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Hi people, Has anyone tried this Manifold add-in for ArcGIS Pro? https://manifold.net/info/sql4arc.shtml Is it really so good in providing spatial SQL for Esri file geodatabases, the steps we miss in ArcMap and ArcGIS Pro?

The 3.30 ‘s-Hertogenbosch release of the groundbreaking QGIS project introduces a wide range of changes and optimizations from the QGIS developer community. The splash screen features a fragment of the “Gemeentekaart”, or Municipality map, of ‘s-Hertogenbosch from 1867. It is part of a series of 1200 maps of all the communities in The Netherlands from that time, which were published in an atlas for each of the 11 regions. All maps were drawn in the same size, although for large municipalities a double format was used and scaled to match the page. The series was internationally rewarded because of its accuracy and completeness. The map was drawn by Jacob Kuyper (1821-1908), the most famous geographer and cartographer of his time in The Netherlands. Text and splash map image provided by atlasandmap.com Importantly, support for backward compatibility of Symbol Styling has been removed for QGIS 3.16, providing significant optimizations to the project file structure, but limiting the capability of older releases of QGIS for rendering symbologies developed with later releases. This change has been ported to the release of 3.28 LTR as well. The native GeoNode integration has also been migrated to an external plugin, leveraging the powerful extensions to the QGIS API for plugins implemented in recent releases. Users can also look forward to new functionality and UX enhancements, including support for raster attribute tables, intelligent and configurable sorting for layer loading, improvements to GPS utilities, more dynamic form widgets, native rich media previews for attachments, better integration with cloud services, extensions to the QGIS metadata standards, and a host of other noteworthy additions. source: Changelog for QGIS 3.30

Yes this earthquake made vast destruction in turkey. Earthquake measured Syria and Turkey with Magnitude 7.8 R

Catalog layers You can create and draw catalog layers in maps and scenes. A catalog layer is a collection of item references to local and shared datasets, layers, services, and workspaces from various work environments. Automatic resizing of layout elements When you change the page size or orientation of a layout, you can automatically resize and reposition layout elements. Time-enabled scene layers You can time-enable point, 3D object, or building scene layers to visualize 3D content temporally. Scale-based label sizing Scale-based label sizing allows you to smoothly change the text size of labels as you move across the scales of your map. Magnifier window In 2D maps, you can open a magnifier window to help with workflows such as seeing what content is visible at a larger scale, and using precise snapping when digitizing new features. Reality Mapping The tools and capabilities in the new ArcGIS Reality for ArcGIS Pro extension allow you to photogrammetrically correct and process drone and digital aerial imagery to produce high-fidelity 3D and 2D products. source: https://pro.arcgis.com/en/pro-app/3.1/get-started/whats-new-in-arcgis-pro.htm

all done, please be more active, post news and question, help us grow

GeoNetwork 4.2.2 change notes Authentication / OAuth2 OpenId Connect Single Sign-on and also support for OIDC Bearer tokens Search / Aggregations / Add icon decorator Search / Autocomplete improvements Indexing / Add analyzer for Dutch Indexing / Improve performance Editor / Easier configuration for custom editor Feature catalogue now provides a table of content when multiple tables are described. Feature catalogue / Use ISO19115-3 instead of ISO19110 Admin / Improve layout for settings CSW / Improve DCAT support INSPIRE / Fix import from Re3gistry GitHub link https://github.com/geonetwork/core-geonetwork/releases Download https://sourceforge.net/projects/geonetwork/files/GeoNetwork_opensource/v4.2.2/ So I have been working with GeoNetwork for few days and installation is a real pain in the ***. I could not find any other robust and open-source geo-data cataloging software with search capability. My system still shows some errors but that will be fine.

