A geographic information system (GIS) was used to create an interface to evaluate the relationship between the amount of greenness and the crime level within the city of Austin, Texas. Results indicated a statistically significant negative correlation between the incidence of crime committed in the Austin greater metropolitan area for the year 1995 and the amount of vegetation within the area in which those crimes occurred. Areas with less than the average mean greenness level in Austin had an increased amount of crime. Results indicated no statistically significant relationship between the level of greenness of the crime sites and the severity of the crimes committed, and income level appeared to have no statistically significant effect on the severity of crimes committed.
A.G. Snelgrove, J.H. Michael, T.M. Waliczek, and J.M. Zajicek
Geographic information system (GIS) tools allow the visualization of research data that have a strong spatial component. Currently, several proprietary desktop GIS tools are available that enable researchers to generate maps and perform spatial analysis. However, these packages often require licensing agreements and do not provide specific options that enable rapid and uncomplicated analysis of biological diversity data. As an alternative, publicly available GIS applications that perform basic GIS as well as specialized functions are available. For example, DIVA–GIS was developed specifically to allow analysis of genebank and herbarium databases as well as to assess genetic, ecological, and geographic patterns in the distribution of crops and wild species. It is potentially useful for researchers who do not have the time to learn how to use proprietary GIS software, or who cannot justify purchasing a license to perform very basic GIS operations like creating and modifying maps. This presentation describes the basic features as well as some advanced functionality of DIVA–GIS and other publicly available GIS applications.
Arthur Villordon*, Craig Roussel, and Tad Hardy
The Louisiana Dept. of Agriculture and Forestry (LDAF) conducts sweetpotato weevil [SPW, Cylas formicarius (Fabricius)] monitoring in support of the statewide SPW quarantine program. The monitoring activity primarily involves a statewide pheromone-based trapping process that generates trap data for sweetpotato beds and production fields. We conducted GIS analysis of SPW trap data, collected over three years, to assess the potential use of GIS tools in managing and interpreting the data. The LDAF has already generated shapefiles for all beds and fields in each of three years, facilitating GIS analysis. However, trap data was manually collected and statewide data was compiled and stored in spreadsheet files. Trap data was mapped to specific beds and fields in each of three years, generating layers that clearly showed fields and parishes that reported high trap counts. GIS analysis showed potential SPW “hotspots” in each year, indicating that certain beds or fields are more prone to SPW infestation than others. This information can be useful in planning SPW management strategies by growers and other stakeholders. The GIS database also provides the foundation for the development of descriptive and predictive models of SPW occurence in Louisiana. Compiling the SPW trap data into a GIS database allows the data to be distributed over the Internet, facilitating real-time access by stakeholders.
D.L. Creech and D. McDonald
Texas is botanically diverse with approximately 5500 native plants identified: east Texas contains about 40% of the total. While most species are stable, many are classified as rare, threatened, vulnerable, or endangered. Databases for east Texas plant communities and vegetative analyses are numerous. However, they are not yet integrated into easy-to-sort-and-query computer files. Computer-Assisted Drafting (CAD) and Geographic Information Systems (GIS) technology offers powerful applications to the storage, management, and spatial analysis of species inventories, plant community dynamics, and long-term habitat monitoring. At SFASU, the College of Forestry's GIS Center is being utilized to develop comprehensive east Texas resource inventories on a ten-station HP Apollo/ArcInfo platform. In the horticulture program, a twenty-station PC/AutoCad teaching laboratory is being used to create layered maps of the SFASU Arboretum, the on-campus landscape and off-campus plant communities. The integration of CAD and GIS projects through a DXF format takes advantage of the attributes of both technologies.
Justin A. Porter, David Berle, and Hazel Y. Wetzstein
use of geographic approaches ( Alexander et al., 2005 ; Anderson and Martinez-Meyer, 2004 ; Vanderpoorten et al., 2005 ). GIS/GPS methods can be effectively used in data collection, record management, and population inventorying. GIS further allows
Arthur Villordon, Craig Roussel, and Tad Hardy
The Louisiana Department of Agriculture and Forestry (LDAF) conducts sweetpotato weevil (SPW) (Cylas formicarius Fabricius) monitoring as part of the statewide SPW quarantine program. This activity involves a statewide pheromone-based trapping program that monitors sweetpotato beds and production fields. We conducted GIS analysis of SPW trap data, collected over three years, to assess the potential use of publicly available GIS tools in managing and interpreting the data. Trap data was mapped to specific beds and fields in each of three years, generating layers that clearly showed fields and parishes that reported high trap counts. GIS analysis showed potential SPW hotspots in each year, indicating that certain beds or fields are predisposed to SPW infestation than others. This information can be useful in planning SPW management strategies by growers and other stakeholders. The GIS database also provides the foundation for the development of descriptive and predictive models of SPW occurence not only in Louisiana, but in other states where SPW is a potential pest. For example, using presence data for Louisiana and Genetic Algorithm for Rule Set Prediction (GARP), a GIS-based ecological niche modelling tool, we were able to generate predicted distribution using mean minimum temperature for January as the predictor variable. Although additional work is needed to identify other predictor variables and verify the models, the results demonstrate the potential use of GIS-based tools for generating warnings or advisories related to SPW.
