Geospatial technologies (remote sensing, GIS, GPS) have the potential to be integrated into exisiting policies that are spatially explicit or implicit. This project explores the technological possibilities in one policy -- farmland preservation -- as a means for understanding the broader implications in many policies. For our case studies, we sought places with robust geographic information systems, complete with parcel-level databases. Hunterdon County and Burlington County, NJ, stood out as places with strong databases and lengthy histories in farmland preservation.
New Jersey has an aggressive open space and farmland preservation program. The passage of the Garden State Preservation Trust Act in 1999 provided the necessary funding to pursue the ambitious goal of preserving an additional one million acres of open space by 2010, half of which will be farmland. The additional pressure this goal places on the existing county and state farmland preservation programs will require the agencies that administer those programs to explore techniques that maximize the efficiency of the preservation process. Geospatial technologies hold great promise to reduce the time, effort and variability involved with many preservation program tasks.
The Center for Remote Sensing and Spatial Analysis at Rutgers University has been engaged in automating the farmland preservation ranking procedure, with one example being Hunterdon County. The results of this project are encouraging to those who seek to make preservation programs more efficient by incorporating geospatial technologies into the preservation process. Using GIS data layers such as land use, SSURGO soils and currently preserved open space, the criteria used to rank farms for preservation (Table 1) were translated into GIS procedures (e.g. soils in Figure 1).
Because the data sets used cover the entire county, every parcel in the county was ranked once appropriate technical procedures were developed for each criterion (Figure 2). This contrasts significantly with the traditional ranking method, where only those farms applying for preservation in a given year were ranked. Having the capacity to rank all farms in the county presents several advantages.
The countywide ranking could be used to target highly ranked farms that are not yet preserved. Because the procedures used to generate the ranking can be easily modified, the effects of alterations to the preservation criteria can be quickly assessed through visual and statistical analyses. For example, the automated ranking could be combined with an econometric model that predicts the probability of farmland converting to development to show the effects of giving extra weight in the ranking to farms which are more likely to be developed (Figure 3). While this is not currently a criterion under consideration, it serves as an example of a criterion that could not easily be considered without the technology.
The success of automating farmland preservation programs depends on the availability of data and technical support. The most important GIS data layer needed for automation is the tax map delineating the parcels in the county. Most counties in New Jersey are currently in the process of creating this data, and several have already completed the task. Other data layers such as currently preserved farms and soils are readily available; if they are not they can often be created from existing data layers with varying levels of effort. The level of technical support required to automate preservation programs is considerable, perhaps beyond what most counties could afford to commit to the process. Because the benefits of automation are so significant, further investigation as to how they could be most efficiently implemented is warranted. For further information, please contact Jim Myers or David Tulloch.
Table 1. Hunterdon County, New Jersey Farmland Preservation Ranking Criteria.
Please note: Farm and family characteristics require individual on-site evaluation of farms by experienced farmers. Therefore, they are not included in the automation.
|Boundaries and Buffers||20|
|Size and Density||24|
|Farm and Family Characterisitics||10|
The results and conclusions derived from this project are the work of CRSSA researchers and are not endorsed by Hunterdon County.
Site last edited 5 April, 2002top