Brazil water data

Date of Images: 5/15/2024, 5/8/2024, 4/21/2024, 4/6/2024 Summary: Scientists at NASA's Marshall Space Flight Center created these water extents using Landsat 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 the ESA Worldview. It's important to note that all flooded areas may not be captured do 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 CDL 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: Landsat Resolution: 30 meters Credits: NASA Disasters Program, Includes copyrighted material of Planet Labs PBC. All rights reserved. Esri REST Endpoint: See URL section on the right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/2602_landsat_WaterExtent/MapServer/WMSServer

Dates of Images: Post-Event: May 6, 2024 Pre-Event: April 21, 2024 Date of Next Image: None Summary: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Suggested Use: The 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. The Short Wave Infrared (SWIR) RGB is a product that can provides value in flood detection. Areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta, snow will appear as a bright blue/cyan, and bare soils being multicolor dependent on their makeup. Compare pre-event imagery to post-event imagery to identify potential flooding. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 Meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See layers below. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel2/ImageServer/WMSServer

Dates of Images: Post-Event: May 6, 2024 Pre-Event: April 21, 2024 Date of Next Image: None Summary: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: For mNDWI, Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 Meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See layers below. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel2_mndwi/ImageServer/WMSServer

Dates of Images: Pre-Event: 04/20/2024 (pre-flood) Post-Event: 05/06/2024, 05/07/2024, 05/09/2024, 05/15/2024, 05/21/2024 Time Zone: GMT (local crossing time of ~1:00 pm) Summary: This product is the apparent visible wavelength (AVW) of each pixel in a scene, approximating the overall color of the surface. It is calculated by taking the harmonic mean of surface reflectances from 350 nm to 895 nm, and can provide a sense of what has changed in the landscape by comparing several days against each other, as the change in apparent color of a surface often occurs under drastic circumstances. Dates covered include one pre-flood day (04/20/2024) and 5 flood days ending on 05/21/2024 at ~1:00 local time. AVW for each day is delivered, as is a % change from the pre-flood day to each of the 5 flood days afterward, showing the magnitude of color change in the area. Depending on the direction of change, one can infer the type of surface change from AVW. Typically, this metric is calculated from Rrs used for ocean color analyses (see https://doi.org/10.1016/j.rse.2020.111900), but can be made from surface reflectances and used over land as well. Suggested Use: Given that AVW is the apparent color of pixel, it can be used to track changes in land and water surfaces. The AVW value indicates average color reflected from a surface, e.g., healthy vegetation will have AVW in the NIR, water in the blues and greens, and turbid water in the reds. During flood days, the area around the Jacui River gets significantly redder (from previous NIR values), which can indicate turbid water supressing the typical vegetated signal in that area. Also, the Lagoa dos Patos gets significantly redder (from the greens), which indicates different conditions in the water (i.e., injection of sediment, which has average colors in the red). Images are typically displayed using the "Spectral" color map, with bounds from 400 - 700 (see attachment). For the percent change images, negative changes signify shorter average wavelengths (can be thought of as blue-shifting) and positive % changes are elongated average wavelengths (i.e., red-shifts). In other words, these shifting wavelengths tell us that some environmental change has caused the average color of a pixel to change. Users should note that pixels on the edges of masked clouds may see an elevated magnitude of percent change relative to neighboring non-cloud-edge pixels due to the adjacency effect. Satellite/Sensor/Resolution: Satellite: PACE, sensor: OCI, temporal resolution: daily, spatial resolution: gridded to 0.015 degrees from a Level 2 product in instrument swath (varying pixel size, 1.2 km at nadir). Credits: Credit: NASA PACE Team, POC: Skye Caplan, Link to data: https://search.earthdata.nasa.gov/search/granules?p=C3620139902-OB_CLOUD&pg[0][v]=f&pg[0][gsk]=-start_date&q=oci%20sfrefl Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_pace_percchange/ImageServer/WMSServer

Dates of Images: Post-Event: 5/8/2024; 5/15/2024 Pre-Event: 4/6/2024; 4/21/2024 Summary: mNDWI: The Modified Normalized Difference Water Index (mNDWI) provides a different view of the Earth's surface combining different bands to make water bodies more obvious. This index can be used to identify flooded areas as well as heavily saturated areas. Suggested Use: mNDWI: Areas of existing water, such as a rivers or lakes appear in the darkest green with high values near 1, while dry land appears in the darkest brown with low values near -1. This product can be used to identify potentially flooded areas that can be seen in varying shades of green and light brown depending on the amount of moisture picked up by the satellite. Note: Areas of cloud cover will show up in varying shades of green/blue similar to water. Satellite/Sensor: Landsat 9 Operational Land Imager (OLI) Resolution: 30 meters Credits: NASA/MSFC, USGS Esri REST Endpoint: See URL section on right side of page WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_landsat_mndwi/ImageServer/WMSServer

