A comparison of methods to predict soil surface texture in an alluvial basin

被引:22
作者
Scull, P [1 ]
Okin, G
Chadwick, OA
Franklin, J
机构
[1] Colgate Univ, Dept Geog, Hamilton, NY 13346 USA
[2] Univ Virginia, Dept Environm Sci, Charlottesville, VA 22904 USA
[3] Univ Calif Santa Barbara, Santa Barbara, CA 93106 USA
[4] San Diego State Univ, San Diego, CA 92182 USA
关键词
predictive soil mapping; soil texture; soil survey; geostatistics; Joshua Tree National Park;
D O I
10.1111/j.0033-0124.2005.00488.x
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Surface soil texture controls many important ecological, hydrological, and geomorphic processes in arid regions and is therefore important from a land-management perspective. Soil survey efforts have traditionally fulfilled this need, but they are constrained by the size, remoteness, and inaccessibility of many arid regions, which renders simple field measurements prohibitively expensive. This article compares several different predictive soil-mapping techniques with a sparse data set in order to develop surficial soil texture maps. Our results suggest that data collected at the landscape scale can be used as input to predictive soil-mapping techniques to create maps of soil texture at higher fidelity and a fraction of the cost than would be required using traditional methods.
引用
收藏
页码:423 / 437
页数:15
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