Mexico environment data

Dates of Images: July 9, 2025 Date of Next Image: None Expected Summary: These maps show the results of a machine learning classification applied to UAVSAR data to identify open water flooding and inundation under tree canopy.  Colored areas in the image show detected flooding, where the color shows the type of landcover which was flooded (see legend below).  Non-flooded areas are transparent.  The classification uses a U-Net machine learning algorithm which was trained using UAVSAR data from previous flood events.  UAVSAR provides polarimetric synthetic aperture radar data from which different types of scattering mechanisms can be observed, which provides information on the type of flooding.  For example, flooding underneath vegetation produces strong double-bounce scattering from the water surface and tree trunks.  However, strong double-bounce scattering from urban areas aligned with the radar viewing direction, such as in Austin, TX, can produce erroneous classifications.  Non-flooded vegetation is generally dominated by volume scattering from the forest canopy.  In comparison, open water flooding exhibits weak radar returns in all polarizations. Suggested Use: Classified Images: Blue   = Open Water Yellow = Flooded Developed Green  = Flooded Vegetation Orange = Flooded Crop Satellite/Sensor: UAVSAR airborne L-band synthetic aperture radar (SAR) aboard a NASA Gulfstream C-20A jet. Resolution: 10 meters Credits: UAVSAR data courtesy of NASA/JPL-Caltech Esri REST Endpoint: See URL section on right side of the page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202507_FLOOD_TX/202507_UAVSAR/MapServer/WMSServer Data Download: https://uavsar.jpl.nasa.gov/cgi-bin/download-files.pl

Storm surge hazard is modeled only along the coastline. The process involves generating a grid along the coastline and 5km inland. In fact, no backwater effects were modeled, this is only due to the continent’s contour map (shapefile) version used to create the grid mentioned on the storm surge hazard map indicates the mean run-up height on the coast for seven return periods: 10, 25, 50, 100, 250, 500, 1000 years. The map has coastal coverage with points in the countries with storm surge hazard coastline. The data were classified into three hazard categories—low, moderate, and high—based on storm surge run-up heights for a 250-year return period, a widely used standard for coastal hazard zoning and infrastructure risk assessment. Run-up values below 0.1 meters are considered as “Low”; run-up values between 0.1 meters and 2 meters (inclusive) are considered as “Moderate”; run-up values greater than 2 meters are considered as “High”. In this project Mediterranean tropical-like cyclones were not included in the hazard assessment process. We considered only tropical cyclones as storms that develop in areas of low pressure over tropical oceans, and that are associated with several hazards such as strong winds and storm surge. These two hazards were assessed at a global level but given that although tropical cyclones are formed along the North Atlantic Ocean but do not occur in Europe, neither strong wings nor storm surge were modeled for European countries. Background paper: Multi-hazard Disaster Risk Model of Infrastructure and Buildings at the Global Level (2023). Cardona, O.D., Bernal, G.A., Villegas, C.P., Molina, J.F., Herrera, S.A., Marulanda, M.C., Rincón, D.F., Grajales, S., Marulanda, P.M., Gonzalez, D., Maskrey, A. (2023). https://giri.unepgrid.ch/sites/default/files/2023-11/2.4-INGENIAR-CDRI-Background-Report-Risk-model.pdf Release date: Fri Jun 30 2023 The layer was clipped to the geographic boundaries of 1) IDB Borrowing Member Countries, 2) Caribbean Development Bank (CDB) Borrowing Countries, 3) Organization of Eastern Caribbean States (OECS) Member Countries.

