These Landsat Collection 2 Tier 1 Level 2 composites are made from Tier 1 Level 2 orthorectified scenes. The Normalized Difference Vegetation Index is generated from the Near-IR and Red bands of each scene as (NIR - Red) / (NIR + Red), and ranges in value from -1.0 to 1.0. …

This layer includes Landsat 8 imagery rendered on-the-fly as Normalized Difference Moisture Index (NDMI) Colorized 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.Landsat 8 revisits each point on Earth's land surface every 16 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 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 RenderingDefault rendering is Normalized Difference Moisture Index Colorized, calculated as (b5 - b6)/(b5 + b6) with a colormap applied. Wetlands and moist areas are blues, and dry areas in deep yellow and brown.Raster Functions enable on-the-fly rendering of band combinations and calculated indices from the source imagery.The DRA version of each layer enables visualization of the full dynamic range of the images.Other pre-defined Raster Functions can be selected via the renderer drop-down or custom functions can be created.This layer is part of a larger collection of Landsat Imagery Layers that you can use to perform a variety of mapping analysis tasks.Pre-defined functions: Natural Color with DRA, Agriculture with DRA, Geology with DRA, Color Infrared with DRA, Bathymetric with DRA, Short-wave Infrared with DRA, Normalized Difference Moisture Index Colorized, NDVI Raw, NDVI Colorized, NBR Raw15 meter Landsat Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral BandsThe table below lists all available multispectral OLI bands. Normalized Difference Moisture Index consumes bands 5 and 6.BandDescriptionWavelength (µm)Spatial Resolution (m)1Coastal aerosol0.43 - 0.45302Blue0.45 - 0.51303Green0.53 - 0.59304Red0.64 - 0.67305Near Infrared (NIR)0.85 - 0.88306SWIR 11.57 - 1.65307SWIR 22.11 - 2.29308Cirrus (in OLI this is band 9)1.36 - 1.38309QA Band (available with Collection 1)*NA30*More about the Quality Assessment BandTIRS BandsBandDescriptionWavelength (µm)Spatial Resolution (m)10TIRS110.60 - 11.19100 * (30)11TIRS211.50 - 12.51100 * (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 on Landsat 8 images, see Landsat8.

Bu Landsat Collection 2 Tier 1 Level 2 kompozitleri, Tier 1 Level 2 ortorektifiye edilmiş sahnelerden oluşturulur. Normalleştirilmiş Fark Bitki Örtüsü İndeksi, her sahnenin yakın kızılötesi ve kırmızı bantlarından (NIR - Kırmızı) / (NIR + Kırmızı) şeklinde oluşturulur ve değeri -1,0 ile 1,0 arasında değişir. Bu kompozitler, yılın ilk gününden başlayıp yılın 360. gününe kadar devam eden her 8 günlük dönemdeki tüm sahnelerden oluşturulur. Yılın son bileşeni, 361. günden başlayarak sonraki yılın ilk bileşeniyle 3 gün boyunca çakışır. 8 günlük her döneme ait tüm görüntüler, bileşik değere en son piksel olarak dahil edilir. Notlar: Kompozitleri oluşturmak için kullanılan kodu burada görebilirsiniz. Yalnızca WRS_ROW < 122 olan gündüz görüntüleri dahil edilir. Landsat 7 için , yörünge kayması nedeniyle 2017-01-01 tarihinden sonraki görüntüler hariç tutulur. Landsat 8 için, 2013-05-01'den önceki görüntüler, yönlendirme sorunları nedeniyle hariç tutulur.

