Published June 16, 2015 | Version v1
Dataset Open

Input data for 'forest_carbon_edge_effects'

  • 1. Stanford University
  • 2. North Carolina State University
  • 3. University of Minnesota
  • 4. Unilever

Description

1. af.tif: Land-cover from MODIS for the continent of Africa clipped to the tropical regions to match the biomass dataset; 16 classes defined by the UMD classification. From Friedl, M. A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang. 2010. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114:168–182.
2. af_biov2ct1.tif: Above-ground biomass for the tropical regions of Africa; biomass measured as tons/ha. From Baccini, A., S. J. Goetz, W. S. Walker, N. T. Laporte, M. Sun, D. Sulla-Menashe, J. Hackler, P. S. A. Beck, R. Dubayah, M. A. Friedl, S. Samanta, and R. A. Houghton. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change 2:182–185.
3. am.tif: Land-cover from MODIS for the Americas; 16 classes defined by the UMD classification. From Friedl, M. A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang. 2010. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114:168–182.
4: am_biov2ct1.tif: Above-ground biomass for the tropical regions of the Americas; biomass measured as tons/ha. From Baccini, A., S. J. Goetz, W. S. Walker, N. T. Laporte, M. Sun, D. Sulla-Menashe, J. Hackler, P. S. A. Beck, R. Dubayah, M. A. Friedl, S. Samanta, and R. A. Houghton. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change 2:182–185.5: anthrome_0.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(0): No data. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
5: anthrome_11.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(11):Urban. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
6: anthrome_12.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(12):Mixed settlements. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
7: anthrome_21.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(21):Rice villages. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
8: anthrome_22.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(22):Irrigated villages. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
9: anthrome_23.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(23):Rainfed villages. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
10: anthrome_24.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(24):Pastoral villages. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
11: anthrome_31.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(31):Residential irrigated croplands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
12: anthrome_32.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(32):Residential rainfed croplands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
13: anthrome_33.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(33):Populated croplands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
14: anthrome_34.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(34):Remote croplands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
15: anthrome_41.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(41):Residential rangelands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
16: anthrome_42.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(42):Populated rangelands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
17: anthrome_43.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(43):Remote rangelands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
18: anthrome_51.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(51):Residential woodlands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
19: anthrome_52.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(52):Populated woodlands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
20: anthrome_53.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(53):Remote woodlands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
21: anthrome_54.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(54):Inhabited treeless and barren lands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
22: anthrome_61.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(61):Wild woodlands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
23: anthrome_62.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. Value(62):Wild treeless and barren lands. From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
24: as.tif: Land-cover from MODIS for the continent of Asia; 16 classes defined by the UMD classification. From Friedl, M. A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang. 2010. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sensing of Environment 114:168–182.
25: as_biov2ct1.tif: Above-ground biomass for the tropical regions of Asia; biomass measured as tons/ha. From Baccini, A., S. J. Goetz, W. S. Walker, N. T. Laporte, M. Sun, D. Sulla-Menashe, J. Hackler, P. S. A. Beck, R. Dubayah, M. A. Friedl, S. Samanta, and R. A. Houghton. 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change 2:182–185.
26-30: ecoregions_projected.(.dbf/.prj/.qpj/.shp/.shx): Terrestrial Ecoregions of the World is a biogeographic regionalization of the Earth’s terrestrial biodiversity. Units are ecoregions, defined as relatively large units of land or water containing a distinct assemblage of natural communities sharing a large majority of species, dynamics, and environmental conditions. From Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'Amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., Loucks, C. J., Allnutt, T. F., Ricketts, T. H., Kura, Y., Lamoreux, J. F., Wettengel, W. W., Hedao, P., Kassem, K. R. 2001. Terrestrial ecoregions of the world: a new map of life on Earth. Bioscience 51(11):933-938.
