A forest fire can be a real ecological disaster regardless of whether it is caused by natural forces or human activities, it is possible to map forest fire risk zones to minimize the frequency of fires, avert damage, etc. A method integrating remote sensing and GIS was developed and applied to forest fire risk zone mapping for Baihe forestry bureau in this paper. Satellite images were interpreted and classified to generate vegetation type layer and land use layers （roads, settlements and farmlands）. Topographic layers （slope, aspect and altitude） were derived from DEM. The thematic and topographic information was analyzed by using ARC/INFO GIS software. Forest fire risk zones were delineated by assigning subjective weights to the classes of all the layers （vegetation type, slope, aspect, altitude and distance from r3ads, farmlands and settlements） according to their sensitivity to fire or their fire-inducing capability. Five categories of forest fire risk ranging from very high to very low were derived automatically. The mapping result of the study area was found to be in strong agreement with actual fire-affected sites.
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.
GU Huiyan, DAI Limin, WU Gang, XU Dong, WANG Shunzhong &WANG Hui Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
Forests in the Changbai Mountains are important timber sources for economic development of the society and provide ecological services in northeast China. In order to strengthen forest resource management, this paper analyzed management-induced changes in forest structure, tree species composition and forest landscape pattern from 1987 to 2000 for Baihe Forestry Bureau in Jilin Province based on digitized forest parcel maps and forest survey data. The results suggested that the area of Mature, High-Stocking, and Close-Canopy Forests decreased by 31.4%, 55.9% and 10.7% respectively; volume of Mixed Forest, the native forest vegetation type, decreased by 17.8%;the number of patches increased tremendously but the mean patch density decreased sharply for Mature, High-Stocking, Close-Canopy, and Mixed Forests. All the changes in forest structure, species composition, and landscape pattern indicated severe degradations going on with the forests in Baihe Forestry Bureau. Because of the effect of degradation to forest services, restoring forest resources and protecting biodiversity has become urgently important. The strategies of sustainable forest management need to be worked out and implemented.
ZHOU Li, DAI Limin , Guofan Shao, XU Dong, WANG Hui & BAI Jianwei Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
