Download .zipA soil mapping unit designates a specific type of soil which has unique characteristics including texture, slope, and erosion class.

These soils were digitized from the paper final soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

Discover the booming soil mapping service market! Learn about its growth drivers, key players (Syngenta, AgriGanic, EarthOptics), regional trends, and future projections to 2033. This in-depth analysis reveals lucrative opportunities in precision agriculture, environmental monitoring, and urban planning.

Tags

   soil survey, soils, Soil Survey Geographic, SSURGO




   Summary


   SSURGO depicts information about the kinds and distribution of

   soils on the landscape. The soil map and data used in the SSURGO

   product were prepared by soil scientists as part of the National

   Cooperative Soil Survey.


   Description


   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 3.75 minute

   quadrangle format and include a detailed, field verified inventory

   of soils and nonsoil 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.


   Credits

   There are no credits for this item.


   Use limitations


   The U.S. Department of Agriculture, Natural Resources Conservation

   Service, should be acknowledged as the data source in products

   derived from these data.


   This data set 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 any

   authority for the decisions that they make. The Natural Resources

   Conservation Service will not perform any evaluations of these maps

   for purposes related solely to State or local regulatory programs.


   Photographic or digital enlargement of these maps to scales greater

   than at which they were originally mapped can cause misinterpretation

   of the data. If enlarged, maps do not show the small areas of

   contrasting soils that could have been shown at a larger scale. The

   depicted soil boundaries, interpretations, and analysis derived from

   them do not eliminate the need for onsite sampling, testing, and

   detailed study of specific sites for intensive uses. Thus, these data

   and their interpretations are intended for planning purposes only.

   Digital data files are periodically updated. Files are dated, and

   users are responsible for obtaining the latest version of the data.


   Extent



   West -76.713689  East -76.526117 

   North 39.374398  South 39.194856 




   Scale Range

   There is no scale range for this item.

Download .zipA soil mapping unit designates a specific type of soil which has unique characteristics including texture, slope, and erosion class.

These soils were digitized from the paper original soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

ArcGIS Map Packages and GIS Data for Gillreath-Brown, Nagaoka, and Wolverton (2019)

**When using the GIS data included in these map packages, please cite all of the following:

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, 2019. PLoSONE 14(8):e0220457. http://doi.org/10.1371/journal.pone.0220457

Gillreath-Brown, Andrew, Lisa Nagaoka, and Steve Wolverton. ArcGIS Map Packages for: A Geospatial Method for Estimating Soil Moisture Variability in Prehistoric Agricultural Landscapes, Gillreath-Brown et al., 2019. Version 1. Zenodo. https://doi.org/10.5281/zenodo.2572018

OVERVIEW OF CONTENTS

This repository contains map packages for Gillreath-Brown, Nagaoka, and Wolverton (2019), as well as the raw digital elevation model (DEM) and soils data, of which the analyses was based on. The map packages contain all GIS data associated with the analyses described and presented in the publication. The map packages were created in ArcGIS 10.2.2; however, the packages will work in recent versions of ArcGIS. (Note: I was able to open the packages in ArcGIS 10.6.1, when tested on February 17, 2019). The primary files contained in this repository are:

Raw DEM and Soils data

Digital Elevation Model Data (Map services and data available from U.S. Geological Survey, National Geospatial Program, and can be downloaded from the National Elevation Dataset)

DEM_Individual_Tiles: Individual DEM tiles prior to being merged (1/3 arc second) from USGS National Elevation Dataset.

DEMs_Merged: DEMs were combined into one layer. Individual watersheds (i.e., Goodman, Coffey, and Crow Canyon) were clipped from this combined DEM.

Soils Data (Map services and data available from Natural Resources Conservation Service Web Soil Survey, U.S. Department of Agriculture)

Animas-Dolores_Area_Soils: Small portion of the soil mapunits cover the northeastern corner of the Coffey Watershed (CW).

Cortez_Area_Soils: Soils for Montezuma County, encompasses all of Goodman (GW) and Crow Canyon (CCW) watersheds, and a large portion of the Coffey watershed (CW).

ArcGIS Map Packages

Goodman_Watershed_Full_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the full Goodman Watershed (GW).