On February 6, around 4:15 a.m. local time, a magnitude 7.8 earthquake struck south central Turkey near the Turkey/Syria border. Just 11 minutes later, it was followed by a magnitude 6.7 aftershock. The largest aftershock at the time of writing was a M7.5 aftershock which struck 95 km (~60 miles) to the north. USGS observations and analyses indicate all these events are occurring within the East Anatolian fault system. Though an earthquake of this magnitude is rare anywhere in the world, this type of event is generally expected on long, plate-boundary strike-slip faults. “It’s difficult to watch this tragedy unfold, especially since we’ve known for a long time about how poorly the buildings in the region tend to behave in earthquakes,” said USGS scientist David Wald. “An earthquake this size has the potential to be damaging anywhere in the world, but many structures in this region are particularly vulnerable.” The two largest earthquakes in the recent series are relatively shallow, with the mainshock 18 kilometers, or 11 miles, deep and the 7.5 magnitude aftershock at 10 kilometers (just over 6 miles) deep. Because the quakes are relatively shallow, the intensity of the shaking is severe. source : USGS

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I'd appreciate a reactivation. Thank you

Hello, I'm back after a few difficult months.... could you please reactivate my account. Thanks

I would like to present a project withthe acronym 4DShoreMap that has been going on for a year. The project is called „Innovative system for multidimensional and multitemporal monitoring of the coastal zone using an autonomous unmanned vessel” (4DShoreMap). It will use an Auonomous Surface Vehicle called HydroDron-1. The goal of the project is development of a prototype of a multidimensional and multitemporal coastal zone monitoring system using autonomous unmanned floating platforms platforms at a single survey pass. Creating a 4D map is based on geodata from such sensors as: - echo sounder, - sonar, - metric camera, - LiDAR. You can read more about our project on the company's website [EN]: https://marinetechnology.pl/en/project/4dshoremap-2/ You can read more about our project on the project website [PL]: http://4dshoremap.marinetechnology.pl/ All scientific publications based on our project will be available on the ResearchGate website [EN]: https://www.researchgate.net/project/Innovative-system-for-multidimensional-and-multitemporal-monitoring-of-the-coastal-zone-using-an-autonomous-unmanned-vessel-4DShoreMap-2

already posted here:

Following the successful launch of Landsat 8 and during the development of Landsat 9, the United States Geological Survey (USGS) and NASA assembled a team of experts from within both agencies for a Joint Agency Sustainable Land Imaging Architecture Study Team to evaluate how to inform an acquisition strategy for a follow-on mission that would best satisfy the diverse and evolving user needs collect by the USGS. The highest-recommended architecture was a small constellation of “superspectral” space-based sensors that would improve the spectral, spatial, and temporal capabilities. Landsat Next data would be sufficiently consistent with data from the earlier Landsat missions to permit studies of land cover and land use change over multi-decadal period. Landsat Next Defined Landsat Next will be a constellation of three observatories sent into orbit on the same launch vehicle, which will provide an improved temporal revisit for monitoring dynamic land and water surfaces such as vegetation, wildfire burns, reservoirs and waterways, coastal and wetland regions, glaciers, and dynamic ice sheets. Landsats 8 and 9 measure 11 spectral bands from the visible to thermal infrared wavelengths. Landsat Next will have 26 bands; this includes refined versions of the 11 Landsat “heritage” bands, five bands with similar spatial and spectral characteristics to the European Space Agency’s Copernicus Sentinel-2 bands to allow easier merging of data products, and ten new spectral bands to support emerging Landsat applications. With these improvements, Landsat Next will collect on average about 20 times more data than its predecessor, Landsat 9, and continue to provide free and open data access for all users. The Landsat Next mission successfully passed Key Decision Point A (KDP-A) and is currently in Phase A. Upcoming project studies will complete the mission design, data management and compression approaches, flight instrument requirements and architecture, and spacecraft resource definition. The mission is planned to launch in late 2030. https://landsat.gsfc.nasa.gov/satellites/landsat-next/

