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.

The dataset consists of three raster GeoTIFF files describing the following soil properties in the US: available water capacity, field capacity, and soil porosity. The input data were obtained from the gridded National Soil Survey Geographic (gNATSGO) Database and the Gridded Soil Survey Geographic (gSSURGO) Database with Soil Data Development tools provided by the Natural Resources Conservation Service. The soil characteristics derived from the databases were Available Water Capacity (AWC), Water Content (one-third bar) (WC), and Bulk Density (one-third bar) (BD) aggregated as weighted average values in the upper 1 m of soil. AWC and WC layers were converted to mm/m to express respectively available water capacity and field capacity in 1 m of soil, and BD layer was used to produce soil porosity raster assuming that the average particle density of soils is equal to 2.65 g/cm3. For each soil property, soil maps with CONUS, Alaska, and Hawaii geographic coverages were derived from s ...

Brief Description: This dataset contains 1 million simulated soil samples from various locations around the globe. Each sample includes data on soil texture, pH, organic matter content, moisture content, bulk density, nutrient levels (N, P, K), cation exchange capacity, electrical conductivity, color, porosity, and water holding capacity. Designed for environmental scientists, agronomists, and data scientists, this dataset is ideal for research, machine learning models, and educational purposes. Purpose: To provide a comprehensive soil dataset for environmental and agricultural research, including machine learning and data analysis applications. Data Collection Method: Simulated data generated using Python with realistic ranges and distributions based on common soil characteristics.

Usage Examples

Predictive modeling of soil properties.
Classification of soil types based on texture and nutrient content.
Analysis of soil health and fertility across different geographic locations.

File Descriptions

soil_data.csv - The main dataset file containing 1 million rows of soil data across 17 features.

Data Fields

Soil_ID: Unique identifier for each soil sample.
Location_Latitude and Location_Longitude: Geographic coordinates of the soil sample.
Depth_cm: Depth at which the soil sample was collected (cm).
Texture: Soil texture classification (sandy, loamy, clayey).
pH: Soil pH level.
Organic_Matter_%: Percentage of organic matter in the soil.
Moisture_Content_%: Soil moisture content percentage.
Bulk_Density_g/cm³: Soil bulk density (g/cm³).
Nitrogen_N_ppm, Phosphorus_P_ppm, Potassium_K_ppm: Nutrient levels in parts per million (ppm).
Cation_Exchange_Capacity_meq/100g: Soil's ability to hold positively charged ions (meq/100g).
Electrical_Conductivity_dS/m: Soil electrical conductivity (dS/m).
Soil_Color: Color of the soil (brown, red, black, yellow).
Porosity_%: Percentage of pore space in the soil.
Water_Holding_Capacity_%: Soil's water holding capacity percentage.

Acknowledgments

If your dataset generation was inspired by specific studies, data sources, or methodologies, acknowledge them here.

These Soil Mapping Data Packages include 1. a Soil Map dataset which includes the equivalents to Soil Project Boundaries, Soil Survey Spatial View mapping polygons with attributes from the Soil Name and Layer Files, plus + A Soil Site dataset which includes soil pit site information and detailed soil pit descriptions and any associated lab analyses, and + The Soil Data Dictionary which documents the fields and allowable codes within the data. The Soil Map geodatabase contains the 'best available' data ranging from 1:20,000 scale to 1:250,000 scale with overlapping data removed. The choice of the datasets that remain is based on connectivity to the soil attributes (soil name and layer files), map scale and survey date. (Note: the BC Soil Landscapes of Canada (BCSLC) 1:1,000,000 data has not been included in the Soil_Map or SIFT, but is available from: CANSIS. (A complete soils data package with overlapping soil survey mapping and BCSLC is available on request. Note that the soil survey data with attributes can also be viewed interactively in the [Soil Information Finder Tool](The Soil Map dataset is also available for interactive map viewing or as KMZs from the Soil Information Finder Tool website.

Context

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Content

Maps of clay, silt and sand contents (g kg-1) were predicted at 0-20 cm, 20-60 cm and 60-100 cm depths intervals by random forest regression in Google Earth Engine. Gridded soil information covers a part of the Midwest Brazil, from 12° S to 20° S and from 45° W to 54° W, and is available with 250m resolution. The maps were cross-validated and had Coefficient of Determination ranging from 0.64 to 0.85 at all depth intervals.

