and ears ready for danger With its flight time and range, the DJI Matrice 300 RTK could be flying some long, complex missions, easily beyond visual line of site (if its owner gets an FAA Part 107 waiver for that). This requires some solid safety measures. While the M200 V2 has front-mounted sensors, the M300 RTK has sensors in six directions for full view of the surroundings. The sensors can register obstacles up to 40 meters (98 feet) away. Like all new DJI drones, the M300 RTK also features the company’s AirSense technology. An ADS-B receiver picks up signals from manned aircraft that are nearby and alerts the drone pilot of their location. It’s been quite a few weeks for DJI. On April 27, it debuted its most compelling consumer drone yet, the Mavic Air 2. Now it’s showing off its latest achievement at the other end of the drone spectrum with the industrial grade Matrice 300 RTK. These two, very different drones help illustrate the depth of product that comes from the world’s biggest drone maker. And the company doesn’t show signs of slowing down, despite the COVID-19 economic crisis. Next up, we suspect, will be a revision to its semi-pro quadcopter line in the firm of a Mavic 3. It is available at DJI.It’s been quite a few weeks for DJI. On April 27, it debuted its most compelling consumer drone yet, the Mavic Air 2. Now it’s showing off its latest achievement at the other end of the drone spectrum with the industrial grade Matrice 300 RTK. These two, very different drones help illustrate the depth of product that comes from the world’s biggest drone maker. And the company doesn’t show signs of slowing down, despite the COVID-19 economic crisis. Next up, we suspect, will be a revision to its semi-pro quadcopter line in the firm of a Mavic 3. It is available at DJI. source: https://dronedj.com/2020/05/07/dji-matrice-300-rtk-drone-official/
  22. 2 points
    @intertronic, thanks for your input. I found a solution that suite my case better due to the fact that we are using both version of QGIS and also because I was looking for interoperability. Therefore I have decided to use QSphere. Most probably not well known around the globe. https://qgis.projets.developpement-durable.gouv.fr/projects/qsphere GUI quiete ugly but at least is doing the job. 😉 darksabersan
  23. 2 points
    DRONE MAKER DJI announced an update to its popular Mavic Air quadcopter today. The Mavic Air 2 will cost $799 when it ships to US buyers in late May. That's the same price as the previous Mavic Air model, so the drone stays as DJI's mid-range option between its more capable Mavic 2 and its smaller, cheaper Mavic Mini. The Mavic Air 2 is still plenty small, but the new version has put on some weight. DJI says that testing and consumer surveys suggested that most people don't mind lugging a few extra grams in exchange for a considerable upgrade in flight time and, presumably, better handling in windy conditions. Even better, thanks to a new rotor design and other aerodynamic improvements, DJI is claiming the Mavic Air 2 can remain aloft for 34 minutes—a big jump from the 21 minutes of flight time on the original Mavic Air. The Camera Eye he big news in this update is the new larger imaging sensor on the drone's camera. The Mavic Air 2's camera ships with a half-inch sensor, up from the 1 2/3-inch sensor found in the previous model. That should mean better resolution and sharper images, especially because the output specs haven't changed much. The new camera is still outputting 12-megapixel stills, but now has a bigger sensor to fill that frame with more detail. There's also a new composite image option that joins together multiple single shots into a large, 48-megapixel image. On the video side, there's some exciting news. The Mavic Air 2 is DJI's first drone to offer 4K video at 60 frames per second and 120 Mbps—previous DJI drones topped out at 30 fps when shooting in full 4K resolution. There are also slow-motion modes that slow down footage to four times slower than real life (1080p at 120 fps), or eight-times slower (1080 at 240 fps). Combine those modes with the more realistic contrast you get with the HDR video standard, and you have considerably improved video capabilities in a sub-$1,000 drone. More interesting in some ways is DJI's increasing forays into computational photography, which the company calls Smart Photo mode. Flip on Smart Photo and the Mavic Air 2 will do scene analysis, tap its machine intelligence algorithm and automatically choose between a variety of photo modes. There's a scene recognition mode where the Mavic Air 2 sets the camera up to best capture one of a variety of scenarios you're likely to encounter with drone photography, including blue skies, sunsets, snow, grass, and trees. In each case, exposure is adjusted to optimize tone and detail. The second Smart Photo mode is dubbed Hyperlight, which handles low-light situations. To judge by DJI's promo materials, this is essentially an HDR photography mode specifically optimized for low-light scenes. It purportedly cuts noise and produces more detailed images. The final smart mode is HDR, which takes seven images in rapid succession, the combines elements of each to make a final image with a higher dynamic range. One last note about the camera: The shape of the camera has changed, so if you have any lenses or other accessories for previous DJI drones, they won't attach to the Air 2. Automatic Flight for the People If you dig through older YouTube videos there's a ton of movies that play out like this: unbox new drone, head outside, take off, tree gets closer, closer, closer, black screen. Most of us just aren't that good at flying, and the learning curve can be expensive and steep. Thankfully drone companies began automating away most of what's difficult about piloting a quadcopter, and DJI is no exception. The company has added some new automated flight tricks to the Air's arsenal. DJI's Active Track has been updated to version 3.0, which brings better subject recognition algorithms and some new 3D mapping tricks to make it easier to automatically track people through a scene, keeping the camera on the subject as the drone navigates overhead to stay with