Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.In the soil, clay and humus have static electrical charges that attract and hold positively charged particles known as cations. These positively charged particles are often plant nutrients and their abundance can be used as a measure of soil fertility.Dataset SummaryThis layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes related to the exchange capacity of the soil derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).Fields for topsoil (0-30 cm) and subsoil (30-100 cm) are available for each of these attributes related to exchange capacity:Cation Exchange Capacity – Clay - cmol/kgCation Exchange Capacity – Soil - cmol/kgBase Saturation - %Total Exchangeable Bases - cmol/kg Total Sodicity (ESP) - % Additionally, class description fields based on the document Harmonized World Soil Database Version 1.2 were added by Esri for the Base Saturation and Total Sodicity fields for the topsoil and subsoil layers of each map unit. These fields are designed for use in web map pop-ups.The layer is symbolized with the Topsoil Base Saturation field.The document Harmonized World Soil Database Version 1.2 provides more detail on the soil exchange capacity attributes contained in this layer.Other attributes contained in this layer include:Soil Mapping Unit Name - the name of the spatially dominant major soil groupSoil Mapping Unit Symbol - a two letter code for labeling the spatially dominant major soil group in thematic mapsData Source - the HWSD is an aggregation of datasets. The data sources are the European Soil Database (ESDB), the 1:1 million soil map of China (CHINA), the Soil and Terrain Database Program (SOTWIS), and the Digital Soil Map of the World (DSMW).Percentage of Mapping Unit covered by dominant componentMore information on the Harmonized World Soil Database is available here.Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:World Soils Harmonized World Soil Database - Bulk DensityWorld Soils Harmonized World Soil Database – ChemistryWorld Soils Harmonized World Soil Database – GeneralWorld Soils Harmonized World Soil Database – HydricWorld Soils Harmonized World Soil Database – TextureThe authors of this data set request that projects using these data include the following citation:FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.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.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:Living Atlas Discussion GroupSoil Data Discussion GroupThe Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

The dataset contains state-wise distribution of land by different types of soil such as Alluvial, Coastal Alluvial, Black, Red, Rock, Desert, Mountain Medow, Glacier, Sub-montane, Brown, Salf, Hill, Water Bodies, Terai, Peat, Mangrove, Swamps, Beach, Creeks, Lagoons, Gullied, etc.

Indian Regions Soil Image Database (IRSID) : A dataset for classification of Indian soil types

Soil erosion has been spotted as one of the major global problems, and soil erodibility is the property of soil which refers to the erosive nature of the soil. India is also struggling with the erosion problem in most parts of the country. A national-scale soil erosion study is needed to assess such types of problems. ISED (Indian Soil Erodibility Dataset) is a step toward building datasets in mapping soil erosion at a national scale after IRED (Indian Rainfall Erosivity Dataset). This dataset consists of K-factor (t-ha-h/ha/MJ/mm), soil erodibility indices like CR (Clay Ratio), Modified Clay Ratio (MCR), and CLOM (Critical Level of Organic Matter) map over India at high resolution (250 m). It also includes a Susceptibility to Erosion map of India due to Organic Matter availability. Distribution maps of soil erodibility corresponding to the districts and soil types of India are also added to this dataset. This dataset is an additional dataset at a national scale for soil erosion modeling which will be handy data for experts and researchers.

For large areas, like Washington State, download as a file geodatabase. Large data sets like this one, for the State of Washington, may exceed the limits for downloading as shape files, excel files, or KML files. For areas less than a county, you may use the map to zoom to your area and download as shape file, excel or KML, if that format is desired.Information for SOILS data layer was derived from the Private Forest Land Grading system (PFLG) and subsequent soil surveys. PFLG was a five-year mapping program completed in 1980 for the purpose of forestland taxation. It was funded by the Washington State Department of Revenue. The Department of Natural Resources, Soil Conservation Service (now known as the Natural Resources Conservation Service or NRCS), USDA Forest Service and Washington State University conducted soil mapping cooperatively following national soil survey standards. Private lands having the potential of supporting commercial forests were surveyed along with interspersed small areas of State lands, Indian tribal lands, and federal lands. Because this was a cooperative soil survey project, agricultural and non-commercial forestlands were included within some survey areas. After the Department of Natural Resources originally developed its geographic information system, digitized soil map unit delineations and a few soil attributes were transferred to the system. Remaining PFLG soil attributes were later added and are now available through associated lookup tables. SCS (NRCS) soils data on agricultural lands also have been subsequently added to this data layer. The SOILS data layer includes approximately 1,100 townships with wholly or partially digitized soils data. State and private lands which have the potential of supporting commercial forest stands were surveyed. Some Indian tribal and federal lands were surveyed. Because this was a cooperative soils survey project, agricultural and non-commercial forestlands were also included within some survey areas. After the Department of Natural Resources originally developed its geographic information system, digitized soils delineations and a few soil attributes were transferred to the system. Remaining PFLG soil attributes were added at a later time and are now available through associated lookup tables. SCS soils data on agricultural lands also have subsequently been added to this data layer. This layer includes approximately 1, 100 townships with wholly or partially digitized soils data (2,101 townships would provide complete coverage of the state of Washington).-