Acknowledgements

Poppiel, Raúl Roberto; Lacerda, Marilusa Pinto Coelho; Safanelli, José Lucas; Rizzo, Rodnei; Pereira de Oliveira Junior, Manuel; Novais, Jean Jesus; Dematte, Jose Alexandre (2020), “250 m-gridded soil texture at multiple depths of Midwest Brazil”, Mendeley Data, V4, doi: 10.17632/52cfcm3xr7.4

Photo by Clay Banks on Unsplash

The USDA-NRCS Soil Series Classification Database contains the taxonomic classification of each soil series identified in the United States, Territories, Commonwealths, and Island Nations served by USDA-NRCS. Along with the taxonomic classification, the database contains other information about the soil series, such as office of responsibility, series status, dates of origin and establishment, and geographic areas of usage. The database is maintained by the soils staff of the NRCS MLRA Soil Survey Region Offices across the country. Additions and changes are continually being made, resulting from on going soil survey work and refinement of the soil classification system. As the database is updated, the changes are immediately available to the user, so the data retrieved is always the most current. The Web access to this soil classification database provides capabilities to view the contents of individual series records, to query the database on any data element and produce a report with the selected soils, or to produce national reports with all soils in the database. The standard reports available allow the user to display the soils by series name or by taxonomic classification. The SC database was migrated into the NASIS database with version 6.2. Resources in this dataset:Resource Title: Website Pointer to Soil Series Classification Database (SC). File Name: Web Page, url: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/class/data/?cid=nrcs142p2_053583 Supports the following queries:

• View Classification Data by Series Name
• Create Report for a List of Series (with download option)
• Create Report by Query (with download option)
• Create National Report (with download option)
• Soil Series Name Search

This map depicts soils data from the USDA NRCS SSURGO dataset. The soil type is indicated in the MUSYM field. The data was downloaded from the NRCS website.The full Kansas geospatial catalog is administered by the Kansas Data Access & Support Center (DASC) and can be found at the following URL: https://hub.kansasgis.org/

The National Cooperative Soil Survey - Soil Characterization Database (NCSS-SCD) contains laboratory data for more than 65,000 locations (i.e. xy coordinates) throughout the United States and its Territories, and about 2,100 locations from other countries. It is a compilation of data from the Kellogg Soil Survey Laboratory (KSSL) and several cooperating laboratories. The data steward and distributor is the National Soil Survey Center (NSSC). Information contained within the database includes physical, chemical, biological, mineralogical, morphological, and mid infrared reflectance (MIR) soil measurements, as well a collection of calculated values. The intended use of the data is to support interpretations related to soil use and management. Data Usage Access to the data is provided via the following user interfaces: 1. Interactive Web Map 2. Lab Data Mart (LDM) for querying data and generating reports 3. Soil Data Access (SDA) web services for querying data 5. Direct download of the entire database in several formats Data at each location includes measurements at multiple depths (e.g. soil horizons). However, not all analyses have been conducted for each location and depth. Typically, a suite of measurements was collected based upon assumed or known conditions regarding the soil being analyzed. For example, soils of arid environments are routinely analyzed for salts and carbonates as part of the standard analysis suite. Standard morphological soil descriptions are available for about 60,000 of these locations. Mid-infrared (MIR) spectroscopy is available for about 7,000 locations. Soil fertility measurements, such as those made by Agricultural Experiment Stations, were not made. Most of the data were obtained over the last 40 years, with about 4,000 locations before 1960, 25,000 from 1960-1990, 27,000 from 1990-2010, and 13,000 from 2010 to 2021. Generally, the number of measurements recorded per location has increased over time. Typically, the data were collected to represent a soil series or map unit component concept. They may also have been sampled to determine the range of variation within a given landscape. Although strict quality-control measures are applied, the NSSC does not warrant that the data are error free. Also, in some cases the measurements are not within the applicability range of the laboratory methods. For example, dispersion of clay is incomplete in some soils by the standard method used for determining particle-size distribution. Soils producing incomplete dispersion include those that are derived from volcanic materials or that have a high content of iron oxides, gypsum, carbonates, or other cementing materials. Also note that determination of clay minerals by x-ray diffraction is relative. Measurements of very high or very low quantities by any method are not very precise. Other measurements have other limitations in some kinds of soils. Such data are retained in the database for research purposes. Also, some of the data for were obtained from cooperating laboratories within the NCSS. The accuracy of the location coordinates has not been quantified but can be inferred from the precision of their decimal degrees and the presence of a map datum. Some older records may correspond to a county centroid. When the map datum is missing it can be assumed that data prior to 1990 was recorded using NAD27 and with WGS84 after 1995. For detailed information about methods used in the KSSL and other laboratories refer to "Soil Survey Investigation Report No. 42". For information on the application of laboratory data, refer to "Soil Survey Investigation Report No. 45". If you are unfamiliar with any terms or methods feel free to consult your NRCS State Soil Scientist. Terms of Use This dataset is not designed for use as a primary regulatory tool in permitting or citing decisions but may be used as a reference source. This is public information and may be interpreted by organizations, agencies, units of government, or others based on needs; however, they are responsible for the appropriate application. Federal, State, or local regulatory bodies are not to reassign to the Natural Resources Conservation Service or the National Cooperative Soil Survey any authority for the decisions that they make. The Natural Resources Conservation Service will not perform any evaluations of these data for purposes related solely to State or local regulatory programs.

