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Estimation of forest volumes by integrating Landsat TM imagery and forest inventory data

Science china(Technological sciences) 2006年第z1期49卷 54-62页

作者： gu huiyan, dai limin, wu gang, xu dong, wang shunzhong &wang hui institute of applied ecology, chinese academy of sciences, shenyang 110016, china School of Forestry, Northeast Forestry University, Harbin 150040, china State Key Lab of Systems ecology, Research Center for Eco-Environmental sciences, chinese academy of sciences, Beijing 100085, china Graduate University of chinese academy of sciences, Beijing 100039, china 1. institute of applied ecology Chinese Academy of Sciences Shenyang 110016 China 2. School of Forestry Northeast Forestry University Harbin 150040 China 3. State Key Lab of Systems ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China 4. Graduate University of chinese academy of sciences Beijing 100039 China

Accurate information about forest volumes is essential for forest management planning. The survey interval of the Forest Resource Inventory of china (FRIC) is too long to meet the demand for timely decision-making required for forest protection, management, and utilization. Analysis of satellite imagery provides good potential for more frequent reporting of forest parameters. In this study, we describe an application of the k-nearest neighbors (kNN) method to Landsat TM imagery for improving estimation of forest volumes. Several spectral features were tested and compared in forest volume estimations, including normalized difference vegetation index, environmental vegetation index, and the combination of the spectral features. The combined index resulted in the most accurate volume estimations. The kNN estimator and the combined index were then used in forest volume estimation. The estimation error (RMSE) of the total volume was44.2%, much lower than those for Larix forest (the RMSE was 51.7%) and those for the Korean pine and broadleaved forests (the estimation errors were over 71.7% and 88.19%,respectively). This preliminary study demonstrates the potential of forest volume estimations with remote sensing data to provide useful information for forest management if only limited ground information is available.

关键词： forest inventory, landsat TM, k-nearest neighbors, spectral extraction.

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Quantifying soil erosion with GIS-based RUSLE under different forest management options in Jianchang Forest Farm

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中国科学：技术科学英文版 2006年第z1期49卷 160-166页

作者： ZHANG Hengming, wang Qingli, dai limin, guofan Shao, TANG Una, wang shunzhong & gu huiyan institute of applied ecology, chinese academy of sciences, shenyang 110016, china Graduate University of chinese academy of sciences, Beijing 100101, china Department of Forestry and Natural Resources, Purdue University, Lafayette IN47901, USA Northeast Forestry University, Harbin 150040, china institute of applied ecology Chinese Academy of Sciences Shenyang 110016 China Graduate University of chinese academy of sciences Beijing 100101 China Department of Forestry Natural Resources Purdue University Lafayette IN 47901 USA Northeast Forestry University Harbin 150040 China

Quantitatively estimating soil erosion with an integration of geographic information system (GIS) and the revised universal soil loss equation (RUSLE) under four different exposed soil proportion scenarios caused by forest management practices was studied at Jianchang Forest Farm. The GIS provided means of input data generation required by RUSLE model and allowed a spatial assessment of the erosion hazard over the study area. Four exposed soil proportion scenarios of 5%, 10%, 20% and 30% were tested with the GIS-based RUSLE model to evaluate soil erosion hazard. The predicted soil erosion potentials were classified into five categories in order to provide valuable aids for management planning.

关键词： geographic information system, RUSLE, soil erosion, forest management.

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