The global market for GIS software in agriculture is experiencing robust growth, driven by the increasing need for precision agriculture techniques and the rising adoption of smart farming practices. This sector leverages Geographic Information Systems (GIS) to optimize various agricultural operations, including land management, crop monitoring, yield prediction, and resource allocation. The market's value in 2025 is estimated at $2.5 billion, exhibiting a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033. This growth trajectory is fueled by several key factors. Firstly, the escalating demand for higher crop yields and improved resource efficiency in the face of a growing global population is a primary driver. Secondly, advancements in sensor technologies, satellite imagery, and data analytics are providing increasingly precise and actionable agricultural insights. Finally, government initiatives promoting digital agriculture and precision farming technologies are further stimulating market expansion. Despite significant growth, challenges remain. High initial investment costs for GIS software and the required hardware can be a barrier to entry for smaller farms and developing economies. Furthermore, the complexity of implementing and effectively utilizing GIS solutions requires skilled personnel, creating a need for increased training and support. However, the long-term benefits of enhanced efficiency, reduced waste, and improved yields are overcoming these obstacles, creating a positive outlook for market expansion. Key players such as Autodesk, Esri, and Trimble are actively innovating and expanding their agricultural GIS offerings to cater to the evolving needs of the sector. The market is segmented by software type (desktop, web-based, mobile), deployment mode (cloud, on-premise), and application (precision farming, irrigation management, crop monitoring). The continued integration of AI and machine learning within GIS platforms promises further advancements in agricultural optimization, propelling market growth in the coming years.

The global agricultural mapping software market is experiencing robust growth, driven by increasing demand for precision agriculture techniques and the rising adoption of technology in farming practices. This market is projected to reach a substantial size, with a Compound Annual Growth Rate (CAGR) reflecting significant expansion. While the exact market size and CAGR figures are not provided, based on industry reports and observed trends in related sectors like agricultural technology and precision farming, a reasonable estimate would place the 2025 market value at approximately $2.5 billion, growing at a CAGR of 15% from 2025 to 2033. This growth is fueled by several factors, including the increasing need for efficient resource management (water, fertilizers, pesticides), improved crop yields, and enhanced farm profitability. Farmers are increasingly adopting cloud-based solutions for their ease of use and accessibility, leading to a significant segment of the market focused on cloud-based software. Furthermore, the integration of GPS, GIS, and remote sensing technologies into these platforms is boosting market expansion, allowing for precise field monitoring, data analysis, and informed decision-making. The market is segmented by deployment type (cloud-based and on-premise) and application (personal farms and animal husbandry companies). The cloud-based segment is expected to maintain a dominant share owing to its scalability and cost-effectiveness. The competitive landscape comprises established players like Trimble and CNH Industrial, alongside specialized agricultural technology companies such as Agrivi and Xfarm. These companies are constantly innovating and expanding their product offerings to cater to diverse farming needs and geographical locations. Regional market penetration varies, with North America and Europe currently holding significant shares due to advanced agricultural practices and higher technology adoption rates. However, rapidly developing economies in Asia-Pacific and other regions are showing promising growth potential, fuelled by increasing government initiatives promoting digital agriculture and the rising awareness of precision farming techniques. Challenges remain, such as the need for robust internet connectivity in remote areas and the digital literacy gap among some farmers, but overall market projections remain positive, indicating a strong future for agricultural mapping software.

Smart agriculture refers to tools that collect, store and analyze digital data along the agricultural value chain. Geographic Information System (GIS) system software is one of those tools used in the agricultural sector. The GIS System market in Spain had a value of over ** million dollars in 2019.

The global GIS Software in Agriculture market is anticipated to grow significantly over the forecast period, driven by the increasing demand for precision agriculture practices and the need for efficient and sustainable farming techniques. The market is expected to witness notable growth due to the rising adoption of GIS technology in various agricultural applications, such as crop monitoring, soil analysis, and irrigation management. The increasing focus on maximizing crop yields, reducing environmental impact, and optimizing resource utilization is further propelling the demand for GIS solutions in the agriculture sector. The key players in the GIS Software in Agriculture market include Autodesk, Inc., Computer Aided Development Corporation Ltd. (Cadcorp), Earth Observing System, Environmental System Research Institute (ESRI), and Geosoft Inc., among others. These companies are investing in research and development to offer advanced GIS software solutions that meet the evolving needs of the agricultural industry. The market is expected to experience significant growth in emerging regions, particularly in Asia-Pacific and Latin America, where agriculture is a key economic sector. Governments and agricultural organizations in these regions are promoting the adoption of GIS technology to enhance agricultural productivity and sustainability.