A Long March-4B (CZ-4B serial number Y55) rocket launched the Gaofen-11 04 observation satellites from Taiyuan Satellite Launch Center (platform LC9), north China's Shanxi Province, Dec. 2022, at 15:37 Beijing time (07:37 UTC). According to official sources, Gaofen-11 04 (高分 十一 号 04, Gāo Fēn Shíyī hào04, “GF11-04”) entered the initial target orbit as planned, and a network with Gaofen-11 01, 02 and 03 will be added to “improve the efficiency of Earth observation and make greater contributions for social development in the areas of land survey, urban planning, land ownership, road network design, crop estimation and disaster prevention and mitigation.” The common initial orbit for GF 11 spacecraft is 248 km x 694 km, inclined at 97.4° to the equator. According to reports, the Gaofen 11 spacecraft may be able to achieve a ground image resolution of 10 cm or less. If this conjecture can be confirmed, China confirms that it has a satellite image capacity second only to that of the United States. Even with a civilian name, the Gaofen 11 clearly demonstrate their military use: they can provide information for the implementation of major national strategies such as the “Belt and Road” and the modernization of Chinese national defense. The satellite imaging system allows “reading a newspaper headline in the hands of someone on the ground”. The satellite is sometimes compared to the Key Hole KH-11 KENNEN of the Americans, and the diameter of the optical telescope aperture is 1.7 meters – which may indicate the presence of a large mirror used by a Dobsonian-type telescope. The largest mirror carried by a commercial observation satellite is the 1.1 m mirror on the Worldview 3 & 4, manufactured in the USA by ITT Exelis. For non-commercial satellites, the French have published images of their Helios 2, suggesting they have a 1.4 m mirror. The GF-1 is better than all of them and is only surpassed in its optical imaging category by two US devices, the Hubble Space Telescope, which has a 2.4 m mirror working at optical wavelengths; the KENNEN spies which must have a mirror size similar to that of Hubble. As the GF-11s are positioned at 247 × 693 km (parameters converted to a circular orbit of 470 km later), a 1.7 m mirror would give a terrestrial resolution of 8 to 10 cm at perigee, around 10:00 am local solar and 20°N, directly over India and the South China Sea. The resolution released in November 2020 by academic Li Deren, in fact, is 0.1 meter. At an average altitude of 470km the resolution is still 15 to 20 cm, surpassing all commercial and most reconnaissance satellites. This puts China in the select club of countries that can acquire NIIRS 8-9 resolution qualities which means the resolution is high enough to identify handheld small arms. Supposedly, the only members of this club are the US and now China, and this will continue to be the case for the foreseeable future, with perhaps Russia joining them later if the Razdan program lives up to its promises. No further details of the satellite released, continuing Chinese reticence with this type of Gaofen. To date, China has launched sixty-two orbital rockets, with 60 of them successful. The rocket and satellite used in this launch were developed by the Fifth Academy of China Aerospace Science and Technology Corporation – CASC and manufactured by Aerospace Dongfanghong Satellite Co. According to official media, this was the 457th flight of a rocket that uses the Long March name, counting all models. The Taiyuan Launch Center experiences very cold weather in December, with temperatures reaching minus 30 degrees Celsius. In order to ensure that the rocket was not affected by environmental conditions and was launched within the allotted time, safeguard measures were taken: on the one hand, low temperature protection for winter, and the combination of insulation layer and pumped hot air is used; on the other hand, preparations in order to improve the trajectory in relation to the load of high altitude winds, when the wind conditions reach a certain limit, the trajectory is modified increasing the probability of launch in the predetermined window. The Long March 4B is developed by the Aerospace Science and Technology Group, capable of operating at room temperature as a three-stage rocket, capable of launching various types of satellites in different orbit capacity requirements, placing a single satellite or multiple payloads. in sun-synchronous orbit or in geosynchronous orbit. The CZ-4B is developed by the Aerospace Science and Technology Group, capable of launching various types of satellites in different orbit capacity requirements, placing a single satellite or multiple payloads, in sun-synchronous orbit or geosynchronous orbit. The orbital payload capacity can reach 2.5 tons. source: https://www.spaceintel101.com/post/china-launches-gaofen-11-04

SpaceX, the space exploration company, launched a research satellite into orbit on Friday 16 December 2022. Named SWOT (Surface Water and Ocean Topography), the satellite – which is the size of a large car – will measure the water level on more than 90% of the planet’s surface from its position 890km above the Earth. Scientists will use this data to identify areas vulnerable to flooding or extreme drought, as well as to track the rate of rising sea levels and the resulting coastal erosion. It will take SWOT three weeks to map the world’s water. By regularly repeating the process, scientists will be able to gain insight into water currents and create a complete picture of the world. Thanks to advanced technology, SWOT allows scientists to observe seas and oceans at previously unattainable scales. Mapping Earth’s Water in Real Time With this new high-resolution satellite, scientists can now capture the behaviour of Earth’s water bodies in real time. This allows for the detection of changes that necessitate accuracy to the centimetre level, such as the motion of coastal currents or streams or rivers. The goal of the satellite mission is to observe the water cycle in all oceans, rivers and seas for a minimum of 3.5 years. The satellite was developed by the American and French space agencies NASA and CNES, with financial support from Canada and the United Kingdom. source: New Satellite Set to Revolutionize Understanding of Water on Earth | GIM International (gim-international.com)

