In the past, the U.S. Geological Survey (USGS) and NASA collaborated on the creation of four global land data sets from Landsat images: one from the 1970s, and one each from circa 1990, 2000, and 2005. Each of these global data sets was created from the primary Landsat sensor in use at the time: the Multispectral Scanner (MSS) in the 1970s, the Thematic Mapper (TM) in 1990, Enhanced Thematic Mapper Plus (ETM+) in 2000, and a combination of TM and ETM+ in 2005.

This data set includes Landsat TM scenes from across the Legal Amazon region. A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94. All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.

Landsat-8/OLI image mosaic of Brazilian Amazon biome with 30m of spatial resolution. The mosaic was prepared in support of TerraClass project. The true color composition is based on the OLI bands 4, 3 and 2 assigned to RGB channels. The temporal composition encompasses 03-months of images, starting in July 2016 and ending in September of 2016, with a best pixel selection approach called Least Cloud Cover First (LCF). More information on LCF can be found at Brazil Data Cube web site (https://brazil-data-cube.github.io/specifications/processing-flow.html#temporal-compositing). This Image Mosaic used more than 1200 Landsat/OLI scenes and was generated based on an existing data cube of Landsat images.

The Brazilian Amazon land cover changes rapidly due to anthropogenic and climate drivers. Deforestation and forest disturbances associated with logging and fires, combined with extreme droughts, warmer air, and surface temperatures, have led to high tree mortality and harmful net carbon emissions in this region. Regional attempts to characterize land cover dynamics in this region focused on one or two anthropogenic drivers (i.e., deforestation and forest degradation). Land cover studies have also used a limited temporal scale (i.e., 10–15 years), focusing mainly on global and country-scale forest change. In this study, we propose a novel approach to characterize and measure land cover dynamics in the Amazon biome. First, we defined 10 fundamental land cover classes: forest, flooded forest, shrubland, natural grassland, pastureland, cropland, outcrop, bare and impervious, wetland, and water. Second, we mapped the land cover based on the compositional abundance of Landsat sub-pixel information that makes up these land cover classes: green vegetation (GV), non-photosynthetic vegetation, soil, and shade. Third, we processed all Landsat scenes with

This dataset provides annual maps of land cover classes for the Colombian Amazon from 2001 through 2016 that were created by classifying time segments detected by the Continuous Change Detection and Classification (CCDC) algorithm. The CCDC algorithm detected changes in Landsat pixel surface reflectance across the time series, and the time segments were classified into land cover types using a Random Forest classifier and manually collected training data. Annual maps of land cover were created for each Landsat scene and then post-processed and mosaicked. Land cover types include unclassified, forest, natural grasslands, urban, pastures, secondary forest, water, or highly reflective surfaces. The training data are not included with this dataset.

This data set includes orthorectified Landsat ETM+ scenes across the Legal Amazon region. At least one scene is provided for each spatial tile, representing the most cloud-free retrievals from mid-1999 through late 2001 (Fig. 1). Dates are therefore not continuous but include scenes from July 8, 1999 to November 13, 2001. Data have been atmospherically corrected and orthorectified. The individual images should be highly useful as they include very little cloud cover, but they should not be mosaicked together since retrieval dates vary.Data files (and format) included for each scene are: six multispectral bands (tif), two thermal bands (tif), one panchromatic band (tif), two preview files (jpg), and one metadata file (txt). The individual Geotiff files have been g-zipped and subsequently all of the files for a scene have been g-zipped together for ordering convenience.

SpatioTemporal Asset Catalog (STAC) Item - MOSAIC-LANDSAT-AMAZON-3M_V1_001008_20160701_20160930_P20240222 in mosaic-landsat-amazon-3m-1

This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set.

The Sentinel-2 mission is a land monitoring constellation of two satellites that provide high resolution optical imagery and provide continuity for the current SPOT and Landsat missions. The mission provides a global coverage of the Earth's land surface every 5 days, making the data of great use in on-going studies. L1C data are available from June 2015 globally. L2A data are available from November 2016 over Europe region and globally since January 2017.

