Research On Remote Sensing Biomass Model And Spatial Distribution Pattern Of Picea Schrenkiana Of Western TianShan Mountain

The forest biomass which approximately composes 90% of the global land vegetation biomass is the important symbol of forest solid carbon ability. It is also the important parameter of appraising the forest carbon revenue and expenditure. The magnitude of forest biomass is affected by nature and the humanity activity factors such as photosynthesis ,respiration ,death ,harvests and so on. Therefore , the change of forest biomass reflects the forest succession, the humanity activity, nature molestation (for example: forest fire, the plant disease and so on)climatic change and air pollution, which is the important index to measure the forest structure and the function change. With 3S appearance and development, it provides the possibility in multi-dimensional perspective of the scale of forest biomass monitoring study.This article uses the ETM remote sensing data, with the support of remote sensing and geographic information system, it synthetizes the geographic and ecology information, establishes the Tianshan spruce forest biomass model of eastern Gongliu forest region, and analyzes its spatial distribution pattern. This paper's contents and results expresses in the following three aspects :(1) Retrieval of spruce forest vegetation index and pertinence analysis of spruce forest between vegetation index and volume/biomass. Using the vegetation remote sensing theory, this paper retrieves vegetation index of different age level spruce forest.On this basis, I analyze the pertinence of spruce forest between different vegetation index and different age grades of Picea Schrenkiana var.tianshanica volume/biomass. The most significant vegetation index is selected from relevance as the parameters and variables of Picea Schrenkiana var.tianshanica forest biomass inversion based remote sensing.(2) The spruce forest biomass remote sensing model study. Using Biomass Expansion Factor(BEF)and volume I convert various age level's biomass . Remote sensing parameters are retrieved by using statistical regression models ,forest biomass remote sensing models of Picea Schrenkiana var.tianshanica are established.Use the final model to calculate the biomass of eastern Gongliu forest region and testify its precision.(3) The research of spruce forest biomass spatial distribution pattern. Selecting the typical grades of Picea Schrenkiana var.tianshanica, the character of the land including altitude, slope-deflection and the direction of the slope can be extracted uniting DEM analysis and the statistical analysis of the land. The western Tianshan spruce forest biomass spatial pattern can be simulated by altitude, slope-deflection and the direction .It can analyze different age grade's biomass visible region and withdraw the terrain characteristic. Through the research, it can obtains the near ripe and the mature Picea Schrenkiana var.tianshanica forest's biomass spatial distribution characteristic and the diversity rule in the region scope.It is showed that excessive mature Picea Schrenkiana var.tianshanica forest's biomass is the largest of those average reaches 229.001t/hm~2,second is near mature Picea Schrenkiana var.tianshanica forest's biomass of those average reaches 146.374t/hm~2, the mature's average reaches 183.51t/hm~2,the middle age's average reaches 146.374t/hm~2,the young age's average reaches 61.889t/hm~2. Picea Schrenkiana var.tianshanica forest's biomass is scattered in 1400-2700m and the slope of 25 o-35 o on the largest proportion, its spatial distribution pattern was evident in the Central Asian mountain forest characteristics.