Dates of Images: Pre-Event: 04/20/2024 (pre-flood) Post-Event: 05/06/2024, 05/07/2024, 05/09/2024, 05/15/2024, 05/21/2024 Time Zone: GMT (local crossing time of ~1:00 pm) Summary: These are NDWI measurements from PACE OCI using surface reflectances from OCI's SFREFL suite of the 2024 flooding in Brazil. NDWI is a normalized band ratio using the green (555 nm) and NIR (860 nm) for water content detection (green - nir / green + nir). The images show how the flood developed from a pre-flood day (04/20/2024) to the proceeding flooded days (through 05/21/2024) at ~1:00 local time (the overpass of the instrument). The changing extent of the floodwaters, along with what looks to be the amount of suspended sediment, is especially clear against the background of vegetation. Users should take into account that these floodwaters were sediment-laden, and thus some of that signal may depress the water signal. However, the change in NDWI from the pre-flood day can be used to identify flood extent. Suggested Use: NDWI is a normalized band ratio measuring the presence of water. Higher positive values water surfaces, low positive values to ~0 indicates flooding or high humidity, and negative values mean non-aqueous or drought conditions. In these images, it is clear that the presence of water increases greatly around the Jacui River during flood days compared to the pre-flood day (04/20/2024), showing the transition of the area around the Jacui River from non-flooded conditions (low NDWI values) to flooded (higher NDWI). Clouds have been screened from these products. Satellite/Sensor/Resolution: Satellite: PACE, sensor: OCI Temporal resolution: daily Spatial resolution: gridded to 0.015 degrees from a Level 2 product in instrument swath (varying pixel size, 1.2 km at nadir). Credits: NASA PACE Team, POC: Skye Caplan, Link to data: https://search.earthdata.nasa.gov/search/granules?p=C3620139902-OB_CLOUD&pg[0][v]=f&pg[0][gsk]=-start_date&q=oci%20sfrefl Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_pace_ndwi/ImageServer/WMSServer

Dates of Images: 5/5/2024, 5/6/2025, 5/15/2025 Background: MODIS Global Flood Product, MCDWD, showing flooding observed on 5/5, 5/6, and 5/15/2024 in Rio Grande do Sol, Brazil. Product is based on optical imagery from the MODIS sensor, on both Terra and Aqua spacecraft. Observation times are approximately 10:30 am and 1:30 pm local time; flood extents at other times may not be observed.  The 1-day composite product is delivered here; this uses observations from only the given date. For this event, 5/5/2024 was the first clear day after the weather system passed. By 5/15, substantial flood water was still visible.  Caveats: Flooding is determined by comparing observed water extent to a reference water map, which may be inaccurate in fine details; some "flood" may be expected surface water, and some "surface water" may actually be flood, but both indicate areas where water was detected. The 1-day product can be particularly susceptible to false-positives from cloud shadows, which often can look like water in the source data. This product looks reasonable with few such false-positives, but users are advised to review the optical imagery (Terra and Aqua) in Worldview to confirm (https://go.nasa.gov/globalflood). Worldview also hosts the 2- and 3-day composite products, but not the 1-day delivered here. At 250 m resolution, this product will also not reliably capture flood extents smaller than 250 m.  As this is optical imagery, flooding under clouds will not be detected. Suggested Use: Red in the displayed image indicates flood; blue indicates expected surface water. Satellite/Sensor/Resolution: Terra and Aqua satellites, MODIS sensor, daily 250m resolution data (~10:30 am local time observation for Terra, ~1:30 pm for Aqua) Credits: NRT MODIS/Aqua+Terra Global Flood Product MCDWD_L3_NRT distributed from NASA LANCE. Available online at: https://www.earthdata.nasa.gov/global-flood-product. doi:10.5067/MODIS/MCDWD_L3_NRT.061 Project website includes FAQs and contacts for support: https://www.earthdata.nasa.gov/global-flood-product Esri REST Endpoint: See URL to the right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_modis_mcdwd/ImageServer/WMSServer

