Application of GIS in Agriculture

Information management plays an important role in improving farming practices and consequently increase agricultural production. In-fact, the practice of agriculture is spatial in nature. The biological and physical aspects of agriculture create spatial variability. Owing to this variability, the  occurrence and distribution of insects along with plant pathogens and diseases that result in decreased crop yield is random. Another word used to describe this variability is, 'patchiness'. Plant disease management practices can be improved by putting epidemiological information and other farm information using a GIS.
Precision farming is based on combining GIS with sophiticated hardware for geographically referenced yield data and variable rate applications of fertilizers and other farm chemicals.
Spatially referenced information provides a gateway to farmers, pest control advisors, extension workers and others to evaluate plant disease problems in a spatial context
GIS relates the data collected by GPS to other sources of geo-referenced information. GIS posseses the ability to integrate layers of spatial information and uncover relationships that were otherwise not obvious.
The process of transforming one layer of spatial information to match a second layer is called registration.
GIS has been applied in agriculture for the spatial analysis of insect pests, weeds and plant diseases.
Since the field of agriculture is primarily spatial in nature, GIS is the appropriate technology to manage the related spatial data.
However, analysis using GIS should be invariably compared with conclusions from a general knowledge of the problem and recheck the methodology and data if there is a major variation with what is generally expected.
GIS risk assessment maps based on a gaussian process regression of field observations were part of a tomato virus management program at the regional scale in Mexico.
Soil structure and chemistry information is linked to a point theme that is displayed as an overlay with field boundaries (polygon features) and roads (line features). The points are colour coded according to the percent total sand in soil. Using GIS, the data can be linked to points using a coordinate system. The 'x' and 'y' coordinates of a point are determined using GPS readings. These points are overlaid on similarly referenced linear and polygon features.
The availability of GIS software, capable of producing attractive maps provides an opportunity to visually communicate plant disease situation to a variety of audiences. GIS output can be used by decision makers to stimulate coordinated action allowing available resources to be focussed on the most significant problems.
GIS is particularly useful in identifying recurring patterns of plant disease and other problems like insect and weed infestations.
The association of environmental factors, landscape features and cropping patterns combined with the recurrence of disease or other problems can be readily communicated to decision makers.

GIS can be used as an agricultural land use planning tool. If soil information is linked from an aerial photograph to a topographic base map and this is added to several other data layers and images like interpretation maps, flood frequency maps and run-off maps, the soil-based GIS would make the decision-making process more accurate, automated and efficient. GIS allows visualization of information in new ways that reveal relationships, patterns and trends not visible easily.
Geographic Information Systems have become an essential and efficient toolkit in all aspects of agriculture from farm management and resource conservation to a wide range of agribusiness applications.
Precision farming is an integrated agricultural management system that incorporates state-of-the-art agronomic knowledge, information from multiple sources, and the global positioning system, geographical information system, yield monitor, variable rate, and remote sensing technologies.

Precision farming allows producers to make management decisions about discrete areas of the field, with the goal of optimizing the crop response based on the production potential and constraints of the specific region. These techniques help in providing good quality land for future generations while preserving the land’s potential for multiple uses, and implement techniques that increase agricultural energy efficiency.
Precision farming can be used to improve fertilizer, seeding, and irrigation rates as well as improved targeting of insecticides and herbicides toward pests. Precision farming techniques are used for improving agricultural efficiency through improved nutrient management. Efficient nutrient use can be improved by adjusting application rates using GIS based precision estimates of crop needs. GIS can be customised to enter soil data and create yield maps. This can be used to  generate fertilizer prescription maps and related reports for site-specific management. GIS is bieng used extensively around the globe as a tool that helps in increased agricultural yield. The spatial analytical tools related to agriculture in GIS are, hydrology parameters, groundwater and data interpolation calculation tools. These tools can be used to adopt efficient sampling strategies and increase profitability. Grid sampling (GIS tool) can be used to reveal soil fertility patterns in farm fields. A latest development in this regard is the Web Soil Survey  (WSS), an interactive online interface providing user defined reports and GIS ready spatial data. Managing data in a GIS ultimately produces a map that helps in visualization of the data.

Precision manure application using GIS and GPS helps farmers to avoid overlapping or missing application areas. GIS also helps in avoiding application of manure in environmentally sensitive areas, turning the applicator off when stepping out of the boundary area and varying the application rate based on projected crop nutrient needs at different locations across fields. The value of manure as a crop input is diminished by improper application. While lack of application of manure causes nutrient deficiency resulting in reduced crop yields, excessive application of manure also results in low crop yield due to excess vegetative growth resulting in increased crop diseases. Geospatial technologies (GIS, Remote Sensing and GPS) can help in implementation of efficient manure management practices like,

1. determining optimum amount of manure to apply at specific locations in fields for specific crops and yield goals, 
2. applying prescribed rates and 
3. when and where manure was applied.

GIS has been used as a decision support tool for a soil-based automated variable rate irrigation sprinkler system. GIS has also been used for soil salinity mapping. GIS can be used to create Soil Organic Carbon (SOC) maps. Thus, site-specific management and assessment would be very difficult if not impossible without GIS mapping and tools. GIS tools can be used to improve distribution of manure nutrients at the national, local and field scales as a means to minimise environmental contamination. GIS plays an important role in managing nutrient imbalances. GIS can be used in conjunction with modelling to understand how crop selection and soils interact to effect environmental outcomes across an agricultural landscape. For example:

1. a public drinking water supply faced with increasing nitrate in groundwater source and
2. planning of a new biomas conversion facility to produce renewable fuels from grain or cellulosic feedstock. 

In the above cases GIS can be used to help the audience gain new understanding of the problems and visualise how to circumvent the problem by growing different crops. In the first case, a soil map can be used to extract soil characteristics and individual polygons of GIS coverages are used to produce final map products depicting areas of high, moderate and low nitrate leaching risks.