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528 results for “Land cover”
LBA-ECO ND-01 Land Cover Classification, Rondonia, Brazil: 1975-2000
This data set provides a time series of land cover classifications for Ariquemes, Ji-Parana, and Luiza, research sites in Rondonia, Brazil. The land cover classifications are derived from the Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) sensors. The time period ranges from June 1975 through June 2000, but all areas do not have images for all the years. The images were classified into the following categories: 1. Primary upland forest, representing the dominant natural vegetation in the area; 2. Pasture and green pasture; 3. Second growth, dominated by small trees and shrubs with low species diversity and biomass relative to primary forest; 4. Soil/urban; 5. Rock/savanna; 6. Water; and 7. Cloud and smoke obscured. In addition, areas covered by rock and savanna were mapped and all areas outside of the overlap zone between all dates within a scene, and scene edges, were masked.There are 75 GeoTIFF files (.tif) with this data set which includes: classified images (*ful.tif) and a corresponding image mask (*ful_mask .tif) for each date (with the exception of 1978 and 1996 images for Ji-Parana, for which there are only ful_mask.tif files), and three mask files for rock, savannah, and scene edges, for each area. By area, there are 31 images for Ariquemes, 23 images for Ji-Parana, and 21 images for Luiza.
MODIS/Terra+Aqua Land Cover Dynamics Yearly L3 Global 500m SIN Grid V061
The Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (MCD12Q2) Version 6.1 data product provides global land surface phenology metrics at yearly intervals from 2001 to 2021. The MCD12Q2 Version 6.1 data product is derived from time series of the 2-band Enhanced Vegetation Index (EVI2) calculated from MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR). Vegetation phenology metrics at 500 meter spatial resolution are identified for up to two detected growing cycles per year. For pixels with more than two valid vegetation cycles, the data represent the two cycles with the largest NBAR-EVI2 amplitudes.Provided in each MCD12Q2 Version 6.1 Hierarchical Data Format 4 (HDF4) file are layers for the total number of vegetation cycles detected for the product year, the onset of greenness, greenup midpoint, maturity, peak greenness, senescence, greendown midpoint, dormancy, EVI2 minimum, EVI2 amplitude, integrated EVI2 over a vegetation cycle, as well as overall and phenology metric-specific quality information. SDS layers may be multi-dimensional with up to two valid vegetation cycles. For areas where the NBAR-EVI2 values are missing due to cloud cover or other reasons, the data gaps are filled with good quality NBAR-EVI2 values from the year directly preceding or following the product year.Known Issues* Known issues are described in Section 3.2 of the User Guide. * For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=MODIS&sat=TerraAqua&as=61).Improvements/Changes from Previous Versions* The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.* A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).* The MCD12Q2 Version 6.1 product has an improved approach to snow filtering.
EASE-Grid Land Cover Classifications Derived from Boston University MODIS/Terra Land Cover Data, Version 1
These data provide land cover classifications derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The data are available in various EASE-Grid azimuthal and global projections, in 12.5 km and 25 km spatial resolutions. The data are in flat binary, 1 byte files that are stored by row.
EASE-Grid 2.0 Land-Ocean-Coastline-Ice Masks Derived from Boston University MODIS/Terra Land Cover Data, Version 1
These Land-Ocean-Coastline-Ice (LOCI) files provide land classification masks derived from the Boston University MOD12Q1 V004 MODIS/Terra 1 km Land Cover Product (Friedl et al. 2002). The masks are available in various EASE-Grid 2.0 azimuthal and global projections, at various spatial resolutions ranging from 3 km to 100 km. The masks are in flat binary, 1 byte files stored by row. Quick-look browse images of the masks are also available in PNG (.png) format.
BOREAS Follow-On DSP-10 Regridded TM Mosaic Land Cover Maps for 1994
Existing 30-m land cover Thematic Mapper classification by CCRS was aggregated and reprocessed and are now available at multiple resolutions (10x5 minutes and 30 minutes). These data were regridded for use by the BOREAS Follow-on Carbon and Hydro-Meteorological modeling groups. Characteristics of the individual products are described in the data set guide document.