Date of Images: 05/18/2024 Summary: The visible-wavelength true color RGB digital camera images were taken by astronauts on board the International Space Station showing flooding in southeastern Texas. These images were manually georeferenced by members of the Earth Science and Remote Sensing Unit at NASA Johnson Space Center. Suggested Use: This image provides regional context, and may be useful for visualization of the ongoing event. Higher spatial resolution images may be suitable for spatial analysis to support decision making or research applications. Sensor: Nikon Z9 Electronic Still Camera. Additional Information about the astronaut photography from the ISS. Credits: International Space Station Program, NASA Johnson Space Center Earth Science and Remote Sensing Unit, ARES Division, Exploration Architecture, Integration & Science Directorate Data Download: Full datasets are available for download at the Gateway to Astronaut Photography of Earth. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=c9bb2094473649b2a3802305f4fc8eb1 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_TX/2408_iss/ImageServer/WMSServer

Date of Images Post-event: 2026-06-21, 2026-06-28 Summary: The Advanced Rapid Imaging and Analysis (ARIA) and Observational Products for End-Users from Remote Sensing Analysis (OPERA) teams at NASA's Jet Propulsion Laboratory (JPL) and the California Institute of Technology produced maps showing areas affected by flooding in Louisiana using the OPERA Dynamic Surface Water Extent from Sentinel-1 (DSWx-S1) product. These maps provide an initial view of the surface water extent observed following the flood event. The results presented here are preliminary and unvalidated, intended primarily to support situational awareness and field response efforts. The ARIA-Share platform emphasizes rapid dissemination of satellite-based products for disaster response. All information is provisional and should be used under emergency response guidelines. These data are provided without warranty of any kind. Use at your own risk. OPERA DSWx-S1 The OPERA DSWx-S1 was used to identify surface water for the flooding event. The images provided are a mosaic of OPERA DSWx-S1 products, producing a composite image for each date. The mosaicking applied prioritized pixels classified as open surface water to preserve water pixels in region of product granule overlap. The images are provided as GeoTIFF files. Water (WTR) Layer Description: Masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water and inundated vegetation), masks (HAND mask and layover/shadow mask), or no data classes. Water (WTR) and Binary Water (BWTR) Layer Values: 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). Masking can result in "not water" (class 0) where land cover masking is applied (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) Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A satellite. Resolution: 30 meters OPERA DSWx-S1 data availability The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20251012_Alaska_Floods/DSWx-S1/. The OPERA DSWx-S1 products have been in production since September 2024, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite. For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov. For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/. REST Endpoint: See URL on the right. Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (mary.grace.p.bato@jpl.nasa.gov) Ines Fenni (ines.fenni@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov) Renato Frasson (renato.prata.de.moraes.frasson@jpl.nasa.gov) Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2026), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The 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. NASA JPL-Caltech ARIA/OPERA Team ==================

Dates of Images: July 9, 2025 Date of Next Image: None Expected Summary: These maps show the results of a machine learning classification applied to UAVSAR data to identify open water flooding and inundation under tree canopy.  Colored areas in the image show detected flooding, where the color shows the type of landcover which was flooded (see legend below).  Non-flooded areas are transparent.  The classification uses a U-Net machine learning algorithm which was trained using UAVSAR data from previous flood events.  UAVSAR provides polarimetric synthetic aperture radar data from which different types of scattering mechanisms can be observed, which provides information on the type of flooding.  For example, flooding underneath vegetation produces strong double-bounce scattering from the water surface and tree trunks.  However, strong double-bounce scattering from urban areas aligned with the radar viewing direction, such as in Austin, TX, can produce erroneous classifications.  Non-flooded vegetation is generally dominated by volume scattering from the forest canopy.  In comparison, open water flooding exhibits weak radar returns in all polarizations. Suggested Use: Classified Images: Blue   = Open Water Red    = Flooded Developed Green  = Flooded Vegetation Orange = Flooded Crop Satellite/Sensor: UAVSAR airborne L-band synthetic aperture radar (SAR) aboard a NASA Gulfstream C-20A jet. Resolution: 10 meters Credits: UAVSAR data courtesy of NASA/JPL-Caltech Esri REST Endpoint: See URL section on right side of the page WMS Endpoint: https://maps.disasters.nasa.gov/ags03/services/texas_flood_202507/uavsar/MapServer/WMSServer Data Download: https://uavsar.jpl.nasa.gov/cgi-bin/download-files.pl

Índice de peligro por inundaciones a nivel municipal, elaborado por la Subdirección de Riesgos Hidrometeorológicos del CENAPRED.

