[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.

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.

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

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.

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.

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 provided data (the Data) represent a raster map of agricultural profit at full equity (PFE) for Australia for the year 2005/06. Values of PFE are provided in ($/ha). PFE is a measure of profit which is calculated as the revenue from the sale of agricultural commodities minus all fixed and variable costs. This concept is based on the assumption that the land is fully owned (100% equity). The unit of PFE is $/ha. The Data are provided as a raster dataset that is compatible with ArcGIS. The spatial resolution is ~ 1km. Values provided are not for individual commodities (e.g. wheat, barley etc.) but for a set of commodity classes known as SPREAD classes (e.g. winter cereals, winter oilseeds) and broad land use categories (grazing, natural pastures etc.). The Data do not provide information with regards to the associated land use. To link values of PFE to the associated land use (SPREAD class) the Data need to be linked to the land use map of the year 2005/06 (Source: ABARE–BRS 2010. Land Use of Australia, Version 4, 2005-06 dataset).

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.

This data set consists of a digital map of the extent of fields and a summary of the irrigated acreage for the period between January 2019 and February 2021 compiled for Broward and Miami-Dade Counties, Florida. Attributes for each field include a general or specific crop type, irrigation system, and primary water source for irrigation.

The GIS shapefile and summary tables provide irrigated agricultural land-use for Hendry and Palm Beach 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 Hendry and Palm Beach Counties, Florida. A map image of the shapefile is provided in the attachment.

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.

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.

A shapefile of the extent of irrigated agricultural fields which includes an attribute table of the irrigated acreage for the period between January and December 2020 was compiled for Lake, Marion, and Orange Counties, Florida. Attributes for each polygon that represents a field include a general or specific crop type, irrigation system, and primary water source for irrigation.

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

These GIS files represent geographic boundaries for lands that are under the protection of NYS Agricultural District Law, administered by the New York State Department of Agriculture and Markets. The boundaries are derived from New York State Agricultural District, 1:24,000-scale, maps produced at county agencies. The district boundaries correspond to tax parcel data. District boundaries are joined into a file representing all of the Agricultural Districts within an entire county. Tax parcel detail is not included in this dataset. Road and utility rights-of-way are only included when they are delineated on the original 1:24,000 scale maps. Please note that boundaries may be generalizations; precise information can be obtained from the county or town tax parcel information.View Dataset on the Gateway

The GIS software market in Agriculture in Latin America was estimated at around *** million U.S. dollars in 2018, and was forecast to surpass *** million dollars in 2019. In the latter year, Brazil was expected to account for nearly ********* of this market, with a value of **** million dollars. Meanwhile, Argentina's market was forecast at **** million dollars in 2019.

Data represents the geographic boundaries of lands under the protection of NYS Agricultural District Law, as administered by the New York State Department of Agriculture and Markets. This layer includes lands included in Agricultural Districts #1 (Berne and Knox), #2 (Rensselaerville and Westerlo), and #3 (all other municipalities) in Albany County, NY.Note, last update 2-2025 for district 2.

The GIS Software in Agriculture market size reached USD 4.04 Billion in 2020 and revenue is forecasted to reach USD 10.54 Billion in 2028 registering a CAGR of 12.8%. Geographic information system software in agriculture industry report classifies global market by share, trend, growth and based on d...

The Agriculture Places in Montgomery County dataset contains boundary information and attributes for agricultural places such as farms, fields, and vineyards within Montgomery County, Texas, sourced from Montgomery County IT-GIS. These areas are designated for agricultural activities and contribute to the county's rural landscape and economy. This filtered view includes polygon features representing agricultural areas and may include additional attributes describing the type and size of agricultural operations.Places Included:FarmsFieldsVineyardsThis dataset is sourced from the Montgomery County IT-GIS and is updated as needed.