Link to the ScienceBase Item Summary page for the item described by this metadata record. Service Protocol: Link to the ScienceBase Item Summary page for the item described by this metadata record. Application Profile: Web Browser. Link Function: information

This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years since 1992. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2019Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: AnnualWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

India Exports of maps, hydrographic or similar charts (printed) to Kazakhstan was US$583 during 2014, according to the United Nations COMTRADE database on international trade. India Exports of maps, hydrographic or similar charts (printed) to Kazakhstan - data, historical chart and statistics - was last updated on June of 2025.

Water bodies are a key element in the landscape. This layer provides a global map of large water bodies for use in landscape-scale analysis.Dataset SummaryThis layer provides access to a 250m cell-sized raster of surface water created by extracting pixels coded as water in the Global Lithological Map and the Global Landcover Map. The layer was created by Esri in 2014.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

The India Lights platform shows light output at night for 20 years for 600,000 villages across India. The Defense Meteorological Satellite Program (DMSP) has taken pictures of the Earth every night from 1993 to 2013. Researchers at the University of Michigan, in collaboration with the World Bank, used the DMSP images to extract the data you see on the India Lights platform. Each point you see on the map represents the light output of a specific village at a specific point in time. On the district level, the map also allows you to filter to view villages that have participated in India’s flagship electrification program. This tremendous trove of data can be used to look at changes in light output, which can be used to complement research about electrification in the country. About the Data: The DMSP raster images have a resolution of 30 arc-seconds, equal to roughly 1 square kilometer at the equator. Each pixel of the image is assigned a number on a relative scale from 0 to 63, with 0 indicating no light output and 63 indicating the highest level of output. This number is relative and may change depending on the gain settings of the satellite’s sensor, which constantly adjusts to current conditions as it takes pictures throughout the day and at night. Methodology To derive a single measurement, the light output values were extracted from the raster image for each date for the pixels that correspond to each village's approximate latitude and longitude coordinates. We then processed the data through a series of filtering and aggregation steps. First, we filtered out data with too much cloud cover and solar glare, according to recommendations from the National Oceanic and Atmospheric Administration (NOAA). We aggregated the resulting 4.4 billion data points by taking the median measurement for each village over the course of a month. We adjusted for differences among satellites using a multiple regression on year and satellite to isolate the effect of each satellite. To analyze data on the state and district level, we also determined the median village light output within each administrative boundary for each month in the twenty-year time span. These monthly aggregates for each village, district, and state are the data that we have made accessible through the API. To generate the map and light curve visualizations that are presented on this site, we performed some additional data processing. For the light curves, we used a rolling average to smooth out the noise due to wide fluctuations inherent in satellite measurements. For the map, we took a random sample of 10% of the villages, stratified over districts to ensure good coverage across regions of varying village density. Acknowledgments The India Lights project is a collaboration between Development Seed, The World Bank, and Dr. Brian Min at the University of Michigan. •Satellite base map © Mapbox. •India village locations derived from India VillageMap © 2011-2015 ML Infomap. •India population data and district boundaries © 2011-2015 ML Infomap. •Data for reference map of Uttar Pradesh, India, from Natural Earth Data •Banerjee, Sudeshna Ghosh; Barnes, Douglas; Singh, Bipul; Mayer, Kristy; Samad, Hussain. 2014. Power for all : electricity access challenge in India. A World Bank study. Washington, DC ; World Bank Group. •Hsu, Feng-Chi, Kimberly Baugh, Tilottama Ghosh, Mikhail Zhizhin, and Christopher Elvidge. "DMSP-OLS Radiance Calibrated Nighttime Lights Time Series with Intercalibration." Remote Sensing 7.2 (2015): 1855-876. Web. •Min, Brian. Monitoring Rural Electrification by Satellite. Tech. World Bank, 30 Dec. 2014. Web. •Min, Brian. Power and the Vote: Elections and Electricity in the Developing World. New York and Cambridge: Cambridge University Press. 2015. •Min, Brian, and Kwawu Mensan Gaba. Tracking Electrification in Vietnam Using Nighttime Lights. Remote Sensing 6.10 (2014): 9511-529. •Min, Brian, and Kwawu Mensan Gaba, Ousmane Fall Sarr, Alassane Agalassou. Detection of Rural Electrification in Africa using DMSP-OLS Night Lights Imagery. International Journal of Remote Sensing 34.22 (2013):8118-8141. Disclaimer Country borders or names do not necessarily reflect the World Bank Group's official position. The map is for illustrative purposes and does not imply the expression of any opinion on the part of the World Bank, concerning the legal status of any country or territory or concerning the delimitation of frontiers or boundaries.