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.

Date of Images: 20260706T0042, 20260718T0042 (UTC) (YYYYMMDD: HHMM) Date of Next Image: No additional images are being delivered 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 two products: Surface Water Extent maps on individual dates Water Gain maps, showing areas where water increased between two dates Dates and Input Data: Pre-event image: July 06, 2026 Post-event image: July 18, 2026 Products were generated using OPERA DSWx-S1 satellite imagery and mosaicked across tiles to provide continuous spatial 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. Additionally, certain pixels within this product have been manually reclassified as water after expert interpretation and direct comparison with the input SAR backscatter. 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: Water (WTR) Layer: The OPERA DSWx-S1 Water (WTR) 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. File names: OPERA_L3_DSWX-S1_V1_WTR_20260706T0042A_mosaic.tif OPERA_L3_DSWX-S1_V1_WTR_20260718T0042A_mosaic.tif WTR Layer Values: 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) Water Gain Layer: The water gain layer 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: OPERA_L3_DSWX-S1_V1_WTR_20260718T0042A_20260706T0042A_water_gain.tif Water Gain Layer Values: 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) Satellite/Sensor/Resolution: Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A/C/D satellites. Spatial Resolution: 30 meters Temporal Resolution: sub-daily to bi-weekly Methodology: DSWx-S1 Algorithm Theoretical Basis Document (ATBD): https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/web-misc/opera/atbd/D-108763_Rev_A_OPERA_DSWx_S1_NI_ATBD_20240530_SIGNED.pdf DSWx website: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite/ Detailed workflows and tools for the disaster products are on our public github page: https://github.com/OPERA-Cal-Val/disasters 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) Jungkyo Jung (jungkyo.jung@jpl.nasa.gov) Mary Grace Bato (bato@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov )

Date of Images Post-event: 2026-06-21 Pre-Event: 2026-06-09 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 two products: Surface Water Extent maps on individual dates Water Gain maps, showing areas where water increased between two dates These maps provide an initial view of the surface water extent observed following the flood event. The results presented here are preliminary and unvalidated, intended primarily to support situational awareness and field response efforts. The ARIA-Share platform emphasizes rapid dissemination of satellite-based products for disaster response. All information is provisional and should be used under emergency response guidelines. These data are provided without warranty of any kind. Use at your own risk. OPERA DSWx-S1 The OPERA DSWx-S1 was used to identify surface water for the flooding event. The images provided are a mosaic of OPERA DSWx-S1 products, producing a composite image for each date. The mosaicking applied prioritized pixels classified as open surface water to preserve water pixels in region of product granule overlap. The images are provided as GeoTIFF files. Water (WTR) Layer Description: Masked interpreted water classification layer. This represents pixel-wise classification into one of three water classes (not water, open water and inundated vegetation), masks (HAND mask and layover/shadow mask), or no data classes. Water (WTR) and Binary Water (BWTR) Layer Values: 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). Masking can result in "not water" (class 0) where land cover masking is applied (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) 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_20260621T0010A_20260609T0010A_water_gain.tif0: 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) Satellite/Sensor: Satellite/Sensor: Synthetic Aperture Radar (SAR) instrument on European Space Agency's (ESA) Sentinel-1A/C satellites. Spatial Resolution: 30 meters Temporal Resolution: sub-daily to bi-weekly Resolution: 30 meters OPERA DSWx-S1 data availability The post-processed products are available to download at https://aria-share.jpl.nasa.gov/20251012_Alaska_Floods/DSWx-S1/. The OPERA DSWx-S1 products have been in production since September 2024, are freely distributed to the public via NASA's Physical Oceanography Distributed Active Archive Center (PO.DAAC), and can be downloaded through NASA's Earthdata search. For more information about the Dynamic Surface Water eXtent product suite, please refer to the DSWx Product page: https://www.jpl.nasa.gov/go/opera/products/dswx-product-suite. For more information about the Caltech-JPL ARIA project, visit https://aria.jpl.nasa.gov. For more information about the JPL OPERA project, visit https://www.jpl.nasa.gov/go/opera/. REST Endpoint: See URL on the right. Product POCs: Cole Speed (cole.speed@jpl.nasa.gov) Mary Grace Bato (bato@jpl.nasa.gov) Alexander Handwerger (alexander.handwerger@jpl.nasa.gov ) Credits: Sentinel-1 data were accessed through the Copernicus Open Hub and the Alaska Satellite Facility server. The product contains modified Copernicus Sentinel data (2026), processed by the European Space Agency and analyzed by the NASA-JPL/Caltech ARIA and OPERA team. The 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. NASA JPL-Caltech ARIA/OPERA Team ==================