This layer includes Landsat 8 and 9 imagery rendered on-the-fly as Natural Color with DRA 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 RenderingDefault rendering is Natural Color (bands 4,3,2) with Dynamic Range Adjustment (DRA).Raster Functions enable on-the-fly rendering of band combinations and calculated indices from the source imagery.The DRA version of each layer enables visualization of the full dynamic range of the images.Other pre-defined Raster Functions can be selected via the renderer drop-down or custom functions can be created.This layer is part of a larger collection of Landsat Imagery Layers that you can use to perform a variety of mapping analysis tasks.Pre-defined functions: Natural Color with DRA, Agriculture with DRA, Geology with DRA, Color Infrared with DRA, Bathymetric with DRA, Short-wave Infrared with DRA, Normalized Difference Moisture Index Colorized, NDVI Raw, NDVI Colorized, NBR Raw15 meter Landsat Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral BandsThe table below lists all available multispectral OLI bands. Natural Color with DRA consumes bands 4,3,2.BandDescriptionWavelength (µm)Spatial Resolution (m)1Coastal aerosol0.43 - 0.45302Blue0.45 - 0.51303Green0.53 - 0.59304Red0.64 - 0.67305Near Infrared (NIR)0.85 - 0.88306SWIR 11.57 - 1.65307SWIR 22.11 - 2.29308Cirrus (in OLI this is band 9)1.36 - 1.38309QA Band (available with Collection 1)*NA30*More about the Quality Assessment BandTIRS BandsBandDescriptionWavelength (µm)Spatial Resolution (m)10TIRS110.60 - 11.19100 * (30)11TIRS211.50 - 12.51100 * (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.

Landsat Collection 2 के टियर 1 लेवल 2 के ये कंपोज़िट, टियर 1 लेवल 2 के ऑर्थोरेक्टिफ़ाइड सीन से बनाए गए हैं. नॉर्मलाइज़्ड डिफ़रेंस वेजिटेशन इंडेक्स (एनडीवीआई) को हर सीन के नियर-आईआर और रेड बैंड से जनरेट किया जाता है. इसका फ़ॉर्मूला (NIR - Red) / (NIR + Red) है. इसकी वैल्यू -1.0 से 1.0 के बीच होती है. इन कंपोज़िट को, साल के पहले दिन से लेकर 360वें दिन तक, हर आठ दिन की अवधि के सभी सीन से बनाया जाता है. साल का आखिरी कंपोज़िट, 361वें दिन से शुरू होगा. यह अगले साल के पहले कंपोज़िट के साथ तीन दिनों तक ओवरलैप करेगा. आठ दिनों के हर पीरियड की सभी इमेज को कंपोज़िट में शामिल किया जाता है. कंपोज़िट वैल्यू के तौर पर सबसे हाल के पिक्सल का इस्तेमाल किया जाता है. ध्यान दें: कंपोज़िट बनाने के लिए इस्तेमाल किया गया कोड यहाँ देखा जा सकता है. इसमें सिर्फ़ दिन के समय की ऐसी इमेज शामिल की जाती हैं जिनमें WRS_ROW < 122 हो. Landsat 7 के लिए, 1 जनवरी, 2017 के बाद की इमेज को ऑर्बिटल ड्रिफ़्ट की वजह से शामिल नहीं किया जाता है. लैंडसैट 8 के लिए, 1 मई, 2013 से पहले की इमेज शामिल नहीं की गई हैं. इसकी वजह यह है कि इमेज में पॉइंटिंग से जुड़ी समस्याएं हैं.

Leaf Area Index (LAI) is a fundamental vegetation structural variable that drives energy and mass exchanges between the plant and the atmosphere. Moderate-resolution (300m – 7km) global LAI data products have been widely applied to track global vegetation changes, drive Earth system models, monitor crop growth and productivity, etc. Yet, cutting-edge applications in climate adaptation, hydrology, and sustainable agriculture require LAI information at higher spatial resolution (< 100m) to model and understand heterogeneous landscapes. This dataset was built to assist a machine-learning-based approach for mapping LAI from 30m-resolution Landsat images across the contiguous US (CONUS). The data was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 LAI/FPAR, Landsat Collection 1 surface reflectance, and NLCD Land Cover datasets over 2006 – 2018 using Google Earth Engine. Each record/sample/row includes a MODIS LAI value, corresponding Landsat surface reflectance in green, red, NIR, SWIR1 bands, a land cover (biome) type, geographic location, and other auxiliary information. Each sample represents a MODIS LAI pixel (500m) within which a single biome type dominates 90% of the area. The spatial homogeneity of the samples was further controlled by a screening process based on the coefficient of variation of the Landsat surface reflectance. In total, there are approximately 1.6 million samples, stratified by biome, Landsat sensor, and saturation status from the MODIS LAI algorithm. This dataset can be used to train machine learning models and generate LAI maps for Landsat 5, 7, 8 surface reflectance images within CONUS. Detailed information on the sample generation and quality control can be found in the related journal article. Resources in this dataset:Resource Title: README. File Name: LAI_train_samples_CONUS_README.txtResource Description: Description and metadata of the main datasetResource Software Recommended: Notepad,url: https://www.microsoft.com/en-us/p/windows-notepad/9msmlrh6lzf3?activetab=pivot:overviewtab Resource Title: LAI_training_samples_CONUS. File Name: LAI_train_samples_CONUS_v0.1.1.csvResource Description: This CSV file consists of the training samples for estimating Leaf Area Index based on Landsat surface reflectance images (Collection 1 Tire 1). Each sample has a MODIS LAI value and corresponding surface reflectance derived from Landsat pixels within the MODIS pixel. Contact: Yanghui Kang (kangyanghui@gmail.com)
Column description