ISLSCP II IGBP DISCover and SiB Land Cover, 1992-1993
This data set describes the geographic distributions of 17 classes of land cover based on the International Geosphere-Biosphere DISCover land cover legend (Loveland and Belward 1997) and the 15 classes of the SiB model processed at the USGS EROS Data Center (EDC). Specifically, the resampled DISCover datasets were derived from the 1km DISCover data set compiled by the USGS. The 1km data sets for each classification scheme were aggregated to 1, 0.5 and 0.25 degree spatial resolutions for this ISLSCP II data collection. Each layer of the aggregated products corresponds to a single DISCover land cover category and the values represent the percentage of the coarse resolution cell (1 degree, etc�) occupied by that land cover category. The dominant class data show the land cover category that occupies the majority of the cell and is derived from the percentage files for each cover type. The objective of this study was to create a land cover map derived from 1 kilometer AVHRR data using a full year of data (April 1992-March 1993). This thematic map was resampled to 0.25, 0.5 and 1.0 degree grids for the International Satellite Land Surface Climatology Project (ISLSCP) data initiative II. During this re-processing, the original EDC land cover type and fraction maps were adjusted to match the water/land fraction of the ISLSCP II land/water mask. These maps were generated for use by global modelers and others. This data set is one of the products of the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) data collection which contains 50 global time series data sets for the ten-year period 1986 to 1995. Selected data sets span even longer periods. ISLSCP II is a consistent collection of data sets that were compiled from existing data sources and algorithms, and were designed to satisfy the needs of modelers and investigators of the global carbon, water and energy cycle. The data were acquired from a number of U.S. and international agencies, universities, and institutions. The global data sets were mapped at consistent spatial (1, 0.5 and 0.25 degrees) and temporal (monthly, with meteorological data at finer (e.g., 3-hour)) resolutions and reformatted into a common ASCII format. The data and documentation have undergone two peer reviews.ISLSCP is one of several projects of Global Energy and Water Cycle Experiment (GEWEX) [http://www.gewex.org/] and has the lead role in addressing land-atmosphere interactions -- process modeling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.
LBA-ECO LC-03 SAR Images, Land Cover, and Biomass, Four Areas across Brazilian Amazon
This data set provides three related land cover products for four study areas across the Brazilian Amazon: Manaus, Amazonas; Tapajos National Forest, Para Western (Santarem); Rio Branco, Acre; and Rondonia, Rondonia. Products include (1) orthorectified JERS-1 and RadarSat images, (2) land cover classifications derived from the SAR data, and (3) biomass estimates in tons per hectare based on the land cover classification. There are 12 image files (.tif) with this data set.Orthorectified JERS-1 and RadarSat images are provided as GeoTIFF images - one file for each study area.For the Manaus and Tapajos sites: The images are orthorectified at 12.5-meter resolution and then re-sampled at 25-meter resolution.For the Rondonia and Rio Branco sites: The images from 1978 are orthorectified at 25-meter resolution and then re-sampled at 90-meter resolution. Each GeoTIFF file contains 3 image channels: - 2 L-band JERS-1 data in Fall and Spring seasons and - 1 C-band RadarSat data.Land cover classifications are based on two JERS-1 images and one RadarSat image and provided as GeoTIFFs - one file for each study area. Four major land cover classes are distinguished: (1) Flat surface; (2) Regrowth area; (3) Short vegetation; and (4) Tall vegetation. The biomass estimates in tons per hectare are based on the land cover classification results and are reported in one GeoTIFF file for each study area.DATA QUALITY STATEMENT: The Data Center has determined that there are questions about the quality of the data reported in this data set. The data set has missing or incomplete data, metadata, or other documentation that diminishes the usability of the products.KNOWN PROBLEMS: The data providers note that due to limited resources, these data have been neither validated nor quality-assured for general use. For that reason, extreme caution is advised when considering the use of these data.Any use of the derived data is not recommended because the results have not been validated. However, the DEM and vectors (related data set), and orthorectified SAR data can be used if the user understands how these were produced and accepts the limitations.
ISLSCP II Historical Land Cover and Land Use, 1700-1990
The Historical Land Cover and Land Use data set was developed to provide the global change community with historical land use estimates. The data set describes historical land use changes over a 300-year historical period (1700-1990).Testing against historical data is an important step for validating integrated models of global environmental change. Owing to long time lags in the climate and biogeochemical systems, these models should aim to simulate the land use dynamics for long periods, i.e., spanning decades to centuries. Developing such models requires an understanding of past and current trends and is therefore strongly data dependent. For this purpose, a historical database of the global environment has been developed: HYDE. Historical statistical inventories on agricultural land (census data, tax records, land surveys, etc) and different spatial analysis techniques were used to create a geographically-explicit data set of land use change, with a regular time interval. The data set can be used to test integrated models of global change. Continental-scale historical data were used for that period.