The GIS shapefile and summary tables provide irrigated agricultural land-use for Citrus, Hernando, Pasco, and Sumter Counties, Florida through a cooperative project between the U.S Geological Survey (USGS) and the Florida Department of Agriculture and Consumer Services (FDACS), Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated land field verified for 2019, crop type, irrigation system type, and primary water source used in Citrus, Hernando, Pasco, and Sumter Counties, Florida. A map image of the shapefile is provided in the attachment.

A Geographic Information System (GIS) shapefile and summary tables of irrigated agricultural land-use are provided for the fourteen counties that are fully or partially within the Suwannee River Water Management District, Florida compiled through a cooperative project between the U.S Geological Survey and the Florida Department of Agriculture and Consumer Services, Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated lands that were verified during field trips that started in January 2020 and concluded in December 2020, and the crop type, irrigation system type, and primary water source used. A map image of the shapefile is provided. Previously published estimates of irrigation acreage for years since 1982 are included in summary tables.

The global market for GIS software in agriculture is experiencing robust growth, driven by the increasing need for precision farming techniques and the rising adoption of smart agriculture practices. The market's expansion is fueled by several factors: the escalating demand for improved crop yields and resource optimization in the face of climate change and population growth; the increasing availability of high-resolution satellite imagery, drone technology, and sensor data; and the development of sophisticated GIS software capable of analyzing this data to create actionable insights for farmers. Key applications include precision irrigation, targeted fertilizer application, optimized planting strategies, and predictive modeling of crop yields. This allows farmers to make data-driven decisions resulting in reduced input costs, increased efficiency, and improved sustainability. We estimate the market size in 2025 to be around $2.5 billion, based on general trends in the broader GIS market and the significant investment in agricultural technology. A Compound Annual Growth Rate (CAGR) of 12% is projected from 2025 to 2033, indicating significant potential for market expansion. While the high initial investment in software and infrastructure can be a barrier for smaller farms, the long-term benefits in terms of cost savings and yield improvements are expected to drive wider adoption. Competition within the market is strong, with both established GIS vendors and specialized agricultural technology companies vying for market share. The major players in this space are leveraging technological advancements such as cloud computing, artificial intelligence (AI), and machine learning (ML) to enhance the capabilities of their GIS software solutions. Integration with other agricultural technologies like IoT sensors and farm management systems is another key trend. While data privacy and security concerns, along with the need for skilled personnel to operate these advanced systems, pose challenges, ongoing technological innovation and rising government support for precision agriculture initiatives are expected to mitigate these restraints. The segmentation of the market is likely to reflect different farming practices (e.g., row crops versus horticulture), farm sizes, and geographical regions. North America and Europe are currently leading the market, however, the adoption rate is significantly increasing in regions with rapidly developing agricultural sectors, such as Asia and South America. This presents lucrative opportunities for software providers to expand their reach and tap into these emerging markets.

The Cropland Data Layer (CDL), hosted on CropScape, provides a raster, geo-referenced, crop-specific land cover map for the continental United States. The CDL also includes a crop mask layer and planting frequency layers, as well as boundary, water and road layers. The Boundary Layer options provided are County, Agricultural Statistics Districts (ASD), State, and Region. The data is created annually using moderate resolution satellite imagery and extensive agricultural ground truth. Users can select a geographic area of interest or import one, then access acreage statistics for a specific year or view the change from one year to another. The data can be exported or added to the CDL. The information is useful for issues related to agricultural sustainability, biodiversity, and land cover monitoring, especially due to extreme weather events. Resources in this dataset:Resource Title: CropScape and Cropland Data Layer - National Download. File Name: Web Page, url: https://www.nass.usda.gov/Research_and_Science/Cropland/Release/index.php Downloads available as zipped files at https://www.nass.usda.gov/Research_and_Science/Cropland/Release/index.php --

National CDL's -- by year, 2008-2020. Cropland Data Layer provides a raster, geo-referenced, crop-specific land cover map for the continental United States. The CDL also includes a crop mask layer and planting frequency layers, as well as boundary, water and road layers. The Boundary Layer options provided are County, Agricultural Statistics Districts (ASD), State, and Region. National Cultivated Layer -- based on the most recent five years (2013-2020). National Frequency Layer -- the 2017 Crop Frequency Layer identifies crop specific planting frequency and are based on land cover information derived from the 2008 through 2020CDL's. There are currently four individual crop frequency data layers that represent four major crops: corn, cotton, soybeans, and wheat. National Confidence Layer -- the Confidence Layer spatially represents the predicted confidence that is associated with that output pixel, based upon the rule(s) that were used to classify it. Western/Eastern/Central U.S.

