**5.1 Geospatial applications**

The term "geospatial technologies" is used to describe the range of tools to produce geographic mapping and analysis of the Earth's surface and human activities. Different types of geospatial technologies include remote sensing, GIS, GNSS, and Internet mapping technologies. GIS can assemble geospatial data that include information on its precise location on the Earth's surface, also called geo-referenced, into a layered set of maps. GIS is a suite of software tools, which enables mapping and analyzing these geospatial data. The use of automated field machinery to accomplish crop production field operations is inevitable for modern

## *Precision Agriculture for Sustainable Soil and Crop Management DOI: http://dx.doi.org/10.5772/intechopen.101759*

agriculture [75]. These machines can be operated with the help of GIS and GNSS along an optimal path to perform field works precisely as per the positioning information provided to it. The success of geospatial technology depends on the collection of accurate data and their proper analyses and interpretations. Remote sensing technology is used to collect imagery and data on Earth's surfaces and human activities. It shows detailed images at a resolution of 1 meter or less area, and helps monitor and address the problems and needs. Software programs such as Google Earth and web features, such as Microsoft Virtual Earth, facilitate changing the way the geospatial data are viewed and shared.

In PA, remote sensing technology facilitates dividing of large fields into smaller management zones [76]. Each zone aggregates specific crop management needs and production limitations. GIS and GNSS are central to the PA technologies for dividing cropland into small management zones. These divisions are accomplished mainly based on a) soil characteristics such as soil types, soil pH, soil EC, soil MC, nutrient availability, and soil compaction; b) crop characteristics such as i) crop canopy and density, insect and disease infestations, fertility requirements, hybrid responses, crop stress; and c) weather predictions. Observation made using remote sensing technology are geo-referenced within a GIS database. Therefore, much of PA relies on remote sensing imagery data, for example, to determine the chlorophyll content of plants as it relates to growth, yield, and productivity of different management zones [77]. A brief illustration of the GIS data-based soil map is shown in **Figure 4**. Datasets are recorded using remote sensing imagery data and can easily be converted into spatial data using GIS techniques and tools such as the "Kriging method" [77]. GIS software is used to develop digital maps that transform spatial information into digital format. These spatial data reflect and delineate all management zones within the farm.
