What is Land Use Data? Examples, Datasets and Providers
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
- Overview
- Datasets
- Providers
- Use Cases
- Attributes
- Guide
- FAQ
What is Land Use Data?
Land use data refers to information that describes how land is utilized or allocated for various purposes, such as residential, commercial, agricultural, industrial, or natural areas. It provides insights into the spatial distribution and patterns of land use activities within a specific region or area. This data helps in understanding the extent and intensity of human activities on the land, facilitating urban planning, environmental management, and decision-making processes.
What Are Examples of Land Use Data?
Examples of land use data include datasets offering insights into how land is designated and used. Key examples include:
- Residential Land Use: Areas allocated for housing, apartments, and living spaces.
- Commercial and Industrial Zones: Land used for businesses, offices, factories, and warehouses.
- Agricultural Areas: Farmland, orchards, and grazing land for livestock.
- Protected Lands: Parks, reserves, and conservation zones for environmental protection.
- Mixed-Use Developments: Areas combining residential, commercial, and recreational uses.
Best Land Use Databases & Datasets
The best land use datasets provide detailed zoning, agricultural, and conservation information to support urban planning and resource management. This curated list features the top land use datasets, selected for precision, quality, and trusted providers.
BatchService - Core Property Data + Land Use Data - 155M+ Properties and 240+ Data Points
U.S. National Land Parcel Data | 190M+ Land Parcel Records | 100+ Property Characteristics | Land Use & Boundary Data
Construction Data | Construction Projects Lead Data | USA | Land Use and Company | Contractor Lists
Land Cover & Urban Planning Data | Satellite Data: Land Use, Real Estate, Construction, Flooding Risk & Management, Infrastructure
Geospatial Data | Land Data | Location Data | Property Data | Parcel Data
US Permit and Construction Records | National Coverage | Bulk or Custom Pull | 330M Permits | 60M Properties | Residential & Commercial
Agriculture & Land Health Data | Satellite Data: Agriculture, Vegetation Data, Health Data, Land Productivity
Location Intelligence Data | 43M+ US Locations
B2B Marketing Data | Construction | 1.6M US Programmatic/Digital Audience Segments | B2B Marketing Data
B2B Leads Data on SaaS-platform | Access & Export Millions of Leads via Success.ai's SaaS-Platform - Unbeatable Price for Top-Quality Data
Can't find the data you're looking for?
Let data providers come to you by posting your request
Post your request
Top Land Use Data Providers & Companies
-
CrawlBee
CoverageUSAUK+247VI contacted CrawlBee's CEO, Ryan DeWitt through Datarade. Ryan is very flexible, friendly, and extremely helpful! he worked with me to get the mortgage data I need for my research project. The data is very thorough and accurate. I highly recommend CrawlBee as I truly had a very good experience!
-
Meteomatics
CoverageUSAUK+247Meteomatics weather API delivers fast, direct, simple access to an extensive range of global weather and environmental data. A single API endpoint to access weather and earth data covering the globe, from weather forecasts, observations. Plus Web Feature Services and Web Map Services -
The Warren Group
CoverageUSAThe Warren Group is the leading national provider of Real Estate Data including Mortgage Data, Loan Originator Data, Sales Data, Property Data & more.99%Coverage1872Year Founded1B+Property & Mortgage Records -
Latitudo 40
CoverageUSAUK+248Latitudo 40 offers seamless access to multi-temporal geospatial data, turning satellite imagery into actionable insights for global climate resilience. Through our AI-powered platform, we help cities, real estate, and infrastructure sectors assess risks like heat islands, floods, and land changes.Coverage100% GLOBALData> 10 years of historyAccuracy99% -
BatchService
CoverageUSADeepen the insights your platform or application offers by harnessing unparalleled property data and accurate owner contact information from a single API.74%Right Party Contact Rate600+Data Points900%Efficiency Improvement -
GIST
CoverageUSAUK+247VSveaskog, Sweden's largest forest owner, has worked with GIST Advisory to perform a full impact value assessment, Integrated Profit and Loss. This has helped us understand impact and added value from our company and operations, and put us in the forefront in Swedish forestry sector. It has provided us with a powerful tool for sustainability reporting, based on scientific references. GIST is very professional and supportive and it is a great joy to work with their team.
Popular Use Cases for Land Use Data
Land use data supports diverse applications across industries, enabling effective planning and analysis. Common use cases include:
- Urban Planning: Designing sustainable cities by analyzing land use patterns and planning infrastructure.
- Environmental Management: Monitoring the impact of land use changes on ecosystems and biodiversity.
- Real Estate Development: Identifying suitable locations for residential, commercial, and industrial projects.
- Agricultural Planning: Assessing farmland usage and optimizing crop selection and irrigation systems.
Main Attributes of Land Use Data
Below, we outline the most popular attributes associated with this type of data—features that data buyers are actively seeking to meet their needs.
| Attribute | Type | Description | Action |
|---|---|---|---|
| Float | The latitude of a point on earth's surface. Commonly abbreviated as "lat". | View 16 datasets | |
| String | The name of a city. | View 12 datasets | |
| String | The name of a company or business, might be the legal or brand name. | View 10 datasets | |
| String | The first name of a contact. | View 10 datasets | |
| String | The last name (surname) of a contact. | View 10 datasets | |
| String | The Zone Improvement Plan (ZIP) code of an address. | View 10 datasets |
Why Is Land Use Data Important?
Land use data plays a pivotal role in sustainable development and decision-making. It helps governments and businesses balance urbanization with environmental preservation.
For example, urban planners use zoning data to design cities that minimize congestion and promote efficient land use. Real estate developers leverage this data to identify high-potential areas for projects, while environmentalists monitor land use changes to mitigate ecological impacts.
Frequently Asked Questions
How Accurate is Land Use Data?
The accuracy depends on the collection methods. High-resolution satellite imagery combined with on-the-ground verification tends to offer the most precise results. If precision is critical—such as for zoning laws or environmental impact studies—we recommend choosing data sources known for their high accuracy and frequent updates.
How Frequently is Land Use Data Updated?
Update frequency varies. Some datasets are refreshed in real-time or monthly using the latest satellite imagery, while others might be updated annually. For projects that require the most current information, opting for data with frequent updates will keep you informed about recent changes in land use patterns.
How Much Does Land Use Data Cost?
Costs can vary widely based on coverage area, data resolution, and update frequency. Prices might range from affordable rates for small regions to higher fees for extensive, detailed datasets. We suggest starting with a free sample or a smaller dataset to ensure it meets your needs before investing in a larger purchase.
What Geographic Areas Are Covered by Land Use Data?
Coverage can range from local areas to global datasets, depending on the provider. Whether you need data for a specific city or multiple countries, there’s likely a dataset that fits your requirements.
How Can I Access Land Use Data?
Access methods include downloadable files in formats like .csv or .json, APIs for real-time integration, or cloud-based platforms with visualization tools. Depending on your needs, you might prefer an API for seamless integration into your systems or downloadable datasets for offline analysis.