Obtained from FEMA's national Flood Hazard Layer. For viewing directly from FEMA, visit the NFHL Viewer. Last revised 5/16/2023.

Fort Bend County NFHL (National Flood Hazard Layer)

Dates of Images: Post-Event: July 18, 2026 Pre-Event: May 1 to July 1, 2026 Date of Next Image: Unknown Summary: We developed a rapid-response workflow to map flooded areas during this emergency event using multi-temporal Sentinel-1 SAR data. Sentinel-1’s SAR backscatter characteristics are particularly effective for detecting surface water: water surfaces typically exhibit low backscatter, whereas non-water areas show higher backscatter. Leveraging this physical property, we distinguished between water and non-water surfaces from both pre- and post-flood observations. To highlight flood-induced surface changes, we computed the differenced co-polarized VV backscatter (dVV = VV_post – VV_pre). This change detection technique enhances the visibility of newly inundated areas. We then applied a simple threshold to the dVV image to separate flooded from non-flooded areas. Suggested Use: The final output is a binary raster product, where pixels with a value of 1 represent flooded areas (dark blue color). A permanent water body layer and a binary layer incorporating land cover are also included. Satellite/Sensor: Sentinel-1 /Synthetic Aperture Radar (SAR) Resolution: 10 meters Credits: Dr. Khuong H. Tran (Khuong.tran@nasa.gov) Esri REST Endpoint: See URL section on right side of page

FEMA National Flood Hazard Layer with Flood Hazard Zones. For more information on FEMA Flood Zones visit https://www.fema.gov/glossary/flood-zones. Important: Only use this layer if needing to symbolize floodplains at a scale of 1:9,000 or larger. Not intended for use across large geographies. For better map rendering, use the FEMA_Flood_Hazard_Zones_Tiled service. Disclaimer: This product is for informational purposes only and may not be suitable for legal, engineering, or surveying purposes. It does not represent an official survey and represents only the approximate relative location of features and boundaries. Mapping may not necessarily reflect on-the-ground conditions. This product and those involved in its production make no claims as to the accuracy or reliability of the data, and neither assumes, nor will accept liability for their use.

The FIRM is the basis for floodplain management, mitigation, and insurance activities for the National Flood Insurance Program (NFIP). Insurance applications include enforcement of the mandatory purchase requirement of the Flood Disaster Protection Act, which "... requires the purchase of flood insurance by property owners who are being assisted by Federal programs or by Federally supervised, regulated or insured agencies or institutions in the acquisition or improvement of land facilities located or to be located in identified areas having special flood hazards, " Section 2 (b) (4) of the Flood Disaster Protection Act of 1973. In addition to the identification of Special Flood Hazard Areas (SFHAs), the risk zones shown on the FIRMs are the basis for the establishment of premium rates for flood coverage offered through the NFIP. The FIRM Database presents the flood risk information depicted on the FIRM in a digital format suitable for use in electronic mapping applications. The FIRM Database serves to archive the information collected during the Flood Risk Project.