them. DJI claims the Point of Interest mode—which allows you to select an object and fly around it in a big circle while the camera stays pointed at the subject—is better at tracking some of the objects that previous versions struggled with, like vehicles or even people. The most exciting new flight mode is Spotlight, which comes from DJI's high-end Inspire drone used by professional photographers and videographers to carry their DSLR cameras into the sky. Similar to the Active Track mode, Spotlight keeps the camera pointed a moving subject. But while Active Track automates the drone's flight, the new Spotlight mode allows the human pilot to retain control of the flight path for more complex shots. Finally, the range of the new Mavic Air 2 has been improved, and it can now wander an impressive six miles away from the pilot in ideal conditions. The caveat here is that you should always maintain visual contact with your drone for safety reasons. However, you aren't going to be able to see the Mavic Air 2 when it's two miles away, let alone six. Despite a dearth of competitors, DJI continues to put out new drones and improve its lineup as it progresses. The Mavic Air 2 looks like an impressive update to what was already one of our favorite drones, especially considering several features—the 60 fps 4K video and 34 minute flight time—even best those found on the more expensive Mavic 2 Pro. links: https://www.dji.com/id/mavic-air-2
  24. 2 points
    I like drones but just got more interested in this,
  25. 2 points
    Harvard Online Courses Advance your career. Pursue your passion. Keep learning. links: https://online-learning.harvard.edu/CATALOG/FREE
  26. 2 points
  27. 2 points
    Saw a similar news last month - Using Machine Learning to “Nowcast” Precipitation in High Resolution by Google. The result seemed pretty good. Here, A visualization of predictions made over the course of roughly one day. Left: The 1-hour HRRR prediction made at the top of each hour, the limit to how often HRRR provides predictions. Center: The ground truth, i.e., what we are trying to predict. Right: The predictions made by our model. Our predictions are every 2 minutes (displayed here every 15 minutes) at roughly 10 times the spatial resolution made by HRRR. Notice that we capture the general motion and general shape of the storm. The two method seem similar.
  28. 2 points
    With Huawei basically blocked from using Google services and infrastructure, the firm has taken steps to replace Google Maps on its hardware by signing a partnership with TomTom to provide maps, navigation, and traffic data to Huawei apps. Reuters reports that Huawei is entering this partnership with TomTom as the mapping tech company is based in the Netherlands — therefore side-stepping the bans on working with US firms. TomTom will provide the Chinese smartphone manufacturer with mapping, live traffic data, and software on smartphones and tablets. TomTom spokesman Remco Meerstra confirmed to Reuters that the deal had been closed some time ago but had not been made public by the company. This comes as TomTom unveiled plans to move away from making navigation hardware and will focus more heavily on offering software services — making this a substantial step for TomTom and Huawei. While TomTom doesn’t quite match the global coverage and update speed of Google Maps, having a vital portion of it filled by a dedicated navigation and mapping firm is one step that might appease potential global Huawei smartphone buyers. There is no denying the importance of Google app access outside of China but solid replacements could potentially make a huge difference — even more so if they are recognizable by Western audiences. It’s unclear when we may see TomTom pre-installed on Huawei devices but we are sure that this could be easily added by way of an OTA software update. The bigger question remains if people are prepared to switch from Google Maps to TomTom for daily navigation. resource: https://9to5google.com/2020/01/20/huawei-tomtom/
  29. 2 points
    January 3, 2020 - Recent Landsat 8 Safehold Update On December 19, 2019 at approximately 12:23 UTC, Landsat 8 experienced a spacecraft constraint which triggered entry into a Safehold. The Landsat 8 Flight Operations Team recovered the satellite from the event on December 20, 2019 (DOY 354). The spacecraft resumed nominal on-orbit operations and ground station processing on December 22, 2019 (DOY 356). Data acquired between December 22, 2019 (DOY 356) and December 31, 2019 (DOY 365) exhibit some increased radiometric striping and minor geometric distortions (see image below) in addition to the normal Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) alignment offset apparent in Real-Time tier data. Acquisitions after December 31, 2019 (DOY 365) are consistent with pre-Safehold Real-Time tier data and are suitable for remote sensing use where applicable. All acquisitions after December 22, 2019 (DOY 356) will be reprocessed to meet typical Landsat data quality standards after the next TIRS Scene Select Mirror (SSM) calibration event, scheduled for January 11, 2020. Landsat 8 Operational Land Imager acquisition on December 22, 2019 (path 148/row 044) after the spacecraft resumed nominal on-orbit operations and ground station processing. This acquisition demonstrates increased radiometric striping and minor geometric distortions observed in all data acquired between December 22, 2019 and December 31, 2019. All acquisitions after December 22, 2019 will be reprocessed on January 11, 2020 to achieve typical Landsat data quality standards. Data not acquired during the Safehold event are listed below and displayed in purple on the map (click to enlarge). Map displaying Landsat 8 scenes not acquired from Dec 19-22, 2019 Path 207 Rows 160-161 Path 223 Rows 60-178 Path 6 Rows 22-122 Path 22 Rows 18-122 Path 38 Rows 18-122 Path 54 Rows 18-214 Path 70 Rows 18-120 Path 86 Rows 24-110 Path 102 Rows 19-122 Path 118 Rows 18-185 Path 134 Rows 18-133 Path 150 Rows 18-133 Path 166 Rows 18-222 Path 182 Rows 18-131 Path 198 Rows 18-122 Path 214 Rows 34-122 Path 230 Rows 54-179 Path 13 Rows 18-122 Path 29 Rows 20-232 Path 45 Rows 18-133 After recovering from the Safehold successfully, data acquired on December 20, 2019 (DOY 354) and from most of the day on December 21, 2019 (DOY 355) were ingested into the USGS Landsat Archive and marked as "Engineering". These data are still being assessed to determine if they will be made available for download to users through all USGS Landsat data portals. source: https://www.usgs.gov/land-resources/nli/landsat/january-3-2020-recent-landsat-8-safehold-update