31: fi_average.tif: Average fire density 1997-2011. Based on the modified algorithm 1 product of World Fire atlas (WFA, ESA-ESRIN) dataset. UNEP/GRID-Europe compiled the monthly data and processed the global fire density. Unit is expected average number of event per 0.1 decimal degree pixel per year multiplied by 100 (e.g. 64 value means 0.64 events per year) and slightly smoothed. From UNEP, DEWA, GRID -Europe, Collection: Global Estimated Risk Index for Multiple Hazards. Web. 30 Sep 2014,http://preview.grid.unep.ch/index.php?preview=data&events=fires.
32: gl_anthrome.tif: Anthromes (Anthropogenic Biomes, or "human biomes") represent the global ecological patterns created by sustained direct human interactions with ecosystems. All values(see items 5-24). From Ellis, E. C., K. Klein Goldewijk, S. Siebert, D. Lightman, and N. Ramankutty. 2010. Anthropogenic transformation of the biomes, 1700 to 2000. Global Ecology and Biogeography xx:xxx-xxx. DOI: 10.1111/j.1466-8238.2010.00540.x
33: glbctd1t0503m.tif:  Gridded Livestock of the World: Cattle. Number per square kilometer. These maps are created through the spatial disaggregation of sub-national statistical data based on empirical relationships with environmental variables in similar agro-ecological zones. From Robinson, T. P. et al. Mapping the Global Distribution of Livestock. PLoS One 9, e96084 (2014).
34: glbgtd1t0503m.tif:  Gridded Livestock of the World: Goats. Number per square kilometer. These maps are created through the spatial disaggregation of sub-national statistical data based on empirical relationships with environmental variables in similar agro-ecological zones. From Robinson, T. P. et al. Mapping the Global Distribution of Livestock. PLoS One 9, e96084 (2014).
35: glbpgd1t0503m.tif:  Gridded Livestock of the World: Pigs. Number per square kilometer. These maps are created through the spatial disaggregation of sub-national statistical data based on empirical relationships with environmental variables in similar agro-ecological zones. From Robinson, T. P. et al. Mapping the Global Distribution of Livestock. PLoS One 9, e96084 (2014).
36: glbshd1t0503m.tif:  Gridded Livestock of the World: Sheep. Number per square kilometer. These maps are created through the spatial disaggregation of sub-national statistical data based on empirical relationships with environmental variables in similar agro-ecological zones. From Robinson, T. P. et al. Mapping the Global Distribution of Livestock. PLoS One 9, e96084 (2014).
37: glds00ag.tif: Gridded Population Density of the World, Version 3: (GPWv3): Population Density Grid. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. From CIESIN, IFPRI, Bank, T. W. & CIAT, Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Population Density Grid. (2011). Web. 26 Sep 2014. http://dx.doi.org/10.7927/H4R20Z93
38: glds00g.tif: Gridded Population Density of the World, Version 3: (GPWv3): Population Density Grid. A proportional allocation gridding algorithm, utilizing more than 300,000 national and sub-national administrative units, is used to assign population values to grid cells. The population density grids are derived by dividing the population count grids by the land area grid and represent persons per square kilometer. From CIESIN, IFPRI, Bank, T. W. & CIAT, Global Rural-Urban Mapping Project, Version 1 (GRUMPv1): Population Density Grid. (2011). Web. 26 Sep 2014. http://dx.doi.org/10.7927/H4R20Z93
39: global_elevation.tiff: GTOPO30 is a global digital elevation model (DEM) with a horizontal grid spacing of 30-arc seconds (0.008333333333333 degrees or approximately 1 kilometer), resulting in a DEM having dimensions of 21,600 rows and 43,200 columns. The horizontal coordinate system is decimal degrees of latitude and longitude referenced to World Geodetic System 84 (WGS84). The vertical units represent elevation in meters above mean sea level. The elevation values range from -407 to 8,752 meters. In the DEM, ocean areas have been masked as no data and have been assigned a value of -9999. Lowland coastal areas have an elevation of at least 1 meter (so in the event that a user reassigns the ocean value from -9999 to 0 the land boundary portrayal will be maintained). Small islands in the ocean less than approximately 1 square kilometer are not represented. GTOPO30 was derived from several raster and vector sources of