Goodman_Watershed_Mesa-Only_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the mesa-only Goodman Watershed.

Crow_Canyon_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Crow Canyon Watershed (CCW).

Coffey_Watershed_SMPM_Analysis: Map Package contains the necessary files to rerun the SMPM analysis on the Coffey Watershed (CW).

For additional information on contents of the map packages, please see see "Map Packages Descriptions" or open a map package in ArcGIS and go to "properties" or "map document properties."

LICENSES

Code: MIT year: 2019 Copyright holders: Andrew Gillreath-Brown, Lisa Nagaoka, and Steve Wolverton

CONTACT

Andrew Gillreath-Brown, PhD Candidate, RPA Department of Anthropology, Washington State University andrew.brown1234@gmail.com – Email andrewgillreathbrown.wordpress.com – Web

Soil Mapping Services Market Outlook

According to our latest research, the global Soil Mapping Services market size reached USD 1.28 billion in 2024, demonstrating robust momentum driven by technological advancements and the increasing need for precise land management. The market is projected to expand at a CAGR of 11.4% during the forecast period, reaching an estimated USD 3.11 billion by 2033. This growth is primarily fueled by the rising adoption of precision agriculture, government initiatives promoting sustainable land use, and the integration of digital technologies in soil analysis.

One of the principal growth factors propelling the Soil Mapping Services market is the surging demand for precision agriculture. Farmers and agribusinesses are increasingly leveraging soil mapping technologies to optimize crop yields, reduce input costs, and minimize environmental impact. The adoption of advanced tools such as digital soil mapping, remote sensing, and Geographic Information Systems (GIS) has enabled real-time soil health monitoring and informed decision-making. These technologies facilitate tailored fertilization, irrigation, and crop selection, which are critical for sustainable agriculture. The growing awareness among farmers about the benefits of soil mapping services, coupled with the need to meet global food demand, is significantly boosting market growth.

Another key driver is the increasing focus on land management and environmental sustainability. Governments and environmental agencies are implementing stringent regulations to combat land degradation, soil erosion, and contamination. Soil mapping services play a pivotal role in supporting these initiatives by providing accurate data for land use planning, restoration projects, and environmental assessments. The integration of soil mapping with remote sensing and GIS allows for large-scale monitoring and assessment of soil health, enabling authorities to take timely corrective actions. Additionally, the construction and infrastructure sectors are utilizing soil mapping services for site suitability analysis, further expanding the marketÂ’s application scope.

Technological advancements continue to revolutionize the Soil Mapping Services market. The emergence of digital soil mapping, machine learning algorithms, and drone-based remote sensing has improved the accuracy, efficiency, and scalability of soil analysis. These innovations are reducing the cost and time associated with traditional soil surveys, making soil mapping services accessible to a broader range of end-users, including smallholder farmers and research institutions. The integration of cloud-based data platforms is also facilitating seamless data sharing and collaboration among stakeholders, driving the adoption of soil mapping services across various sectors.

The integration of drones in soil mapping services is revolutionizing the way soil organic matter is assessed and managed. Drone-Enabled Soil Organic Matter Map technologies provide a bird's-eye view of agricultural fields, allowing for the precise measurement of soil organic content across large areas. This innovative approach not only enhances the accuracy of soil analysis but also significantly reduces the time and labor traditionally required for soil sampling. By capturing high-resolution images and data, drones can identify variations in soil organic matter, enabling farmers to implement targeted interventions for improving soil health and crop productivity. As the demand for sustainable agriculture intensifies, the adoption of drone-enabled mapping solutions is expected to grow, offering a powerful tool for enhancing soil management practices.

