GIS in Agriculture
Anne Mims Adrian, Auburn University, USA
Chris Dillard, Auburn University, USA
Paul Mask, Auburn University, USA
Abstract
This chapter introduces the use of geographic information systems (GIS) and global positioning systems (GPS) in agricultural production. Precision agriculture is a catch-all term that describes using GIS and GPS technologies to manage specific areas of fields. Precision agriculture technologies use information from multiple sources to assist farmers in making crop production and management decisions based on the variability of production potential within fields. In this chapter, we describe the technologies used in production agriculture and we review some of the research associated with the use and future trends of these technologies. The purpose of this chapter is to define and explain GIS and GPS technologies used in agriculture and some of the economic benefits, impacts, and challenges of using these technologies.
Introduction
Farmers have long known variation existed within their fields, but did not have the tools to properly quantify, view and manage that variation. Geographic information systems (GIS), along with global positioning system (GPS) enabled technologies, have given farmers the ability to make management decisions with more precision and information
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than ever before. Fields no longer have to be managed on an across-the-board basis, but rather fields can be managed on the production potential of each area of the field.
Agricultural crop production can be limited by soil chemical or physical characteristics, topography, crop variety, or a number of other variables. GIS allows farmers to determine where deficiencies exist, search for the cause of the deficiencies, and make management decisions necessary to improve productivity in the problem areas. With GIS and GPS systems, farmers can have access to a tremendous amount of information on yield variation, soil properties, topography, water absorption, plant health during the growing season, and records of chemical use.
The catch-all term, precision agriculture, means to use GIS and GPS technologies that allow farmers to manage specific areas of fields. GIS serves as one component of decision support systems (Grupe, 1990), which lends itself to the working definition of precision agriculture that is published by the National Research Council (National Research Center, 1997) as, “a management strategy that uses information technology to bring data from multiple sources to bear on decisions associated with crop production.” Farmers see that their production is being squeezed with higher input costs and tougher international competition and some have considered adopting precision agriculture as a way to lower production costs, protect the environment, and to manage large farms (Olson, 1998).
Precision agriculture tools are used to monitor crop yields, apply inputs at a variable, rather than constant rate, and to guide equipment. Other tools are used to determine soil electrical conductivity, manage soil on a site-specific basis, and to monitor crop growth and health from satellite or aerial images. All of these tools utilize GIS to acquire, process, analyze, and transform the data collected into information that farmers can use to better manage production and improve profitability. The incorporation of precision agriculture tools began in the mid 1980s (NRC, 1997) and the initial adoption has been slow (Swinton
& Lowenberg-DeBoer, 1998). While economic benefit is the deciding factor for sustained use of a precision agriculture technology, other reasons, such as attitudes toward technology, may possibly affect adoption (Cochrane, 1993). Although the research on the economic benefits is mixed, (Malcolm, 1996; Sawyer, 1994, Swinton & Lowenberg- DeBoer, 1998), farmers are primarily investing in them sequentially (Isik, Khanna, &
Winter-Nelson, 2000; Dillon, 2002).
The purpose of this chapter is to define and explain the technologies used in precision agriculture, to explain some of the economic benefits, the impacts of producers’
decisions, the challenges of using these technologies, and to review some of the precision agriculture technology research. Benefits of precision agriculture technology include: reduced variable costs, increased yields, increased profits, and reduced envi- ronmental effects (Intarapapong, Hite, & Hudson, 2002; Sawyer, 1994). Increased yields result from increasing inputs in more productive areas of managed fields, thereby increasing yields. Sometimes fewer inputs are applied in areas of the field that have lower yield potential, which reduces variable costs (Intarapapong et al., 2002). Fewer environ- mental effects are possible because of the more precise application of inputs (Kitchen, Hughes, Sudduth, & Birrell, 1995; Intarapapong et al., 2002; Sawyer, 1994). However, farmers cannot vary the input until they have the information that shows how yields or soil properties, such as pH levels, vary across the fields.