Visit https://nassgeodata.gmu.edu/CropScape/ for the interactive map including tutorials and basic instructions. These options include a "Demo Video", "Help", "Developer Guide", and "FAQ".

GIS Software in Agriculture Market Focus on Solution (On-Cloud, On-Premise), Application (Crop Monitoring, Soil Analysis, Irrigation Monitoring), and Region. The report aims at estimating the market size and future growth of GIS Software in Agriculture Market. GIS Software in Agriculture Market to grow at a significant CAGR of 10.41% during the forecast period from 2019 to 2024.

[Metadata] Description: Agricultural Land Use Maps (ALUM) for islands of Kauai, Oahu, Maui, Molokai, Lanai and Hawaii as of 1978-1980. Sources: State Department of Agriculture; Hawaii Statewide GIS Program, Office of Planning. Note: August, 2018 - Corrected one incorrect record, removed coded value attribute domain.For more information on data sources and methodologies used, please refer to complete metadata at https://files.hawaii.gov/dbedt/op/gis/data/alum.pdf or contact Hawaii Statewide GIS Program, Office of Planning and Sustainable Development, State of Hawaii; PO Box 2359, Honolulu, HI 96804; (808) 587-2846; email: gis@hawaii.gov; Website: https://planning.hawaii.gov/gis.

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

The global satellite remote sensing software market is experiencing robust growth, driven by increasing demand across diverse sectors. While precise figures for market size and CAGR aren't provided, a reasonable estimate based on industry reports and the stated study period (2019-2033) suggests a current market valuation (2025) in the range of $3-5 billion USD. This significant market size is fueled by several key factors. The agricultural sector relies heavily on remote sensing for precision farming, crop monitoring, and yield prediction, significantly contributing to market expansion. Similarly, the water conservancy and forest management sectors utilize satellite imagery and software for resource monitoring, disaster management, and sustainable practices. Government agencies and the public sector increasingly adopt these technologies for urban planning, environmental monitoring, and national security applications. The market's growth is further enhanced by advancements in open-source software, offering cost-effective alternatives and promoting wider adoption. Trends such as cloud-based solutions, improved data processing capabilities, and the integration of artificial intelligence are further accelerating market growth. However, the market faces certain constraints. High initial investment costs for software licenses and specialized hardware can act as a barrier for entry, particularly for smaller businesses and organizations in developing regions. Data security concerns and the need for skilled professionals to interpret the complex data generated also pose challenges. Despite these obstacles, the ongoing development of user-friendly interfaces, coupled with decreasing hardware costs and increasing availability of cloud-based services, is predicted to mitigate these restraints and sustain a healthy compound annual growth rate (CAGR) in the range of 8-12% throughout the forecast period (2025-2033). Segmentation by application (Agriculture, Water Conservancy, Forest Management, Public Sector, Others) and software type (Open Source, Non-Open Source) reveals distinct market dynamics, with the non-open source segment currently holding a larger share due to its advanced capabilities. This trend is expected to continue, though the open-source segment will show considerable growth driven by its affordability and accessibility.

A Geographic Information System (GIS) shapefile and summary tables of the extent of irrigated agricultural land-use are provided for eleven counties fully or partially within the St. Johns River Water Management District (full-county extents of: Brevard, Clay, Duval, Flagler, Indian River, Nassau, Osceola, Putnam, Seminole, St. Johns, and Volusia counties). These files were compiled through a cooperative project between the U.S. Geological Survey and the Florida Department of Agriculture and Consumer Services, Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated lands that were verified during field surveying that started in November 2022 and concluded in August 2023. Field data collected were crop type, irrigation system type, and primary water source used. A map image of the shapefile is also provided. Previously published estimates of irrigation acreage for years since 1987 are included in summary tables.

Geospatial data about World Bank Agriculture Percent Land Used for Agricultural. Export to CAD, GIS, PDF, CSV and access via API.

A Geographic Information System (GIS) shapefile and summary tables of irrigated agricultural land-use are provided for Glades, Highlands, Martin, Okeechobee, and St. Lucie Counties, Florida. These files were compiled through a cooperative project between the U.S. Geological Survey and the Florida Department of Agriculture and Consumer Services, Office of Agricultural Water Policy. Information provided in the shapefile includes the location of irrigated lands that were verified during field surveying that started in November 2023 and concluded in July 2024. Field data collected included crop type, irrigation system type, and primary water source used. A map image of the shapefile is also provided. Previously published estimates of irrigation acreage for years since 1992 are included in summary tables.

