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  12. For most uses, Google Maps is a flat, 2D app, and if your device can handle more graphics and a bit more data, you can fire up the Google Earth 3D data set and get 3D buildings. At Google I/O Google has announced a new level that turns the graphics slider way, way up on Google Maps: Immersive View. When exploring an area in Google Maps, the company says Immersive View will make it "feel like you’re right there before you ever set foot inside." The video for this feature is wild. It basically turns Google Maps into a 3D version of SimCity with AAA video game graphics. There are simulated cars that drive through the roads, and birds fly through the sky. Clouds pass overhead and cast shadows on the world. The weather is simulated, and water has realistic reflections that change with the camera. London even has an animated Ferris wheel that spins around. Google can't possibly be tracking things like the individual positions of birds (yet!), but a lot of this is real data. The cars represent the current traffic levels on a given street. The weather represents the actual weather, even for historical data. The sun moves in real time with the time of day. Another part of the video shows flying into a business that also has a whole 3D layout. All of this is possible thanks to combining the massive data sets from Google Maps, Google Earth, and Street View, but even then, this level of fidelity will be very limited by the initial data sets. Google says that at first, Immersive View will "start... rolling out in Los Angeles, London, New York, San Francisco, and Tokyo later this year with more cities coming soon." The company says that "Immersive view will work on just about any phone and device," but just like the 3D building mode, this will be an optional toggle.
  13. Massive earthquakes don’t just move the ground — they make speed-of-light adjustments to Earth’s gravitational field. Now, researchers have trained computers to identify these tiny gravitational signals, demonstrating how the signals can be used to mark the location and size of a strong quake almost instantaneously. It’s a first step to creating a very early warning system for the planet’s most powerful quakes, scientists report May 11 in Nature. Such a system could help solve a thorny problem in seismology: how to quickly pin down the true magnitude of a massive quake immediately after it happens, says Andrea Licciardi, a geophysicist at the Université Côte d’Azur in Nice, France. Without that ability, it’s much harder to swiftly and effectively issue hazard warnings that could save lives. As large earthquakes rupture, the shaking and shuddering sends seismic waves through the ground that appear as large wiggles on seismometers. But current seismic wave–based detection methods notoriously have difficulty distinguishing between, say, a magnitude 7.5 and magnitude 9 quake in the few seconds following such an event. That’s because the initial estimations of magnitude are based on the height of seismic waves called P waves, which are the first to arrive at monitoring stations. Yet for the strongest quakes, those initial P wave amplitudes max out, making quakes of different magnitudes hard to tell apart. But seismic waves aren’t the earliest signs of a quake. All of that mass moving around in a big earthquake also changes the density of the rocks at different locations. Those shifts in density translate to tiny changes in Earth’s gravitational field, producing “elastogravity” waves that travel through the ground at the speed of light — even faster than seismic waves. Such signals were once thought to be too tiny to detect, says seismologist Martin Vallée of the Institut de Physique du Globe de Paris, who was not involved in the new study. Then in 2017, Vallée and his colleagues were the first to report seeing these elastogravity signals in seismic station data. Those findings proved that “you have a window in between the start of the earthquake and the time at which you receive the [seismic] waves,” Vallée says. But researchers still pondered over how to turn these elastogravity signals into an effective early warning system. Because gravity wiggles are tiny, they are difficult to distinguish from background noise in seismic data. When scientists looked retroactively, they found that only six mega-earthquakes in the last 30 years have generated identifiable elastogravity signals, including the magnitude 9 Tohoku-Oki earthquake in 2011 that produced a devastating tsunami that flooded two nuclear power plants in Fukushima, Japan (SN: 3/16/11). (A P wave–based initial estimate of that quake’s magnitude was 7.9.) That’s where computers can come in, Licciardi says. He and his colleagues created PEGSNet, a machine learning network designed to identify “Prompt ElastoGravity Signals.” The researchers trained the machines on a combination of real seismic data collected in Japan and 500,000 simulated gravity signals for earthquakes in the same region. The synthetic gravity data are essential for the training, Licciardi says, because the real data are so scarce, and the machine learning model requires enough input to be able to find patterns in the data. Once trained, the computers were then given a test: Track the origin and evolution of the 2011 Tohoku quake as though it were happening in real time. The result was promising, Licciardi says. The algorithm was able to accurately identify both the magnitude and location of the quake five to 10 seconds earlier than other methods. This study is a proof of concept and hopefully the basis for a prototype of an early warning system, Licciardi says. “Right now, it’s tailored to work … in Japan. We want to build something that can work in other areas” known for powerful quakes, including Chile and Alaska. Eventually, the hope is to build one system that can work globally. The results show that PEGSNet has the potential to be a powerful tool for early earthquake warnings, particularly when used alongside other earthquake-detection tools, Vallée says. Still, more work needs to be done. For one thing, the algorithm was trained to look for a single point for an earthquake’s origin, which is a reasonable approximation if you’re far away. But close-up, the origin of a quake no longer looks like a point, it’s actually a larger region that has ruptured. If scientists want an accurate estimate of where a rupture happened in the future, the machines need to look for regions, not points, Vallée adds. Bigger advances could come in the future as researchers develop much more sensitive instruments that can detect even tinier quake-caused perturbations to Earth’s gravitational field while filtering out other sources of background noise that might obscure the signals. Earth, Vallée says, is a very noisy environment, from its oceans to its atmosphere. “It’s a bit the same as the challenge that physicists face when they try to observe gravitational waves,” Vallée says. These ripples in spacetime, triggered by colossal cosmic collisions, are a very different type of gravity-driven wave (SN: 2/11/16). But gravitational wave signals are also dwarfed by Earth’s noisiness — in this case, microtremors in the ground.