From a regional perspective, North America and Europe currently dominate the Soil Mapping Services market due to their advanced agricultural infrastructure, strong regulatory frameworks, and high adoption of precision farming technologies. Asia Pacific, however, is emerging as the fastest-growing region, fueled by rapid population growth, increasing food security concerns, and government initiatives to modernize agriculture. Countries such as China, India, and Australia are witnessing significant investments in digital agriculture and soil health monitoring, positioning the region as a key growth engine for the global market. Meanwhile, Latin America and the Middle East &

For more information on this dataset please go to https://gis.epa.ie/geonetwork/srv/eng/catalog.search#/metadata/2cd0c5e9-83b2-49a9-8c3e-79675ffd18bfSIS SOIL:The new Irish Soil Information System concludes a 5 year programme, supported by the Irish Environmental Protection Agency (STRIVE Research Programme 2007-2013) and Teagasc, to develop a new 1:250,000 scale national soil map (https://soils.teagasc.ie). The Irish Soil Information System adopted a unique methodology combining digital soil mapping techniques with traditional soil survey application. Developing earlier work conducted by An Foras Talúntais, the project generated soil-landscape models for previously surveyed counties. These soil-landscape (‘soilscape’) models formed the basis for training statistical ‘inference engines’ for predicting soil mapping units, checked during field survey. 213 soil series are identified, each with differing characteristics, having contrasting environmental and agronomic responses. Properties were recorded in a database able to satisfy national and EU policy requirements. The Irish soil map and related soil property data will also serve public interest, providing the means to learn online about Irish soil resources. Use the Symbology layer file 'SOIL_SISNationalSoil.lyr' based on Value Field 'Association_Unit'. SIS SOIL DRAINAGE:In Ireland, soil drainage category is considered to have a predominant influence on soil processes (Schulte et al., 2012). The maritime climate of Ireland drives wet soil conditions, such that excess soil moisture in combination with heavy textured soils is considered a key constraint in relation to achieving productivity and environmental targets. Both soil moisture content and the rate at which water drains from the soil are critical indicators of soil physical quality and the overall functional capacity of soil. Therefore, a natural extension to the Irish Soil Information System included the development of an indicative soil drainage map for Ireland. The soil subgroup map was used to develop the indicative drainage map, based on diagnostic criteria relating to the subgroup categorization. Use the Symbology layer file 'SOIL_SISSoilDrainage.lyr' based on Value Field 'Drainage'. SIS SOIL DEPTH: Soil depth is a measure of the thickness of the soil cover and reflects the relationship between parent material and length of soil forming processes. Soil depth determines the potential rooting depth of plants and any restrictions within the soil that may hinder rooting depth. Plants derive nearly 80 per cent of their water needs from the upper part of the soil solum, i.e. where the root system is denser. The rooting depths depend on plant physiology, type of soil and water availability. Generally, vegetables (beans, tomatoes, potatoes, parsnip, carrots, leek, broccoli, etc.) are shallow rooted, about 50–60 cm; fruit trees and some other plants have medium rooting depths, 70–120 cm and other crops such as barley, wheat, oats, and maize may have deeper roots. Furthermore, rooting depths vary according to the age of the plants. The exact soil depth is difficult to define accurately due to its high variability across the landscape. The effective soil depth can be reduced by the presence of bedrock or impermeable layers. Use the Symbology layer file 'SOIL_SISSoilDepth.lyr' based on Valued Field 'Depth'. SIS SOIL TEXTURE:Soil texture is an important soil characteristic that influences processes such as water infiltration rates, rootability, gas exchanges, leaching, chemical activity, susceptibility to erosion and water holding capacity. The soil textural class is determined by the percentage of sand, silt, and clay. Soil texture also influences how much water is available to the plant; clay soils have a greater water holding capacity than sandy soils. Use the Symbology layer file 'SOIL_SISSoilTexture.lyr' based on Value Field 'Texture'. SIS SOIL SOC:In the previous national soil survey conducted by An Foras Taluntais, 14 counties were described in detail with soil profile descriptions provided for the representative soil series found within a county. Soil samples were taken at each soil horizon to a depth of 1 meter and analyses performed for a range of measurements, including soil organic carbon, texture, cation exchange capacity, pH; however in most cases no bulk density measurements were taken. This meant that while soil organic carbon concentrations were available this could not be related to a stock for a given soil series. In 2012/2013, 246 profile pits were sampled and analysed as part of the Irish Soil Information System project to fill in gaps in the description of representative profile data for Ireland. Use the Symbology layer file 'SOIL_SISSoilSOC.lyr' based on Value Field 'SOC'.