  30. 1 point
    Earth is known as the “Blue Planet” due to the vast bodies of water that cover its surface. With an over 70% of our planet’s surface covered by water, ocean depths offer basins with an abundance of features, such as underwater plateaus, valleys, mountains and trenches. The average depth of the oceans and seas surrounding the continents is around 3,500 meters and parts deeper than 200 meters are called "deep sea". This visualization reveals Earth’s rich bathymetry, by featuring the ETOPO1 1-Arc Minute Global Relief Model. ETOPO1 integrates land topography and ocean bathymetry and provides complete global coverage between -90° to 90° in latitude and -180° to 180° in longitude. The visualization simulates an incremental drop of 10 meters of the water’s level on Earth’s surface. As time progresses and the oceans drain, it becomes evident that underwater mountain ranges are bigger in size and trenches are deeper in comparison to those on dry land. While water drains quickly closer to continents, it drains slowly in our planet’s deepest trenches. These trenches start to become apparent below 5,000 meters, as the majority of the oceans have been drained of water. In the Atlantic Ocean, there are two trenches that stand out. In the southern hemisphere, the South Sandwich trench is located between South America and Antarctica, while in the northern hemisphere the Puerto Rico trench in the eastern Caribbean is its deepest part. The majority of the world’s deepest trenches though are located in the Pacific Ocean. In the southern hemisphere, the Peru-Chile or Atacama trench is located off the coast of Peru and the Tonga Trench in the south-west Pacific Ocean between New Zealand and Tonga. In the northern hemisphere, the Philippines Trench is located east of the Philippines, and in the northwest Pacific Ocean we can see a range of trenches starting from the north, such as the Kuril-Kamchatka, and moving to the south all the way to Mariana’s trench that drains last. It is worth recalling that the altitude values of ETOPO1 range between 8,333 meters (topography) and -10,833 meters (bathymetry). This range of altitude values reflects the limitations of the visualization, since Challenger Deep - the Earth’s deepest point located at Mariana's trench - has been measured to a maximum depth of 10,910 meters and Mount Everest the highest peak above mean sea level is at 8,848 meters. In this visualization the vertically exaggerated by 60x ETOPO1 relief model, utilizes a gray-brown divergent colormap to separate the bathymetry from topography. The bathymetry is mapped to brownish hues (tan/shallow to brown/deep) and the dry land to greys (dark gray/low to white/high). A natural consequence of this mapping is that areas of the highest altitude are mapped to whitish hues, as they are almost always covered in snow. Furthermore, in an effort to help viewer’s eyes detect surface details that would otherwise be unnoticeable, the topography and bathymetry have been rendered with ambient occlusion - a shadowing technique that in this particular visualization darkens features and regions that present changes in altitude, such as mountains, ocean crevices and trenches. download: https://svs.gsfc.nasa.gov/vis/a000000/a004800/a004823/OceanDrain_Colorbar_1920x1080_30fps.mp4 https://svs.gsfc.nasa.gov/vis/a000000/a004800/a004823/OceanDrain_1920x1080_30fps.mp4 source: https://svs.gsfc.nasa.gov/4823
  31. 1 point
    Planet is set to launch three more new SkySats (SkySats 19-21) into Low Earth Orbit on August 18th (date subject to change), rounding out the fleet of SkySats already in operations and joining SkySats 16-18 that successfully launched aboard the SpaceX Falcon 9 in June. Planet SkySats 1-15 operate in Sun Synchronous Orbits, a specific type of Low Earth Orbit that results in the Earth’s surface always being illuminated by the Sun at the same angle when the satellite is capturing imagery. Half of the SkySats currently pass overhead in a morning crossing plane, while the other half moves in an afternoon crossing plane, so together they provide the twice-daily coverage of anywhere on Earth. Both sets of new SkySats, 16-18 and 19-21, will operate in a “mid-inclination” orbit of 53 degrees that complements the sun synchronous fleet, and will offer more targeted coverage and imaging capacity in the latitude bands between +53 degrees and -53 degrees where the majority of human activity occurs. By taking advantage of SpaceX’s rideshare program, we were able to get these satellites launched much faster compared to a dedicated launch. In addition, by splitting the payload across two launches, we’re able to phase the mid-inclination SkySats into their respective planes much faster as well, all of which results in Planet’s customers benefiting from these enhanced products much sooner than any other provider can offer. SkySats 19-21 will be launched aboard SpaceX’s Falcon 9, a two-stage reusable rocket that has successfully flown satellites and cargo over 80 times to orbit. They will do so as rideshare payloads on SpaceX’s Starlink satellites, and will launch from the Cape Canaveral Air Force Base in Florida. The rapid launch of SkySats 16-21, as well as the development of our enhanced 50 cm imagery, are just a few examples of how Planet continues to push the envelope to provide industry-leading geospatial offerings that continuously improve over time. source: https://www.planet.com/pulse/skysats-19-21-to-launch-on-spacex-falcon-9-rideshare-mission/
  32. 1 point
    this response basically in every big software company, if you got error on windows for example, you will get pretty much same sh*t, ahahahaha I prefer search on 3rd party forum, like stakeoverflow or such....