Dates of Images: 5/2/2024, 5/4/2024 Date of Next Image: Varies by region, typically 12 days since previous pass. Set time slider to most recent interval and click on area of interest to identify date of last pass. Summary: The Alaska Satellite Facility has developed false color Red, Green, Blue (RGB) and Radiometrically Terrain-Correct (RTC) composites and surface water extent products of the Sentinel-1A/B Synthetic Aperture Radar (SAR) instrument which assigns the co- and cross-polarization information to a channel in the composite. When used to support a flooding event, areas in blue denotes water present at the time of the satellite overpass before or after the start of the flooding event. Sentinel-1 RGB Decomposition of RTC VV and VH imagery over United States coastlines. Blue areas have low returns in VV and VH (smooth surfaces such as calm water, but also frozen/crusted soil or dry sand), Green areas have high returns in VH (volume scatterers such as vegetation or some types of snow/ice), and Red areas have relatively high VV returns and relatively low VH returns (such as urban or sparsely vegetated areas). To identify the date of an image either set the time slider to a 1 day interval or zoom in to AOI, set time slider to desired range and click on the imagery. The name may contain a full date and time in a format like this example: S1A_IW_20210705T231453_DVR_RTC30_G_gpufed_27F4 The date and time would be 07/05/2021 at 23:14:53 UTC. Suggested Use: In this image, water appears in blue, vegetated areas in shades of green and urban areas in bright orange. It is recommended to use this product with ancillary information to derive flooded areas. Satellite/Sensor: Synthetic Aperture Radar on European Space Agency's (ESA) Copernicus Sentinel-1A/B satellite NOTE: Sentinel-1B is no longer acquiring data and is only available into December 2021 Resolution: 30 meters Esri REST Endpoint: See direct subsetted information on the link the to the right with WMS options. RGB Product: https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RGB/ImageServer RTC Product: VV - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VV/ImageServer VH - https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_RTC_VH/ImageServer Surface Water Extent Product: https://gis.asf.alaska.edu/arcgis/rest/services/ASF_S1/ASF_S1_WM/ImageServer WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_202405_FLOOD_BRAZIL/2407_sentinel1/ImageServer/WMSServer Data Download: Data can be downloaded via the Pop-Ups in the Web Map or through each service's attribute table.

Water features across the area: rivers, streams, canals, lakes, ponds, and water bodies tagged with `waterway`, `water`, or `natural=water`. Useful for flood-risk modelling, watershed analysis, and environmental basemap context. Coverage reflects where volunteer mappers have been active. Urban areas are usually well represented, remote areas may be sparse. Cross-check critical decisions with local field knowledge. - Source: OpenStreetMap, a free, collaborative world map - Tags: waterway, water, natural - Part of the country exports on HDX by HOT

Date of Images: 5/15/2024, 5/8/2024, 4/21/2024, 4/6/2024 Summary: Scientists at NASA's Marshall Space Flight Center created these water extents using Landsat 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 the ESA Worldview. It's important to note that all flooded areas may not be captured do 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 CDL 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: Landsat Resolution: 30 meters Credits: NASA Disasters Program, Includes copyrighted material of Planet Labs PBC. All rights reserved. Esri REST Endpoint: See URL section on the right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_landsat_WaterExtent/MapServer/WMSServer

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

Dates of Images: 20240508T2206, 20240511T0849 (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 two products: Surface Water Extent maps on individual dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Flood images: May 08, 2024 and May 11, 2024 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_20240508T2206_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20240511T0849_mosaic.tif Water (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) 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_20240508T2206_20240511T0849_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 inundated vegetation was detected during the time period of the images. (suggested color: #ff15e4) Satellite/Sensor/Resolution: 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 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 to the bottom right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_s1/MapServer/WMSServer

Date of Images: 5/5/2022 Summary: Scientists at NASA's Marshall Space Flight Center created these water extents using Landsat 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 the ESA Worldview. It's important to note that all flooded areas may not be captured do 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 CDL 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: Copernicus Sentinel-2 Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on the right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2603_202205_FLOOD_MN/ex2603_sentinel2_WaterExtent/MapServer/WMSServer

Dates of Images: 20240508T2206, 20240511T0849 (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 two products: Surface Water Extent maps on individual dates Maximum Surface Water Extent maps, showing the full extent of water observed over a defined time period Dates and Input Data: Flood images: May 08, 2024 and May 11, 2024 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_20240508T2206_mosaic.tif, OPERA_L3_DSWX-S1_V1_WTR_20240511T0849_mosaic.tif Water (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) 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_20240508T2206_20240511T0849_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 inundated vegetation was detected during the time period of the images. (suggested color: #ff15e4) Satellite/Sensor/Resolution: 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 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 to the bottom right. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/EX2602_opera_dswx_s1/MapServer/WMSServer