The National Flood Hazard Layer (NFHL) data incorporates all Flood Insurance Rate Map (FIRM) databases published by the Federal Emergency Management Agency (FEMA), and any Letters Of Map Revision (LOMRs) that have been issued against those databases since their publication date. It is updated on a monthly basis. The FIRM Database is the digital, geospatial version of the flood hazard information shown on the published paper FIRMs. The FIRM Database depicts flood risk information and supporting data used to develop the risk data. The primary risk classifications used are the 1-percent-annual-chance flood event, the 0.2-percent-annual-chance flood event, and areas of minimal flood risk. The FIRM Database is derived from Flood Insurance Studies (FISs), previously published FIRMs, flood hazard analyses performed in support of the FISs and FIRMs, and new mapping data, where available. The FISs and FIRMs are published by FEMA. The NFHL is available as State or US Territory data sets. Each State or Territory data set consists of all FIRM Databases and corresponding LOMRs available on the publication date of the data set. The specification for the horizontal control of FIRM Databases is consistent with those required for mapping at a scale of 1:12,000. This file is georeferenced to the Earth's surface using the Geographic Coordinate System (GCS) and North American Dataum of 1983 (NSRS-2007).

Subset of the National Flood Hazard Layer (NFHL) services for when FEMA's official REST service is down.  Downloaded as needed from the National Flood Hazard Layer Status page, re-projected to Texas State Plane S Central, then published to Harris County Engineering ArcGIS Server.

Areas of New Orleans that are known to experience flooding during high rainfall rate events. These areas were created from FEMA Special Flood Hazard Areas and mimic the previous Ponding Areas produced by the agency. Property owners should take extra precautions in these areas and remain vigilant when the city is experiencing heavy rainfall rates.  Reconsider parking in these areas during rainy weather. Keep personal property (homes, vehicles, trailers, offices) protected by ensuring items are elevated off of the ground. Flooding can be experienced on any street in New Orleans given an extreme rainfall event. This map layer DOES NOT predict flooding in any part of New Orleans. This map layer should not be used as an indicator of future flooding. This layer is to be used as a reference for protecting property but not necessarily to determine flooding chances or insurance requirements. This dataset is derived from The National Flood Hazard Layer. The National Flood Hazard Layer (NFHL) is a digital database that contains flood hazard mapping data from FEMA’s National Flood Insurance Program (NFIP). This map data is derived from Flood Insurance Rate Map (FIRM) databases and Letters of Map Revision (LOMRs).The NFHL is for community officials and members looking to view effective regulatory flood hazard information in a Geographic Information Systems (GIS) application.

Obtained from FEMA's national Flood Hazard Layer. For viewing directly from FEMA, visit the NFHL Viewer. Last revised 5/16/2023. Shared in Internal Interactive Map/App

FEMA's National Flood Hazard Layer (NFHL) flood hazard zones for the Houston metropolitan area. Flood hazard zones are simplified and merged into the following categories:within the floodway (gold) 100-year (1% percent) flood zone (orange) 500-year (0.2% percent) flood zone (red) FEMA NFHL data was provided via the Texas Natural Resources Information System, and processed and styled by the Esri Story Maps team.

FEMA National Flood Hazard Layer Flood Hazard Zones. Map services is configured to be rendered at a scale of 1:145,000 or larger. Disclaimer: This product is for informational purposes only and may not be suitable for legal, engineering, or surveying purposes. It does not represent an official survey and represents only the approximate relative location of features and boundaries. Mapping may not necessarily reflect on-the-ground conditions. This product and those involved in its production make no claims as to the accuracy or reliability of the data, and neither assumes, nor will accept liability for their use.

FEMA National Flood Hazard Layer Floodplains. HARC Disclaimer: This product is for informational purposes only and may not be suitable for legal, engineering, or surveying purposes. It does not represent an official survey and represents only the approximate relative location of features and boundaries. Mapping may not necessarily reflect on-the-ground conditions. This product and those involved in its production make no claims as to the accuracy or reliability of the data, and neither assumes, nor will accept liability for their use.