The soils_sv resolves one to many relationships and as such is one of those special "DNR" spatial views ( ie. is implemented similar to a feature class). Column names may not match between SOILS_SV and the originating datasets. Use limitations

This Spatial View is available to Washingotn DNR users and those with access to the Washington State Uplands IMS site.

The following cautions only apply to one-to-many and many-to-many spatial views! Use these in the metadata only if the SV is one-to-many or many-to-many.

CAUTIONS: Area and Length Calculations: Use care when summarizing or totaling area or length calculations from spatial views with one-to-many or many-to-many relationships. One-to-many or many-to-many relationships between tabular and spatial data create multiple features in the same geometry. In other words, if there are two or more records in the table that correspond to the same feature (a single polygon, line or point), the spatial view will contain an identical copy of that feature's geometry for every corresponding record in the table. Area and length calculations should be performed carefully, to ensure they are not being exaggerated by including copies of the same feature's geometry.

Symbolizing Spatial Features:
Use care when symbolizing data in one-to-many or many-to-many spatial views. If there are multiple attributes tied to the same feature, symbolizing with a solid fill may mask other important features within the spatial view. This can be most commonly seen when symbolizing features based on a field with multiple table records.

Labeling Spatial Features: Spatial views with one-to-many or many-to-many relationships may present duplicate labels for those features with multiple table records. This is because there are multiple features in the same geometry, and each one receives a label.Soils Metadata

Soil Taxonomy

This harmonized set of soil parameter estimates for the Indo-Gangetic Plains (IGP) of India, at scale 1:1 000 000, has been derived from soil and terrain data collated in SOTER format by staff of the National Bureau of Soil Survey and Land Use Planning (NBSS and LUP) at Nagpur, India. The data set has been prepared for use in the project on "Assessment of soil organic carbon stocks and change at ... national scale" (GEFSOC), which has IGP-India as one of its four case study areas (see http://www.nrel.colostate.edu/projects/gefsoc-uk/).

The land surface of IGP-India has been characterized using 36 unique SOTER units, corresponding with 497 polygons. The major soils of these units have been described using 36 profiles, selected by national soil experts as being representative for these units. The associated soil analytical data have been derived from soil survey reports.

Gaps in the measured soil profile data have been filled using a scheme of taxotransfer rules. Parameter estimates are presented by soil unit for fixed depth intervals of 0.2 m to 1 m depth for: organic carbon, total nitrogen, pH(H2O), CECsoil, CECclay, base saturation, effective CEC, aluminum saturation, CaCO3 content, gypsum content, exchangeable sodium percentage (ESP), electrical conductivity of saturated paste (ECe), bulk density, content of sand, silt and clay, content of coarse fragments, and available water capacity(-33 to-1500 kPa). These attributes have been identified as being useful for agro-ecological zoning, land evaluation, crop growth simulation, modelling of soil carbon stocks and change, and analyses of global environmental change.

The current parameter estimates should be seen as best estimates based on the current selection of soil profiles and data clustering procedure; taxotransfer rules have been flagged to provide an indication of the confidence in the derived data.

Results are presented as summary files and can be linked to the 1:1M scale SOTER map in a GIS, through the unique SOTER-unit code.

The secondary SOTER data set for IGP-India is considered appropriate for exploratory studies at regional scale (greater than1:1M); correlation of soil analytical data should be done more rigorously when more detailed scientific work is considered.

This data set is a digital soil survey and generally is the most detailed level of soil geographic data developed by the National Cooperative Soil Survey. The information was prepared by digitizing maps, by compiling information onto a planimetric correct base and digitizing, or by revising digitized maps using remotely sensed and other information. This data set consists of georeferenced digital map data and computerized attribute data. The map data are in a soil survey area extent format and include a detailed, field verified inventory of soils and miscellaneous areas that normally occur in a repeatable pattern on the landscape and that can be cartographically shown at the scale mapped. A special soil features layer (point and line features) is optional. This layer displays the location of features too small to delineate at the mapping scale, but they are large enough and contrasting enough to significantly influence use and management. The soil map units are linked to attributes in the National Soil Information System relational database, which gives the proportionate extent of the component soils and their properties.