This data set contains Landsat TM imagery for the years 1986, 1989, 1996, and 1999, that have been classified into four land use/land cover (LULC) classes: Forest, Non-Forest Vegetation, Urban/Barren, and Water; and a fifth class of Clouds/Shadows. The areas of interest were the four Intensive Study Areas (ISA) of the University of North Carolina's Carolina Population Center (CPC) Ecuador Projects: Eastern Intensive Study Area; Northern Intensive Study Area; Southern Intensive Study Area, and Southwestern Intensive Study Area. These areas are in the Northern Ecuadorian Amazon, in the area known as the northern Oriente of Ecuador. The resolution of the data is 30 meters. There are 12 image files (.tif) with this data set.

This map contains a number of world-wide dynamic image services providing access to various Landsat scenes covering the landmass of the World for visual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled so that the applications can restrict the displayed scenes to a specific date range. This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.For more information on each of the individual layers, see http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ; http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ; http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6

This data set includes Landsat TM scenes from across the Legal Amazon region. A single image is provided for each spatial tile, representing the most cloud-free retrieval from 9/21/86 to 9/17/94. All files are in a single directory, including one band-sequential (bsq) file and one database (ddr) file for each scene.

This map contains a number of world-wide dynamic image services providing access to various Landsat scenes covering the landmass of the World for visual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled so that the applications can restrict the displayed scenes to a specific date range. This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.For more information on each of the individual layers, see http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ; http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ; http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6

This data set contains a time series of early Landsat-4 MSS satellite imagery as well as Landsat-5 TM and Landsat-7 ETM+ satellite imagery of the northern Ecuadorian Amazon. Some of the TM and ETM images have been georectified to UTM Zone 18 South, WGS84 Datum. Not all of the images have been georectified.

This layer includes Landsat 8 and 9 imagery for use in visualization and analysis. This layer is time enabled and includes a number of band combinations and indices rendered on demand. The imagery includes eight multispectral bands from the Operational Land Imager (OLI) and two bands from the Thermal Infrared Sensor (TIRS). It is updated daily with new imagery directly sourced from the USGS Landsat collection on AWS.Geographic CoverageGlobal Land Surface.Polar regions are available in polar-projected Imagery Layers: Landsat Arctic Views and Landsat Antarctic Views.Temporal CoverageThis layer is updated daily with new imagery.Working in tandem, Landsat 8 and 9 revisit each point on Earth's land surface every 8 days.Most images collected from January 2015 to present are included.Approximately 5 images for each path/row from 2013 and 2014 are also included.Product LevelThe Landsat 8 and 9 imagery in this layer is comprised of Collection 2 Level-1 data.The imagery has Top of Atmosphere (TOA) correction applied.TOA is applied using the radiometric rescaling coefficients provided the USGS.The TOA reflectance values (ranging 0 – 1 by default) are scaled using a range of 0 – 10,000.Image Selection/FilteringA number of fields are available for filtering, including Acquisition Date, Estimated Cloud Cover, and Product ID.To isolate and work with specific images, either use the ‘Image Filter’ to create custom layers or add a ‘Query Filter’ to restrict the default layer display to a specified image or group of images.Visual RenderingThe default rendering on this layer is Agriculture (bands 6,5,2) with Dynamic Range Adjustment (DRA). Brighter green indicates more vigorous vegetation.The DRA version of each layer enables visualization of the full dynamic range of the images.Rendering (or display) of band combinations and calculated indices is done on-the-fly from the source images via Raster Functions.Various pre-defined Raster Functions can be selected or custom functions can be created.15 meter Landsat Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral Bands

Band

Description

Wavelength (µm)

Spatial Resolution (m)

1

Coastal aerosol

0.43 - 0.45

30

2

Blue

0.45 - 0.51

30

3

Green

0.53 - 0.59

30

4

Red

0.64 - 0.67

30

5

Near Infrared (NIR)

0.85 - 0.88

30

6

SWIR 1

1.57 - 1.65

30

7

SWIR 2

2.11 - 2.29

30

8

Cirrus (in OLI this is band 9)

1.36 - 1.38

30

9

QA Band (available with Collection 1)*

NA

30

*More about the Quality Assessment BandTIRS Bands

Band

Description

Wavelength (µm)

Spatial Resolution (m)

10

TIRS1

10.60 - 11.19

100 * (30)

11

TIRS2

11.50 - 12.51

100 * (30)

*TIRS bands are acquired at 100 meter resolution, but are resampled to 30 meter in delivered data product.Additional Usage NotesImage exports are limited to 4,000 columns x 4,000 rows per request.This dynamic imagery layer can be used in Web Maps and ArcGIS Pro as well as web and mobile applications using the ArcGIS REST APIs.WCS and WMS compatibility means this imagery layer can be consumed as WCS or WMS services.The Landsat Explorer App is another way to access and explore the imagery.This layer is part of a larger collection of Landsat Imagery Layers.Data SourceLandsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted by the Amazon Web Services as part of their Public Data Sets program.For information, see Landsat 8 and Landsat 9.