Date of Images: 5/5/2022 Summary: Scientists at NASA's Marshall Space Flight Center created these water extents using Landsat 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 the ESA Worldview. It's important to note that all flooded areas may not be captured do 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 CDL 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: Copernicus Sentinel-2 Resolution: 10 meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See URL section on the right side of page. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel2_WaterExtent/MapServer/WMSServer

**UNOSAT code: FL20211213BRA** This map illustrates satellite-detected surface waters in Alcobaca, Prado and Itamaraju municipalities, State of Bahia, Brazil as observed from Sentinel-2 image acquired on 11 Dec. 2021 & Sentinel-1 image acquired on 09 Dec. 2021. Within the analyzed area of about 300,000 ha, about 13,500 ha of lands appear to be flooded. Along the Jucuruçu river, mainly agricultural lands appear to be flooded. This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to the United Nations Satellite Centre (UNOSAT). Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to backscattering properties of the radar signal.

Dates of Images: Dates: 04/20/2024 (pre-flood), 05/06/2024, 05/07/2024, 05/09/2024, 05/15/2024, 05/21/2024 Time Zone: GMT (local crossing time of ~1:00 pm) Summary: These are NDWI measurements from PACE OCI using surface reflectances from OCI's SFREFL suite of the 2024 flooding in Brazil. NDWI is a normalized band ratio using the green (555 nm) and NIR (860 nm) for water content detection (green - nir / green + nir). The images show how the flood developed from a pre-flood day (04/20/2024) to the proceeding flooded days (through 05/21/2024) at ~1:00 local time (the overpass of the instrument). The changing extent of the floodwaters, along with what looks to be the amount of suspended sediment, is especially clear against the background of vegetation. Users should take into account that these floodwaters were sediment-laden, and thus some of that signal may depress the water signal. However, the change in NDWI from the pre-flood day can be used to identify flood extent. Suggested Use: NDWI is a normalized band ratio measuring the presence of water. Higher positive values water surfaces, low positive values to ~0 indicates flooding or high humidity, and negative values mean non-aqueous or drought conditions. In these images, it is clear that the presence of water increases greatly around the Jacui River during flood days compared to the pre-flood day (04/20/2024), showing the transition of the area around the Jacui River from non-flooded conditions (low NDWI values) to flooded (higher NDWI). Clouds have been screened from these products. Satellite/Sensor/Resolution: Satellite: PACE, sensor: OCI Temporal resolution: daily Spatial resolution: gridded to 0.015 degrees from a Level 2 product in instrument swath (varying pixel size, 1.2 km at nadir). Credits: NASA PACE Team, POC: Skye Caplan, Link to data: https://search.earthdata.nasa.gov/search/granules?p=C3620139902-OB_CLOUD&pg[0][v]=f&pg[0][gsk]=-start_date&q=oci%20sfrefl

Dates of Images: Post-Event: May 6, 2024 Pre-Event: April 21, 2024 Date of Next Image: None Summary: The True Color RGB composite provides a product of how the surface would look to the naked eye from space. The RGB is created using the red, green, and blue channels of the respective instrument. The Short Wave Infrared (SWIR) RGB is a product that is created using the SWIR, NIR, and Red channels of the respective instrument. The Color Infrared composite is created using the near-infrared, red, and green channels. The near-infrared gives the ability to see through thin clouds. Healthy vegetation is shown as red, water is in blue. Suggested Use: The 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. The Short Wave Infrared (SWIR) RGB is a product that can provides value in flood detection. Areas of water will appear blue, healthy green vegetation will appear as a bright green, urban areas in various shades of magenta, snow will appear as a bright blue/cyan, and bare soils being multicolor dependent on their makeup. Compare pre-event imagery to post-event imagery to identify potential flooding. A Color Infrared composite depicts healthy vegetation as red, water as blue. Some minor atmospheric corrections have occurred. Satellite/Sensor: MultiSpectral Instrument (MSI) on European Space Agency's (ESA) Copernicus Sentinel-2A/2B satellites Resolution: 10 Meters Credits: NASA/MSFC, USGS, ESA Copernicus Esri REST Endpoint: See layers below. WMS Endpoint: https://gis.earthdata.nasa.gov/portal/rest/services/DISASTERS_EX2602_202405_FLOOD_BRAZIL/ex2602_sentinel2/ImageServer