UID: Unique identifier. Format: LATITUDE_LONGITUDE_SENSOR_PATHROW_DATE
Landsat_ID: Landsat image ID Date: Landsat image date in "YYYYMMDD" Latitude: Latitude (WGS84) of the MODIS LAI pixel center Longitude: Longitude (WGS84) of the MODIS LAI pixel center MODIS_LAI: MODIS LAI value in "m2/m2" MODIS_LAI_std: MODIS LAI standard deviation in "m2/m2" MODIS_LAI_sat: 0 - MODIS Main (RT) method used no saturation; 1 - MODIS Main (RT) method with saturation NLCD_class: Majority class code from the National Land Cover Dataset (NLCD) NLCD_frequency: Percentage of the area cover by the majority class from NLCD Biome: Biome type code mapped from NLCD (see below for more information) Blue: Landsat surface reflectance in the blue band Green: Landsat surface reflectance in the green band Red: Landsat surface reflectance in the red band Nir: Landsat surface reflectance in the near infrared band Swir1: Landsat surface reflectance in the shortwave infrared 1 band Swir2: Landsat surface reflectance in the shortwave infrared 2 band Sun_zenith: Solar zenith angle from the Landsat image metadata. This is a scene-level value. Sun_azimuth: Solar azimuth angle from the Landsat image metadata. This is a scene-level value. NDVI: Normalized Difference Vegetation Index computed from Landsat surface reflectance EVI: Enhanced Vegetation Index computed from Landsat surface reflectance NDWI: Normalized Difference Water Index computed from Landsat surface reflectance GCI: Green Chlorophyll Index = Nir/Green - 1

Biome code

1 - Deciduous Forest
2 - Evergreen Forest
3 - Mixed Forest
4 - Shrubland
5 - Grassland/Pasture
6 - Cropland
7 - Woody Wetland
8 - Herbaceous Wetland

Reference Dataset: All data was accessed through Google Earth Engine Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., & Moore, R. (2017). Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote Sensing of Environment. MODIS Version 6 Leaf Area Index/FPAR 4-day L5 Global 500m Myneni, R., Y. Knyazikhin, T. Park. MOD15A2H MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V006. 2015, distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD15A2H.006 Landsat 5/7/8 Collection 1 Surface Reflectance Landsat Level-2 Surface Reflectance Science Product courtesy of the U.S. Geological Survey. Masek, J.G., Vermote, E.F., Saleous N.E., Wolfe, R., Hall, F.G., Huemmrich, K.F., Gao, F., Kutler, J., and Lim, T-K. (2006). A Landsat surface reflectance dataset for North America, 1990–2000. IEEE Geoscience and Remote Sensing Letters 3(1):68-72. http://dx.doi.org/10.1109/LGRS.2005.857030. Vermote, E., Justice, C., Claverie, M., & Franch, B. (2016). Preliminary analysis of the performance of the Landsat 8/OLI land surface reflectance product. Remote Sensing of Environment. http://dx.doi.org/10.1016/j.rse.2016.04.008. National Land Cover Dataset (NLCD) Yang, Limin, Jin, Suming, Danielson, Patrick, Homer, Collin G., Gass, L., Bender, S.M., Case, Adam, Costello, C., Dewitz, Jon A., Fry, Joyce A., Funk, M., Granneman, Brian J., Liknes, G.C., Rigge, Matthew B., Xian, George, A new generation of the United States National Land Cover Database—Requirements, research priorities, design, and implementation strategies: ISPRS Journal of Photogrammetry and Remote Sensing, v. 146, p. 108–123, at https://doi.org/10.1016/j.isprsjprs.2018.09.006 Resource Software Recommended: Microsoft Excel,url: https://www.microsoft.com/en-us/microsoft-365/excel