General Distribution of Soils (8 500 000)

Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.Dataset SummaryThis layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes describing the basic properties of soil derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).Attributes in this layer include:Soil Phase 1 and Soil Phase 2 - Phases identify characteristics of soils important for land use or management. Soils may have up to 2 phases with phase 1 being more important than phase 2.Other Properties - provides additional information important for agriculture.Additionally, 3 class description fields were added by Esri based on the document Harmonized World Soil Database Version 1.2 for use in web map pop-ups:Soil Phase 1 DescriptionSoil Phase 2 DescriptionOther Properties DescriptionThe layer is symbolized with the Soil Unit Name field.The document Harmonized World Soil Database Version 1.2 provides more detail on the soil properties attributes contained in this layer.Other attributes contained in this layer include:Soil Mapping Unit Name - the name of the spatially dominant major soil groupSoil Mapping Unit Symbol - a two letter code for labeling the spatially dominant major soil group in thematic mapsData Source - the HWSD is an aggregation of datasets. The data sources are the European Soil Database (ESDB), the 1:1 million soil map of China (CHINA), the Soil and Terrain Database Program (SOTWIS), and the Digital Soil Map of the World (DSMW).Percentage of Mapping Unit covered by dominant componentMore information on the Harmonized World Soil Database is available here.Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:World Soils Harmonized World Soil Database - Bulk DensityWorld Soils Harmonized World Soil Database – ChemistryWorld Soils Harmonized World Soil Database - Exchange CapacityWorld Soils Harmonized World Soil Database – HydricWorld Soils Harmonized World Soil Database – TextureThe authors of this data set request that projects using these data include the following citation:FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.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.Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:Living Atlas Discussion GroupSoil Data Discussion GroupThe Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.

The digital soil map for North and Central Eurasia region (covering China, Taiwan Province of China, Mongolia, CIS and the Baltic States) was prepared by FAO and IIASA in co-operation with: ? the Institute of Soil Science, Academia Sinica (Li Jin, Zhou House in 1978) for China and Taiwan Province of China (scale 1:4 million). ? the Pocveni Institute, V. Stolbovoy and B. Sheremet (1994) for Mongolia (scale 1:2.5 million) The original soil maps from China, Mongolia and CIS_BS have been merged by introducing DCW boundaries between: China-CIS_BS; China-Mongolia; Mongolia-CIS_BS. The original soil map of China includes the Chinese line between India and China, which extends beyond the Indian line, and the South China Sea islands (no soil information is present for the South China Sea islands). Those boundaries do not imply the expression of any opinion whatsoever on the part of FAO concerning the legal or constitutional states of any country, territory, or sea area, or concerning delimitation of frontiers. For further information on related tables, texture etc. please read the readme.rtf and readme.xls documents available for downloading.

Data are presented for daily rainfall, stream discharge and hydraulic conductivity of soils from catchments located in the Upper Nilgiris Reserve Forest in the state of Tamil Nadu. The catchments are dominated by four land cover types, shola, grassland, pine and wattle. The data were collected between May 2014 and December 2016. Tipping bucket wired rain gauges were used to measure rainfall. Stream discharge was measured from stilling wells and capacitance probe-based water level recorders. A mini-disk infiltrometer was used to measure the hydraulic conductivity of soils. Dry season data has not been included in this dataset as its focus is on extreme rain events. The data were collected as part of a series of eco-hydrology projects that explored the impact of land cover on rain-runoff response, carbon sequestration and nutrient and sediment discharge. The dataset presented here was collected by a team of three to five researchers and field assistants who were engaged in the installation of the data loggers and their regular operation and maintenance. Four research agencies have partnered across multiple projects to sustain the data collection efforts that started in June 2013 and continue (June 2020). These are the Foundation for Ecological Research, Advocacy and Learning - Pondicherry, the Ashoka Trust for Research in Ecology and the Environment - Bangalore, the Lancaster Environmental Centre, Lancaster University - UK, and the National Centre for Biological Sciences - Bangalore. Funding was provided by Ministry of Earth Sciences Government of India from the Changing Water Cycle programme (Grant Ref: MoES/NERC/16/02/10 PC-II) and the Hydrologic footprint of Invasive Alien Species project (MOES/PAMC/H&C/85/2016-PC-II). Additional funding was provided by UKRI Natural Environment Research Council grant NE/I022450/1 (Western Ghats-Capacity within the NERC Changing Water Cycle programme) and WWF-India as part of the Noyyal-Bhavani program.This research took place inside protected areas in the Nilgiri Division for which permissions and support were provided continually by the Tamil Nadu Forest Department, particularly the office of the District Forest Officer, Udhagamandalam.

Description

The global pedogenon map classifies soil units based on similarities in their formation processes while excluding anthropogenic effects, at a high spatial resolution of 90 metersin the Equator.