Shapely 2.0 version is a major release featuring a complete refactor of the internals and new vectorized (element-wise) array operations, providing considerable performance improvements (based on the developments in the PyGEOS package), along with several breaking API changes and many feature improvements. Refactor of the internals# Shapely wraps the GEOS C++ library for use in Python. Before 2.0, Shapely used ctypes to link to GEOS at runtime, but doing so resulted in extra overhead and installation challenges. With 2.0, the internals of Shapely have been refactored to expose GEOS functionality through a Python C extension module that is compiled in advance. Vectorized (element-wise) geometry operations Before the 2.0 release, Shapely only provided an interface for scalar (individual) geometry objects. Users had to loop over individual geometries within an array of geometries and call scalar methods or properties, which is both more verbose to use and has a large performance overhead. Shapely 2.0 API changes (deprecated in 1.8) The Shapely 1.8 release included several deprecation warnings about API changes that would happen in Shapely 2.0 and that can be fixed in your code (making it compatible with both <=1.8 and >=2.0). See Migrating to Shapely 1.8 / 2.0 for more details on how to update your code. It is highly recommended to first upgrade to Shapely 1.8 and resolve all deprecation warnings before upgrading to Shapely 2.0. Summary of changes: Geometries are now immutable and hashable. Multi-part geometries such as MultiPolygon no longer behave as “sequences”. This means that they no longer have a length, are not iterable, and are not indexable anymore. Use the .geoms attribute instead to access individual parts of a multi-part geometry. Geometry objects no longer directly implement the numpy array interface to expose their coordinates. To convert to an array of coordinates, use the .coords attribute instead (np.asarray(geom.coords)). The following attributes and methods on the Geometry classes were previously deprecated and are now removed from Shapely 2.0: array_interface() and ctypes asShape(), and the adapters classes to create geometry-like proxy objects (use shape() instead). empty() method source: Version 2.x — Shapely 2.0.0 documentation

Landsat Next is on the horizon—the new mission will not only ensure continuity of the longest space-based record of Earth’s land surface, it will fundamentally transform the breadth and depth of actionable information freely available to end users. Landsat Next will also provide new capabilities for the next generation of Landsat users. The enhanced spatial and temporal resolution of the 26-band “superspectral” Landsat Next constellation will unlock new applications for water quality, crop production and plant stress, climate and snow dynamics, soil health and other essential environmental variables. Landsat Next also continues Landsat’s decades-long data record of multispectral imagery, which affords global, synoptic, and repetitive coverage of Earth’s land surfaces at a scale where natural and human-induced changes can be detected, differentiated, characterized, and monitored over time. Landsat Next Defined Landsat Next will be a constellation of three observatories sent into orbit on the same launch vehicle, which will provide an improved temporal revisit for monitoring dynamic land and water surfaces such as vegetation, wildfire burns, reservoirs and waterways, coastal and wetland regions, glaciers, and dynamic ice sheets. Landsats 8 and 9 measure 11 spectral bands from the visible to thermal infrared wavelengths. Landsat Next will have 26 bands; this includes refined versions of the 11 Landsat “heritage” bands, five bands with similar spatial and spectral characteristics to the European Space Agency’s Copernicus Sentinel-2 bands to allow easier merging of data products, and ten new spectral bands to support emerging Landsat applications. With these improvements, Landsat Next will collect on average about 20 times more data than its predecessor, Landsat 9, and continue to provide free and open data access for all users. The mission is planned to launch in late 2030. The Path to Landsat Next Following the successful launch of Landsat 8 and during the development of Landsat 9, the United States Geological Survey (USGS) and NASA assembled a team of experts from within both agencies for a Joint Agency Sustainable Land Imaging Architecture Study Team to evaluate how to inform an acquisition strategy for a follow-on mission that would best satisfy the diverse and evolving user needs collect by the USGS (Wu et al., 2019). The highest-recommended architecture was a small constellation of “superspectral” space-based sensors that would improve the spectral, spatial, and temporal capabilities. Landsat Next data would be sufficiently consistent with data from the earlier Landsat missions to permit studies of land cover and land use change over multi-decadal period. Why Landsat Next Landsat is a civilian satellite program that was initiated to map, monitor, and manage Earth’s natural resources. It has provided an unbiased and unvarnished history of the planet and its changing conditions during the past half-century. Landsat data are critical for mapping natural resources and impact numerous society benefits such as food security, water use, disaster response and more. Landsat also provide essential data for monitoring the ecosystems, water quality, land cover and land use change, and an unparalleled data record of the environment and climate change. Landsat has been the cornerstone of Earth observing for more than half a century, and Landsat Next will add to this record for the next generation: Landsat has been ranked as a top Earth-observation program in terms of societal benefits provided, along with GPS and weather satellites according to the 2014 National Science and Technology Council report. Landsat is the most widely used land remote sensing data source within Federal civil agencies. Commercial providers rely on Landsat’s rigorous calibration to build/improve products. Landsat has been an essential data source for a wide range of Earth science research. Landsat is the most cited Earth-observation data set within the scientific literature (Wulder et al., 2022). Landsat Next will provide enhancements to Landsat “heritage” data: Improved temporal revisit for monitoring dynamic land and water surfaces such as vegetation and crop phenology, burn severity, water use and quality, coastal and wetland change, glacier, and ice sheet dynamics. Improved spatial resolution for agricultural monitoring, ecological monitoring, urban studies, water resources management and other applications. Landsat Next will provide new capabilities for the next generation of Landsat users: New spectral bands and refined bands will support new and evolving applications, including surface water quality, cryospheric science, geology, and agricultural applications including crop management and water consumption. The new bands will have similar spatial/spectral characteristics to those of the European Space Agency’s Copernicus Sentinel-2 satellite, to allow easier merging of data products. source: Landsat Next | Landsat Science (nasa.gov)