Global positioning system (GPS) and geographic information system (GIS) technologies are at the cutting edge of an emerging agricultural revolution called site-specific management. Anticipated benefits are both economic and environmental because in this system, herbicides, fertilizers and other inputs are placed only where needed in the precise amounts required. The opportunities for site-specific management of crops, soils, and pests are innumerable. However, most students of agriculture and land resource sciences have little, if any, experience with the GPS and GIS technologies that provide these new opportunities. Beginning in 1995, efforts were undertaken to integrate GPS/GIS technology into the College of Agriculture curriculum. The process began with GPS/GIS training workshops for local and regional faculty. Key faculty modified curriculum within several departmental options and produced instructional modules for 12 different agriculture science courses. Experiential learning opportunities were developed and in some classes, farmer practitioners of site-specific management participated with students in identifying management problems and solutions. Instructional modules and active learning exercises were formally evaluated as to their effects on enhanced student decisionmaking skills and competency in GPS/GIS applications. Recently the new course LRES 357 “GPS/GIS Applications” was added to the curriculum and work is underway to place this course on-line.
Ghazal Tarar, Coleman L. Etheredge, Amy McFarland, Amy Snelgrove, Tina M. Waliczek, and Jayne M. Zajicek
Visual Information Solutions, Redlands, CA). This process resulted in a grid with values ranging from −1 to 1. The NDVI grid was transferred to the GIS software, where statistics were calculated for each MSA. Statistics generated included the minimum NDVI
Amy Barr, Mark Bennett, and John Cardina
The objective of this study was to ascertain if stand establishment of sh2 sweet corn (Zea mays L.) would benefit from variable planting depths determined by the use of geographic information systems (GIS). Spring and fall research plots were established in a field [80 × 20 m (262 × 66 ft)] containing Crosby silt loam and Kokomo silty clay loam soil series in Columbus, Ohio. Three sh2 sweet corn cultivars (Starship, Skyline, and Confection) were planted at three depths on the two soil types in the fall study, with an additional transition soil added in the spring. Emergence counts as well as soil moisture and temperature were monitored. In the spring, sites were also sampled for nutrient levels and soil compaction. Significant variability was found within the field with respect to soil moisture, temperature, nutrient levels, and compaction. Seedling emergence fluctuated with average soil moisture increasing in blocks with up to 24% moisture and then leveling off. Daily minimum soil temperatures impacted stand establishment. Although heat units accumulated faster on the Crosby soil, emergence was slower and less complete on these soil series than on Kokomo soil series. Further investigation determined that although temperatures of the Crosby soil were 3 to 4.5 °C (5.4 to 8.1 °F) warmer during the day than the Kokomo soil, temperatures on the Crosby soil averaged 2 °C (3.6 °F) cooler at night. Analysis of emergence patterns and field variability was performed on ArcView mapping software. Although `Skyline' planted at 2 cm (0.8 inches) had the best emergence overall, final stand would have been increased with `Skyline' planted variably at 2 and 4 cm (1.6 inches). Mapping the field under these different scenarios showed that although area with less than 70% stand would exist with a 2-cm uniform planting depth, the entire field would have a stand of 70% or greater with variable planting depth using a high vigor seedlot.
Arthur Villordon*, Simon Gichuki, Heneriko Kulembeka, Simon C. Jeremiah, and Don LaBonte
Africa represents a unique secondary site of genetic diversity for the sweetpotato [Ipomoea batatas (L.) Lam.]. Despite the genetic resources available for sweetpotato breeding and cultivar selection, regional conflicts and adverse weather in the last two decades have accelerated the risk of germplasm loss, particularly in East and Central Africa. A cooperative research project is currently underway to assess genetic diversity as well as help conserve sweetpotato germplasm in East Africa. One of the tools that are currently being used is a web-accessible GIS database that enables access to spatial and temporal data by project investigators and other stakeholders. Although proprietary methods are available for delivering GIS data through web interfaces, these methods often require expensive licensing agreements. The use of ALOV Map, a freely available Java® application for publishing vector and raster maps, along with basemaps and other thematic maps downloaded from publicly accessible web sites, helped provide the framework for a web-accessible GIS database. DIVA-GIS, a free desktop based GIS software was used to generate shapefiles as well as preview files prior to uploading. This demonstrates that the availability of publicly available software requiring minimal or flexible licensing costs provide a cost-effective alternative to institutions that are considering access to GIS databases via a web-accessible interface. We describe procedures, software, and other applications that we used to develop a publicly accessible web interface to a GIS database of sweetpotato germplasm collections in Kenya and Tanzania.