This layer includes Landsat GLS, Landsat 8, and Landsat 9 imagery for use in visualization and analysis. This layer is time enabled and includes a number band combinations and indices rendered on demand. The Landsat 8 and 9 imagery includes nine 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.Together, 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.This layer also includes imagery from the Global Land Survey* (circa 2010, 2005, 2000, 1990, 1975).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 ‘Layer Filter’ to restrict the default layer display to a specified image or group of images.To isolate a specific mission, use the Layer Filter and the dataset_id or SensorName fields.Visual RenderingThe default rendering in 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.Pre-defined functions: Natural Color with DRA, Agriculture with DRA, Geology with DRA, Color Infrared with DRA, Bathymetric with DRA, Short-wave Infrared with DRA, Normalized Difference Moisture Index Colorized, NDVI Raw, NDVI Colorized, NBR Raw15 meter Landsat Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral Bands BandDescriptionWavelength (µm)Spatial Resolution (m)1Coastal aerosol0.43 - 0.45302Blue0.45 - 0.51303Green0.53 - 0.59304Red0.64 - 0.67305Near Infrared (NIR)0.85 - 0.88306SWIR 11.57 - 1.65307SWIR 22.11 - 2.29308Cirrus (in OLI this is band 9)1.36 - 1.38309QA Band (available with Collection 1)*NA30 *More about the Quality Assessment BandTIRS BandsBandDescriptionWavelength (µm)Spatial Resolution (m)10TIRS110.60 - 11.19100 * (30)11TIRS211.50 - 12.51100 * (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.Data SourceLandsat imagery is sourced from the U.S. Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA). Data is hosted in Amazon Web Services as part of their Public Data Sets program.For information, see Landsat 8 and Landsat 9.*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 GLS.