(Link to Metadata) 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. Survey Dates - https://www.nrcs.usda.gov/wps/portal/nrcs/surveylist/soils/survey/state/?stateId=VT

The International Soil Reference and Information Centre-World Inventory of Soil Emission Potentials (ISRIC-WISE) international soil profile data set consists of a homogenized, global set of 1,125 soil profiles for use by global modelers. These profiles provided the basis for the Global Pedon Database (GPDB) of the International Geosphere-Biosphere Programme (IGBP) - Data and Information System (DIS). The data set consists of a selection of 665 profiles originating from the Natural Resources Conservation Service (NRCS, Lincoln), 250 profiles obtained from the Food and Agriculture Organization (FAO, Rome), and 210 profiles from the reference collection of the International Soil Reference and Information Centre (ISRIC, Wageningen). All profiles are georeferenced and classified according to the 1974 Legend of the FAO-UNESCO Soil Map (FAC-UNESCO, 1974) of the World, as well as the 1988 Revised Legend of FAO-UNESCO (FAO, 1990). The data set includes information on soil classification, site data, soil horizon data, source of data, and methods used for determining analytical data. The data files are in a comma-delimited format. Data Citation: The data set should be cited as follows: Batjes, N. H. (ed). 2000. Global Soil Profile Data (ISRIC-WISE). Available on-line from the ORNL Distributed Active Archive Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A.

The SSURGO database contains information about soil as collected by the National Cooperative Soil Survey over the course of a century. The information can be displayed in tables or as maps and is available for most areas in the United States and the Territories, Commonwealths, and Island Nations served by the USDA-NRCS (Natural Resources Conservation Service). The information was gathered by walking over the land and observing the soil. Many soil samples were analyzed in laboratories. The maps outline areas called map units. The map units describe soils and other components that have unique properties, interpretations, and productivity. The information was collected at scales ranging from 1:12,000 to 1:63,360. More details were gathered at a scale of 1:12,000 than at a scale of 1:63,360. The mapping is intended for natural resource planning and management by landowners, townships, and counties. Some knowledge of soils data and map scale is necessary to avoid misunderstandings. The maps are linked in the database to information about the component soils and their properties for each map unit. Each map unit may contain one to three major components and some minor components. The map units are typically named for the major components. Examples of information available from the database include available water capacity, soil reaction, electrical conductivity, and frequency of flooding; yields for cropland, woodland, rangeland, and pastureland; and limitations affecting recreational development, building site development, and other engineering uses. SSURGO datasets consist of map data, tabular data, and information about how the maps and tables were created. The extent of a SSURGO dataset is a soil survey area, which may consist of a single county, multiple counties, or parts of multiple counties. SSURGO map data can be viewed in the Web Soil Survey or downloaded in ESRI® Shapefile format. The coordinate systems are Geographic. Attribute data can be downloaded in text format that can be imported into a Microsoft® Access® database. A complete SSURGO dataset consists of:

GIS data (as ESRI® Shapefiles) attribute data (dbf files - a multitude of separate tables) database template (MS Access format - this helps with understanding the structure and linkages of the various tables) metadata

Resources in this dataset:Resource Title: SSURGO Metadata - Tables and Columns Report. File Name: SSURGO_Metadata_-_Tables_and_Columns.pdfResource Description: This report contains a complete listing of all columns in each database table. Please see SSURGO Metadata - Table Column Descriptions Report for more detailed descriptions of each column.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Metadata - Table Column Descriptions Report. File Name: SSURGO_Metadata_-_Table_Column_Descriptions.pdfResource Description: This report contains the descriptions of all columns in each database table. Please see SSURGO Metadata - Tables and Columns Report for a complete listing of all columns in each database table.