  33. 1 point
    Current u-blox GNSS platforms — from u-blox M8 and beyond — support the recently completed BeiDou navigation satellite system modernizations, improving the availability of GNSS positioning services. The opening ceremony of the BeiDou-3 global navigation satellite system (GNSS) was held in Beijing on July 31, officially celebrating the expansion of coverage offered by the critical Chinese space infrastructure to a global user base. As a global supplier of GNSS positioning and wireless communication technologies, u-blox has been driving technological innovation and deeply involved in the Chinese market for many years. Tests conducted across China and Europe have shown that including the BeiDou system can improve the positioning accuracy of GNSS receivers when multiple navigation satellite systems are tracked concurrently. When signals are partially obstructed, positioning accuracy can be significantly improved by incorporating the BeiDou system. Data shows that in 2019, the overall output value of the Chinese satellite navigation and location service industry reached nearly 345 billion yuan, an increase of 14.4% over 2018, with the output value expected to exceed 400 billion yuan in 2020. Additional Services Provided by BeiDou The BeiDou system provides a suite of additional services, including satellite and ground-based augmentation services, precise single-point positioning, precise timing and global short message services, laying a solid foundation for BeiDou’s ubiquitous navigation and tracking applications. Applications of GNSS technology continue to diversify, leveraging the all-weather, all-time, tracking, navigation and timing services it offers. GNSS technology is penetrating deeper into traditional industrial verticals, such as agriculture, forestry, animal husbandry and fishery, power and energy, as well as in railway and air transportation, including their infrastructure construction and management. At the same time, GNSS technology has become an indispensable and “smart” factor in emerging application fields such as the internet of things and the “internet of vehicles,” as well as in innovative applications such as autonomous driving, automatic parking and automatic logistics, and is now commonplace in many industrial and consumer use cases. “U-blox has been closely following the modernization of the BeiDou navigation system and is ready to work with partners in various industries to promote the expansion of industry applications, expand emerging markets and jointly create a green industry ecosystem,” said Hamilton Chen, China country manager at u-blox. source: https://www.gpsworld.com/u-blox-technology-platforms-support-beidou-3/
  34. 1 point
    The video shows a landslide analysis of Tersun Dam simulated with FLOW-3D. For more examples of how FLOW-3D can be used to analyze the catastrophic events. A fully 3D simulation was performed in the vicinity of the breach to capture the complex 3D hydraulic conditions. https://www.youtube.com/watch?time_continue=3&v=f9QzOn0vxpc&feature=emb_title
  35. 1 point
    Despite the controversy related to China-India border, this articles show us the importance of Remote Sensing as a strategic tools on Politic and Military The recent deaths of at least 20 soldiers along the contested border at Ladakh between India and China represents the largest loss of life from a skirmish between the two countries since the clashes in 1967 that left hundreds dead. It also highlights the tensions that have been building along the Line of Actual Control since early May. Using this satellite imagery, I will try to illustrate the approximate reality on the ground. My analysis disproves some of the more extreme claims that have been made about the incident, such as that thousands of Chinese soldiers have crossed the LAC and encamped in Indian-controlled territory. The satellite pictures also highlight the obvious threats to a peaceful status quo that exist along the western sector of India’s border with China. The analysis includes evidence that strongly suggests People’s Liberation Army forces have been regularly crossing into Indian territory temporarily on routine patrol routes. The details of this week’s clashes are still murky. But based on recent satellite imagery and media reporting, it appears the bulk of casualties were the result of soldiers falling during hand-to-hand fighting along a steep ridgeline that marks the LAC. The small area that is at the heart of this dispute appears to straddle the LAC and likely houses less than 50 Chinese troops. Neither Beijing nor Delhi considers the loosely demarcated line that separates the two countries in Ladakh to be an authoritative border. It approximates areas of territorial control established at the end of the 1962 Sino-Indian War when China withdrew from much of its captured territory on the Himalayan plateau. The border standoff at Ladakh has become a politically charged issue in India. The Indian government has revealed few details about the situation over the past few weeks. Former Indian Army officers, however, have been providing information to journalists and the media have been consistently painting a picture of a substantial conflict, often involving claims of the incursion of 10,000 PLA troops into undisputed Indian territory. The reality is less dramatic, but does represent a significant change to the status quo along the India–China border that threatens to escalate. By analysing satellite imagery from late May and early June it’s possible to make informed judgements about the positions of forces at multiple hotspots. Along the India–China border there are three key areas that produce the majority of tension between the two countries: Arunachal Pradesh; Sikkim and nearby Doklam (the site of a major skirmish in 2017 that saw Indian troops enter Bhutanese territory to prevent the completion of a strategic road being built by China); and Ladakh. The build-up of troops and military positions in recent months has been mostly in the Ladakh sector. Developments have occurred in three strategic areas along the LAC: the Galwan River Valley, where this week’s deadly clashes occurred; Hot Springs, where satellite evidence suggests that Chinese forces have regularly entered Indian territory; and the Pangong Tso. complete story : https://www.aspistrategist.org.au/satellite-images-show-positions-surrounding-deadly-china-india-clash/ https://www.indiatoday.in/india/story/latest-satellite-images-show-situation-far-from-normal-at-ladakh-s-pangong-tso-1706373-2020-07-31
  36. 1 point