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data globally between 52° N and 52° S latitudes. A map of the acquisition coverage can be found in figure 2 on the ECOSTRESS website.The ECOSTRESS Tiled Ancillary NDVI and Albedo Level 2 Global 70 m (ECO_L2T_STARS) Version 2 data product provides Normalized Difference Vegetation Index (NDVI) and albedo aligned with each daytime ECOSTRESS overpass. ECO_L2T_STARS is an ancillary data product derived from Visible Infrared Imaging Radiometer Suite (VIIRS) and Harmonized Landsat Sentinel (HLS) Version 2 data sources with application to the ECOSTRESS mission. This data product fuses fine resolution inputs from HLS surface reflectance products and moderate resolution inputs from the daily NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS surface reflectance (VNP09GA) product. The data fusion is performed using a variant of the Spatial Timeseries for Automated high-Resolution multi-Sensor data fusion (STARS) algorithm to create tiles matching the ECOSTRESS standard resolution of 70 meters (m). STARS is a Bayesian timeseries methodology that provides streaming data fusion and uncertainty quantification through efficient Kalman filtering. Refer to Section 3.1 of the ECOSTRESS Jet Propulsion Laboratory (JPL) EvapoTranspiration (JET) Level-3 Algorithm Theoretical Basis Document (ATBD) for further details of the Bidirectional Reflectance Distribution Function (BRDF) implementation and albedo calculations.The ECO_L2T_STARS Version 2 data product is provided in Cloud Optimized GeoTIFF (COG) format using a modified version of the Military Grid Reference System (MGRS), which divides Universal Transverse Mercator (UTM) zones into square tiles that are 109.8 km by 109.8 km with a 70 m spatial resolution. Each band is distributed as a separate COG. This product contains four layers including NDVI, NDVI uncertainty, albedo, and albedo uncertainty. The ECO_L2T_STARS ancillary NDVI and albedo product is only generated for corresponding daytime ECOSTRESS Tiled Land Surface Temperature and Emissivity Instantaneous Level 2 Global 70 m (ECO_L2T_LSTE) Version 2 tiles.Known Issues Data acquisition gap: ECOSTRESS was launched on June 29, 2018, and moved to autonomous science operations on August 20, 2018, following a successful in-orbit checkout period. On September 29, 2018, ECOSTRESS experienced an anomaly with its primary mass storage unit (MSU). ECOSTRESS has a primary and secondary MSU (A and B). On December 5, 2018, the instrument was switched to the secondary MSU and science operations resumed. On March 14, 2019, the secondary MSU experienced a similar anomaly, temporarily halting science acquisitions. On May 15, 2019, a new data acquisition approach was implemented, and science acquisitions resumed. To optimize the new acquisition approach TIR bands 2, 4, and 5 are being downloaded. The data products are as previously, except the bands not downloaded contain fill values (L1 radiance and L2 emissivity). This approach was implemented from May 15, 2019, through April 28, 2023. Data acquisition gap: From February 8 to February 16, 2020, an ECOSTRESS instrument issue resulted in a data anomaly that created striping in band 4 (10.5 micron). These data products have been reprocessed and are available for download. No ECOSTRESS data were acquired on February 17, 2020, due to the instrument being in SAFEHOLD. Data acquired following the anomaly have not been affected. Data acquisition: ECOSTRESS has now successfully returned to 5-band mode after being in 3-band mode since 2019. This feature was successfully enabled following a Data Processing Unit firmware update (version 4.1) to the payload on April 28, 2023. To better balance contiguous science data scene variables, 3-band collection is currently being interleaved with 5-band acquisitions over the orbital day/night periods. Solar Array Obstruction: Some ECOSTRESS scenes may be affected by solar array obstructions from the International Space Station (ISS), potentially impacting data quality of obstructed pixels. The 'FieldOfViewObstruction' metadata field is included in all Version 2 products to indicate possible obstructions: * Before October 24, 2024 (orbits prior to 35724): The field is present but was not populated and does not reliably identify affected scenes. * On or after October 24, 2024 (starting with orbit 35724): The field is populated and generally accurate, except for late December 2024, when a temporary processing error may have caused false positives. * A list of scenes confirmed to be affected by obstructions is available and is recommended for verifying historical data (before October 24, 2024) and scenes from late December 2024.* The ISS native pointing information is coarse relative to ECOSTRESS pixels, so ECOSTRESS geolocation is improved through image matching with a basemap. Metadata in the L1B_GEO file shows the success of this geolocation improvement, using categorizations "best", "good", "suspect", and "poor". We recommend that users use only "best" and "good" scenes for evaluations where geolocation is important (e.g., comparison to field sites). For some scenes, this metadata is not reflected in the higher-level products (e.g., land surface temperature, evapotranspiration, etc.). While this metadata is always available in the geolocation product, to save users additional download, we have produced a summary text file that includes the geolocation quality flags for all scenes from launch to present. At a later date, all higher-level products will reflect the geolocation quality flag correctly (the field name is GeolocationAccuracyQA).

Ces composites Landsat Collection 2 de niveau 1 et de niveau 2 sont créés à partir de scènes orthorectifiées de niveau 1 et de niveau 2. L'indice de végétation par différence normalisée est généré à partir des bandes proche infrarouge et rouge de chaque scène, sous la forme (NIR - Red) / (NIR + Red), et sa valeur est comprise entre -1 et 1. Ces composites sont créés à partir de toutes les scènes de chaque période de 32 jours, en commençant par le premier jour de l'année et en continuant jusqu'au 352e jour de l'année. Le dernier composite de l'année, qui commence le jour 353, chevauchera le premier composite de l'année suivante de 20 jours. Toutes les images de chaque période de 32 jours sont incluses dans la composite, avec le pixel le plus récent comme valeur composite. Remarques : Le code utilisé pour créer les composites est disponible ici. Seules les images de jour avec WRS_ROW < 122 sont incluses. Pour Landsat 7 , les images postérieures au 1er janvier 2017 sont exclues en raison de la dérive orbitale. Pour Landsat 8, les images antérieures au 01/05/2013 sont exclues en raison de problèmes de pointage.