Find the Soil Survey Geographic (SSURGO) web site at https://www.nrcs.usda.gov/wps/portal/nrcs/detail/vt/soils/?cid=nrcs142p2_010596#Datamart Title: SSURGO Data Dictionary. File Name: SSURGO 2.3.2 Data Dictionary.csvResource Description: CSV version of the data dictionary

This data set provides gridded data for selected soil parameters derived from data and methods developed by the Global Soil Data Task, an international collaborative project with the objective of making accurate and appropriate data relating to soil properties accessible to the global change research community. The task was coordinated by the International Geosphere-Biosphere Programme (IGBP-DIS). The data in this data set were produced by the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP II) staff from data obtained from the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC, http://daac.ornl.gov/). See the related data sets section below. Two-dimensional gridded maps of selected soil parameters, including soil texture, at a 1.0 by 1.0 degree spatial resolution and for two soil depths are provided. All data layers have been adjusted to match the ISLSCP II land/water mask. There are 36 data files with this data set.

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

A soil survey is an inventory of soils and their spatial distribution over a landscape. Soil survey reports contain two parts. The first part is a soil map or series of maps at a particular scale with coding for each soil. Soil survey reports also include a supporting document that contains background information such as how the soil survey was conducted, and an explanation of interpretive criteria and a summary of the area occupied by various soil types. The detailed soil surveys identify more of the variation in soil types across smaller landscapes, as compared to Generalized (1:100 000, i.e. provincial overview) and Reconnaissance or General (1:125 000, or 1/2 inch to 1 mile.) soil surveys. Detailed soil survey information is much more accurate and reliable for making decisions at the farm-level. Soil surveys have been published for most of the agricultural areas, and many surrounding areas, across Canada. Data from these surveys comprise the most detailed soil inventory information in the National Soil Database (NSDB). Version 3 was created by Agriculture and Agri-Food Canada in the 2010's by amalgamating version 2 data. It introduced some minor refinements to the version 2 data structure to provide closer alignment with the Soil Landscapes of Canada data structure.

This data set is a digital soil survey and generally is the mostdetailed level of soil geographic data developed by the NationalCooperative Soil Survey. The information was prepared by digitizingmaps, by compiling information onto a planimetric correct baseand digitizing, or by revising digitized maps using remotelysensed and other information.This data set consists of georeferenced digital map data andcomputerized attribute data. The map data are in a soil survey areaextent format and include a detailed, field verified inventoryof soils and miscellaneous areas that normally occur in a repeatablepattern on the landscape and that can be cartographically shown atthe scale mapped. The soil map units are linked to attributes in theNational Soil Information System relational database, which givesthe proportionate extent of the component soils and their properties.

Sixty one soils (soil types) represent the range of soils found across South Australia’s agricultural lands. Mapping shows the most common soil within each map unit, while more detailed proportion data are supplied for calculating respective areas of each soil type (spatial data statistics).

A global data set of soil types is available at 0.5-degree latitude by 0.5-degree longitude resolution. There are 106 soil units, based on Zobler?s (1986) assessment of the FAO/UNESCO Soil Map of the World. This data set is a conversion of the Zobler 1-degree resolution version to a 0.5-degree resolution. The resolution of the data set was not actually increased. Rather, the 1-degree squares were divided into four 0.5-degree squares with the necessary adjustment of continental boundaries and islands. The computer code used to convert the original 1-degree data to 0.5-degree is provided as a companion file. A JPG image of the data is provided in this document. The Zobler data (1-degree resolution) as distributed by Webb et al. (1993) [http://www.ngdc.noaa.gov/seg/eco/cdroms/gedii_a/datasets/a12/wr.htm#top] contains two columns, one column for continent and one column for soil type. The Soil Map of the World consists of 9 maps that represent parts of the world. The texture data that Webb et al.(1993) provided allowed for the fact that a soil type in one part of the world may have different properties than the same soil in a different part of the world. This continent-specific information is retained in this 0.5-degree resolution data set, as well as the soil type information which is the second column. A code was written (one2half.c) to take the file CONTIZOB.LER distributed by Webb et al. (1993) [http://www.ngdc.noaa.gov/seg/eco/cdroms/gedii_a/datasets/a12/wr.htm#top] and simply divide the 1-degree cells into quarters. This code also reads in a land/water file (land.wave) that specifies the cells that are land at 0.5 degrees. The code checks for consistency between the newly quartered map and the land/water map to which the quartered map is to be registered. If there is a discrepancy between the two, an attempt was made to make the two consistent using the following logic. If the cell is supposed to be water, it is forced to be water. If it is supposed to be land but was resolved to water at 1 degree, the code looks at the surrounding 8 cells and picks the most frequent soil type and assigns it to the cell. If there are no surrounding land cells then it is kept as water in the hopes that on the next pass one or more of the surrounding cells might be converted from water to a soil type. The whole map is iterated 5 times. The remaining cells that should be land but couldn't be determined from surrounding cells (mostly islands that are resolved at 0.5 degree but not at 1 degree) are printed out with coordinate information. A temporary map is output with -9 indicating where data is required. This is repeated for the continent code in CONTIZOB.LER as well. A separate map of the temporary continent codes is produced with -9 indicating required data. A nearly identical code (one2half.c) does the same for the continent codes. The printout allows one to consult the printed versions of the soil map and look up the soil type with the largest coverage in the 0.5-degree cell. The program manfix.c then will go through the temporary map and prompt for input to correct both the soil codes and the continent codes for the map. This can be done manually or by preparing a file of changes (new_fix.dat) and redirecting stdin. A new complete version of the map is outputted. This is in the form of the original CONTIZOB.LER file (contizob.half) but four times larger. Original documentation and computer codes prepared by Post et al. (1996) are provided as companion files with this data set. Image of 106 global soil types available at 0.5-degree by 0.5-degree resolution. Additional documentation from Zobler?s assessment of FAO soil units is available from the NASA Center for Scientific Information.