    This is without a doubt the most anticipated feature of the year for CarPlay users, as Google Maps can now replace Apple Maps on the multi-view screen. Apple originally locked the maps card on the CarPlay dashboard to Apple Maps, which means that users weren’t allowed to configure any other application to display real-time information in this panel. It goes without saying this was quite an issue for many users, especially as Google Maps and the Google-owned Waze are extremely popular choices among CarPlay users. The release of iOS 13.4 in April brought massive changes in this regard, as the maps card was unlocked for third parties, essentially allowing any developer of such an app to add support for the dashboard and thus be able to replace Apple Maps. Google, however, has never been in a rush to make the whole thing happen, so here we are in early August finally getting support for Google Maps on the dashboard. What you need to know, however, is that the feature is only available for testers who are part of the beta program, but chances are that support for the multi-view screen on CarPlay will be included in one of the next Google Maps updates rolling out this month for production devices. In the meantime, Waze is yet to get this feature, as not even the beta builds of the app come with it. However, I’m guessing it’s all now just a matter of time until Waze is being updated with dashboard support on CarPlay, and I’m expecting Google to make this happen in its traffic navigation app rather sooner than later. On a side note, Google has also released a new Google Maps update for the stable channel on iOS, bringing the app to version 5.49. This one, however, includes only fixes and improvements, so no dashboard support for now on production devices. source: https://www.autoevolution.com/news/google-releases-the-most-anticipated-google-maps-carplay-feature-for-testers-146802.html#
  37. 1 point
    Hi remoteguy ! Welcome on board and enjoy your time with us and the community. darksabersan
  38. 1 point
    GRASS GIS was, for a long time, something I dismissed as ‘too complex’ for my everyday geospatial operations. I formulated any number of excuses to work around the software and could not be convinced it had practical use in my daily work. It was ‘too hard to set-up’, ‘never worked well with QGIS’, and ‘made my scripting processes a nightmare’. In this example we will: part 1: 1. Download a small piece of elevation data from the LINZ Data Service 2. Build a GRASS environment to process these data 3. Build a BASH script to process the catchments 4. Import the elevation into the GRASS environment 5. Perform some basic GRASS operations (fill and watershed) 6. Export raster format for viewing 7. Export the vector catchments to shapefile part 2: 1. Creating multiple watershed boundaries of different sizes with GRASS and using a basic loop in BASH for the process. 2. Clipping the original raster by the watershed boundaries using GDAL and SQL with a basic loop in BASH. links: part 1: https://xycarto.com/2020/05/03/basic-grass-gis-with-bash/ part 2: https://xycarto.com/2020/05/05/basic-grass-gis-with-bash-plus-gdal/ source code: https://github.com/xycarto/xycarto_code/tree/master/scripts/grass/GRASS_BASH_blog
  39. 1 point
    Changes in ocean circulation may have caused a shift in Atlantic Ocean ecosystems not seen for the past 10,000 years, new analysis of deep-sea fossils has revealed. This is the striking finding of a new study led by a research group I am part of at UCL, funded by the ATLAS project and published in the journal Geophysical Research Letters. The shift has likely already led to political tensions as fish migrate to colder waters. The climate has been quite stable over the 12,000 years or so since the end of the last Ice Age, a period known as the Holocene. It is thought that this stability is what allowed human civilisation to really get going. In the ocean, the major currents are also thought to have been relatively stable during the Holocene. These currents have natural cycles, which affect where marine organisms can be found, including plankton, fish, seabirds and whales. Yet climate change in the ocean is becoming apparent. Tropical coral reefs are bleaching, the oceans becoming more acidic as they absorb carbon from the atmosphere, and species like herring or mackerel are moving towards the poles. But there still seems to be a prevailing view that not much has happened in the ocean so far – in our minds the really big impacts are confined to the future. Looking into the past To challenge this point of view, we had to look for places where seabed fossils not only covered the industrial era in detail, but also stretched back many thousands of years. And we found the right patch of seabed just south of Iceland, where a major deep sea current causes sediment to pile up in huge quantities. To get our fossil samples we took cores of the sediment, which involves sending long plastic tubes to the bottom of the ocean and pushing them into the mud. When pulled out again, we were left with a tube full of sediment that can be washed and sieved to find fossils. The deepest sediment contains the oldest fossils, while the surface sediment contains fossils that were deposited within the past few years. One of the simplest ways of working out what the ocean was like in the past is to count the different species of tiny fossil plankton that can be found in such sediments. Different species like to live in different conditions. We looked at a type called foraminifera, which have shells of calcium carbonate. Identifying them is easy to do using a microscope and small paintbrush, which we use when handling the fossils so they don't get crushed. A recent global study showed that modern foraminifera distributions are different to the start of the industrial era. Climate change is clearly already having an impact. Similarly, the view that modern ocean currents are like those of the past couple of thousand years was challenged by our work in 2018, which showed that the overturning "conveyor belt" circulation was at its weakest for 1,500 years. Our new work builds on this picture and suggests that modern North Atlantic surface circulation is different to anything seen in the past 10,000 years – almost the whole Holocene. The effects of the unusual circulation can be found across the North Atlantic. Just south of Iceland, a reduction in the numbers of cold-water plankton species and an increase in the numbers of warm-water species shows that warm waters have replaced cold, nutrient-rich waters. We believe that these changes have also led to a northward movement of key fish species such as mackerel, which is already causing political headaches as different nations vie for fishing rights. Further north, other fossil evidence shows that more warm water has been reaching the Arctic from the Atlantic, likely contributing to melting sea ice. Further west, a slowdown in the Atlantic conveyor circulation means that waters are not warming as much as we would expect, while furthest west close to the US and Canada the warm gulf stream seems to be shifting northwards which will have profound consequences for important fisheries. One of the ways that these circulation systems can be affected is when the North Atlantic gets less salty. Climate change can cause this to happen by increasing rainfall, increasing ice melt, and increasing the amount of water coming out of the Arctic Ocean. Melting following the peak of the Little Ice Age in the mid 1700s may have triggered an input of freshwater, causing some of the earliest changes that we found, with modern climate change helping to propel those changes beyond the natural variability of the Holocene. We still don't know what has ultimately caused these changes in ocean circulation. But it does seem that the ocean is more sensitive to modern climate changes than previously thought, and we will have to adapt. source: https://www.sciencealert.com/fossils-reveal-our-ocean-is-changing-in-a-ways-it-hasn-t-for-10-000-years