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Generally, the first precision agricultural tools farmers implement are yield monitors or grid soil sampling. They learn the GIS and equipment technologies, gather data, and begin to make production decisions that may not require variable aspects of the field, such as changing cropping sequence. Additionally, information is obtained by targeted soil sampling to gather nutrient and physical characteristics of the soil.
Agriculture has always been a driving force in the growth of the United States and its economy. The agriculture sector contributes over $200 billion annually to the U.S.
economy and employs almost one million workers (U.S. Census Bureau, 2002). Global- ization of trade, decreased commodity prices and reduction in farm subsidies increase the importance for farmers to utilize their resources as efficiently as possible. GIS and GPS technologies provide farmers with techniques to help maximize production and efficiency and increase the information available to make sound business decisions. Precision agriculture technologies are provided by farm equipment manufacturers, agrochemical companies, pharmaceutical/biotech companies, data management firms, and high-tech Pentagon and intelligence community contractors (Marrero, 2003). We will describe many of these techniques and their economic benefits, the impact of the additional information on the producers’ decisions, and some of the challenges that producers face with the new technologies.
GIS-Enabled Precision Agriculture Tools
Yield Monitors
Yield monitors serve as information gathering tools and decision support systems for the precision agriculture practitioner. The information gathered by yield monitors serves as the basis for many production and management decisions. Examples of these are determining management zones, selecting crop varieties, and applying inputs such as fertilizer or nitrogen. Creating zones within fields of different yield productivity levels is one of the primary techniques for managing fields on a site-specific basis. The delineation of yield zones based on yield variances would not be possible without GIS analytical tools.
Farmers have always known that variability existed within their fields, but had no way to quantify that variability until the advent of the yield monitor. Yield monitors are devices installed on crop harvesting equipment, such as a combine or cotton picker. Yield monitors use GPS, GIS, computer, and sensor technologies to accurately measure the amount of crop harvested at a specific location and time. In addition to measuring yield, monitors allow for the recording of crop moisture, elevation, variety, and a number of other harvest variables. It is estimated that 48 million of the 160 million acres of corn and soybean harvested in the United States in 2000 were harvested with a yield monitor- equipped combine (Lems et al., 2003).
Yield monitors are used on a variety of crops including corn, wheat, soybeans, sugar beets, potatoes, and cotton. Yield monitors utilize sensors to measure the crops’ mass
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or volume and are found to be accurate to +/- 3% of actual harvested amount, but require routine calibration to maintain accuracy (Lems et al., 2003). The mass or volume measurements are recorded in the on-board computer along with harvester travel speed, crop moisture, and harvester width to produce once per second indirect yield measure- ments. GPS provides the field location for each measurement. The location and yield data are recorded onto a storage card and transferred to a desktop GIS for processing, viewing, and analysis.
Yield monitors provide a large amount of valuable data while harvesting, but they do not provide critical decision-making information until the data are processed in a GIS. The data gathered from yield monitors are transformed with GIS into the information required for subsequent management decisions, such as management zone creation, variable rate application, and targeted soil sampling. The management zones delineated in a GIS are used to manage the fields according to variation. Each zone may be sampled for deficiencies in order to manage them in a targeted manner, rather than applying inputs in a uniform application. The separately managed zones allow farmers to accurately diagnose problems, and compare management records on a year-to-year basis. Farmers are able to use their GIS to produce detailed harvest reports, determine trends from harvest to harvest, and compare the production capabilities of different varieties and crop inputs. When properly implemented, yield monitors and GIS serve as valuable accounting, record keeping, and decision support tools for farmers.
Targeted Soil Sampling
The ability of farmers to produce high yielding crops is heavily dependent upon the soil in which the crops are grown. The soil type and its physical and chemical characteristics must be in proper balance in order to maximize production potential, and ultimately, return on investment. The more farmers know about the environment in which they are operating the more knowledge they have to make prudent business management decisions that will increase profitability and reduce adverse environmental impacts.
