Title :
Investigating the spatial distribution of beech-magnolia with remotely sensed data
Author :
Clarke, Faith ; Pancholy, Sunil ; Onokpise, Oghenekome ; Milla, Katherine
Author_Institution :
Coll. of Eng. Sci., Technol. & Agric., Florida Agric. & Mech. Univ., Tallahassee, FL, USA
Abstract :
A Landsat Thematic Mapper (Landsat TM) scene, Global Positioning System (GPS), and geographic information systems (GIS) were used to investigate the spatial distribution of American beech and Southern magnolia in Gadsden county, Florida. The objective of the study was to determine the various environmental factors such as soil type, slope, aspect, and topography associated with the location of beech-magnolia communities. Earth Resources Data Analysis System (ERDAS) Imagine image analysis software was used to generate and evaluate training signatures, perform a supervised classification of the Landsat TM image, and to select random points for accuracy assessment. The findings of the accuracy assessment were reported in an error matrix and the Kappa statistic was used to measure the overall accuracy of the classification. The classified image delineating the spatial distribution of beech-magnolia communities was incorporated in a GIS with other layers containing information on soils, aspect, slope, and topographic contours. The slope, aspect and topographic contour layers were generated from a digital elevation model (DEM). The spatial analysis indicated that the beech-magnolia communities predominantly occur along the ravine system on Muckalee and Luka soils with slopes between 10-12 percent, and aspect due South east (112.5-157.5 degrees) and East (67.5-112.5 degrees)
Keywords :
botany; forestry; geographic information systems; geophysical signal processing; geophysical techniques; image classification; multidimensional signal processing; remote sensing; vegetation mapping; American beech; ERDAS; Fagus grandifolia; Florida; GIS; GPS; Gadsden county; Global Positioning System; Imagine image analysis software; Kappa statistic; Landsat TM; Landsat Thematic Mapper; Luka; Magnolia grandiflora; Muckalee; Southern magnolia; USA; United States; biogeography; botany; digital elevation model; distribution mapping; forest; forestry; geographic information systems; land surface topography; measurement technique; multispectral remote sensing; ravine; slope; soil type; spatial distribution; supervised classification; vegetation mapping; Data analysis; Earth; Environmental factors; Geographic Information Systems; Global Positioning System; Layout; Remote sensing; Satellites; Soil; Surfaces;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
DOI :
10.1109/IGARSS.1999.774539