This repository contains data from a scientific work that was presented in the Digital Soil Mapping & GlobalSoilMap conference in Bengalore, India, 2025 (Francos et al., 2025):

• The global pedogenon map in 90-meters resolution: GPM_mosaic_17062025.tif
• The centroids of the pedogenon classes: RGB_CENTROIDS_04062025.csv
• Sampling points after data processing and before classification: POINTS_04062025.csv

Format:

• Raster map in GeoTIFF format (*.tif).
• Spatial resolution: 90 meters in the Equator.
• Coordinate reference system: EPSG:4326 (WGS 84).

Reference:

Francos, N., McBratney, A., 2025. The Global Pedogenon Map. In: Soil Mapping for Sustainable Land UsePlanning, 3rd Joint Workshop of the IUSS Working Groups on Digital Soil Mapping & GlobalSoilMap, 21st–24th January 2025, Bengaluru, India.

Fluazinam a promising fungicide, is not yet registered in India. Consequently it is important to study the dissipation of its specific formulation in Indian soil and water. This study focuses on the degradation and residue dynamics of Fluazinam (40% SC) in different soil types (alluvial, lateritic, coastal saline and black) and water pH (4.0, 7.0, 9.2). Adsorption kinetic models suggested that the half-life period (days) varies among soils following the order lateritic (Jhargram), 54.07 > alluvial (Mohanpur), 45.10 > coastal saline (Canning), 28.33 > black (Pune) 26.18. These differences are attributed to soil pH and organic carbon (OC) content, where higher pH levels reduce pesticide adsorption, leading to quicker dissipation, while higher organic carbon content provides more binding sites, slowing down the process. The first order kinetics explained the dissipation better compared to second order model across all soil types. The study also found that the half-life of was lowest at pH 9.2, as compared to pH 7.0, and very high stability at pH 4.0. Additionally, the study introduces an interactive R-based tool for analysing dissipation kinetics and half-life of different pesticides offering a valuable resource for researchers and stakeholders.

Summary of India’s three dominant soil types using classification scheme by Indian Council of Agricultural Research (ICAR) and descriptions of the soil characteristics that affect crop growth [70].

Soil erosion induced by water has been identified as one of the major environmental problems worldwide. The erosive force of rainfall, also known as rainfall erosivity (R-factor), is the potential of rain to cause soil degradation and one of the factors in the widely adopted RUSLE (Revised Universal Soil Loss Equation) empirical soil erosion estimation model. About 68.4% of total eroded soil in India is eroded due to erosion by water, and rainfall erosivity is one of the major factors. The past assessments of rainfall erosivity in India were however largely based on rain-gauge recordings and surveys which hinders its understanding and estimation over large areas. Growing availability of gridded precipitation datasets presents an unprecedented opportunity to study long-term rainfall erosivity over varied terrains and address some of the limitations of point data-based studies. IRED (Indian Rainfall Erosivity Dataset) is the first such national-scale assessment of rainfall erosivity over India using gridded precipitation datasets, which will be helpful for agricultural experts, watershed managers, agronomists, and soil-conservational experts in order to understand and mitigate rainfall-induced erosion. In this dataset, long term yearly average R-factor, Fourier Index (FI), and Modified Fourier Index (MFI) maps have been included with a distributional analysis over IMD (India Metrological Department) defined regions, states and districts of India.

This coverage contains information about the buried valleys within the Standing Rock Indian Reservation, Sioux County, North Dakota, and Corson County, South Dakota. The delineation of the buried valleys was included as part of the surficial geology map (figure 5) created by Howells (1982). The digital data were produced by the U.S. Geological Survey (USGS) in cooperation with the U.S. Environmental Protection Agency. Figure 5 in Howells (1982) was scanned and digitized on-screen to create this coverage. See cross reference information for more detail. According to the map credit for figure 5, the geology for Sioux County was based on soil maps prepared by the U.S. Bureau of Indian Affairs (1959), data collected by Randich (1975), and a geologic map by Carlson (1978). The geology for Corson County was based on soil maps prepared by the U.S. Bureau of Indian Affairs (1959) and unpublished maps of the U.S Soil Conservation Service, modified by test drilling and field reconnaissance.

Saturated soil water content calculated over the Ghataprabha (K3) sub-basin area. The dataset is derived from the High Resolution Soil Map of Hydraulic Properties (HiHydroSoils v1.0).

India Exports of agricultural for soil preparation to Australia was US$3.48 Million during 2024, according to the United Nations COMTRADE database on international trade. India Exports of agricultural for soil preparation to Australia - data, historical chart and statistics - was last updated on July of 2025.

Saturated soil water content calculated over the Malaprabha (K4) sub-basin area. The dataset is derived from the High Resolution Soil Map of Hydraulic Properties (HiHydroSoils v1.0).