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

Dosya Dosya geçmişi Dosya kullanımı Küresel dosya kullanımı üstveriBu SVG dosyasının PNG önizlemesinin boyutu 543 600 pi

India Exports of maps, hydrographic or similar charts (printed) to Grenada was US$22 during 2014, according to the United Nations COMTRADE database on international trade. India Exports of maps, hydrographic or similar charts (printed) to Grenada - data, historical chart and statistics - was last updated on June of 2025.

Seafloor geomorphology is the study of physical features on the seafloor. This layer represents the characterizations of geomorphic features and the zones within the ocean where they occur. The data for this layer are from the first map of seafloor geomorphology ever published; this map was published 2014 by GRID Arendal.“The new seafloor features map provides a foundation on which to build an understanding of the living and non-living resources of the ocean and to improve decision making on a range of global issues like food security, resource use and conservation.” - Dr. Peter Harris, the project leader and Managing Director of GRID-Arendal.Dataset SummaryThe geomorphic features in this layer were created by automated and manual processes over the course of many months. The source data for the process is a modified 30-arc second (~1 km) resolution version of SRTM30_PLUS global bathymetry produced in 2009. The following features and zones are included as sub-layers:FeaturesCanyons - Submarine canyons are defined as steep-walled, sinuous valleys with V-shaped cross sections, axes sloping outward as continuously as river-cut land canyons and relief comparable to even the largest of land canyons.Seamounts - Seamounts are a single or group of peaks, greater than 1,000 meters in relief above the sea floor, characteristically of conical form.Guyots - Guyots are isolated or a group of seamount having a comparatively smooth flat top. Also called tablemounts.Troughs - Troughs are long depressions of the sea floor characteristically flat bottomed and steep sided and normally shallower than a trench. In this study we found that troughs are also commonly open at one end (i.e. not defined by closed bathymetric contours) and their broad, flat floors may exhibit a continuous gradient. Troughs may originate from glacial erosion processes or have form through tectonic processes.Glacial Troughs - Glacial troughs are the largest of the shelf valleys at high latitudes incised by glacial erosion during the Pleistocene ice ages to form elongate troughs, typically trending across the continental shelf and extending inland as fjord complexes. Glacial troughs are characterized by depths of over 100 m (often exceeding 1,000 m depth) and are distinguished from shelf valleys by an over-deepened longitudinal profile that reaches a maximum depth inboard of the shelf break, thus creating a perched basin on the shelf with an associated sill.Trenches - Trenches are long narrow very deep asymmetrical depressions of the sea floor, with relatively steep sides. Trenches are generally distinguished from troughs by their “V” shape in cross section (in contrast with flat-bottomed troughs). Bridges - Bridge features are blocks of material that partially infill Trenches forming a “bridge”across the trench.Sills - Sills are a sea floor barrier of relatively shallow depth restricting water movement between basins. Thus every basin has a sill, over which fluid would escape if the basin were filled to overflowing. Shelf Valleys - Shelf valleys are greater than 10 km in length and greater than 10 m in depth overall with an elongate shape more than 4 times greater in length than width.Rift Valleys - Rift valleys are confined to the central axis of mid-ocean spreading ridges; they are elongate, local depressions flanked generally on both sides by ridges.Ridges - Ridges are isolated or a group of elongated narrow elevations of varying complexity with steep sides, often separating basin features. Ridges have greater than 1,000 meters of relief.Spreading Ridges - Spreading ridges are mid-oceanic mountain systems of global extent.Terraces - Terraces an isolated or a group of relatively flat horizontal or gently inclined surface(s), sometimes long and narrow, which is (are) bounded by a steeper ascending slope on one side and by a steeper descending slope on the opposite side. Fans - Fans are relatively smooth, fan-like, depositional featured normally sloping away from the outer termination of a canyon or canyon system. Fans overlay and comprise part of the continental rise and are located offshore from the base of the continental slope. Fans are inter-related with submarine canyons and sediment drift deposits; in cases where canyon axes extend across the rise, the canyon-channels may be flanked by sediment drift deposits, which have been grouped with fans in this study. Fans are defined in the present study by 100 m isobaths that form a concentric series exhibiting an expanding spacing in a seaward direction away from the base of the slope, sometimes clearly associated with a canyon mouth, but also comprising low-relief ridges between canyon-channels on the abyssal plain.Rises - Continental rises are areas with sediment thickness greater than 300 meters and the occurrence of a smooth sloping seabed as indicated by evenly-spaced, slope-parallel contours. In this study, the term “Rise” was restricted to features that abut continental margins and does not include the mid-ocean ridge.Plateaus - Plateaus are flat or nearly flat elevations of considerable areal extent, dropping off abruptly on one or more sides. TerrainMountains - Greater than 1,000 meters of local relief within ~25 kilometers.Hills - Between 300 and 1,000 meters of local relief within ~25 kilometers.Plains - Less than 300 meters of local relief within ~25 kilometers.Basins - Basins are depressions in the sea floor that are more or less equi-dimensional in plan, of variable extent, and are restricted to seafloor depressions defined by closed bathymetric contours.Escarpments - Escarpments are “an elongated, characteristically linear, steep slope separating horizontal or gently sloping sectors of the sea floor in non-shelf areas. Also abbreviated to scarp” (IHO, 2008). Escarpments, like basins, overlay other features (i.e. other individual features may be partly or wholly covered by escarpments). Thus features like the continental slope, seamounts, guyots, ridges and submarine canyons (for example) may be sub-classified in terms of their area of overlain escarpment.ZonesShelf - The zone adjacent to the continents or islands. Slope - The deepening seafloor from the edge of the shelf to the top of the continental rise.Abyss - Areas below the foot of the continental rise and includes all depths up to 6,000 meters.Hadal - Depths greater than 6,000 metersNote that the above definitions are brief summarizations of the definitions contained in Geomorphology of the Oceans.Esri staff edited several of the layers: Zones, Terrain, Basins, and Glacial Troughs to improve drawing performance. All of these edits were split polygon operations; no vertexes were moved, only at cut points were vertexes introduced. If these layers are downloaded, these edits can be removed by using the Dissolve tool, with all fields, including shape, and producing no multi-part polygons in the output.For metadata info, please see Bluehabitats.org.What can you do with this layer?This layer is based on a dynamic map service, which means there are several sub-layers of vector features that can be used for visualization and analysis throughout the ArcGIS Platform. This layer is not editable.This layer is part of a larger collection of Oceans layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about oceans layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.