These Landsat Collection 2 Tier 1 Level 2 composites are made from Tier 1 Level 2 orthorectified scenes. The Enhanced Vegetation Index (EVI) is generated from the Near-IR, Red and Blue bands of each scene, and ranges in value from -1.0 to 1.0. See Huete et al. (2002) for details. …

这些 Landsat Collection 2 Tier 1 Level 2 合成影像由Tier 1 Level 2 正射校正后的场景构成。归一化差异植被指数是根据每个场景的近红外波段和红色波段计算得出的，计算公式为(NIR - Red) / (NIR + Red)，值范围为-1.0 到 1.0。…

The BOREAS RSS-07 team focused their efforts on developing and validating procedures and algorithms that would allow the retrieval of LAI from remotely sensed vegetation indices. This data set contains images of LAI and FPAR that were produced from the AVHRR Level-4c ten-day composite NDVI images produced at CCRS for the three summer IFCs in 1994. The algorithms were developed based on ground measurements and Landsat TM images (Chen and Cihlar, 1996; Chen, 1996b). The data are provided in binary image format files. Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.

This regional land cover classification is based on the use of multitemporal 1-km Advanced Very High Resolution Radiometer (AVHRR) National Oceanic and Atmospheric Administration (NOAA 11) data that were analyzed in combination with selected Landsat Thematic Mapper (TM) and extensive field observations within a 619-km by 821-km subset of the 1,000-km by 1,000-km BOReal Ecosystem-Atmosphere Study (BOREAS) region (Steyaert et al., 1997). Following the approach developed by Loveland et al. (1991) for 1-km AVHRR land cover mapping in the conterminous United States, monthly Normalized Difference Vegetation Index (NDVI) image composites (April-September 1992) of this subset in the BOREAS region were used in an unsupervised image cluster analysis algorithm to develop an initial set of seasonal land cover classes. Extensive ground data with Global Positioning System (GPS) georeferencing, observations from low-level aerial flights over remote areas, and selected Landsat image composites for the study areas were analyzed to split, aggregate, and label the spectral-temporal clusters throughout the BOREAS region. Landsat TM image composites (bands 5, 4, and 3) were available for the 100-km by 100-km Northern Study Area (NSA) and Southern Study Area (SSA). This AVHRR land cover product was compared with Landsat TM land cover classifications for the BOREAS study areas (Steyaert et al., 1997). Companion files include example thumbnail images that may be viewed and the image data files downloaded using a convenient viewer utility.

This layer includes Landsat 8 and 9 imagery rendered on-the-fly as Bathymetric with DRA 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 RenderingDefault rendering is Bathymetric (bands 4,3,1) with Dynamic Range Adjustment (DRA), useful in bathymetric mapping applications. Raster Functions enable on-the-fly rendering of band combinations and calculated indices from the source imagery.The DRA version of each layer enables visualization of the full dynamic range of the images.Other pre-defined Raster Functions can be selected via the renderer drop-down or custom functions can be created.This layer is part of a larger collection of Landsat Imagery Layers that you can use to perform a variety of mapping analysis tasks.Pre-defined functions: Natural Color with DRA, Agriculture with DRA, Geology with DRA, Color Infrared with DRA, Bathymetric with DRA, Short-wave Infrared with DRA, Normalized Difference Moisture Index Colorized, NDVI Raw, NDVI Colorized, NBR Raw15 meter Landsat Imagery Layers are also available: Panchromatic and Pansharpened.Multispectral BandsThe table below lists all available multispectral OLI bands. Bathymetric with DRA consumes bands 4,3,1.BandDescriptionWavelength (µm)Spatial Resolution (m)1Coastal aerosol0.43 - 0.45302Blue0.45 - 0.51303Green0.53 - 0.59304Red0.64 - 0.67305Near Infrared (NIR)0.85 - 0.88306SWIR 11.57 - 1.65307SWIR 22.11 - 2.29308Cirrus (in OLI this is band 9)1.36 - 1.38309QA Band (available with Collection 1)*NA30*More about the Quality Assessment BandTIRS BandsBandDescriptionWavelength (µm)Spatial Resolution (m)10TIRS110.60 - 11.19100 * (30)11TIRS211.50 - 12.51100 * (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.