LBA-ECO CD-06 Ji-Parana River Basin Land Use and Land Cover Map, Brazil: 1999
This data set provides a land use/land cover map of the Ji-Parana River Basin in the state of Rondonia, Brazil produced from the digital classification of eight Landsat 7-ETM+ scenes from 1999 acquired from the Tropical Rain Forest Information Center (TRFIC) at Michigan State University. Nine land cover classes covering the Ji-Parana Basin were identified. There is one GeoTiff file with this data set.
Urban Land Cover Maps for Mekelle, Ethiopia and Polokwane, South Africa, 2020
This dataset consists of very high resolution urban land cover maps for two African cities, Mekelle, Ethiopia and Polokwane, South Africa for 2020. Maps were generated from Planet SuperDove satellite imagery at 3.125-m spatial resolution, and Worldview-3 satellite imagery (Maxar Techologies) at two spatial resolutions, 2 m for multispectral imagery and 0.5-m spatial resolution for pansharpened imagery. An object-based image classification approach was used to produce a multi-class land cover product for each image source. The aim of this work was to support fine scale urban land cover analyses and comparative assessments between different high resolution satellite imagery sources. The data are provided in shapefile format.
LBA-ECO ND-07 Hydrochemistry of Natural and Developed Land Cover, Brasilia, Brazil
This data set reports on dissolved nutrient concentrations, as well as dissolved oxygen, alkalinity, conductivity, turbidity, and pH measured in water samples collected from nine streams located in the state of Brasilia, Brazil, between September, 2004 and December, 2006. Streams were located in different land cover types including natural (forest), rural (agricultural), and developed landscapes. In addition, water samples from wells, lysimeters, surface runoff, and precipitation were collected from four sites, 2 natural and 2 rural, and analyzed for nutrient concentrations. Streams were sampled every 2-4 weeks; rain water was collected approximately monthly during the wet season and once during a dry season; wells and lysimeters were sampled monthly; and surface runoff collections were event based. There are three comma-delimited data files with this data set.
LBA-ECO LC-24 Land Cover Classes from Landsat TM, Uruara, Para: 1986-1991
This data set provides course land cover classifications derived from Landsat TM images for 1986, 1988, and 1991 for the area surrounding the municipality of Uruara, Para, Brazil. Five land cover classes (Water, Clouds/Shadow, Forest, Not Forest, and Background) were derived (Aldrich et al. 2006). The Land Cover is in a compressed (*.zip) GeoTIFF file for each year.
SAFARI 2000 Estimated BVOC Emissions for Southern African Land Cover Types
Improved vegetation distribution and emission data for Africa south of the equator were developed for the Southern African Regional Science Initiative (SAFARI 2000) and combined with biogenic volatile organic compound (BVOC) emission measurements to estimate BVOC emissions for the southern African region. BVOC emissions were estimated for southern Africa on a monthly basis over a one-year period by combining GIS layers of vegetation, LAI, and climate with a biogenic emissions model, GLOBEIS (Guenther et al, 1993; Guenther, 1999). Model input data included: vegetation data (Rutherford et al., 2000); species emission capacity data (Greenberg et al., 2003; Guenther et al., 1996; Harley et al., 2003; Klinger et al., 1998; Otter et al., 2002; Serca et al., 2001; Wiedinmyer et al., 2004); LAI data (1987-88 ISLSCP LAI; Sellers et al., 1994); cloud cover (MODIS LAI cloud mask); and temperature data (NOAA NCDC data).Model output includes emissions estimates for isoprene, light-dependent monoterpene, stored monoterpene, and other volatile organic compounds by land cover category and by vegetation type (g C m-2 mo-1). Emissions were modeled for a summer (January) and a winter (July) month in 2001. Monthly and annual total emissions per constituent for the year 2001 were also calculated. The data files containing the model outputs are ASCII comma-delimited files. Graphics (.jpgs) included with this data set show the distribution of light dependent monoterpene emissions across southern Africa during January, the average monthly isoprene emissions over southern Africa in January and in July, and the average monthly stored monoterpene emissions over southern Africa in January and in July.
LBA-ECO CD-06 Land Use/Land Cover Time Series, Ji-Parana Basin, Brazil: 1986-2001
This data set contains four land use/land cover maps (1986, 1992, 1996 and 2001) for the Ji-Parana River Basin, derived from the digital classification of 8 Landsat images obtained from The Tropical Rain Forest Information Center (TRFIC).
Land Cover and Vegetation Map Collection for Seward Peninsula, Alaska
This data set provides two landcover and vegetation maps for the Seward Peninsula, Alaska. These maps were produced from existing maps, Landsat imagery, and color infrared aerial photography covering the period 1976-06-01 to 1999-09-01.