  14. you want to combine? use merge in arctoolbox, you can merge all. or if you want to do it manually, just start editing, and then do it one by one select 2 lines and then with using edit tool, click merge
  15. How to combine multiple line feature into a single feature? How can this be done in ArcMap? Can only be selected and combined. But how to merge automatically? It doesn't dissolve
  16. all done, please be more active and to all, active is not only login and silently lurking around, active is post some stuff or reply topic
  17. Please activate my account. Thank you in advance!!
  18. To Admin, Please reactivate my account. Thank you
  19. Governments and businesses across the world are pledging to adopt more sustainable and equitable practices. Many are also working to limit activities that contribute to climate change. To support these efforts, Esri, the global leader in location intelligence, in partnership with Impact Observatory and Microsoft, is releasing a globally consistent 2017–2021 global land-use and land-cover map of the world based on the most up-to-date 10-meter Sentinel-2 satellite data. In addition to the new 2021 data, 10-meter land-use and land-cover data for 2017, 2018, 2019, and 2020 is included, illustrating five years of change across the planet. This digital rendering of earth’s surfaces offers detailed information and insights about how land is being used. The map is available online to more than 10 million users of geographic information system (GIS) software through Esri’s ArcGIS Living Atlas of the World, the foremost collection of geographic information and services, including maps and apps. “Accurate, timely, and accessible maps are critical for understanding the rapidly changing world, especially as the effects of climate change accelerate globally,” said Jack Dangermond, Esri founder and president. “Planners worldwide can use this map to better understand complex challenges and take a geographic approach to decisions about food security, sustainable land use, surface water, and resource management.” Esri released a 2020 global land-cover map last year as well as a high-resolution 2050 global land-cover map, showing how earth’s land surfaces might look 30 years from now. With the planned annual releases, users will have the option to make year-to-year comparisons for detecting change in vegetation and crops, forest extents, bare surfaces, and urban areas. These maps also provide insights about locations with distinctive land use/land cover, as well as human activity affecting them. National government resource agencies use land-use/land-cover data as a basis for understanding trends in natural capital, which helps define land-planning priorities and determine budget allocations. Esri’s map layers were developed with imagery from the European Space Agency (ESA) Sentinel-2 satellite, with machine learning workflows by Esri Silver partner Impact Observatory and incredible compute resources from longtime partner Microsoft. The Sentinel-2 satellite carries a range of technologies including radar and multispectral imaging instruments for land, ocean, and atmospheres, enabling it to monitor vegetation, soil and water cover, inland waterways, and coastal areas. “World leaders need to set and achieve ambitious targets for sustainable development and environmental restoration,” said Steve Brumby, Impact Observatory cofounder and CEO. “Impact Observatory [and] our partners Esri and Microsoft are once again first to deliver an annual set of global maps at unprecedented scale and speed. These maps of changing land use and land cover provide leaders in governments, industry, and finance with a new AI [artificial intelligence]-powered capability for timely, actionable geospatial insights on demand.” Esri and Microsoft have released this 10-meter-resolution time-series map under a Creative Commons license to encourage broad adoption and ensure equitable access for planners working to create a more sustainable planet. Users can manipulate the map layers and other data layers with GIS software to create more dynamic visualizations. In addition to being freely available in ArcGIS Online as a map service, these resources are also available for download and viewing. To explore the new 2021 global land-use/land-cover map, visit livingatlas.arcgis.com/landcover.
  20. Dear Admin, requesting to reactivate my account. Thank you.
  21. Landsat 9 Data Users Handbook Detailed Description The Landsat 9 Data Users Handbook provides an understanding and associated reference material for the Landsat 9 Observatory, the data acquired, and subsequent science products and processing systems. https://d9-wret.s3.us-west-2.amazonaws.com/assets/palladium/production/s3fs-public/media/files/LSDS-2082_L9-Data-Users-Handbook_v1.pdf
