Discover the booming market for agricultural mapping software! Learn about its $2.5 billion (2025 est.) value, 15% CAGR, key drivers, trends, and leading companies shaping precision agriculture. Explore regional market shares and future growth projections in this comprehensive analysis.

Global Precision Agriculture Market size is set to expand from $ 10.10 Billion in 2023 to $ 24.62 Billion by 2032, with CAGR of 10.4% from 2024 to 2032.

Discover the booming Satellite Remote Sensing Software market! Explore key trends, growth drivers, and regional market shares in our comprehensive analysis. Learn about leading companies and the future of this technology in agriculture, forestry, and beyond. Get the insights you need to make informed decisions.

Crop growth and yield monitoring over agricultural fields is an essential procedure for food security and agricultural economic return prediction. The advances in remote sensing have enhanced the process of monitoring the development of agricultural crops and estimating their yields. Therefore, remote sensing and GIS techniques were employed, in this study, to predict potato tuber crop yield on three 30 ha center pivot irrigated fields in an agricultural scheme located in the Eastern Region of Saudi Arabia. Landsat-8 and Sentinel-2 satellite images were acquired during the potato growth stages and two vegetation indices (the normalized difference vegetation index (NDVI) and the soil adjusted vegetation index (SAVI)) were generated from the images. Vegetation index maps were developed and classified into zones based on vegetation health statements, where the stratified random sampling points were accordingly initiated. Potato yield samples were collected 2–3 days prior to the harvest time and were correlated to the adjacent NDVI and SAVI, where yield prediction algorithms were developed and used to generate prediction yield maps. Results of the study revealed that the difference between predicted yield values and actual ones (prediction error) ranged between 7.9 and 13.5% for Landsat-8 images and between 3.8 and 10.2% for Sentinel-2 images. The relationship between actual and predicted yield values produced R2 values ranging between 0.39 and 0.65 for Landsat-8 images and between 0.47 and 0.65 for Sentinel-2 images. Results of this study revealed a considerable variation in field productivity across the three fields, where high-yield areas produced an average yield of above 40 t ha-1; while, the low-yield areas produced, on the average, less than 21 t ha-1. Identifying such great variation in field productivity will assist farmers and decision makers in managing their practices.

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.

A Geographic Information System (GIS) shapefile and summary tables of irrigated agricultural land-use are provided for the 15 counties fully within the Northwest Florida Water Management District (Bay, Calhoun, Escambia, Franklin, Gadsden, Gulf, Holmes, Jackson, Leon, Liberty, Okaloosa, Santa Rosa, Wakulla, Walton, and Washington 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 May 2021 and concluded in August 2021. 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 1982 are included in summary tables.

The agricultural mapping software market is booming, projected to reach $8 billion by 2033. Discover key trends, drivers, and restraints shaping this rapidly evolving sector, featuring leading companies like Trimble and CNH Industrial. Explore market size, CAGR, and regional breakdowns in this comprehensive analysis.

Discover the booming GIS Data Collector market! This comprehensive analysis reveals a $2.5B market in 2025, projected to reach $4.2B by 2033, fueled by precision agriculture, infrastructure development, and technological advancements. Explore key trends, drivers, restraints, and leading companies shaping this dynamic sector.

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 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.

Precision Farming Agriculture Market Outlook

The global precision farming agriculture market size was estimated at USD 7.0 billion in 2023 and is projected to reach USD 15.6 billion by 2032, growing at a compound annual growth rate (CAGR) of 9.2% from 2024 to 2032. The growth of this market is primarily driven by advancements in technology and increasing demand for food production efficiency.

One of the most significant growth factors in the precision farming agriculture market is the rapid advancement in agricultural technologies. Innovations such as Internet of Things (IoT), big data analytics, and artificial intelligence have enabled farmers to collect and analyze data from their fields, leading to more informed decision-making processes. This shift towards data-driven farming helps optimize resources such as water, fertilizers, and pesticides, thereby increasing yield and reducing costs. Additionally, the integration of Geographic Information Systems (GIS) and GPS technology in farming practices allows for more precise planting, cultivating, and harvesting, which further boosts productivity and efficiency.

Another critical factor contributing to the market's growth is the increasing global population, which drives the demand for more efficient food production systems. With the world's population projected to reach 9.7 billion by 2050, there is an urgent need to produce more food while minimizing environmental impact. Precision farming offers a viable solution by enabling farmers to manage their resources more effectively, reducing waste, and maximizing crop yields. The rising awareness about sustainable farming practices and the need to address climate change concerns have also led to the adoption of precision farming techniques.

Government initiatives and subsidies aimed at promoting precision farming are further propelling the market's growth. Various governments across the globe are recognizing the potential benefits of precision farming in enhancing food security and agricultural sustainability. As a result, they are investing in research and development, providing financial assistance, and implementing favorable policies to encourage the adoption of precision farming technologies. For instance, the European Union's Common Agricultural Policy (CAP) includes measures to support precision farming practices, while the United States Department of Agriculture (USDA) offers grants and loans to farmers for implementing advanced agricultural technologies.

