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  2. link: https://press.anu.edu.au/publications/new-releases
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  5. please share ERDAS IMAGINE 208 or 2020

    with regards


    1. mhmdiarto


      i do not have...sorry

  6. A possible design flaw has surfaced by DJI Mavic Mini owners experiencing the propellers rubbing against the drone‘s body due to the lightweight and flexible design of the arms. It looks to be a known problem with people already working on fixes for it. Images have appeared on DJI’s community website with a user posting images of their Mavic Mini with what looks be marks caused by the propellers contacting the body. The user had shared that they recently started to notice the front set of propellers tend to hit the drone body, even if new ones were put on. He also stated it was more likely to happen when the drone is in sport mode. It looks like the cause of the problem is the flexibility in the arms used due to the weight restrictions DJI was able to keep within. The arms can flex due to the torque of the motors, causing the propellers to get closer to the drone body, and therefore rub against it. It looks to be a known problem for some as a company has already produced prop mounts that raise the height of the propellers just enough to clear the body fully. There are also designs on Thingeverse that replace the soft foam inserts in the arms with stiff 3D printed plastic. Both of these options will likely set the Mavic Mini over the 250-gram weight limit. source: https://dronedj.com/2020/03/24/dji-mavic-mini-design-flaw-pops-hit-done-body/
  7. preciso de ajuda para trabalhar operaction Dashbord ArcGis ja crie a conta esri mais não me deixa usar operaction Dashbord ArcGis
  8. The Area, and SphericalArea, functions are to be used on lat/long data. Here you are using degrees for coordinates CartesianArea is to be used on projected data, that's typically data stored in a local (cartesian) projection. Here you would be using meters for coordinates.
  9. Earlier
  10. Five new remote-sensing satellites were sent into planned orbit from the Jiuquan Satellite Launch Center in northwest China's Gobi Desert Thursday. The five satellites were launched by a Long March-11 carrier rocket at 2:42 p.m. (Beijing Time). The satellites belong to a commercial remote-sensing satellite constellation project "Zhuhai-1," which will comprise 34 micro-nano satellites, including video, hyperspectral, and high-resolution optical satellites, as well as radar and infrared satellites. The carrier rocket was developed by the China Academy of Launch Vehicle Technology, and the satellites were produced by the Harbin Institute of Technology and operated by the Zhuhai Orbita Aerospace Science and Technology Co. Ltd. Thursday's launch was the 311th mission for the Long March series carrier rockets. The newly launched satellites comprise four hyperspectral satellites with 256 wave-bands and a coverage width of 150 km, and a video satellite with a resolution of 90 centimeters. The Zhuhai-1 hyperspectral satellites have the highest spatial resolution and the largest coverage width of their type in China. The data will be used for precise quantitative analysis of vegetation, water and crops, and will provide services for building smart cities, said Orbita, the largest private operator of hyperspectral satellites in orbit. The company aims to cooperate with government organizations and enterprises to expand the big data satellite services. source: https://www.spacedaily.com/reports/China_launches_new_remote_sensing_satellites_999.html
  11. I think is related to the two main option for surfaces calculus from MI. They are exposed , as an example, at general settings in older MI: you have the option to calculate a surface in "cartesian" or "spherical" . In the new versions this is more hidden. In your case, I think that you are working in a long/lat system, perhaps WGS84; this one is entering in the so called spherical calculus, and you have this as implicit (the screen capture). The cartesian calculus are exposed as options. You must chose, evaluate carefully what you need, what you are targeting in the project. You will make unhappy an engineer if you are offering him a map with degrees... m.....seconds. In reverse, a sailor if you are offering him metric coordinates....
  12. sorry i cant see your picture, our country block imgur, really suck 😷
  13. Thank Pro, Is here, but i can't insert picture: https://imgur.com/a/wejXC97
  14. did you mean for function area is Spherical function area?
  15. Thanks for sharing, it is possible to share again, there is no access to the page. Someone has the models that can provide them.
  16. When we are use function area and When we are use function Cartesian area in the mapinfo . Help me please !
  17. 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
  18. 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
  19. Hi Dante, Welcome to Gis-Area !
  20. LuthfilB43


  21. Hi everyone, my names is Jorge Galván and I'm from México. I hope to contribute to this forum. I'm student of Geomatic Engineer. My best wishes to all. Greetings.🤙
  22. Would you please reactivate my account. Have been away for a while.
  23. Hi mhmdiart, I wish you could share the Erdas 2018 program with your medicine, I would really appreciate it. Cheers

  24. 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
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