An Integrated Decision Tree Approach (IDTA) to mapping landcover using satellite remote sensing in support of grizzly bear habitat analysis in the Alberta yellowhead ecosystem

被引:54
作者
Franklin, SE
Stenhouse, GB
Hansen, MJ
Popplewell, CC
Dechka, JA
Peddle, DR
机构
[1] Univ Calgary, Dept Geog, Calgary, AB T2N 1N4, Canada
[2] Foothills Model Forest, Hinton, AB T7V 1X6, Canada
[3] GeoAnalyt Inc, Calgary, AB T2P 3J4, Canada
[4] Univ Lethbridge, Dept Geog, Lethbridge, AB T1K 3M4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
D O I
10.1080/07038992.2001.10854899
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Multi-source data consisting of 1999 Landsat satellite imagery; topographic descriptors derived from DEMs, and GIS-based vegetation inventory information have been used to generate a detailed landcover classification map to quantify and analyze the spatial distribution and configuration of grizzly bear habitat within the Alberta Yellowhead Ecosystem study area. The map is needed as part of a larger ecosystem assessment to help determine if bear movement and habitat use patterns are affected by changing landscape conditions and human activities. An Integrated Decision Tree Approach (IDTA) was developed that incorporated unsupervised (K-means) clustering, empirically-derived DEM- and GIS-based decision rules (proximity; slopes, etc.), and maximum likelihood supervised classification of forest and vegetation classes based on field sampling. This approach was based on an earlier finding, using a 1998 Landsat image in this area, that different classifiers performed at different levels of success in various classes. The map produced with the IDTA method was determined to be approximately 80% accurate (kappa = 0.783) using 494 randomly sampled points unambiguously identified on available digital orthophotography.
引用
收藏
页码:579 / 592
页数:14
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