The Mysuru City Bird Atlas is an ambitious volunteer project to map the birds of an entire city – the first systematic effort of its kind in India. Mysuru city was gridded into a set of square cells, and each cell was surveyed for birds in the winter and in the summer of 2014, 2015 and 2016. The goal of this effort was to assess the distribution and abundance of the birds of Mysuru such that the accumulated information can be used to assess seasonal changes in avifauna as well as to examine the relationship between birds and their habitat in an urban setting. In this article, we present selected outcomes, including maps as well as raw comparisons of abundance across the two seasons and the three years of the atlas surveys. Some of the results recapture broadly understood phenomena, such as long-distance migration resulting in seasonal differences in bird communities and species richness. Other results are suggestive of previously undescribed patterns, such as seasonal local movements. F...

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

This layer is sourced from gis.wim.usgs.gov.

1.27.2014 --ESM-- created for DOI building location map.

This layer provides slope values calculated from elevation data. The values are integer and represent the angle of the downward sloping terrain from 0 (flat) to 90 degrees (vertical). The layer is designed for use in landscape-scale analysis.Dataset SummaryThis layer provides access to a 250m cell-sized raster of slope in degrees. The layer was created with the ArcGIS Slope Tool using the GMTED elevation layer as an input. The layer was created in 2014 by Esri.What can you do with this layer?This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. The source data for this layer are available here.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

India Exports of maps, hydrographic or similar charts (printed) to Lesotho was US$307 during 2014, according to the United Nations COMTRADE database on international trade. India Exports of maps, hydrographic or similar charts (printed) to Lesotho - data, historical chart and statistics - was last updated on June of 2025.

