Leaf_Drop_Sites

The National Flood Hazard Layer (NFHL) dataset represents the current effective flood risk data for those parts of the country where maps have been modernized by the Federal Emergency Management Agency (FEMA). The data in this service was published by FEMA as of July 18, 2025 (Latest Study Effective Date = 07/08/2025; Latest LOMR Effective Date = 07/09/2025). Also see the Feature Service and Tile service. See full details.

Overview This layer shows the grasslands priority conservation areas (GPCAs) within North America's Central Grasslands, an ecosystem considered among the most threatened on the continent and the world. GPCAs are areas of tri-national importance due to their ecological significance and threatened nature, which require international cooperation for their successful conservation. This layer is part of the North American Environmental Atlas, produced through a collaboration between the national atlas programs of Canada, Mexico, and the United States, in partnership with the Commission for Environmental Cooperation (CEC). The 55 original GPCAs were identified in 2004 by 36 experts from Canada, Mexico, and the United States, during a workshop co-organized by the CEC and The Nature Conservancy (TNC). In 2010, the Rocky Mountain Bird Observatory (RMBO) updated the dataset using national and international land cover, elevation, habitat, species, and bird survey data, bringing the total to 59 GPCAs. Each area was scored and ranked based on its importance to key grassland species and the rate at which its habitat was being lost. Geographic Coverage This layer covers the Central Grasslands ecosystem of North America, spanning parts of Canada, Mexico, and the United States. Data Sources and Licensing This dataset draws on more than 120 physical, biological, and social data sets from federal, state, and provincial governments, engineering and environmental firms, universities, industries, and conservation organizations, including USGS land cover and elevation layers, USGS Breeding Bird Surveys and Christmas Bird Counts, RMBO bird and vegetation surveys, and Canadian Wildlife Service bird surveys. Further detail on the selection methodology is available in the North American Grassland Priority Conservation Areas: Technical Report and Documentation. This material is licensed under CC BY 4.0, allowing non-exclusive rights to distribute, remix, adapt, and build upon the material in any medium or format, including for commercial purposes, so long as attribution is given to the creator. Update frequency: Not planned Limitations of use: None. Acknowledgement of the Commission for Environmental Cooperation, the Rocky Mountain Bird Observatory, and (or) the Nature Conservancy would be appreciated in products derived from these data. Vintage: 2010 Applications (Intended Use) Conservation planning and priority-setting for grassland habitats across North America. Biodiversity research and monitoring of grassland-dependent species. Cross-border collaboration in the conservation of shared grassland ecosystems. Land use and natural resource management, including habitat protection. Integration with other thematic layers in the North American Environmental Atlas for continental-scale analysis. Supporting environmental cooperation and policy-making among Canada, Mexico, and the United States. Files Download

GLIDEnumbers are GLobal unique IDEntifiers for Disasters. Each disaster is registered in a record that contains a GLIDEnumber that uniquely identifies it and allows information to be interoperable across multiple disaster information sources, both structured and textual. Accessing disaster information can be a time consuming and laborious task. Not only is data scattered but frequently identification of the disaster can be confusing in countries with many disaster events and across borders. To address both of these issues, Asian Disaster Reduction Center (ADRC) proposed a globally common Unique ID code for disasters. Among the institutions using actively GLIDEnumbers are UN-OCHA (ReliefWeb, FSCC, HDX), UNDRR, UNDP, WMO, IFRC, FAO, the European Commission and the Centre for Research on the Epidemiology of Disasters (CRED), among many others. Country datasets are only produced for countries with at least one GLIDE event since 1 January 2022. The global dataset contains all events available from the GLIDE API, including those not assigned to a country.

