Geographic Information Systems (GIS), Global Positioning Systems (GPS) and remote sensing techniques were utilized to characterize and subsequently predict potential habitat of Gaillardia aestivalis var. Winkleri, occurring in Hardin County, TX. Field investigations along with CIR positive aerial photographs were used to study local distribution and ecological requirements (soil, site, plant associations) of the plant. Data were obtained from paper maps, aerial photographs and a Landsat TM image. Sites occupied by G. aestivalis var. Winkleri were characterized as having highly acidic soils with poor nutrient content, good drainage and rapid permeability. Along with soil types, vegetation also is an important factor in affecting distribution of the plant. Supervised classification of Landsat TM Image for vegetation classes produced satisfactory results as shown by error matrix. Spatial analysis of coverages were then used to produce potential habitat maps, classified either as favorable or unfavorable. The methodology employed in this study should be useful in conservation of G. aestivalis var. Winkleri, as well as other rare plant species.
","abstract_html":"<p>Geographic Information Systems (GIS), Global Positioning Systems (GPS) and remote sensing techniques were utilized to characterize and subsequently predict potential habitat of Gaillardia aestivalis var. Winkleri, occurring in Hardin County, TX. Field investigations along with CIR positive aerial photographs were used to study local distribution and ecological requirements (soil, site, plant associations) of the plant. Data were obtained from paper maps, aerial photographs and a Landsat TM image. Sites occupied by G. aestivalis var. Winkleri were characterized as having highly acidic soils with poor nutrient content, good drainage and rapid permeability. Along with soil types, vegetation also is an important factor in affecting distribution of the plant. Supervised classification of Landsat TM Image for vegetation classes produced satisfactory results as shown by error matrix. Spatial analysis of coverages were then used to produce potential habitat maps, classified either as favorable or unfavorable. The methodology employed in this study should be useful in conservation of G. aestivalis var. Winkleri, as well as other rare plant species.</p>","abstract_has_math":false,"creators":["Rajasekhar, Dasyam Samuel"],"institution":null,"degree_name":"Master of Forestry (MF)","degree_level":"Thesis","degree_discipline":"Forestry","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":1997,"date_issued":"1997-03-01T08:00:00Z","date_published":"1997-03-01T08:00:00Z","updated_at":"2026-07-24T04:30:03Z","subjects":["Forest Sciences","Other Forestry and Forest Sciences"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarworks.sfasu.edu/etds/29","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Rajasekhar, Dasyam Samuel"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2015-11-10T08:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Forestry"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Forestry (MF)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Forest Sciences","Other Forestry and Forest Sciences"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarworks.sfasu.edu/etds/29"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Geographic Information Systems (GIS), Global Positioning Systems (GPS) and remote sensing techniques were utilized to characterize and subsequently predict potential habitat of Gaillardia aestivalis var. Winkleri, occurring in Hardin County, TX. Field investigations along with CIR positive aerial photographs were used to study local distribution and ecological requirements (soil, site, plant associations) of the plant. Data were obtained from paper maps, aerial photographs and a Landsat TM image. Sites occupied by G. aestivalis var. Winkleri were characterized as having highly acidic soils with poor nutrient content, good drainage and rapid permeability. Along with soil types, vegetation also is an important factor in affecting distribution of the plant. Supervised classification of Landsat TM Image for vegetation classes produced satisfactory results as shown by error matrix. Spatial analysis of coverages were then used to produce potential habitat maps, classified either as favorable or unfavorable. The methodology employed in this study should be useful in conservation of G. aestivalis var. Winkleri, as well as other rare plant species.
"]},{"key":"dc:title","label":"Title","values":["Development of a Predictive Habitat Evaluation Model for Gaillardia Aestivalis (Walt.) Rock. Var. Winkleri (Cory) Turner Using GPS, Remote Sensing and GIS Techniques"]}]}],"canonical_facts":{"dc:creator":["Rajasekhar, Dasyam Samuel"],"dc:date.available":["2015-11-10T08:00:00Z"],"dc:description.abstract":["Geographic Information Systems (GIS), Global Positioning Systems (GPS) and remote sensing techniques were utilized to characterize and subsequently predict potential habitat of Gaillardia aestivalis var. Winkleri, occurring in Hardin County, TX. Field investigations along with CIR positive aerial photographs were used to study local distribution and ecological requirements (soil, site, plant associations) of the plant. Data were obtained from paper maps, aerial photographs and a Landsat TM image. Sites occupied by G. aestivalis var. Winkleri were characterized as having highly acidic soils with poor nutrient content, good drainage and rapid permeability. Along with soil types, vegetation also is an important factor in affecting distribution of the plant. Supervised classification of Landsat TM Image for vegetation classes produced satisfactory results as shown by error matrix. Spatial analysis of coverages were then used to produce potential habitat maps, classified either as favorable or unfavorable. The methodology employed in this study should be useful in conservation of G. aestivalis var. Winkleri, as well as other rare plant species.
"],"dc:identifier":["https://scholarworks.sfasu.edu/etds/29"],"dc:subject":["Forest Sciences","Other Forestry and Forest Sciences"],"dc:title":["Development of a Predictive Habitat Evaluation Model for Gaillardia Aestivalis (Walt.) Rock. Var. Winkleri (Cory) Turner Using GPS, Remote Sensing and GIS Techniques"],"thesis:degree_discipline":["Forestry"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["Master of Forestry (MF)"]},"updated_at":"2026-07-24T04:30:03Z"}