BigFoot Land Cover Surfaces for North and South American Sites, 2000-2003
The BigFoot project gathered data for nine EOS Land Validation Sites located from Alaska to Brazil from 2000 to 2003. Each site is representative of one or two distinct biomes, including the Arctic tundra; boreal evergreen needleleaf forest; temperate cropland, grassland, evergreen needleleaf forest, and deciduous broadleaf forest; desert grassland and shrubland; and tropical evergreen broadleaf forest. These surfaces were produced from Landsat ETM+ imagery to explicitly characterize the land cover at the BigFoot Sites to provide validation of the MODIS land cover product. The land cover scheme is consistent with the categories defined by the MOD12 IGBP (http://geography.bu.edu/landcover/userguidelc/index.html) strategy. Each BigFoot land cover product covers approximately a 7 x 7 km extent and consists of the land cover surface image in standard geotiff format, an accompanying text file which provides metadata specific to the image (such as projection, data type, class names, etc), and associated auxiliary and world files. For an in depth discussion of methods used to produce these surfaces, please see references.Additional information on land cover surface development can be found on the BigFoot website at http://www.fsl.orst.edu/larse/bigfoot/ovr_mthd.html.BigFoot Project Background:Reflectance data from MODIS, the Moderate Resolution Imaging Spectrometer onboard NASA's Earth Observing System (EOS) satellite Terra (http://landval.gsfc.nasa.gov/MODIS/index.php), is used to produce several science products including land cover, leaf area index (LAI) and net primary production (NPP). The overall goal of the BigFoot Project was to provide validation of these products. To do this, BigFoot combined ground measurements, additional high resolution remote sensing data, and ecosystem process models at nine flux tower sites representing different biomes to evaluate the effects of the spatial and temporal patterns of ecosystem characteristics on MODIS products. BigFoot characterized up to a 7 x 7 km area (49 MODIS pixels) surrounding the CO2 flux towers located at each of the nine sites. We collected multi-year, in situ measurements of ecosystem structure and functional characteristics related to the terrestrial carbon cycle. Our sampling design allowed us to examine scales and spatial pattern of these properties, the inter-annual variability and validity of MODIS products, and provided for a field-based ecological characterization of the flux tower footprint. BigFoot was funded by NASA's Terrestrial Ecology Program.
ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001
This data set, ISLSCP II MODIS (Collection 4) IGBP Land Cover, 2000-2001, contains global land cover classifications (dominant type, classification confidence and fractional cover) generated using a full year of MODerate Resolution Imaging Spectroradiometer (MODIS) data covering the period from October 2000 to October 2001. The objective of the MODIS Land Cover Product is to provide a suite of land cover types useful to global system science modelers by exploiting the information content of MODIS data in the spectral, temporal, spatial, and directional domains. These products describe the geographic distribution of the 17 land cover classification scheme proposed by the International Geosphere-Biosphere Programme (IGBP).
BOREAS Follow-On DSP-01 NBIOME Level-4 AVHRR Land Cover, Canada, Ver. 1.1, 1995
This land cover product was produced by NBIOME to generate an up-to-date, spatially and temporally consistent land cover map of the landmass of Canada for use by scientists and other users interested in environmental information at national and regional scales. The data were acquired by CCRS and were provided to BORIS for use. This data set is gridded and was produced from 10-day composite data of surface parameters. Temporally, the 10-day compositing periods begin 11-April-95 and ends 31-Oct-95. Spatially, the data cover the entire landmass of Canada. The data are stored in binary image format files.
LBA-ECO LC-24 Landsat TM and ETM+ Land Cover, Southern Para, Brazil: 1984-2003
This data set is a five-class land cover for Southern Para for the years 1984 (Landsat MSS), 1988 (Landsat TM), 1996, and 2003 (Landsat ETM+). The final classification shows five classes derived using visual comparison (Water, Clouds/Shadow, Forest, Not Forest, Background). These data were used in 2007 to illustrate the nature of deforestation in Southern Para, Brazil over the past twenty years (Simmons et al. 2007). There are four annual GeoTIFF files distributed with this data set. Each GeoTIFF file and accompanying *.tfw file have been compressed into a single *.zip file.
BOREAS Follow-On DSP-01 Landsat TM Land Cover Mosaic of the BOREAS Transect
The objective of this land cover mosaic is to provide a data product that characterises the detailed land cover of a significant portion of the BOREAS Region. Seven Landsat-5 TM images have been assembled to completely cover the BOREAS Transect. Entire TM scenes were used to create this land cover map. A detailed classification scheme was employed, permitting the extraction of virtually all land cover information that can be discerned from digitally enhanced TM images. The data are provided in a binary image format file.
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