Dates of Images: 20220422T1234, 20220427T1242, 20220501T0015, 20220504T1234, 20220509T1242, 20220516T1234, 20220528T1234 (GMT) (YYYYMMDD: HHMM) Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at the Jet Propulsion Laboratory, California Institute of Technology produced flood mapping products using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) dataset. These products provide a rapid assessment of surface water extent to support emergency response and situational awareness during flood events. The dataset provided includes three products: Surface Water Extent maps on individual dates Water Gain maps, showing areas where water increased between two dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Pre-event image: April 22, 2022 Flood images: April 27, 2022, May 01, 2022, May 05, 2022, May 16, 2022, May 28, 2022 Products are generated from OPERA DSWx-S1 satellite imagery and mosaicked across tiles to provide continuous coverage. Product Description: Surface water is identified from Synthetic Aperture Radar (SAR) satellite imagery and mapped at 30 m spatial resolution. Maximum Surface Water Extent maps show all locations where water was detected at any time during the analysis period. Caveats and Limitations: Detecting inundation under vegetation, in the urban perimeter, in arid environments, and along water body edges is known to be challenging. The local accuracy of the flood maps in such environments may be impacted. These results are intended to support rapid emergency response. All information is provisional for use under emergency response guidelines. These data are provided with absolutely no warranty of any kind. Use at your own risk. Suggested Use: The OPERA DSWx-S1 Water product classifies the Sentinel-1 (S1) input imagery into "not water", "open surface water", and "inundated vegetation”, masks include Height Above Nearest Drainage (HAND) mask and layover/shadow mask), or no data classes. Water (WTR) Layer Values: File names:, OPERA_L3_DSWX-S1_V1_WTR_20220528T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220516T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220509T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220504T1234_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220501T0015_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220427T1242_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_mosaic.tif 0: Not Water - an area with valid data that is not open water (class 1), inundated vegetation (class 3), height above nearest drainage masked (class 250), or layover/shadow masked (class 251) (suggested color: #ffffff) 1: Open Water - an area that is entirely water and unobstructed to the sensor, including obstructions by vegetation, terrain, and buildings. (suggested color: #0000ff) 3: Inundated vegetation - an area that is considered inundated, extracted from the high value in dual polarization ratio and the wetland class in land cover map. (suggested color: #00ff00) 250: Height Above Nearest Drainage (HAND) masked - an area where topographic height is higher than the HAND threshold (suggested color: #c8c8c8) 251: Layover/shadow masked - an area identified as layover or shadow computed from the geometry of the digital elevation model and sensor. The area is directly copied from input burst RTC-S1 products (suggested color: #808080) 255: No data (suggested color: transparent) Maximum Water Extent Layer Values: The maximum water extent observed during the event was created by aggregating OPERA DSWx-S1 water products. File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220601T0007_max_extent.tif 0: Not Water. No water was detected within the time period of the images. Masked pixels are set to No data. (suggested color: #ffffff) 1: Water - an area where open water or partial surface water was detected during the time period of the images. (suggested color: #ff15e4) Water Gain Layer Values: The water gain shows any location where there was a change from “not water” to “inundated vegetation”, “not water” to “open surface water”, or “inundated vegetation” to “open surface water" between two OPERA DSWx-S1 products. File names: ARIA-OPERA_L3_DSWX-S1_V1_WTR_20220422T1234_20220504T1234_water_gain.tif 0: No Change or Water Loss- an area that had no change (e.g., open water in both images) or water loss (e.g., open water to not water). Masked pixels are set to No data. (suggested color: #ffffff) 1: Water Gain - an area that gained water in the most recent image. This includes change from Not Water to Inundated Vegetation, Not Water to Open Water, and Inundated Vegetation to Open Water. (suggested color: #ff15e4) Credits: The product contains modified Copernicus Sentinel data, processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA/OPERA team. The DSWx products are produced as part of the OPERA project, which is funded by NASA to address remote sensing needs identified by the Satellite Needs Working Group, and managed by NASA's Jet Propulsion Laboratory. Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (bato@jpl.nasa.gov) Emre Havazli (emre.havazli@jpl.nasa.gov) Renato Frasson (renato.prata.de.moraes.frasson@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov ) Esri REST Endpoint: See URL on the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_opera_dswx_s1/MapServer/WMSServer

Preliminary NFHL data containing flood risks and regulatory flood determination data. This data is not yet effective.

Wisconsin Flood Risk Management Application spatial data map service.