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) - is a mission instrument launched aboard NASA's Aqua Satellite on 4 May 2002. The Soil Moisture Experiments (SMEX) are designed to evaluate the accuracy of AMSR-E soil moisture data. Specific validation objectives include: assessing and refining soil moisture algorithm performance; verifying soil moisture estimation accuracy; investigating the effects of vegetation, surface temperature, topography, and soil texture on soil moisture accuracy; and determining the regions that are useful for AMSR-E soil moisture measurements.

The main elements of the Soil Moisture Experiments (SMEX) 2002 were to:

1. Study land-atmosphere interactions and extend remote sensing observations and algorithms to more challenging vegetation conditions than previously studied;
2. Validate AMSR-E satellite brightness temperature and soil moisture measurements; and
3. Evaluate new instrument technologies for soil moisture remote sensing.

The following SMEX02 data sets are available for AMSR-E Validation soil moisture experiments:

Ground Soil Moisture Data: SMEX02 Soil Climate Analysis Network (SCAN) Station 2031, Ames, Iowa SMEX02 Iowa Regional Ground Soil Moisture Data SMEX02 Soil Moisture and Temperature Profiles, Walnut Creek, Iowa SMEX02 Sliced Core Soil Moisture Data, Walnut Creek Watershed, Iowa SMEX02 Watershed Soil Moisture Data, Walnut Creek, Iowa SMEX02 Watershed Vitel Network Soil Moisture Data, Walnut Creek, Iowa

Aircraft Remote Sensing Data:
SMEX02 Passive and Active L and S band System (PALS) Data
SMEX02 Airborne GPS Bistatic Radar Data, Iowa
SMEX02 Aircraft Polarimetric Scanning Radiometer (PSR) Data
SMEX02 Airborne Synthetic Aperture Radar (AIRSAR) Data, Iowa
SMEX02 Electronically Steered Thinned Aperture Radiometer (ESTAR)

Satellite Remote Sensing Data:
SMEX02 Iowa Satellite Vegetation and Water Index (NDVI and NDWI) Data SMEX02 AMSR-E Level-3 Daily Gridded Brightness Temperatures, Iowa
SMEX02 ASTER Level 1B Data, Iowa
SMEX02 European Remote Sensing Satellite 2 (ERS-2) AMI Data, Iowa
SMEX02 Landsat Thematic Mapper Imagery, Iowa
SMEX02 Landsat 5 and 7 Thematic Mapper Land Surface Brightness Temperatures
SMEX02 SSM/I Brightness Temperature Data, Iowa
SMEX02 QuickSCAT/SeaWinds Data

Vegetation Data:
SMEX02 Regional Vegetation Sampling Data, Iowa
SMEX02 Watershed Vegetation Sampling Data, Walnut Creek, Iowa
SMEX02 Vegetation Water Content, Iowa Regional and Walnut Creek Watershed

Meteorological Data:
SMEX02 Rain Gauge Network, Walnut Creek, Iowa
SMEX02 Atmospheric Aerosol Optical Properties Data
SMEX02 CODIAC Soil Climate Analysis Network (SCAN) Data, Iowa
SMEX02 Tower-Based Radiometric Surface Temperature, Walnut Creek, Iowa
SMEX02 Soil Moisture-Atmosphere Coupling Experiment (SMACEX) Walnut Creek, Iowa
SMEX02 Balloon-borne Radiosonde Data, Iowa

Ancillary Data:
SMEX02 Land Surface Information: Geolocation, Surface Roughness, and Photographs
SMEX02 Land Surface Information: Land Use Classification
SMEX02 Land Surface Information: Soils Database