The digital soil mapping platforms market is experiencing robust growth, driven by the increasing need for precise and efficient soil analysis in agriculture and related sectors. The market's expansion is fueled by several key factors, including the rising adoption of precision agriculture techniques, the growing demand for improved crop yields, and the increasing availability of advanced technologies such as satellite imagery, mobile scouting applications, and sophisticated data analytics. Government initiatives promoting sustainable agriculture and research in soil science further contribute to market expansion. The market is segmented by application (agriculture cooperatives, government and research institutes, agribusiness companies, and others) and type of technology (mobile scouting, satellite imagery, and others). While the precise market size in 2025 is unavailable, considering a plausible CAGR of 15% (a conservative estimate based on the adoption rate of similar precision agriculture technologies) and assuming a 2024 market size of $800 million, the 2025 market size could be estimated around $920 million. North America and Europe currently hold significant market share, but the Asia-Pacific region shows significant potential for growth due to increasing agricultural activities and technological advancements. Despite its growth trajectory, the market faces certain restraints. High initial investment costs associated with implementing digital soil mapping platforms can be a barrier for entry for smaller farms and businesses. Data security concerns and the need for skilled professionals to interpret and utilize the complex data generated also pose challenges. However, ongoing technological advancements, reducing costs of sensors and cloud computing, and the development of user-friendly software solutions are expected to mitigate these restraints in the coming years. Companies such as SoilOptix, Veris Technologies, and Trimble are major players driving innovation and market penetration. Future growth will likely be shaped by the increasing integration of AI and machine learning in soil mapping and analysis. The forecast period of 2025-2033 suggests substantial expansion, likely exceeding $2 billion by 2033, driven by continued technological improvements and widespread adoption across different agricultural sectors.

Explore the burgeoning Soil Mapping Service market: drivers, trends, restraints, applications, types, and regional insights. Discover market size estimations and growth forecasts driven by precision agriculture and sustainable land management.

Soil Mapping Services Market Outlook

As per our latest research, the global soil mapping services market size reached USD 1.42 billion in 2024, reflecting a robust industry expansion driven by increasing demand for precision agriculture and sustainable land management practices. The market is projected to grow at a CAGR of 12.1% during the forecast period, with the market expected to reach USD 3.98 billion by 2033. This growth is primarily attributed to the rapid adoption of advanced geospatial technologies, heightened environmental awareness, and the pressing need for optimized agricultural productivity worldwide.

The accelerating growth of the soil mapping services market is underpinned by the global shift toward precision agriculture. Farmers and agribusinesses are increasingly leveraging soil mapping services to maximize crop yields, minimize resource wastage, and improve overall farm profitability. Detailed soil information allows for site-specific management practices, such as variable rate fertilization and irrigation, which are essential for sustainable farming. Furthermore, the growing prevalence of food security concerns and the need to feed a burgeoning global population have compelled stakeholders to adopt cutting-edge technologies for soil assessment and land management. This trend is further reinforced by governmental incentives and funding for digital agriculture solutions, which have spurred investments in soil mapping technologies across both developed and developing regions.

Another significant growth factor for the soil mapping services market is the rising awareness of environmental sustainability and land conservation. Soil degradation, erosion, and contamination are pressing issues affecting agricultural productivity and ecosystem health. Soil mapping services provide critical insights into soil properties, enabling land managers and policymakers to implement targeted conservation measures. By identifying areas at risk of degradation or contamination, these services facilitate the adoption of best practices for soil restoration and remediation. Additionally, the integration of soil mapping data with environmental assessment tools supports compliance with regulatory requirements and promotes responsible land use planning, further driving market growth.

Technological advancements have also played a pivotal role in propelling the soil mapping services market forward. The integration of remote sensing, Geographic Information Systems (GIS), and Global Positioning Systems (GPS) has revolutionized the accuracy, efficiency, and scalability of soil mapping. Digital soil mapping, which combines traditional survey techniques with advanced data analytics and machine learning, has become increasingly prevalent. These innovations enable the rapid collection, analysis, and dissemination of soil data, empowering stakeholders to make informed decisions in real-time. The proliferation of affordable sensing devices and the expansion of cloud-based data platforms have further democratized access to soil mapping services, fostering widespread adoption across diverse end-user segments.