Until the industrialization and mechanization of farming occurred, farmers worked fields of relatively small size (Morgan & Ess, 1997). In the early 1900s, farmers were intimately familiar with each field and were able to manage each in a uniform manner. The advent of the tractor changed the farm structure dramatically by allowing farmers to farm larger fields and more acres. The small fields were primarily uniform in their soil properties, whereas the larger fields could contain significant variability. While mechanization allowed farmers greater efficiencies in production, it prevented them from managing the variability found within the larger fields. Today, more detailed information about the soil properties gives farmers the knowledge to make management decisions with more accuracy and economy. GIS is an integral part of the targeted soil sampling management technique.
Targeted soil sampling consists of two primary methods, grid and zone sampling. In each method GIS software is used in conjunction with GPS to create a boundary of a field and break down the areas within the boundary into individual segments for study. The field boundary and zones, or grids, are viewable on laptops or handheld computers and are
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used to assist farmers in navigating to the sampling site. Grids are normally square in shape and range in size from one-half to two and one-half acres. The smaller grid sizes provide a more detailed view of the field, but result in increased sampling costs. Larger grids require fewer samples, and hence less costs, but they do not provide as detailed a view. Zones are generally not uniform in shape, or size, and can be based on Natural Resource Conservation Service (NRCS) soil maps, areas of similar yield production, or any variable farmers are interested in using for delineation.
GIS provides the capability to collect and view soil sampling data, but its impact on economic return comes from its ability to reveal field deficiencies and correct those deficiencies in the most environmentally friendly and economic fashion. The benefits of utilizing GIS in targeted soil sampling are reduced costs by decreasing inputs and increased profits through maximized productivity.
Targeted soil sampling utilizing GIS is a valuable information gathering tool for making better business management decisions. Regardless of the technique employed, the result is a better understanding of the soil being used for crop production, and more information available for deciding how to manage farm resources. GIS allows farmers to gather the information that will help them increase productivity, lessen environmental impact, and increase profits.
Variable Rate Application
The high costs of pesticides, herbicides, fertilizer, and labor make it important to utilize such inputs as accurately and efficiently as possible. Farmers have traditionally taken a blanket approach to inputs by applying chemicals or nutrients at a constant rate across a field. Labor costs are greatly reduced, and the impact of inputs is maximized, by using machinery that efficiently and evenly applies product. The problem with the uniform approach is that not all areas within a field require deficiency correction, herbicide treatment, or pesticides at the same rate. Some areas of a field may require heavy treatments, while others require none at all. The purpose of variable rate application (VRA) is to utilize the information collected about a field to only apply inputs where necessary. Applying inputs at a variable, rather than constant rate reduces input and labor costs, maximizes productivity, and reduces the impact over-application may have on the environment.
Before inputs can be applied at a variable rate, farmers must determine what the application will be based upon. For example, nitrogen application decisions are generally based on the average yield from previous years. Fertilizer and lime application decisions are based on the information gathered from targeted soil sampling. Additionally, farmers may use aerial imagery or NRCS soil maps to break the field into management zones and treat the areas individually. Another option for farmers is to apply inputs based on soil physical properties as determined by NRCS soil maps. Regardless of the input being applied, VRA is dependent upon a GIS for data analysis and application map creation.
All of the data by which application maps will be created will reside initially in the GIS.
Farmers can optimize resources and avoid damaging the soil and environment by only applying inputs at the rates that will maximize the productivity of each area. The idea is
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not to maximize the inputs for each plant, but to create small areas of similar productivity that can be managed on a site-specific basis. GIS gives farmers the ability to create the areas of similar treatment based on prior field productivity. By creating management zones of low, medium, and high productivity, farmers can create application maps that integrate with the application equipment on-board GIS and controller unit. As mentioned earlier, it is important for farmers to adhere to sound agronomic principles when developing VRA maps. Applying inputs at a variable rate will only maximize productivity if the individual areas receive the proper amount of input.
Given the high cost of inputs, such as pesticides and fertilizer, it is extremely important for farmers to utilize them as effectively and efficiently as possible to maximize the return on investment. GIS can help farmers determine if VRA is economically and agronomically feasible for their situation and it gives them the tools to incorporate it into their business operations. VRA requires a certain level of expertise and investment of both time and money, but the reward can be a maximization of return on investment, increased productivity, reduced labor costs, and a reduced environmental impact from over- application. Introducing technological solutions without basing them in sound agro- nomic principles will only exacerbate the existing field deficiencies and not maximize return on investment.
