Reducing cost to livestock producers: Very large scale aerial (VLSA) imagery compared to traditional range field monitoring methods

Project Overview

Project Type: Graduate Student
Funds awarded in 2008: $9,870.00
Projected End Date: 12/31/2008
Grant Recipient: North Dakota State University
Region: North Central
State: North Dakota
Graduate Student:
Faculty Advisor:
Christopher Schauer
North Dakota State University


  • Additional Plants: native plants
  • Animals: bovine


  • Animal Production: grazing management, preventive practices
  • Farm Business Management: whole farm planning
  • Natural Resources/Environment: indicators
  • Sustainable Communities: sustainability measures


    One of the biggest challenges to rangeland monitoring is finding a cost and time effective method to monitor millions of acres. Traditionally, field monitoring methods have taken large amounts of time, skill, and labor. North Dakota State University was approached independently by three grazing associations (Grand River, McKenzie and Medora) that are comprised of members from Montana, North Dakota and South Dakota to conduct unbiased, third party range monitoring on the Dakota Prairie National Grasslands. We worked with the grazing associations and their associated Forest Service ranger districts to provide data collected both on-the-ground and by aerial imagery. This rancher-initiated project seeks to reduce the costs and time associated with range monitoring by using very large scale aerial (VLSA) imagery. This true color, digital photography has a ground sample distance (GSD) of ?1mm (similar to resolution). VLSA imagery will be analyzed for species composition, bare ground, and biomass production and compared to data collected on the ground. R2coefficients were determined to predict the accuracy of VLSA imagery compared to traditional field monitoring methods.


    Historically, rangeland monitoring has been accomplished by the use of trained rangeland professionals. Typically, measurements taken would reflect some measure of canopy cover, bare ground, production, and species composition. While the first three tasks can be successfully accomplished with a moderate amount of training, species composition requires an extensive knowledge of plant identification. Quality rangeland monitoring is extremely difficult over large tracts of land (Sanders 1999). The cost of labor has increased dramatically over the years. In a study by Pellent et al. (1999), the authors found that it cost $893 to sample a 0.16 ha (0.4 acre) plot. Current recommendations for monitoring sites on the Northern Great Plains prairie are five plots per half section (320 acres) as recommended by North Dakota State University (Sedivec pers. comm).
    For many years, range and other natural resource professionals have tried various means to acquire remotely sensed imagery. One of the more common methods to acquire imagery is by satellite. In recent years, technology has advanced giving the NASA Landsat satellites a resolution of 15 meters. Although 15 meter imagery works well in many systems, particularly at a landscape level, it proves too coarse for rhizomatous grasslands ecosystems (Muldavin et al. 2001). Private companies such as GeoEye’s IKONOS Quickbird, the European SPOT system, and others have capitalized on the fine resolution image market with imagery nearing the 1 meter mark. Other creative works have been experimented using media such as blimps (Murden and Reisenhoover 2000), radio controlled airplanes (Thome and Thome 2000) and kites (Aber et al. 1999). The very large scale aerial (VLSA) imagery technique uses an ultralight-type aircraft to acquire digital photographs. VLSA imagery has been successfully used to monitor areas of interest in the sagebrush steppe (Seefeldt and Booth 2006), western riparian areas (Booth et al. 2006), short grass prairie (Booth and Cox 2006) and invasive species identification (Booth pers. comm.). The aerial photography technique has the potential to reduce costs of monitoring by reducing time spent in the field. VLSA imagery also allows for systematic sampling that better reflects the landscape, and captures all plots at the same phenologic stage.

    Project objectives:

    Short Term: 1) Increase ranchers’ awareness of vegetative communities on their grazing allotments. 2) Decrease perceived tensions between Forest Service and McKenzie, Medora and Grand River Grazing Associations.
    Intermediate Term: 1) Change the basis upon which ranchers make management decisions. 2) Influence the ways in which the Forest Service uses vegetative data to develop policies.
    Anticipated Long Term: 1) Facilitate improved conditions to grazing pastures leading to healthier ecological communities and more sustainable conditions for ranching families.

    Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the U.S. Department of Agriculture or SARE.