  40. 1 point
    In March, the U.S. government received an unusual inquiry about GPS disruptions. It was from a user in Iran reporting what appeared to be “circle spoofing” — a phenomenon that had only previously been observed in China. “Some of GPS devices received fake signal and show the fake valid location. Yesterday I test a device, it can get signal and give real position. After 10 minutes the device show moving around a big circle in tehran by 35 km/h speed. I can’t fix this problem by restarting the device. “The GPS module time is correct but the location is not. I attach Excel file of data and map of the track. I can’t get any response from Communications Regulatory Authority (CRA) of The I.R. of Iran. Do you know about this?” A little internet research showed that the spoofing was taking place at or near Iran’s “AJA University of Command and Staff,” formerly called the “War University.” It is the staff college for Iran’s Army. Reports to the U.S. government about GPS disruption are normally listed on the U.S. Coast Guard’s Navigation Center website. This one has not been posted. Coast Guard officials said that it is because the report was received by another agency and did not contain sufficient information. Attempts by Coast Guard personnel to contact the reporting source for more information to enable the report to be posted were unsuccessful. GPS spoofing is often easiest to detect in maritime areas. Ship automatic identification system (AIS) transmissions include location data and are detected by satellite. The data is then aggregated and used by various companies for a number of applications. Viewing ship location reports over time has revealed thousands of ship receivers spoofed to airports in Russia, and hundreds spoofed into circles (presumably around the spoofing device) in China. Clearly, though, any system that aggregates and displays GPS location data can help detect wide area spoofing activity. Strava is a mobile app for runners and cyclists. The company aggregates location data and displays it on a heat map to highlight athletes’ favorite routes. The Strava heat map for Tehran shows that circle spoofing has also been employed in at least one other location. The below screenshot shows GPS-enabled fitness trackers circling a government complex that houses offices for several defense and technology-related organizations. Iran was the first nation to publicly announce it had the ability to spoof GPS signals and seems to have used it to great advantage. In 2011, a CIA drone that had been operating across the border in Afghanistan landed at an Iranian airfield. Iran’s government claimed that its forces had sent false signals to the drone’s GPS receiver in order to capture it. At first, U.S. government officials said that this kind of spoofing was not possible. Several months later, Prof. Todd Humphreys demonstrated how it could be done to a drone at the University of Texas football stadium. U.S. officials then admitted that spoofing was possible, but said it wasn’t what happened to the CIA drone. At the same time, they offered no alternate explanation of how the drone was captured. In 2016 Iranian forces captured two U.S. Navy boats that had strayed into Iran’s territorial waters. This was just after President Obama had succeeded in pressing that nation to give up nuclear weapons research, and was on the same day as Obama’s last State of the Union address. There was little reason for the U.S. Navy boats to have veered so far off course, and it was clear that the Iranian Navy was waiting for them. Many speculated that Iran had spoofed GPS signals to lure the U.S. Navy boats into Iranian waters. U.S. officials have denied that this was the cause of the incident, but have not publicly offered an alternate explanation other than “mis-navigation.” During heightened tensions in the Persian Gulf in 2019, Iran shot down a U.S. surveillance drone and President Trump seemed ready to launch a retaliatory strike. This was called off at the last minute. According to some reports, the strike was canceled because of the likelihood the drone was in Iranian airspace at the time. At about the same time British intelligence was warning merchant vessels in the area that Iran was attempting to use GPS spoofing to lure them into Iranian waters as a pretext for seizing the ships. While the Middle East has been a hotbed of jamming and conventional spoofing for years, these recent circle-spoofing incidents are the first of the kind we know of in the region. It may well be that Iranian forces have recently received equipment from China and are experimenting with it. They could also be using it to deter GPS guided drones and disrupt other surveillance systems in the vicinity of sensitive government facilities. source: https://www.gpsworld.com/gps-circle-spoofing-discovered-in-iran/
  41. 1 point
    preciso de ajuda para trabalhar operaction Dashbord ArcGis ja crie a conta esri mais não me deixa usar operaction Dashbord ArcGis
  42. 1 point
    sorry i cant see your picture, our country block imgur, really suck 😷
  43. 1 point
    Simple Analysis of Vegetative Trends in Earth Engine - SAVETREE - is a tool developed in Google Earth Engine for the Lassen Volcanic National park, it estimates tree mortality by fitting a linear trend to time serries data of a user chosen spectral index. The user can export their new map in the form of TIFF files,add historic fire layers, and the user can produce graphs which view the values in the time series for a particular pixel by clicking on the layer. Running SAVETREE Hit the “run” button in the center panel to make the widget appear. Using SAVETREE the user can do the following things: * Spectral Index: Choose from NDMI, NDVI, NDWI or NBR to select which spectral index you would like to create a linear regression layer for. The default is NDMI. * Area of interest: Choose from Lassen Volcanic National Park, Lassen National Forest, DEVELOP T2 Study Area, the Badger Planning area or choose Your asset (below) to perform the analysis on an asset you load yourself see Loading an Asset for instructions on loading your own asset. The default is LVNP. * End year and duration: The year must be in YYYY format, it is the last year of the duration of the analysis. The duration should be a number less than 20, with the most meaningful results coming from 3-7 years, it is the number of years it will create the time series for. For example, if you put in 1990 and a duration of 3, the analysis will be run on 1988, 1989, and 1990. The defaults are 2016 and 5. * Add Coefficient map: Performs the coefficient trend map analysis on the spectral index and area of interest for