Equipment Guidance
Whether farmers are planting, applying inputs, or harvesting, it is important to operate the machinery in the most efficient manner possible. Labor, fuel and input costs, and potential for breakdown increase if the machinery is operating more than necessary.
Overlapping areas of the field or skipping areas will result in over-application or under- application of inputs such as herbicides and pesticides. Over-application can result in damage to the crop and environment, and under-application will result in the input not achieving the desired crop effect. Equipment guidance and VRA are similar in that they both serve to maximize the return on investment of equipment, inputs, and labor.
Equipment guidance systems can be placed on any type of agricultural machinery that would benefit farmers to drive in a more concise pattern. Equipment operators have traditionally relied on visual cues such as a point on the horizon, a marking system consisting of foam emitters that mark the applied areas, tire tracks, or by counting over a certain number of rows to begin the next application pass. These methods work, but most lack the accuracy needed to avoid skips and overlaps, and they do not work in low- light conditions. Equipment guidance technologies serve to eliminate these problems by integrating GIS, GPS, on-board computing, and direction indicator devices to keep the machinery traveling in the most efficient manner across a field.
Reducing overlaps and skips are two primary economic benefits equipment guidance gives farmers. The high cost of chemicals, fertilizers, and labor make it essential to apply these items in the most economic and time-efficient manner possible. The equipment operators’ time is best utilized if they are applying the product in question without overlapping. Eliminating overlaps also reduces the amount of time the machinery is running, resulting in lower fuel consumption and hours of operation. Guidance systems
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also extend business operating hours for farmers by giving them the ability to operate equipment and perform applications at night. Traditional guidance methods are only viable options during daylight hours.
The equipment guidance system that is the easiest and least expensive for farmers to adopt is the lightbar. The lightbar consists of a GPS antenna, on-board computer with built-in GIS, and a directional indicator device (lightbar) that provides navigational information to the operator. Lightbar is a generic term for a device that provides the equipment operator with navigation cues. Navigation cues are based on guidance information received from the GPS and on the desired driving pattern the operator enters into the on-board GIS. In addition to directional cues, lightbars may also display information to the operator such as speed, heading, number of pass, and warning signals to notify the operator that the machinery is traveling through an area that has already been covered.
The auto-steer systems work along the same principle as lightbar systems, but they actually steer the machinery instead of the equipment operator. Auto-steer systems utilize a real-time kinematic form of GPS that incorporates a base station located on the farm in a known location that sends GPS data that is accurate to the centimeter-level to the mobile antenna located on the equipment. The lightbar will guide the operator within a meter of the desired pass location, while the auto-steer will guide the equipment within two inches of the desired location. Auto-steer systems are much more expensive to adopt than lightbars, but they allow farmers to hire a less skilled seasonal driver, plant fields at the optimum spacing, reduce soil compaction, and record elevation data to the GIS for use in irrigation system layout. An auto-steer system has the capability to help farmers maximize return on investment in any area of operations where precise equipment use is important.
Equipment guidance is a viable agricultural business tool for farmers to implement.
Integration with a desktop GIS allows farmers to track what inputs were applied, and exactly where those inputs were placed. The GIS-enabled lightbar and auto-steer systems maximize land utilization through precise row placement, and expand the hours of operation for expensive equipment. Labor costs are reduced by eliminating the need for an experienced driver, and the driver is able to perform at a higher level because of navigation assistance and reduction in fatigue. The problems inherent with over- application or under-application of inputs are also reduced because they are only applied where they are needed, and in the amount required. The reduction in land compaction, combined with the other equipment guidance benefits, helps farmers reduce environmen- tal impact, efficiently utilize inputs, and ultimately maximize return on investment.
Remote Sensing
Remote sensing, like yield monitoring and targeted soil sampling, is an information gathering tool. Bird’s eye views of farmers’ fields provided by airborne sensors give farmers unique field perspectives. Aerial photographs have been available to farmers for many years, but they did not have the ability to capitalize on this business tool until the development of GIS. Integrating remotely sensed data into a GIS can reveal information