The restoration of the riparian vegetation disturbed by human activities is one of the hotspots of watershed ecology. Through interpreting the images of Remote Sensing in 1985 and 1999, the basic information of forest resources of Lushuihe Forest Bureau, which is a typical forest area of Changbai Mountain, was obtained with support of GIS. By dividing Land covers of Lushuihe area into 10 types (water body, residential land, stump land, farming land, wetland, mature conifer forest, midlife conifer forest, mature broadleaf forest, midlife broadleaf forest, and man-made young forest) and dividing the riparian zone into four buffers (in turn, 1000, 2000, 3000, 4000 m away from the river), the changes of riparian forest resources during 1985-1999 were analyzed. The results showed that the deforestation intension has obviously decreased and the whole environment has been evidently improved, but the riparian ecosystem was still flimsy. In buffer 1, 2, 3, the area of midlife conifer forest increased largely, but the areas of other types of land covers all decreased. Midlife conifer forest had a comparatively good status in the three buffers. In buffer 4, midlife conifer forest, mature conifer forest, and mature broadleaf forest formed a forest-age rank that is helpful to stabilize the forest ecosystem and exert its functions. Area percentage of wetland decreased in buffer 1, buffer 2, and buffer 3, even in buffer 4 in which forest ecosystem rehabilitated comparatively well, so protecting and rehabilitating wetland is a very difficult task.
The utilization and changes of forest resources were studied in the Lishuihe Forest Bureau. Based on remote sensing images in 1985 and 1999, changes of major forest resources were analyzed by statistical and overlap method and classified quantitatively. The results showed that in recent 15 years, logging spots and man-made young forest changed violently, which was due to human activities. Different forest management manners and harvesting intensity played an important role in forest resources change. Dongsheng and Xilinhe tree farms were typical cases of different forest status and management for the Bu-reau, where forest succession was intervened by either human or natural disturbance. Dongsheng Tree Farm underwent a light harvest intensity and maintained a unit stock volume of 536.27 m3hm-2, as much as that of broadleaf/Korean pine forest of Changbai Mountain Natural Reserve; Xilinhe Tree Farm underwent an intense harvest and was composed of secondary forests, where mature forests just had a small percentage and the unit stock volume was low. The study was useful to guide future forest management. What抯 more, problems found in the research were also analyzed and reasonable advice was given to the local forest management.
Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.
