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Agriculture and GIS

Filed in GIS in Use by Caitlin Dempsey on July 3, 2012 • 2 Comments

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Geospatial technology plays a significant role in many aspects of precision farming (click on image for a larger view).Geospatial Technologies in Precision Agriculture New Plant Hardiness Zone MapNew Plant Hardiness Zone Map

GIS technology has become a vital tool for crop management.  Geographic data about soil condition helps farmers to be more efficient in segmenting arable land in order to apply differential rates of fertilizer, and forecasting to determine when, where, and what to plant in what is known as precision agriculture.  Satellite and aerial imagery is used to analyze existing conditions of the land, soil samples taken from the fields are used to create a more precise understanding of the condition of a farm.  By understanding the condition of the land on a micro scale, farmers and those in the agriculture field can better manage fertilizer and water application, resulting in reduced costs and better crop yields.

More detail about the use of geospatial technologies in precision farming can be found in the article by Peter Rodericks Oisebe entitled “Geospatial Technologies in Precision Agriculture.”

Remote Sensing Organic Crops

The variations in crops grown organically versus conventionally are significant enough to be detected by analysis on satellite imagery.  The European Space Agency  (ESA) has been working with Ecocert, an organic certification organization, as well as consulting firms Keyobs and VISTA, and Belgium’s University of Liège, to develop a methodology to analyze satellite imagery to differentiate crop fields based on whether the crops were grown via organic or conventional methods.

ESA analyzed multi- and hyperspectral imagery from five different satellites, SPOT-4, Kompsat-2, Landsat-5, Proba, and WorldView-2 as part of the study.  Using indicators that included crop spectral reflectance, yield forecasts and spatial heterogeneity, ESA was able to predict with an average accuracy of 90% which crops were grown organically versus conventionally.  Dr Pierre Ott from Ecocert, concluded,  “Accuracy rates of 80% to 100% in discriminating organic from conventional fields are a performance in itself. It seems very promising as far as the potential of future developments is concerned.”

Efforts are ongoing to further refine this methodology so that it can be commercially utilized.

Cornfield classification determinations using a WorldView-2 satellite image acquired on August 10, 2010. The fields in light green are classified as organic (KMO) and the ones shaded dark green are classified as conventional (KM). An accuracy of +90% was obtained on the classification between organic and conventional.   Credits: VISTA

Cornfield classification determinations using a WorldView-2 satellite image acquired on August 10, 2010. The fields in light green are classified as organic (KMO) and the ones shaded dark green are classified as conventional (KM). An accuracy of +90% was obtained on the classification between organic and conventional. Credits: VISTA

 

Resources on the use of GIS in Agriculture.

Access to articles, case studies and user groups in agricultural GIS.

Plant Hardiness Zone Map
Showing zones of plant hardiness by the U.S. Department of Agriculture (USDA).

GIS and Agribusiness
ESRI’s web page on agriculture. Articles and support for utilizing GIS in this field.

GIS Agriculture Models
Research article on “Potential for Integrated GIS-Agriculture Models for Precision Farming Systems”.

MapShots
Web site for the EASI suite of software with a focus on data management for agriculture. Find information about this software including conferences and trainings.

Books

GIS Applications in Agriculture – by Francis J. Pierce (Editor), David Clay (Editor)

GIS in Site-Specific Agriculture – by James D. Westervelt (Author), Harold F. Reetz (Author)

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  • Geospatial Technologies in Precision AgricultureGeospatial Technologies in Precision Agriculture
  • Using Remote Sensing to Measure Land DeformationUsing Remote Sensing to Measure Land Deformation
  • Monitoring Driver Fatigue from SpaceMonitoring Driver Fatigue from Space
  • Detecting Surface Change and Avalanche MappingDetecting Surface Change and Avalanche Mapping


Tags: agriculture, case studies, esa, ESRI, gis, organic crops, presentations, remote sensing



Comments (2)

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  1. Zach says:
    February 12, 2009 at 4:48 pm

    GIS and agriculture articles are hard to find! Interesting article out of Idaho where they use GIS maps to measure water use by farms.

    Reply
  2. Martin Schaffranek says:
    October 10, 2012 at 11:43 am

    I have agricultural education and experience. I am in the process of getting my certification in Agronomy. I am VERY interested in using G.I.S. in Agriculture. Please keep me posted on new applications in this area, Thankyou. Martin Schaffranek

    Reply

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