This removal includes all Collection 1 Level-1, Level-2, Level-3, and ESPA- related Landsat 1-8 products. Collection 1 has not been updated with Landsat products since December 31, 2021 and does not include Landsat 9 data. Users are encouraged to migrate their workflow to Landsat Collection 2 as soon as possible. Due to advancements in data processing and algorithm development, users are discouraged from using Collection 1 and Collection 2 interchangeably within the same workflow. Landsat Collection 2 was first made available in 2020, marking the second major reprocessing of the Landsat Archive by the USGS. The effort harnessed recent advancements in data processing, algorithm development, and data access and distribution capabilities to substantially enhance Landsat data products. The collection includes Landsat Level-1 data for all sensors since 1972 as well as global Level-2 surface reflectance and surface temperature scene-based products from 1982 to present. source: https://www.usgs.gov/landsat-missions/news/landsat-collection-1-datasets-be-removed-december-30-2022

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Black Friday is here, despite the inflation. All the developers and designers who are looking for something here is a curated list. https://github.com/trungdq88/Awesome-Black-Friday-Cyber-Monday Hurry up !!

Good news because I've been waiting for it since a long time. I have already tried it but I was really disappointed. "Input" from merginmap is really far more efficient than QField. I've been using this tool for 2 years now and it's really powerful.

Amazing dude , thanks for shared, regards.

QField’s main new feature of this 2.5 release cycle is its brand new elevation profiling functionality which has been added to the measuring tool. Users are now able to dynamically build and analyze elevation profiles wherever they are – in the field or on their desktop – by simply drawing paths onto their maps and projects. This is a great example of QField’s capability at bringing the power of QGIS through a UI that keeps things simple and avoids being in your way until you need it. Oh and while we’re speaking of the measuring tool, check out the new azimuth measurement! This new version also brings multi-column support to feature forms. QField now respects the number of columns set by users in the attributes’ drag and drop designer while building and tweaking projects in QGIS. The implementation will take into account the screen availability and on narrow devices will revert to a one-column setup. Pro tip: try to change the background color of your individual groups to ease understanding of the overall feature form. Another highlight of this release is a brand new screen lock action that can be triggered through QField’s main menu found in the side dashboard or in the map canvas menu shown when long pressing on the map itself. Once activated, QField will become unresponsive to touch and mouse events while keeping the display turned on. When locked, QField also hides tool buttons which results in a more complete view of the map extent. Stability improvements As with every release, our ninjas have been spending time hunting nasty bugs and improving stability and QField 2.5 is no exception. In particular, the feature form should feel more reliable and even more polished. sites: QField - Efficient field work built for QGIS