The GIS dataset supports in part, the First Nations and Treaties Map produced by the Ministry of Indigenous Relations and Reconciliation published May 20, 2014.

Status Unknown: frequency of maintenance of the data is not known

Maintenance and Update Frequency Unknown: frequency of maintenance of the data is not known

Contact

Richard Carr, Negotiations and Reconciliation Division, Richard.Carr@ontario.ca

Layered GeoPDF 7.5 Minute Quadrangle Map. Layers of geospatial data include orthoimagery, roads, grids, geographic names, elevation contours, hydrography, and other selected map features.

India Exports: Volume: HS: 49059990: Other Maps or Charts data was reported at 218.650 kg th in 2018. This records an increase from the previous number of 118.330 kg th for 2017. India Exports: Volume: HS: 49059990: Other Maps or Charts data is updated yearly, averaging 218.650 kg th from Mar 2004 (Median) to 2018, with 15 observations. The data reached an all-time high of 414.460 kg th in 2014 and a record low of 31.010 kg th in 2006. India Exports: Volume: HS: 49059990: Other Maps or Charts data remains active status in CEIC and is reported by Ministry of Commerce and Industry. The data is categorized under India Premium Database’s Foreign Trade – Table IN.JBZ003: Foreign Trade: Harmonized System 8 Digits: By Commodity: HS49: Printed Books, Newspapers, Pictures etc: Exports: Volume.

Ecophysiographic facets are unique combinations of climate, lithology, landcover, and landform. This layer is designed for use as a geoprocessing input and to support pop-ups in ArcGIS Online.This layer is designed for use as a geoprocessing input and to support pop-ups in ArcGIS Online. Because of the large number of unique values in the image service it cannot be symbolized and displays as an all black or white layer. Include this layer in web maps by making it draw 100% transparent.This 2015 map contains updates to the 2014 Ecophysiographic Facets layer in the form of landforms and land cover data, which have greater variety of classes and better spatial coherence (less arbitrary fragmentation). The result is more than twice as many unique facet combinations.Ecophysiographic Facets are areas of distinct bioclimate, landform, lithology, and land cover that form the basic components of terrestrial ecosystem structure. The Ecophysiographic Facets layer was produced by combining the values in four 250-m cell-sized rasters using the ArcGIS Combine tool (Spatial Analyst). The first three of these inputs (climate, landforms, lithology) represent the primary environmental factors that determine the distribution of living organisms while the fourth (land cover) is vegetation's response to the physical environment.Dataset SummaryThis layer provides access to a 250-m cell-sized raster of unique combinations of climate, lithology, land cover, and landform known as ecophysiographic facets. The layer was created in 2015 by Esri and the USGS. The following layers were used to create this map:World BioclimatesWorld Landforms Improved Hammond MethodWorld LithologyWorld Land Cover ESA 2010A simplified classification of the ecological facets is available in the World Ecophysiographic Land Units layer. A layer summarizing the local diversity of ecophysiographic facets is available here. A service is available providing access to the data tables associated with this and other global layers. These data table services can be used by developers to create custom applications. For more information see the World Ecophysiographic Tables.The process used to produce this layer is documented in the publication:Sayre and others. 2014. A New Map of Global Ecological Land Units — An Ecophysiographic Stratification Approach. Washington, DC: Association of American Geographers. 46 pages. What can you do with this layer?This layer is suitable for analysis and can be used in ArcGIS Online to support pop-ups. It can be used in ArcGIS Desktop. Because of the large number of unique values in the image service it cannot be symbolized and displays as an all white layer. To use in pop-ups set the transparency to 100% and configure the pop-up.This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

India Exports of maps, hydrographic or similar charts (printed) to Namibia was US$769 during 2014, according to the United Nations COMTRADE database on international trade. India Exports of maps, hydrographic or similar charts (printed) to Namibia - data, historical chart and statistics - was last updated on June of 2025.

India Imports from Jordan of Maps, Hydrographic or Similar Charts (Printed) was US$48 during 2014, according to the United Nations COMTRADE database on international trade. India Imports from Jordan of Maps, Hydrographic or Similar Charts (Printed) - data, historical chart and statistics - was last updated on June of 2025.