topographic information. These sources include: Digital Terrain Elevation Data, Digital Chart of the World, USGS 1-degree Digital Elevation Models, Army Map Service 1:1,000,000-scale Maps, International 1:1,000,000-scale Map of the World, Peru 1:1,000,000-scale Map, New Zealand DEM, and Antarctic digital Database. GTOPO30 was developed to meet the needs of the geospatial data user community for regional and continental scale topographic data. The data are suitable for many regional and continental applications, such as climate modeling, continental-scale land cover mapping, extraction ofdrainage features for hydrologic modeling and geometric and atmospheric correction of medium and coarse resolution satellite image data. An example of a recent application derived from GTOPO30 is HYDRO1k, a geographic database (at a resolution of 1 km) developed to provide comprehensive and consistent global coverage of topographically derived data sets, including streams, drainage basins, and ancillary layers . HYDRO1k provides a suite of geo-referenced data sets, both raster and vector, which will be of value for all users who need to organize, evaluate, or process hydrologic information on a continental scale. The raster data sets are the hydrologically correct DEM, derived flow directions, flow accumulations, slope, aspect, and a compound topographic (wetness) index. The derived streamlines and basins are distributed as vector data sets. GTOPO30 was developed through a collaborative effort led by staff at the U.S. Geological Survey's EROS EDC. The following organizations participated by contributing funding or source data: the National Aeronautics and Space Administration (NASA), the United Nations Environment Programme/Global Resource Information Database (UNEP/GRID), the U.S. Agency for International Development (USAID), the Instituto Nacional de Estadistica Geografica e Informatica (INEGI) of Mexico, the Geographical Survey Institute (GSI) of Japan, Manaaki Whenua Landcare Research of New Zealand, and the Scientific Committee on Antarctic Research (SCAR).  From Grenlee S., Gesch, D, available online [http://webmap.ornl.gov/wcsdown/dataset.jsp?ds_id=10003] from ORNL DAAC, Oak Ridge, Tennessee, U.S.A..
40: global_precip.tiff: The Global Precipitation Climatology Centre (GPCC), which is operated by the Deutscher Wetterdienst (National Meteorological Service of Germany), is a component of the Global Precipitation Climatology Project (GPCP) with the main emphasis on the treatment of the global in-situ observations. The GPCC simultaneously contributes to the Global Climate Observing System (GCOS) and other international research and climate monitoring projects. This rain gauge-only data set was acquired from GPCC and resampled to 0.5 degree grid boxes for use in the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II. The GPCC collects precipitation data which are locally observed at rain gauge stations and distributed as CLIMAT and SYNOP reports via the Global Telecommunication System of the World Weather Watch (GTS) of the World Meteorological Organization (WMO). The Centre acquires additional monthly precipitation data from meteorological and hydrological networks which are operated by national services. Meeson B., Los, S, Landis, D., Hall F., Collatz, G., Brown de Colstoun, E. available online [http://webmap.ornl.gov/wcsdown/wcsdown.jsp?dg_id=995_20] from ORNL DAAC, Oak Ridge, Tennessee, U.S.A..
41: global_soil_types.tiff: A global data set of soil types is available at 1-degree latitude by 1-degree longitude resolution. There are 26 soil units based on Zobler’s assessment of FAO Soil Units (Zobler, 1986). The data set was compiled as part of an effort to improve modeling of the hydrologic cycle portion of global climate models. A more extensive version of these data, including 106 soil units as well as soil texture and slope, is available from NCAR, Scientific Computing Division, Data Support Section; the more extensive data set is entitled "Staub and Rosenweig's GISS Soil & Sfc Slope, 1-Deg" [http://www.dss.ucar.edu/datasets/ds770.0/]. A help file prepared by Matthews and Fung (1987) (soil1x1.help) is provided as a companion file. Image of 26 soil types available at 1-degree by 1-degree resolution. Additional documentation from Zobler’s assessment of FAO soil units is available from the NASA Center for Scientific Information. 
