Texture Analysis for Mapping Tamarix parviflora Using Aerial Photographs along the Cache Creek, California
Texture Analysis for Mapping Tamarix parviflora Using Aerial Photographs along the Cache Creek, California
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DOI:
10.1007/s10661-006-1071-z
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发表时间:
2006-03
影响因子:
3
通讯作者:
S. Ge;R. Carruthers;P. Gong;Angelica M. Herrera
中科院分区:
文献类型:
--
作者:
S. Ge;R. Carruthers;P. Gong;Angelica M. Herrera
Natural color photographs were used to detect the coverage of saltcedar,Tamarix parviflora, along a 40 km portion of Cache Creek near Woodland, California. Historical aerial photographs from 2001 were retrospectively evaluated and compared with actual ground-based information to assess accuracy of the assessment process. The color aerial photos were sequentially digitized, georeferenced, classified using color and texture methods, and mosaiced into maps for field use. Eight types of ground cover (Tamarix, agricultural crops, roads, rocks, water bodies, evergreen trees, non-evergreen trees and shrubs (excludingTamarix)) were selected from the digitized photos for separability analysis and supervised classification. Due to color similarities among the eight cover types, the average separability, based originally only on color, was very low. The separability was improved significantly through the inclusion of texture analysis. Six types of texture measures with various window sizes were evaluated. The best texture was used as an additional feature along with the color, for identifyingTamarix. A total of 29 color photographs were processed to detectTamarixinfestations using a combination of the original digital images and optimal texture features. It was found that the saltcedar covered a total of 3.96 km2(396 hectares) within the study area. For the accuracy assessment, 95 classified samples from the resulting map were checked in the field with a global position system (GPS) unit to verifyTamarixpresence. The producer's accuracy was 77.89%. In addition, 157 independently located ground sites containing saltcedar were compared with the classified maps, producing a user's accuracy of 71.33%.