This data set provides active fire detection images and associated summary information derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images for various locations in Brazilian Amazonia during 2001-2003. There are two image types: (1) GeoTiff images (masks) of active fire pixels, and (2) GeoTiff images (masks) of clustered active fire pixels where a distinct cluster identification number has been assigned to each individual group of contiguous active fire pixels. There are 122 GeoTiff format files of each type of fire mask; a total of 244 images. The spatial resolution of the fire mask images is 30 meters. ETM+ images were selected based on data quality, availability, as well as on the occurrence of vegetation fires.In addition to the two image types, there are also two types of fire pixel summary information provided in text files: (1) one file of active fire pixel summary information derived from the active fire pixel images, and (2) 122 files of clustered active fire pixel information derived from individual clustered fire pixel masks, each of which correspond to a clustered image.

The River Sediment Database-Amazon (RivSed-Amazon) database contains surface suspended sediment concentrations (SSC) derived from Landsat 5, 7, and 8 Level 1 Collection 1 surface reflectance from all rivers in the Amazon River Basin that are ~60 meters wide or greater. SSC represent spatially integrated "reach" median concentrations over the footprint of SWOT River Database (SWORD, Altenau et al., 2021) centerlines (median reach length = 10 km) where high quality river water pixels were detected within each Landsat image from 1984-2018.

The methods used to produce this database were initially developed in the following publications:

Gardner, J., Pavelsky, T. M., Topp, S., Yang, X., Ross, M. R., & Cohen, S. (2023). Human activities change suspended sediment concentration along rivers. Environmental Research Letters. https://iopscience.iop.org/article/10.1088/1748-9326/acd8d8 and

Gardner et al. (2020). The color of rivers. Geophysical Research Letters. https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020GL088946

The publication associated with RivSed-Amazon is in review.

Files:

1) Metadata (rivSed_Amazon_metadata_v1.01.pdf): Description key data files associated with this repository.

2) RiverSed (RiverSed_Amazon_v1.1.txt). Table of SSC and associated data that is joinable to SWORD based on the ""reach_id".

3) Shapefile of river centerlines over South America to which the reflectance data can be attached (SWORD_SA.shp).

4) Shapefile of the reach polygons associated with SWORD_SA over the Amazon Basin. (reach_polygons_amazon.shp).

5) SSC-Landsat matchup database with extended metadata on locations and in-situ data (train_full_v1.1.csv).

6) The final training data used to build the xgboost machine learning model (train_v1.1.csv).

7) The xgboost model that can make SSC predictions over inland waters in USA using Landsat bands/band combinations (tssAmazon_model_v1.1.rds and .rda). The model can only be loaded and used in R at this time.

8) The correction coefficients applied to Landsat 5 and 8 to harmonized surface reflectance across Landsat 5,7,8 and over all bands to enable time series analysis.

This map contains a number of world-wide dynamic image services providing access to various Landsat scenes covering the landmass of the World for visual interpretation. Landsat 8 collects new scenes for each location on Earth every 16 days, assuming limited cloud coverage. Newest and near cloud-free scenes are displayed by default on top. Most scenes collected since 1st January 2015 are included. The service also includes scenes from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).

The service contains a range of different predefined renderers for Multispectral, Panchromatic as well as Pansharpened scenes. The layers in the service can be time-enabled so that the applications can restrict the displayed scenes to a specific date range.

This ArcGIS Server dynamic service can be used in Web Maps and ArcGIS Desktop, Web and Mobile applications using the REST based image services API. Users can also export images, but the exported area is limited to maximum of 2,000 columns x 2,000 rows per request.

Data Source: The imagery in these services is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). The data for these services reside on the Landsat Public Datasets hosted on the Amazon Web Service cloud. Users can access full scenes from https://github.com/landsat-pds/landsat_ingestor/wiki/Accessing-Landsat-on-AWS, or alternatively access http://landsatlook.usgs.gov to review and download full scenes from the complete USGS archive.