42: global_water_capacity: Plant-extractable water capacity of soil is the amount of water that can be extracted from the soil to fulfill evapotranspiration demands. It is often assumed to be spatially invariant in large-scalecomputations of the soil-water balance. Empirical evidence, however, suggests that this assumption is incorrect. This data set provides an estimate of the global distribution of plant-extractable water capacity of soil. A representative soil profile, characterized by horizon (layer) particle size data and thickness, was created for each soil unit mapped by FAO (Food and Agriculture Organization of the United Nations)/Unesco. Soil organic matter was estimated empirically from climate data. Plant rooting depths and ground coverages were obtained from a vegetation characteristic data set. At each 0.5 x 0.5 degree grid cell where vegetation is present, unit available water capacity (cm water per cm soil) was estimated from the sand, clay, and organic content of each profile horizon, and integrated over horizon thickness. Summation of the integrated values over the lesser of profile depth and root depth produced an estimate of the plant-extractable water capacity of soil. The global average of the estimated plant-extractable water capacities of soil is 8.6 cm (Greenland, Antarctica and bare soil areas excluded). Estimates are less than 5, 10 and 15 cm - over approximately 30, 60, and 89 per cent of the area, respectively. Estimates reflect the combined effects of soil texture, soil organic content, and plant root depth or profile depth. The most influential and uncertain parameter is the depth over which the plant-extractable water capacity of soil is computed, which is usually limited by root depth. Soil texture exerts a lesser, but still substantial, influence. Organic content, except where concentrations are very high, has relatively little effect. The file is available in an ascii array format. The format is such that j=1 corresponds to the grid cell bounded by 90.0 and 89.5 degrees south latitude (centered on 89.75) and i=1 corresponds to the grid cell bounded by 0.0 and 0.5 degrees east longitude (centered on 0.25). No data are given for land ice grid cells, most of which occur in Antarctica and Greenland, or for other unvegetated areas. A value of -99.0 indicates either a water grid cell or a land ice grid cell. A value of -1.0 indicates that vegetation is absent (and the plant-extractable water capacity of soil is undefined). Units are cm. The data file may be read as follows: dimension whcdat(720,360) do j=1,360 read(iunit,'(36f5.1)') (whcdat(i,j),i=1,720) enddo Data Citation The data set should be cited as follows: Dunne, K. A., and Cort J. Willmott. 2000. Global Distribution of Plant-extractable Water Capacity of Soil (Dunne). Available on-line from Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.43-49: ilf2000_last_proj(.cpg/.dbf/.prj/.qpj/.shp/.shx/.tif): Intact Forest Landscape, 2000 (IFL2000). The world's IFL map is a spatial database (scale 1:1,000,000) that shows the extent of the intact forest landscapes (IFL) for year 2000. IFL is an unbroken expanse of natural ecosystems within the zone of current forest extent, showing no signs of significant human activity, and large enough that all native biodiversity, including viable populations of wide-ranging species, could be maintained. From Potapov P., Yaroshenko A., Turubanova S., Dubinin M., Laestadius L., Thies C., Aksenov D., Egorov A., Yesipova Y., Glushkov I., Karpachevskiy M., Kostikova A., Manisha A., Tsybikova E., Zhuravleva I. 2008. Mapping the World's Intact Forest Landscapes by Remote Sensing. Ecology and Society, 13 (2) http://www.ecologyandsociety.org/vol13/iss2/art51/
50: lighted_area_luminosity.tif: NASA Earth Observation Satellite.

