DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landslide

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Service Description: <div style='text-align:Left;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Date of Images:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Dates used for landslide mapping: April 20, 2024; April 21, 2024; May 6, 2024; May 7, 2024; May 8, 2024<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Dates of Planet Imagery: 4/20/2023, 5/6/2024, 5/7/2024<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Summary:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>The NASA GSFC landslides team manually mapped landslide initiation points after the April 29, 2024 heavy rainfall in Rio Grande do Sul, Brasil. The landslide initiation points were derived from PlanetScope imagery. This is only a portion of the region where landslides occurred, and areas covered with clouds were not included. More landslides will be mapped in coming days.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>NOTE: This is a rapid response product. These landslides were manually mapped using different dates of PlanetScope imagery, but all are presumed to have been triggered by the 4/29/2024 heavy rainfall event. As clouds cleared, more landslides were identified.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>This PlanetScope imagery captured by Planet Labs Inc. in May 2024 shows landslides following the heavy rainfall in Brasil. True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB s produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Suggested Use:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>True Color RGB provides a product of how the surface would look to the naked eye from space. The True Color RGB is produced using the 3 visible wavelength bands (red, green, and blue) from the respective sensor. Some minor atmospheric corrections have occurred.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Satellite/Sensor:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>PlanetScope<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Resolution:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>3 meters<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Credits:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>NASA Disasters Program, NASA GSFC, Includes copyrighted material of Planet Labs PBC. All rights reserved.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'><p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>Esri REST Endpoint:<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>See Layers below.<p style='box-sizing:border-box; border-width:0px; border-style:solid; border-color:currentcolor; margin:0px 0px 1rem; color:rgb(74, 74, 74); font-family:"Avenir Next", Avenir, "Helvetica Neue", sans-serif; font-size:16px;'>WMS Endpoint:<a href='https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landslide_points/MapServer/WMSServer' target='_blank'>https://gis.earthdata.nasa.gov/gis05/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landslide_points/MapServer/WMSServer</a></div>

Map Name: landslide_points

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brasil_landslides (0)

Description: The Cooperative Open Online Landslide Repository (COOLR) contains citizen science data from Landslide Reporter Catalog (LRC), data from NASA’s Global Landslide Catalog (GLC), NASA manually or automatically digitized landslides, and other inventories contributed by the research community. These are sorted into two main layers, "coolr_reports" and "coolr_events". The layers are further differentiated into a point or polygon layer, named accordingly. Within these layers, the user can further query out the manual or automated landslide inventories, events of a certain date, event triggers, and more. Each feature has a “title” in the attribute table with the digitization method, location, and event date (written as YYYY-MM-DD). The citation for each event inventory is located within the attribute table field “citation”. See the methods section for further detail about manual vs automatic landslide detection. For more information about the fields, see the How-to-Guide documentation under the “Trainings” tab at https://landslides.nasa.gov and the publications below. The citation for each event inventory is located within the attribute table field “citation”. If you utilize this inventory, please reference each citation of the event(s) used. For example, if you use the entire inventory layer, please reference all the event citations contained within the layer. If you use just the events past a certain date, or another subset of the layer, please query those citations out and reference those. In addition, a CSV containing all citations can be found on the download page: https://maps.nccs.nasa.gov/arcgis/apps/MapAndAppGallery/index.html?appid=574f26408683485799d02e857e5d9521. Methods We use 'landslide' as a general term to represent all event types. The catalog differentiates between landslide types when the information is available in the ls_type field. Manually digitized landslides (method = Manual): These are hand-digitized landslide points or polygons, created by NASA scientists or contributed by other institutions. They are created on a case-by-case basis, depending on time and resources, or if there is an event where a partner requests it. The ability to hand-digitize depends on the availability of high-resolution cloud-free imagery, ideally before and after the event. Depending on the event size, location, and the satellite overpass, imagery from multiple dates may be used. For points, the scientist tries to identify where the initiation zone of each landslide is using an elevation layer. For polygons, the initiation zone is not differentiated. Automatically digitized landslides (method = Automatic): The open-source Semi-Automatic Landslide Detection (SaLaD) system was created to rapidly map landslides. SALaD uses object-based image analysis and machine learning to detect landslides from optical imagery. To successfully detect landslides, cloud-free imagery from before and after an event is needed, in addition to training data from that region or a region nearby. The raw polygon output of this system can be useful for situational awareness, but it will require manual corrections to weed out false positives for other use cases. Once that is done, initiation points can be created using a DEM. For Further Reference Landslides.nasa.gov Amatya, P., Kirschbaum, D., Stanley, T., and Tanyas, H. (2021). Landslide mapping using object-based image analysis and open source tools. Engineering Geology. 282. doi: 10.1016/j.enggeo.2021.106000. Amatya, P., Kirschbaum, D., and Stanley, T. (2021). Rainfall-induced landslide inventories for Lower Mekong based on Planet imagery and a semi-automatic mapping method. Geoscience Data Journal. doi: 10.1002/gdj3.145. Juang CS, Stanley TA, and Kirschbaum DB (2019) Using citizen science to expand the global map of landslides: Introducing the Cooperative Open Online Landslide Repository (COOLR). PLOS ONE. 14(7): e0218657. doi: 1371/journal.pone.0218657. Kirschbaum, D.B., Stanley, T., & Zhou, Y. (2015). Spatial and temporal analysis of a global landslide catalog. Geomorphology, 249, 4-15. doi:10.1016/j.geomorph.2015.03.016 Kirschbaum, D.B., Adler, R., Hong, Y., Hill, S., & Lerner-Lam, A. (2010). A global landslide catalog for hazard applications: method, results, and limitations. Natural Hazards, 52, 561-575. doi:10.1007/s11069-009-9401-4

Service Item Id: 428c387d16264757b17126b462de9a6d

Copyright Text: NASA Disasters Program, NASA GSFC, Includes copyrighted material of Planet Labs PBC. All rights reserved.

Spatial Reference: 4326 (4326) LatestVCSWkid(0)

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Child Resources: Info Dynamic Layer

Supported Operations: Export Map Identify QueryLegends QueryDomains Find Return Updates

DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landslide_points (MapServer)