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.

Abstract

This dataset created by the Native Lands Advocacy Project contains spatial and tabular data derived from the NRCS's 2020 national SSURGO soils database and has been formatted to include only data within current American Indian areas for the conterminous United States. Boundary data was acquired from the US Census Bureau's Tiger Database (2010) reported by the federally recognized tribal governments through the Census Bureau's Boundary and Annexation Survey (BAS) and includes a total of 549 areas associated with 398 unique American Indian groups. The boundary data includes all Indian Lands defined by CFR 25 CFR § 502.12 which includes both lands held in trust by the United States Government and fee lands within the boundaries of American Indian Lands encompassing a total of 109,465,623 acres of land. The spatial data includes each soil unit and its associated MUKEY making it possible to join this data with other GSSURGO soil characteristics tables.According to the NRCS4, "The SSURGO database provides the most detailed level of information and was designed primarily for farm and ranch, landowner/user, township, county, or parish natural resource planning and management. Using the soil attributes, this database serves as an excellent source for determining erodible areas and developing erosion control practices; reviewing site development proposals and land use potential; making land use assessments and chemical fate assessments; and identifying potential wetlands and sand and gravel aquifer areas." The NRCS's SSURGO data is used in numerous land valuation, carbon and hydrologic assessment models including the proprietary AcreValue™ valuation estimation tool5, NRCS's Rapid Carbon Assessment RaCa6, the EPA's Automated Geospatial Watershed Assessment (AGWA), and the Soil and Water Assessment Tool (SWAT), to name a few.

🌿 Soil-Climate-Crop Compatibility Dataset

This is a synthetic dataset designed for training and evaluating machine learning models that classify whether certain soil and climate conditions are compatible for growing a given crop. The data includes environmental and soil features for a variety of crops commonly grown in India.

📌 Overview

This dataset simulates the relationship between crop types, soil properties, and climate conditions. The goal is to predict whether a given combination of soil, weather, and crop factors is compatible for cultivation — making it ideal for binary classification tasks.

It is especially useful for: - Crop recommendation systems - Soil-climate compatibility prediction - Educational ML applications in agriculture

📁 File

• soil_climate_crop_data.csv: Main dataset file with synthetic records

📊 Features / Column Descriptions

🌾 Crop Types Included (19)

Wheat, Rice, Maize, Soybean, Niger, Urd, Summer Paddy, Gram, Tiwra, Millets, Arhar, Mustard, Jwar, Moong, Kulthi, Groundnut, Masoor, Til, Pea

🧱 Soil Types Covered

• Red and Yellow Soils
• Laterite Soils
• Black Soils
• Alluvial Soils

🧪 Source of Data

This dataset is synthetically generated using domain-inspired rules and randomized inputs.
It is not based on real-world data but reflects typical patterns observed in Indian agricultural settings. The labels for compatibility are assigned based on plausible thresholds and combinations of soil, climate, and crop requirements.

🧠 Use Cases

• Train binary classification models for agricultural use-cases
• Evaluate decision tree, random forest, or neural network performance
• Build prototype crop advisory systems

📄 License

License: CC0 1.0 Universal (Public Domain Dedication)
You are free to use, modify, and share this dataset for any purpose without restrictions.

🙋 Author

Created by: Rajeev
Open to feedback and collaboration!