the duration you supplied ending with the year you specified and adds that layer to the map. * Add Bivariate map: Performs the Bivariate map analysis on the spectral index and area of interest for the duration you supplied ending with the year you specified and adds that layer to the map. * Reset Map: Clears all layers. Note: it does not reset the area of interest or any items in the widget. To reset the area of interest, choose a different area of interest from the dropdown before running a new analysis. * Fire history start and end years: These years must be in YYYY format. These numbers create a filter for the fire history data where the only data to be added to the map will be fires or treatments that occurred during those years. * Fire History Dataset: Select from FRAP Statewide Wildfire Dataset, RX fire, Other treatment, or load your own fire data asset. To load your own asset see Loading an Asset. The wildfire, rx fire and other treatments are FRAP datasets, for more details on the FRAP data and for the most up-to-date data sets please go to http://frap.fire.ca.gov/projects/fire_data/fire_perimeters_index * Export Coefficient Map: Exports the Coefficient trend layer as a TIFF file. See Exporting a Layer to get details on how to export layers to your Google Drive. * Export Bivariate Map: Exports the Bivariate map layer as a TIFF file. See Exporting a Layer to get details on how to export layers to your Google Drive. * Change Inspector: Click on any part of the Coefficient Trend or Bivariate Map layers and a graph of the change during each year for your duration for that particular point will appear at the bottom of the widget. Click the little box with the arrow in the upper right hand corner of the graph to open the graph in a new tab. You can download this graph from this new tab. SAVETREE was developed over two terms with DEVELOP: * Authors v1.0: Joshua Verkerke, Anna McGarrigle, John Dilger * Authors v2.0: Heather Myers, Anna McGarrigle, Peter Norton, Andrea Ferrer Download code
  44. 1 point
    Take a look on this: links: https://www.cambridge.org/core/what-we-publish/textbooks untested, maybe you need make free user account first they have nice collection of engineering and geosciences books https://www.cambridge.org/core/what-we-publish/textbooks/listing?aggs[productSubject][filters]=F470FBF5683D93478C7CAE5A30EF9AE8 https://www.cambridge.org/core/what-we-publish/textbooks/listing?aggs[productSubject][filters]=CCC62FE56DCC1D050CA1340C1CCF46F5
  45. 1 point
    The British Geological Survey (BGS) has amassed one of the world’s premier collections of geologic samples. Housed in three enormous warehouses in Nottingham, U.K., it contains about 3 million fossils gathered over more than 150 years at thousands of sites across the country. But this data trove “was not really very useful to anybody,” says Michael Stephenson, a BGS paleontologist. Notes about the samples and their associated rocks “were sitting in boxes on bits of paper.” Now, that could change, thanks to a nascent international effort to meld earth science databases into what Stephenson and other backers are describing as a “geological Google.” This network of earth science databases, called Deep-time Digital Earth (DDE), would be a one-stop link allowing earth scientists to access all the data they need to tackle big questions, such as patterns of biodiversity over geologic time, the distribution of metal deposits, and the workings of Africa’s complex groundwater networks. It’s not the first such effort, but it has a key advantage, says Isabel Montañez, a geochemist at University of California, Davis, who is not involved in the project: funding and infrastructure support from the Chinese government. That backing “will be critical to [DDE’s] success given the scope of the proposed work,” she says. In December 2018, DDE won the backing of the executive committee of the International Union of Geological Sciences, which said ready access to the collected geodata could offer “insights into the distribution and value of earth’s resources and materials, as well as hazards—while also providing a glimpse of the Earth’s geological future.” At a meeting this week in Beijing, 80 scientists from 40 geoscience organizations including BGS and the Russian Geological Research Institute are discussing how to get DDE up and running by the time of the International Geological Congress in New Delhi in March 2020. DDE grew out of a Chinese data digitization scheme called the Geobiodiversity Database (GBDB), initiated in 2006 by Chinese paleontologist Fan Junxuan of Nanjing University. China had long-running efforts in earth sciences, but the data were scattered among numerous collections and institutions. Fan, who was then at the Chinese Academy of Sciences’s Nanjing Institute of Geology and Paleontology, organized GBDB around the stacks of geologic strata called sections and the rocks and fossils in each stratum. Norman MacLeod, a paleobiologist at the Natural History Museum in London who is advising DDE, says GBDB has succeeded where similar efforts have stumbled. In the past, he says, volunteer earth scientists tried to do nearly everything themselves, including informatics and data management. GBDB instead pays nonspecialists to input reams of data gleaned from earth science journals covering Chinese findings. Then, paleontologists and stratigraphers review the data for accuracy and consistency, and information technology specialists curate the database and create software to search and analyze the data. Consistent funding also contributed to GBDB’s success, MacLeod says. Although it started small, Fan says GBDB now runs on “several million” yuan per year. Earth scientists outside China began to use GBDB, and it became the official database of the International Commission on Stratigraphy in 2012. BGS decided to partner with GBDB to lift its data “from the page and into cyberspace,” as Stephenson puts it. He and other European and Chinese scientists then began to wonder whether the informatics tools developed for GBDB could help create a broader union of databases. “Our idea is to take these big databases and make them use the same standards and references so a researcher could quickly link them to do big science that hasn’t been done before,” he says. The Beijing meeting aims to finalize an organizational structure for DDE. Chinese funding agencies are putting up $75 million over 10 years to get the effort off the ground, Fan says. That level of support sets DDE apart from other cyberinfrastructure efforts “that are smaller in scope and less well funded,” Montañez says. Fan hopes DDE will also attract international support. He envisions nationally supported DDE Centers of Excellence that would develop databases and analytical tools for particular interests. Suzhou, China, has already agreed to host the first of them, which will also house the DDE secretariat. DDE backers say they want to cooperate with other geodatabase programs, such as BGS’s OneGeology project, which seeks to make geologic maps of the world available online. But Mohan Ramamurthy, project director of the U.S. National Science Foundation–funded EarthCube project, sees little scope for collaboration with his effort, which focuses on current issues such as climate change and biosphere-geosphere interactions. “The two programs have very different objectives with little overlap,” he says. Fan also hopes individual institutions will contribute, by sharing data, developing analytical tools, and encouraging their scientists to participate. Once earth scientists are freed of the drudgery of combing scattered collections, he says, they will have time for more important challenges, such as answering “questions about the evolution of life, materials, geography, and climate in deep time.” source: https://www.sciencemag.org/news/2019/02/earth-scientists-plan-meld-massive-databases-geological-google