  22. I am returning back to GIS work, after many years off. Please, reactivate my account. Thank you.
  23. L3Harris Technologies third high-resolution weather instrument is set to launch March 1 onboard a NOAA satellite – strengthening the nation’s ability to monitor the environment and rapidly detect severe weather. The Advanced Baseline Imager (ABI) is the primary instrument for the Geostationary Operational Environmental Satellite-T (GOES-T), the third in a series of four advanced geostationary weather satellites with L3Harris’ ABI onboard. The ABIs are controlled by L3Harris’ enterprise ground system. The ABI provides high-resolution video of weather and environmental systems using 16 spectral bands delivering three times the amount of spectral coverage, four times the resolution and five times faster than the previous generation of GOES satellites. The Advanced Baseline Imagers on NOAA’s two current geostationary operational satellites, GOES-East and GOES-West, enable more accurate meteorological forecasts, greater ability to study and monitor climate change, and allow experts to provide early warnings of severe weather conditions such as tornadoes, wildfires, and hurricanes. “L3Harris’ ABI has helped NOAA improve detection of wildfires, tornadoes and other extreme events that threaten lives,” said Rob Mitrevski, Vice President and General Manager, Spectral Solutions, Space and Airborne Systems, L3Harris. “We have been pioneers in space-based weather monitoring for more than 60 years and continue to set a high standard of capability with our Advanced Baseline Imager. We look forward to driving further forecasting advancements, as we continue our collaborative partnership with NOAA into the future.” The company also announced the delivery of its fourth imager to NASA in late 2021. The fourth and final ABI was integrated into the GOES-U satellite last month and is slated to launch in 2024. GOES-U will complete NOAA’s GOES-R series of advanced geostationary weather sensors and provides the groundwork for future Geostationary Extended Observations (GeoXO) imager programs, currently in the Phase A Formulation stage, with L3Harris underway with the next generation geostationary imager concept design.
  24. At this time, USGS Landsat 9 Collection 2 Level-1 and Level-2 data will be made available for download from EarthExplorer, Machine to Machine (M2M), and LandsatLook. Initially, USGS will provide only full-bundle downloads. USGS will provide single band downloads and browse images, and Landsat 9 Collection 2 U.S. Analysis Ready Data shortly thereafter. Commercial cloud data distribution will take 3-5 days to reach full capacity. The recently deployed Landsat 9 satellite passed its post-launch assessment review and is now operational. This milestone marks the beginning of the satellite’s mission to extend Landsat's unparalleled, 50-year record of imaging Earth’s land surfaces, surface waters, and coastal regions from space. Landsat 9 launched September 27, 2021, from Vandenberg Space Force Base in California. The satellite carries two science instruments, the Operational Land Imager 2 (OLI-2) and the Thermal Infrared Sensor 2 (TIRS-2). The OLI–2 captures observations of the Earth’s surface in visible, near-infrared, and shortwave-infrared bands, and TIRS-2 measures thermal infrared radiation, or heat, emitted from the Earth’s surface. Landsat 9 improvements include higher radiometric resolution for OLI-2 (14-bit quantization increased from 12-bits for Landsat 8), enabling sensors to detect more subtle differences, especially over darker areas such as water or dense forests. With this higher radiometric resolution, Landsat 9 can differentiate 16,384 shades of a given wavelength. In comparison, Landsat 8 provides 12-bit data and 4,096 shades, and Landsat 7 detects only 256 shades with its 8-bit resolution. In addition to the OLI-2 improvement, TIRS-2 has significantly reduced stray light compared to the Landsat 8 TIRS, which enables improved atmospheric correction and more accurate surface temperature measurements. All commissioning and calibration activities show Landsat 9 performing just as well, if not better, than Landsat 8. In addition to routine calibration methods (i.e., on-board calibration sources, lunar observations, pseudo invariant calibration sites (PICS), and direct field in situ measurements), an underfly of Landsat 9 with Landsat 8 in mid-November 2021 provided cross-calibration between the two satellites’ onboard instruments, ensuring data consistency across the Landsat Collection 2 archive. Working in tandem with Landsat 8, Landsat 9 will provide major improvements to the nation’s land imaging, sustainable resource management, and climate science capabilities. Landsat’s imagery provides a landscape-level view of the land surface, surface waters (inland lakes and rivers) and coastal zones, and the changes that occur from both natural processes and human-induced activity. “Landsat 9 is distinctive among Earth observation missions because it carries the honor to extend the 50-year Landsat observational record into the next 50 years,” said Chris Crawford, USGS Landsat 9 Project Scientist. Partnered in orbit with Landsat 8, Landsat 9 will ensure continued eight-day global land and near-shore revisit.” Since October 31, 2021, Landsat 9 has collected over 57,000 images of the planet and will collect approximately 750 images of Earth each day. These images will be processed, archived, and distributed from the USGS Earth Resources Observation and Science (EROS) Center in Sioux Falls, South Dakota. Since 2008, the USGS Landsat Archive has provided more than 100 million images to data users around the world, free of charge. Landsat 9 is a joint mission between the USGS and NASA and is the latest in the Landsat series of remote sensing satellites. The Landsat Program has been providing global coverage of landscape change since 1972. Landsat’s unique long-term data record provides the basis for a critical understanding of environmental and climate changes occurring in the United States and around the world. Data Availability Learn more about Landsat 9 data access Visit the Landsat 9 webpages to learn more about the latest mission: USGS Landsat 9 NASA Landsat 9
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