Obtained from FEMA's national Flood Hazard Layer. For viewing directly from FEMA, visit the NFHL Viewer. Last revised 5/16/2023. Shared in Internal Interactive Map/App

Esta base de datos contiene la ubicación de los albergues temporales localizados en el estado de Jalisco, nombre del lugar, capacidad (en número de personas).

Esta base de datos contiene la ubicación de los albergues temporales localizados en el estado de Nayarit, nombre del lugar, capacidad (en número de personas).

Esta base de datos contiene la ubicación de los albergues temporales localizados en el estado de Colima, nombre del lugar, capacidad (en número de personas).

Áreas susceptibles a deslizamiento de laderas El mapa nacional de susceptibilidad a deslizamientos de laderas contempla una clasificación por pixel de cinco posible valores de acuerdo a la tabla siguiente: Valores de pixel Clasificación 1- Muy bajo 2- Bajo 3- Medio 4-Alto 5-Muy Alto

Fuente: Secretaría de Salud, Dirección General de Información en Salud. Formato de captación: Plataforma web y formatos Excel. Periodicidad de actualización: Anual. Es o no información oficial: Es información oficial. Contenido de la base de datos: La base de datos contiene información de los establecimientos en salud (unidades médicas, establecimientos de apoyo y de asistencias social), con datos de ubicación geográfica y domiciliaria, institución y tipo de establecimiento. Uso e interpretación de la información publicada: Identificación de la infraestructura en salud instalada a nivel nacional, orientada a la prestación de servicios de salud. Descripción de los catálogos auxiliares: Se utiliza el catálogo CLUES, el catálogo de instrumental y equipo del Consejo de Salubridad General.

Deslizamiento de laderas sin probabilidad de ocurrencia regionalizada en Baja California, Baja California Sur, Eje Neovolcánico, Golfo California, Chihuahua, Durango, Golfo Norte, Golfo de México, Pacífico Norte y Pacífico Sur.

Date of Images: 5/5/2024 Date of Next Image: N/A Summary: Scientists at NASA's Marshall Space Flight Center created these water extents on May 5, 2024 using PlanetScope imagery. These images can be used to see where open water is visible at the time of the satellite overpass. This product shows all water detected and differentiates between normal water areas and some flooded areas. This product was classified using WorldCover. It's important to note that all flooded areas may not be captured due to the sensors limitations of not being able to "see" through vegetation and buildings. To determine where additional flooding may have occurred, combine this layer with other data sets. Suggested Use: This product shows water that is detected by the sensor with different colors indicating different land cover/land use classifications from WorldCover that appear to have water and are potentially flooded. Blue (1): Known Water Red (2): Flooded Developed Green (3): Flooded Vegetation Orange (4): Flooded Cropland/Grassland Gray (5): Clouds/Cloud Shadow (0): No Data Satellite/Sensor: PlanetScope Resolution: 3 meters Credits: NASA Disasters Program, Includes copyrighted material of Planet Labs PBC. All rights reserved. Service URL: https://gis.earthdata.nasa.gov/portal/home/item.html?id=24843d7f43694de290c000b0aacae919 WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_TX/2408_planet_water/ImageServer/WMSServer

Date of Images: July 8, 2025, July 10, 2025 Date of Next Image: None planned Suggested Use: This image provides regional context, and may be useful for visualization of the ongoing event. Higher spatial resolution images may be suitable for spatial analysis to support decision making or research applications. More information on the aircraft and program can be found here: https://www.nasa.gov/specials/jsc-aircraft-ops/wb-57.html#top Sensor: HD resolution, 1280x720. Focal length was 950mm. Photos were collected in batch orbits at 25,000'. Resolution: Up to 3in (7.6cm) Credits: NASA Johnson Space Center, Flight Operations Directorate, Aircraft Operations Division, WB-57 Program Esri REST Endpoint: See URL to the right Data Download: https://nasagov.app.box.com/s/km2xgabrquxnx45kl8l2jv00pay4bjn9/folder/330348891753