  46. 1 point
    really nice, is it possible to leverage into forecast? that would be interesting
  47. 1 point
    Google announced Dataset Search, a service that lets you search for close to 25 million different publicly available data sets, is now out of beta. Dataset Search first launched in September 2018. Researchers can use these data sets, which range from pretty small ones that tell you how many cats there were in the Netherlands from 2010 to 2018 to large annotated audio and image sets, to check their hypotheses or train and test their machine learning models. The tool currently indexes about 6 million tables. With this release, Dataset Search is getting a mobile version and Google is adding a few new features to Dataset Search. The first of these is a new filter that lets you choose which type of data set you want to see (tables, images, text, etc.), which makes it easier to find the right data you’re looking for. In addition, the company has added more information about the data sets and the organizations that publish them. Searched 'remote sensing' and found this Geographic information A lot of the data in the search index comes from government agencies. In total, Google says, there are about 2 million U.S. government data sets in the index right now. But you’ll also regularly find Google’s own Kaggle show up, as well as a number of other public and private organizations that make public data available, as well. As Google notes, anybody who owns an interesting data set can make it available to be indexed by using a standard schema.org markup to describe the data in more detail. Source
  48. 1 point
    I have a project with autocad files fire up my Workstation Laptop (Dell Precission 5510) and load CAD data. Holly cr*p, this software run like a snail, 🤣 try to disable Hardware acceleration, yeah much better experience, but still laggy as old Arcgis Pro beta 😂 searching around and found this article: https://knowledge.autodesk.com/support/autocad/troubleshooting/caas/sfdcarticles/sfdcarticles/Optimize-Performance-within-Windows-7-Environments.html?_ga=2.205082898.303799305.1579712200-1066991414.1579712200 didnt have time to try all the suggestion yet, but, hey all GISArea members, do you use Autocad? how to improve your CAD Experience? share with me, 😉
  49. 1 point
    While many advancements have been made this last decade in automated classification of above surface features using remote sensing data, progress for detecting underground features has lagged in this area. Technologies for detecting features, including ground penetrating radar, electrical resistivity, and magnetometry exist, but methods for feature extraction and identification mostly depend on the experience of instrument user. One problem has been creating approaches that can deal with complex signals. Ground penetrating radar (GPR), for instance, often produces ambiguous signals that can have a lot different noise interference relative to the feature one wants to identify. One approach has been to apply approximation polynomials to classify given signals that are then inputs for an applied neural networks model using derived coefficients. This technique can help reduce noise and differentiate signals that follow clear patterns that vary from larger background signals. Differentiation of signals based on minimized coefficients are one way to simplify and better differentiate data signals.[1] Another approach is to use multilayer perceptron that has a nonlinear activation function which transforms the data. This is effectively a similar technique but uses different transform functions than other neural network models. Applications of this approach include being able to differentiate thickness of underground structures from surrounding sediments and soil.[2] Other methods have been developed to determine the best location to place source and receivers that can capture relevant data. In seismic research, the use of convolutional neural networks (CNNs) has been applied to determine better positioning of sensors so that better data quality can be achieved. This has resulted in very high precision and recall rates at over 0.99. Using a series of filtered layers, signals can be assessed for their data quality with that of manually placed instruments. The quality of the placement can also be compared to other locations to see if the overall signal capture improves. Thus, rather than focusing on mainly signal processing, this method also focuses on signal placement and capture that compares to other placements to optimize data capture locations.[3] One problem in geophysical data is inversion, where data points are interpreted to be the opposite of what they are due to a reflective signal that may hid the nature of the true data. Techniques using CNNs have also been developed whereby the patterning of data signals around a given inversion can be filtered and assessed using activation functions. Multiple layers that transform and reduce data to specific signals helps to identify where patterns of data suggest an inversion is likely, while checking if this follows patterns from other data using Bayesian learning techniques.[4] source: https://www.gislounge.com/automated-remote-sensing-of-underground-features/
  50. 1 point
    The Klencke Atlas is one of the world's biggest: it measures 176 x 231 cm when open. It takes its name from Joannes Klencke, who presented it to Charles II on his restoration to the British thrones in 1660. Its size and its 40 or so large wall maps from the Golden Age of Dutch mapmaking were supposed to suggest that it contained all the knowledge in the world. At another level, it was a bribe intended to spur the King into granting Klencke and his associates trading privileges and titles. Charles, who was a map enthusiast, appreciated the gift. He placed the atlas with his most precious possessions in his cabinet of curiosities, and Klencke was knighted. Later generations have benefited too. The binding has protected the wall maps which have survived for us to enjoy - unlike the vast majority of other wall maps which, exposed to light, heat and dirt when hung on walls, have crumbled away. visit : https://www.bl.uk/collection-items/klencke-atlas


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