title: [Estimation of shelter forest area in Three-North Shelter Forest Program region based on multi-sensor remote sensing data].
abstract: The Three-North Shelter Forest Program is a key forestry ecological project in China. The quantity and spatial distribution of the shelter forest in the program affect the ecological environment of the entire Three-North region. In this paper, multi-sensor remote sensing data were used to scientifically, objectively and comprehensively estimate the quantity and spatial distribution pattern of the shelter forest in this region in 1978-2008. Firstly, the Landsat TM images (30 m in resolution) were adopted to extract the shelter forest data in this region in 2008. Then, based on random sampling techniques, the calibration formulae for the shelter forest area in different precipitation climate regions estimated by the SPOT5 (2.5 m in resolution) and Landsat TM were constructed. By using the above-mentioned results, the shelter forest area in the Three-North region in 2008 was estimated. In 2008, the total area of the shelter forest (canopy density of arbor shelter forest was >0.3, coverage of shrub shelter forest was > 40%, and accuracy was about 85%) in this region was 328360.03 km2, with 116244.55 km2 in Northeast China, 42981.32 km2 in North China, 76767.05 km2 in Loess Plateau, and 92367.11 km2 in Mongolia-Xinjiang Region. According to the classification of shelter forest types, the areas of coniferous forest, broadleaved forest, mixed broadleaf-conifer forest and shrubland were 62614.74, 121628.51, 22144.09 and 121972.69 km2, respectively.
authors.affiliation: State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China. zhengxiao303@163.com
authors.forename: Xiao
authors.initials: X
authors.lastname: Zheng
authors.affiliation: State Key Laboratory of Forest and Soil Ecology, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110164, China.
authors.forename: Jiao-jun
authors.initials: JJ
authors.lastname: Zhu
mesh_terms: D002681:China; D003247:Conservation of Natural Resources / Q000706:statistics & numerical data*; D016468:Forestry / Q000379:methods*; D065928:Forests; D058998:Remote Sensing Technology / Q000379:methods*; D014197:Trees / Q000254:growth & development*