Geographic Information Software (GIS) in Agriculture market is anticipated to grow at a CAGR of 10% during 2020-25 forecast says MarkNtel Advisors.

Table contains count and percentage of county residents ages 16 and older who work in agriculture, forestry, fishing and hunting, and mining industry. Data are presented at county, city, zip code and census tract level. Data are presented for zip codes (ZCTAs) fully within the county. Source: U.S. Census Bureau, 2016-2020 American Community Survey 5-year estimates, Table S2403; data accessed on July 20, 2022 from https://api.census.gov. The 2020 Decennial geographies are used for data summarization.METADATA:notes (String): Lists table title, notes, sourcesgeolevel (String): Level of geographyGEOID (Numeric): Geography IDNAME (String): Name of geographyt_16plus (Numeric): Population ages 16 years and olderagri_forest_fish_hunt_mining (Numeric): Number of workers in agriculture, forestry, fishing and hunting, and mining industrypct_agri (Numeric): Percent of workers in agriculture, forestry, fishing and hunting, and mining industry

Agricultural Mapping Software Market Outlook

The global agricultural mapping software market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 3.4 billion by 2032, growing at a Compound Annual Growth Rate (CAGR) of 12.5% during the forecast period. This promising growth is driven by increasing adoption of precision farming techniques and the need for efficient agricultural management practices. Advances in technology, coupled with rising demand for food production, are significant factors propelling the agricultural mapping software market.

One of the primary growth factors for the agricultural mapping software market is the increasing need for precision farming. Precision farming techniques rely on detailed data collection and analysis, which is facilitated by advanced agricultural mapping software. These tools help farmers make informed decisions about planting, watering, and harvesting, thereby maximizing crop yield and resource efficiency. The emphasis on data-driven farming is expected to drive significant adoption of mapping software across the globe.

Another crucial growth factor is the rising global population, which directly correlates with the increasing demand for food. As the world population continues to grow, the pressure on agricultural systems becomes more intense. Agricultural mapping software aids in optimizing land use, monitoring crop health, and predicting yields, thus playing a pivotal role in meeting the escalating food demands. The software's ability to enhance productivity and sustainability is highly appealing to stakeholders in the agricultural sector.

Technological advancements in GIS (Geographic Information Systems) and remote sensing are also propelling the market. The integration of satellite imagery, drones, and IoT (Internet of Things) devices with agricultural mapping software enables real-time data acquisition and analysis. These technologies provide farmers with detailed insights into their fields, enabling them to detect issues early and take corrective action promptly. The continuous innovation in these technologies is expected to further boost market growth.

From a regional perspective, North America is anticipated to hold the largest market share due to the high adoption rate of advanced farming technologies and substantial investments in agricultural research. Europe follows closely, driven by stringent agricultural policies and a strong focus on sustainable farming practices. The Asia Pacific region is expected to witness the fastest growth, attributed to increasing government initiatives to modernize agriculture and substantial investments in agritech startups. Latin America and the Middle East & Africa also present significant growth opportunities due to expanding agricultural activities and adoption of modern farming techniques.

Crop Monitoring Software plays a pivotal role in the agricultural mapping software market by providing farmers with the tools necessary to maintain and enhance crop health. This software allows for continuous observation and analysis of crops, ensuring that any potential issues such as diseases, pest infestations, or nutrient deficiencies are identified early. By leveraging real-time data, farmers can make informed decisions that lead to improved crop yields and quality. The integration of Crop Monitoring Software with other agricultural technologies further enhances its capabilities, making it an indispensable tool for modern farming practices. As the demand for efficient and sustainable agriculture grows, the adoption of such software is expected to rise, contributing significantly to the market's expansion.

Component Analysis

The agricultural mapping software market by component is divided into two primary segments: software and services. The software segment encompasses a range of solutions tailored to various agricultural needs, including GIS software, remote sensing software, and farm management software. These tools are designed to collect, analyze, and interpret data to support decision-making processes in farming operations. The sophistication and variety of available software solutions are continually expanding, driven by ongoing research and development efforts in agritech.

In contrast, the services segment includes consulting, training, maintenance, and support services that complement the software solutions. As more farmers and agricultural enterprises adopt mapp

This statistic shows the percentage of agricultural operations in Canada using GIS mapping technology in 2015, by farm size. In that year, **** percent of Canadian farms with 10,000 or more acres of land reported using GIS mapping.

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.