Files

af.tif

Files (7.9 GB)

Name Size Download all
md5:d0d18699f4eb1dec8ffe37b85082aa3b
396.0 MB Preview Download
md5:6590866df8f6e94ef2c0c3cb2335e268
398.1 MB Preview Download
md5:a1cb7d0380cb4a0ba3663bf04123fdd1
712.7 MB Preview Download
md5:f0efd2c09c6b145dac0b4f7b83e29d9a
715.5 MB Preview Download
md5:6213ab940fe71f329fede9a8f29137fa
31.2 MB Preview Download
md5:786a07dafd0c92a12c67056fca140e4d
31.2 MB Preview Download
md5:d1d77f1122c296877b4b619a327ae9ba
31.2 MB Preview Download
md5:cabd23a8bc6ff0b74df113aef0ff324e
31.2 MB Preview Download
md5:ec5577e8a6a5889f6fbad94cfbbd1653
31.2 MB Preview Download
md5:2b00bb6543c3e19249bc56cc2e74620f
31.2 MB Preview Download
md5:6b40b75141e50c1a869f97d68625427e
31.2 MB Preview Download
md5:76fbc18e9c2834b216b978dd15c0d49e
31.2 MB Preview Download
md5:13718c151ce73cceaa18a51f4d037903
31.2 MB Preview Download
md5:e6760b4fddace54bd33333893a8ba6f1
31.2 MB Preview Download
md5:c0644134423132a6015e66fba2c2cb15
31.2 MB Preview Download
md5:b1e56f360e214392cf62777883635f6f
31.2 MB Preview Download
md5:2078a1ef63825f1b7660ca9124ec9842
31.2 MB Preview Download
md5:64d7c2e1f7834d5fb8eedcf3eb954110
31.2 MB Preview Download
md5:456af6da90a9eefab713f3d948601d72
31.2 MB Preview Download
md5:003cb104a1b24b4e682adea7e31db581
31.2 MB Preview Download
md5:edb4d28bff424bc96095aca9c50f0d3c
31.2 MB Preview Download
md5:cb8600b08b86d99ded6d24e24160520b
31.2 MB Preview Download
md5:81a07e6b3cd37efcb8fc6991b4ae0f32
31.2 MB Preview Download
md5:c613a3c6dad5b56268cd084053769ff9
31.2 MB Preview Download
md5:e1e1ac87dcd4a63b86d1b83a800fe1b7
31.2 MB Preview Download
md5:b9490d3a359d0f55637ebe166726af7f
544.4 MB Preview Download
md5:04d14d50f68325d0f7c8d720c7845dfb
548.2 MB Preview Download
md5:0f245390bed80e7f7c3d55838cdfeee7
632.2 kB Download
md5:2fe4e31bc1f0ede7c5262f0e954febeb
293 Bytes Download
md5:2235817794e35587a706bbccf96c1f38
286 Bytes Download
md5:e755249ac1f35f2e7abaa770394908b8
66.4 MB Download
md5:b1d7b4de0fe754df989b3e8685cb8141
6.6 kB Download
md5:8c6ff66baae115b0776a9b821fcc3640
65.4 MB Preview Download
md5:c3e90c2243c2e995e4e09b1c779235e5
31.2 MB Preview Download
md5:8466cfee75d16df9a9fcfc76a8dfa3ab
518.5 MB Preview Download
md5:c8b96b65521c900cbb6a91863433012c
518.5 MB Preview Download
md5:8d90585e62b6259b1f3867349c9ba451
518.5 MB Preview Download
md5:de5284e76d15ded90bb199d90f73e575
518.5 MB Preview Download
md5:a25f1d70b8a5a58c27f0052df2cb432c
118.7 MB Preview Download
md5:17ffe2bf85a3f92772f61ac909fd12f5
118.7 MB Preview Download
md5:f050645f2428cbf823d50ae84cea5fb4
5.1 MB Preview Download
md5:75f5c3eccfb3d96ae986f476bd13c2e7
55.1 MB Preview Download
md5:327793e98e378000b44c0ba7de219e52
10.4 kB Preview Download
md5:df73d0add2db619be342cf4919250304
577.2 kB Preview Download
md5:d3f75bafb4efe772ddb5596d8ca9dccc
1.5 MB Preview Download
md5:ae3b3df9970b49b6523e608759bc957d
5 Bytes Download
md5:7b08016034946bd33bede3608e2412be
91.9 kB Download
md5:2fe4e31bc1f0ede7c5262f0e954febeb
293 Bytes Download
md5:2235817794e35587a706bbccf96c1f38
286 Bytes Download
md5:619e88965d2dab014418b64acb5f5619
298.1 MB Download
md5:a7e23691ec9e27782b66fb029d5b384b
18.5 kB Download
md5:77c42b355fdd95e132385a90bdb07575
700.9 MB Preview Download
md5:9819dedde6992dbd6860a8090c54e36f
362.4 MB Preview Download