Regionally, North America remains the dominant market for soil mapping services, accounting for the largest share in 2024, followed closely by Europe and the Asia Pacific. The presence of technologically advanced agricultural sectors, strong research and development infrastructure, and supportive policy frameworks have contributed to the market’s strength in these regions. Meanwhile, rapid urbanization, increasing investments in smart agriculture, and growing environmental concerns are expected to fuel significant growth in the Asia Pacific region over the forecast period. Latin America and the Middle East & Africa are also emerging as promising markets, driven by expanding agricultural activities and the need for sustainable land management solutions.

Service Type Analysis

The soil mapping services market is segmented by service type into soil sampling, soil analysis, soil survey, digital soil mapping, and others. Soil sampling remains a foundational service, as it provides the raw data necessary for all subsequent analyses and mapping processes. The increasing adoption of automated and sensor-based soil sampling techniques has enhanced the accuracy and efficiency of data collection, reducing human error and enabling high-resolution spatial analysis. This evolution in sampling methods has made it easier for service pr

Soil-geomorphological mapping is a reliable tool for analyzing the patterns of soil distribution in various parts of Earth’s surface. Cryogenic and watershed areas are the most dynamic landscapes with relatively rapid transformation under the influence of climate change and river activity. The soil-geomorphological map obtained by unmanned aerial vehicle (UAV) imaging, classical soil sections, geomorphological observation, and determination of the main chemical parameters of soils are presented. Mapping of the spatial distribution was performed using QGIS 3.22, SAGA GIS 7.9.1, and ArcGIS 10.6 software. The investigation of soil cover was performed according to WRB soil classification. From the obtained data, four types of soils were identified due to their position in the relief and chemical parameters. The dominant soil type is Folic Cryosol (Siltic) (41.1%) which is formed on the periglacial landscape of wet polygons on Samoylov Island. The application of high-resolution UAV imaging to construct soil-geomorphological maps is the most relevant method for analyzing soils formed in cryogenic, watershed, and mountainous landscapes. Based on SOC distribution, it was found that the highest SOC content corresponds to Holocene terrace (Cryosol and Histosol soil types), in areas that are not subject to the flooding process. According to the analysis of the chemical composition of soils, it was found that the main elements accumulating in the soil are SiO2, Al2O3, CaO, and K2O, which have a river origin. The soil-geomorphological maps can be used to analyze the reserves and contents of organic and inorganic components with high accuracy.

Download .zipA soil mapping unit designates a specific type of soil which has unique characteristics including texture, slope, and erosion class.

These soils were digitized from the paper original soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

Abstract Easily understandable thematic maps of geo-scientific parameters are important for land use decision making. If several parameters are relevant and have to be compared, it is important that they are consistent with each other, available at the same spatial range and detail and normed to a common data range. In the current study, geological and topographical data have been used to derive a set of 90 geo-scientific maps for an area of 400 km² in the northern part of the metropolitan area of Belo Horizonte. Each parameter has been transferred to a common data range between 0 and 1 using a Semantic Import Model strategy and afterwards combined to derive new parameters for soil hydrology and hydrogeology. From these, many intermediate geo-scientific parameters, maps of geo-resources (sand/gravel, carbonates, fertile soils) and geo-hazards (erosion, groundwater pollution) have been derived that they can be used as base information for a participatory and sustainable land use planning. The workflow is transparently stored in GIS-tools and can be modified and updated if new information is available.