For more information on Landsat 8 images, see http://landsat.usgs.gov/landsat8.php.

*The Global Land Survey includes images from Landsat 1 through Landsat 7. Band numbers and band combinations differ from those of Landsat 8, but have been mapped to the most appropriate band as in the above table. For more information about the Global Land Survey, visit http://landsat.usgs.gov/science_GLS.php.

For more information on each of the individual layers, see

http://www.arcgis.com/home/item.html?id=d9b466d6a9e647ce8d1dd5fe12eb434b ;

http://www.arcgis.com/home/item.html?id=6b003010cbe64d5d8fd3ce00332593bf ;

http://www.arcgis.com/home/item.html?id=a7412d0c33be4de698ad981c8ba471e6

Land cover of the lower Amazon floodplain ca. 2008-2009 was mapped at 30 m resolution using a combination of multi-temporal Landsat Thematic Mapper (TM) and ALOS PALSAR-1 data. To enable mapping of seasonal changes in lake and channel areas, map inputs included TM scenes acquired at very low, mid, and high stage levels of the Amazon River. Land cover classes mapped were open water (with separate classes for the Amazon mainstem channel and floodplain lakes and channels), "campo" (3 classes), shrub, and forest. "Campo" refers to seasonally flooded areas that transition among bare ground, herbaceous, aquatic macrophyte, and open water states. Campo areas were further divided between those flooded at low-, mid-, and high-water levels. Excluding the main stem channel, the primary  land cover in the study region was seasonally inundated lakes and channels (59.4%), followed by permanently inundated lakes and channels (17.9%; these retained water even at extreme low water stage), seasonally ..., Mapping was carried out for the floodplain of the lower Amazon River (referred to locally as várzea) within a17,674 km² study area in Pará State, Brazil. Wetlands within a 10 km buffer of the floodplain were also mapped. The study area contains a mosaic of forests, lakes, and secondary channels that are continually re-shaped by dynamic processes of erosion and sedimentation. The várzea supports diverse plant communities, with herbaceous and shrub communities occurring near margins of lakes and channels, and forests occupying higher ground along natural levees. The annual river flood pulse as measured at the Óbidos gauge is monomodal and varies by 4 to 8 m annually (mean variation of 5.7 m), creating marked differences in floodplain conditions between high-water periods, when most areas are flooded, and low-water periods when only lakes and connecting channels retain water. The river water level begins to rise during December and reaches its maximum during late May or early June. Water ..., , # Land cover of the lower Amazon floodplain, ca. 2008-2009

https://doi.org/10.5061/dryad.tx95x6b7k

Description of the data and file structure

These analyses were funded by NASA Land-Cover and Land-Use Change program grant NNX12AD27G (L. Hess and D. McGrath, PIs): Land and resource use on the Amazon floodplain under evolving management systems and environmental change: Fish, forests, cattle, and settlements. Land cover classes were selected to emphasize habitats relevant for fish abundance and biodiversity, and fisheries productivity.

Files and variables

LowerAmazonFloodplainLandCoverBW.tif, *.tfw

Single-band byte GeoTiff (UTM, zone 21S, WGS 84, (EPSG:32721), 30 m pixels) with DN codes for land cover classes. The data range is 0 to 240. See README_LowerAmazonFloodplainLandCover.xlsx for further documentation.

LowerAmazonFloodplainLandCoverColor.tif, *.tfw

Three-band byte GeoTiff (UTM, zone 21S, WGS 84, (EPSG:32721), ...

A mesoscale network has been set up in the Santarem region of Para, Brazil. This network consists of eight meteorological stations named Belterra, Km 117 (Fazenda Sr. Davi), Mojui, Jamaraqua, Guarana, Embrapa (Cacoal Grande), Vila Franca and Sudam (Curua Una). Belterra and Km117 stations have been almost continuously collecting data since August, 1998, respectively. Mojui, Jamaraqua, and Guarana have been collecting data since July, 2000. Embrapa, Vila Franca and Sudam stations have been collecting data since 2002.

Data are presented in 52 individual comma-separated ASCII files. Each file contains data from one calendar year for one site; both site and year are identified clearly in the data file name and all files follow the same header information and organizational structure. Measurements include air temperature and pressure, wind speed and direction, relative humidity, downward solar radiation, and at some stations soil temperature and moisture.