Chapter 16

Geographical Information Systems in Agriculture

Geospatial Data Acquisition

Geospatial data acquisition is the process of collecting spatial (location-based) information for use in Geographic Information Systems (GIS). This data can describe natural features, human-made structures, or environmental conditions and is foundational to any GIS project.

Categories of Geographic Data Acquisition

In GIS, data sources are categorized as either primary or secondary. Primary data is collected directly for a specific GIS project, such as GPS data, remote sensing images, or field surveys. Secondary data, on the other hand, is data that was originally collected for another purpose and needs to be adapted for GIS use, like census data, existing maps, or online databases.

Primary Data Sources

Primary data sources in GIS are those from which data is directly collected and generated, often used specifically for GIS purposes. Examples include field surveys, GPS measurements, remote sensing data (like satellite imagery), and data from digital aerial photography. These sources are considered "first-hand" because they are collected directly for the intended GIS analysis. Remotely sensed data offers the advantage of obviating the need for physical access to the area being imaged.

Secondary Data Sources

Obtaining spatial data by direct spatial data capture is not always feasible. In contrast to the direct methods of data capture, spatial data can also be sourced indirectly. This type of data is known as secondary data. Geospatial data providers are organizations that collect, process, and/or distribute different types of location-based data in digital format. In the United States, many federal, state, regional, and local government agencies have set up websites for distributing GIS data.

Geospatial Data Acquisition Methods

Remote Sensing

Remote sensing is a powerful geospatial data acquisition method that involves collecting information about the Earth's surface from a distance using sensors on satellites, aircraft, or drones. It measures the electromagnetic radiation emitted or reflected from the surface to identify and monitor physical attributes. This data is used in GIS to analyze, visualize, and manage spatial phenomena over large or inaccessible areas (Table 16.1).

Field Surveys / Ground-Based Collection

Field surveys or ground-based data collection involve direct measurement and observation of features on the Earth’s surface. This method is essential for high-accuracy, site-specific, and real-time geospatial data collection, especially where remote sensing lacks detail or verification is needed (Table 16.2).

Geospatial Databases and Portals

Geospatial databases and data portals are essential sources for acquiring existing spatial data for use in GIS. These platforms host pre-collected, curated, and often standardized geospatial datasets from government agencies, research institutions, and international organizations. They are vital for saving time and ensuring reliable data for mapping, analysis, and decision-making (Table16.3).

Crowdsourcing / VGI (Volunteered Geographic Information)

Crowdsourcing is a data collection method whereby users contribute freely to building spatial databases. This rapidly expanding methodology is utilized in such applications as TomTom’s MapShare application, Google Earth, Bing Maps, and ArcGIS (Table 16.4).

Types of GIS Data

GIS (Geographic Information System) data represents real-world features and phenomena, combining spatial data (location-based) with attribute data (descriptive information). GIS data is broadly classified into two main types:

Spatial Data (Geospatial Data)

Vector Data. Vector data is the most common type of data loaded into GIS software and represents data in the form of points, lines, and polygons. Points are zero-dimensional objects that contain only a single coordinate pair. Points are typically used to model singular, discrete features such as crop distribution, soil types, or pest locations. Points have only the property of location. Lines are one-dimensional features composed of multiple, explicitly connected points. Lines are used to represent linear features such as irrigation lines, field boundaries, drainage ditches, roads, and other linear features.
Raster Data. The raster data consists of rows and columns of equally sized pixels interconnected to form a planar surface. These pixels are used as building blocks for creating points, lines, areas, networks, and surfaces. In raster data, points are represented by a single pixel, lines are a chain of connected pixels with the same value, and polygons are groups of contiguous pixels with the same value, effectively creating a filled area to represent a feature. Unlike vector data, where precise coordinates define points, lines, and polygons, raster data uses a grid of cells to represent spatial information, with each cell holding a single value.

Types of Geospatial Formats

Geospatial data is created, shared, and stored in many different formats. GIS data formats determine how spatial and attribute information is stored, shared, and processed. These formats fall into categories based on the type of data they represent: vector, raster, attribute, or web service (Table 16.5). Vector data is represented as either points, lines, or polygons. Discrete (or thematic) data is best represented as a vector. Data that has an exact location or hard boundaries is typically shown as vector data. It's essential for precision farming, land use planning, field monitoring, and resource management. By contrast, raster data is best suited for continuous data, or information that does not have hard boundaries or locations.

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