To better understand factors potentially contributing to the occurrence of rainfall-induced landslides in Puerto Rico, we evaluated the locations of landslides there following Hurricane Maria (Hughes et al., 2019) and potential contributing factors. This data release provides results of evaluations of landslide locations compared to soil classification and land cover, which involved frequency-ratio analyses (for example, Lee and Pradhan, 2006; Lee et al., 2007; He and Beighley, 2008; Lepore et al., 2012; Chalkias et al., 2014). Soil classification data were obtained from the U.S. Department of Agriculture Natural Resources Conservation Service (2018) and land cover data were obtained from the Puerto Rico Gap Analysis Program (Gould et al., 2008). The data presented herewith were produced during a study described in Hughes, K.S., and Schulz, W.H., ####, Map depicting susceptibility to landslides triggered by intense rainfall, Puerto Rico: U.S. Geological Survey Open-file Report #####. Three files are included with this data release. Data files soil_classification_results.csv and land_cover_results.csv provide results of the analyses of landslide locations compared to soil classification and land cover, respectively. A read-me file (readme.txt) provides the information contained in this summary and additional description of data available from the data files. References Chalkias, C., Kalogirou, S., and Ferntinou, M., 2014, Landslide susceptibility, Peloponnese Peninsula in South Greece: Journal of Maps, v. 10, no. 2, p. 211-222. Gould, W.A., Alarcón, C., Fevold, B., Jiménez, M.E., Martinuzzi, S., Potts, G., Quiñones, M., Solórzano, M., and Ventosa, E., 2008, The Puerto Rico Gap Analysis Project. Volume 1: Land cover, vertebrate species distributions, and land stewardship. Gen. Tech. Rep. IITF-GTR-39. Río Piedras, PR: U.S. Department of Agriculture, Forest Service, International Institute of Tropical Forestry. 165 p. https://www.sciencebase.gov/catalog/item/560c3b2de4b058f706e5411e. Last accessed 12 September 2019. He, Y., and Beighley, R.E., 2008, GIS‐based regional landslide susceptibility mapping: a case study in southern California: Earth Surface Processes and Landforms, v. 33, no. 3, p. 380-393. Hughes, K.S., Bayouth García, D., Martínez Milian, G.O., Schulz, W.H., and Baum, R.L., 2019, Map of slope-failure locations in Puerto Rico after Hurricane María: U.S. Geological Survey data release: https://doi.org/10.5066/P9BVMD74. https://www.sciencebase.gov/catalog/item/5d4c8b26e4b01d82ce8dfeb0. Last accessed 12 September 2019. Lee, S., and Pradhan, B., 2006, Probabilistic landslide hazards and risk mapping on Penang Island, Malaysia: Journal of Earth System Science, v. 115, no. 6, p. 661-672. Lee, S., Ryu, J-H., and Kim, I-S., 2007, Landslide susceptibility analysis and its verification using likelihood ratio, logistic regression, and artificial neural network models: case study of Youngin, Korea: Landslides v. 4, p. 327–338. Lepore, C., Kamal, S.A., Shanahan, P., and Bras, R.L., 2012, Rainfall-induced landslide susceptibility zonation of Puerto Rico: Environmental Earth Sciences, v. 66, p. 1667-1681. U.S. Department of Agriculture Natural Resources Conservation Service, 2018, Soil Survey Geographic (SSURGO) database for Puerto Rico, all regions: https://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx. Last accessed 12 September 2019.

Download .zipA soil mapping unit designates a specific type of soil which has unique characteristics including texture, slope, and erosion class.

These soils were digitized from the paper final soil survey sheets. These sheets were taped together to form an area covering each of the USGS 7.5 minute quadrangle maps in the county. The areas for each quadrangle were then digitized using run-length encoding technique sampling along horizontal lines which represented the midline of cells with a height of 250 feet. The measurement increment along these lines was one decafoot (10 feet). The quadrangle files were then merged into a county file which has subsequently been converted to Arc/Info format.

The user should bear in mind that this coverage is only an approximation of the soil survey and should not be used for site specific analysis.

Additional details of the digitizing process are available upon request.

Original coverage data was converted from the .e00 file to a more standard ESRI shapefile(s) in November 2014.Contact Information:GIS Support, ODNR GIS ServicesOhio Department of Natural ResourcesReal Estate & Land ManagementReal Estate and Lands Management2045 Morse Rd, Bldg I-2Columbus, OH, 43229Telephone: 614-265-6462Email: gis.support@dnr.ohio.gov Data Update Frequency: As Needed

The Digital Soil Mapping Market will grow from USD 147.61 Million in 2024 to USD 231.65 Million by 2030 at a 7.80% CAGR.