Agriculture Variable Rate Technology (VRT) is revolutionizing the way farmers manage their fields by allowing precise application of inputs like fertilizers, pesticides, and water. This technology leverages data from various sources, such as soil sensors and yield monitors, to customize the application rates for different areas within a field. By doing so, VRT not only enhances crop productivity but also minimizes the environmental impact of farming practices. Farmers can achieve significant cost savings by reducing the overuse of chemicals and water, which is increasingly important in the context of sustainable agriculture. As awareness about the benefits of VRT grows, more farmers are expected to adopt this technology, further driving the precision farming market.

From a regional perspective, North America holds a significant share of the precision farming agriculture market, driven by the early adoption of advanced technologies and the presence of a large number of key market players. The Asia Pacific region is expected to witness substantial growth during the forecast period, primarily due to the increasing demand for food production and the adoption of modern farming practices in countries such as China and India. Europe is also a noteworthy market, with countries like Germany and France focusing on sustainable agriculture and smart farming initiatives.

Technology Analysis

The precision farming agriculture market can be segmented by technology into guidance systems, remote sensing, variable rate technology, and others. Guidance systems, such as GPS-based auto-steering, play a crucial role in precision farming by enabling farmers to automate their machinery, ensuring precise and efficient field operations. These systems help in reducing overlaps and gaps in field activities, thereby saving time, fuel, and labor costs. The increasing adoption of autonomous tractors and drones equipped with guidance systems is further driving the growth of this segme

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.

A Geographic Information System (GIS) shapefile and summary tables of irrigated agricultural land-use are provided for Lake, Marion, and Orange Counties, 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.

A shapefile of the extent of irrigated agricultural fields which includes an attribute table of the irrigated acreage for the period between November 2022 and June 2023 was compiled for the full county extents of Brevard, Clay, Duval, Flagler, Indian River, Nassau, Osceola, Putnam, Seminole, St. Johns, and Volusia Counties, Florida. These eleven counties are fully or partially within the St. Johns River Water Management District (SJRWMD). Attributes for each polygon that represents a field include a general or specific crop type, irrigation system, and primary water source for irrigation.

Precision agriculture systems and services have experienced substantial growth over the past five years. This growth is primarily driven by the increased adoption of IoT and smart devices, allowing farmers to optimize production efficiencies through real-time data on soil conditions, crop health and weather patterns. Despite initial disruptions from the COVID-19 pandemic, the industry demonstrated resilience due to technological advancements, improved agricultural markets and increasing demand for larger equipment. As a result, industry revenue has grown at a CAGR of 10.9% to $7.6 billion in 2024, with a 1.4% increase in 2024 alone. Advances in drone technology, precision farming software and data analytics have further contributed to this robust growth, enabling more precise and efficient farming practices. Industry profit is predominantly driven by demand from agribusiness sectors, government support and ongoing technological innovations. The various downstream markets, including farm machinery manufacturers, family-owned farms and publicly funded research operations, significantly contribute to revenue generation. The rapid adoption of cutting-edge technologies such as AI, ML and smart devices, combined with government policies promoting sustainable agricultural practices, has bolstered industry profit during the current period. Additionally, partnerships between tech companies and agricultural firms have accelerated innovation, enhancing the capabilities of precision agriculture technologies and supporting higher profitability for machinery manufacturers and service providers. The industry is projected to sustain its robust expansion, growing at a CAGR of 2.7% to $8.7 billion over the next five years. The continuation of favorable policies, such as the potential renewal of the Farm Bill, will support rural development and provide financial aid that make precision agriculture products more accessible. Advances in AI and machine learning will further revolutionize farm management through predictive analytics and automated decision-making capabilities. However, challenges persist, such as the reluctance of some farmers to adopt new technologies and concerns over data security and privacy. Despite these challenges, the expansion of autonomous farming equipment and the increased penetration of broadband and mobile technologies in rural areas are expected to drive greater acceptance and integration of precision agriculture practices, ensuring the industry's sustained growth and profitability.

The GIS software market for agricultural use in South America was forecast to reach over *** million U.S. dollars in 2019, up from an estimated ***** million dollars a year earlier. Crop monitoring was the largest application in the region, accounting for more than half of the market's value in the period.

Explore the content in this pathway to see the role of GIS in agriculture education. Understand the opportunities that GIS opens for students in the career cluster for agriculture, food, and natural resources.

Discover the booming market for satellite imaging in agriculture! Learn about its $4 billion valuation in 2025, 15% CAGR, key players, and regional trends impacting precision farming, crop monitoring, and yield optimization. Explore market forecasts to 2033 and investment opportunities.

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.