More MetadataAbstract: The general soil association map outlines broad areas which have distinctive patterns in landscape and general geographic appearance. Each of the soil associations has a unique set of features which effect general use and management including shape and length of slope; width of ridgetops and valleys; frequency, size, and direction of streams; type of vegetation, rate of growth; and agriculture. These differences are largely the result of broad differences in kinds of soils and in the geologic materials from which the soils formed. A mapping unit typically consists of one or more major soils with minor soils, and is named for the major soils. This map shows, in small scale, a summary of the information contained on the individual detailed soil maps for Loudoun County. Because of its small scale and general soil descriptions, it is not suitable for planning small areas or specific sites, but it does present a general picture of soils in the County, and can show large areas generally suited to a particular kind of agriculture or other special land use. For more detailed and specific soils information, please refer to the detailed soils maps and other information available from the County Soil Scientist. Digital data consists of mapping units of the various soil types found in Loudoun County, Virginia. The data were collected by digitizing manuscript maps derived from USDA soil maps and supplemented by both field work and geological data. Field work for the soil survey was first conducted between 1947 and 1952. Soils were originally shown at the scale of 1:15840 and then redrafted by the County soil scientist to 1:12000; the data were redrafted a final time to fit Loudoun County's base map standard of 1:2400. Although the current data rely heavily on the original soil survey, there have been extensive field checks and alterations to the soil map based on current soil concepts and land use. The data are updated as field site inspections or interpretation changes occur.Purpose: Digital data are used to identify the mapping unit potential for a variety of uses, such as agriculture drainfield suitability, construction concerns, or development possibility. This material is intended for planning purposes, as well as to alert the reader to the broad range of conditions, problems, and use potential for each mapping unit. The mapping unit potential use rating refers to the overall combination of soil properties and landscape conditions. The information in this data set will enable the user to determine the distribution and extent of various classes of soil and generally, the types of problems which may be anticipated. HOW NOT TO USE THIS INFORMATION The information in this guide is NOT intended for use in determining specific use or suitability of soils for a particular site. It is of utmost importance that the reader understand that the information is geared to mapping unit potential and not to specific site suitability. An intensive on-site evaluation should be made to verify the soils map and determine the soil/site suitability for the specific use of a parcel. The original Soil Survey was written for agricultural purposes, but the emphasis has shifted to include urban/suburban uses. The Revised Soil Survey is currently under technical review and is expected to be published by 2006.Supplemental information: The Interpretive Guide to the Use of Soils Maps; Loudoun County, Virginia contains more detailed soils information. Data are stored in the corporate GIS Geodatabase as a polygon feature class. The coordinate system is Virginia State Plane (North), Zone 4501, datum NAD83 HARN.

The global soil erosion testing market is booming, projected to reach $4.3 billion by 2033 with a 7% CAGR. Learn about market drivers, trends, key players (TRI Environmental, AgSource Labs, SGS SA), and regional insights in this comprehensive analysis. Discover how advanced testing methods and sustainable agriculture are shaping this crucial sector.

The agricultural mapping software market is experiencing robust growth, driven by the increasing adoption of precision agriculture techniques and the need for efficient farm management. The market, estimated at $1.5 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $4.2 billion by 2033. This expansion is fueled by several key factors. Firstly, the rising demand for higher crop yields and improved resource utilization is compelling farmers to adopt technology-driven solutions. Agricultural mapping software provides crucial insights into field conditions, allowing for optimized planting, fertilization, and irrigation strategies, leading to significant cost savings and increased profitability. Secondly, advancements in sensor technology, GPS accuracy, and data analytics are enhancing the capabilities of agricultural mapping software, making it more accessible and user-friendly. Finally, government initiatives promoting precision agriculture and digital farming are further stimulating market growth. The market is segmented by software type (e.g., cloud-based, on-premise), application (e.g., yield mapping, soil analysis), and farm size. Key players like Trimble, CNH Industrial, and Geosys are actively shaping the market through continuous innovation and strategic partnerships. Despite the significant growth potential, certain challenges remain. High initial investment costs for software and hardware can act as a barrier to entry for small-scale farmers. Furthermore, the reliance on robust internet connectivity and technical expertise can hinder adoption in regions with limited infrastructure. However, ongoing technological advancements, coupled with the increasing availability of affordable solutions and training programs, are gradually addressing these limitations. The market will continue to witness consolidation through mergers and acquisitions, as larger players seek to expand their market share and offerings. Future growth will be particularly driven by the integration of artificial intelligence and machine learning into agricultural mapping software, enabling more predictive and insightful analytics for improved farm management.