| Vegetation is a main and most distinctive part of a terrestrial ecosystem. It is the first layer of terrestrial vegetation observed and recorded by remote sensing. Its changes have great affections on the energy and material biochemistry circulations either in a regional or the global scale. Vegetation cover directly reflects the vegetation changes. Large scale of regional vegetation restoration (degradation and recovering) reflects the affections of natural evolution and human activities on ecological environments. Along with the advancements of the knowledge on vegetation, vegetation change investigations gradually focus on researching significance in theory and practice on national economic construction and sustentation in all aspects. Especially, facing the problems of population explosion, food shortage, ecological environment deterioration, and resources and energy exhaustation, we can easily find that vegetation cover is closely related to social science.The study area is located in Eastern Jilin Province, one of the important forestry wood bases. Heavily covered by vegetation, the area is very rich in forestry resources. About more than 80 speces of economic trees grow in the area. In recent years, Jilin provincial government always insists on the national protected forest and strictivley preserved forest policy, the further implementing natural forest protection engineering, and the farmland, zoology forest construction. The improvement and development has been made in the vegetation coverage and ecological construction in the area.In order to investigate the situations and improvements of vegetation cover and analysis the vegetation coverage evolution rule in Eastern Jilin Province, the author conducts the following researches on the vegetation of the study area through analysis of NDVI index using RS and GIS techniques. (1) Extract vegetation indexes, terrain factors, meteorological factors, wetland ecological environment, urban changes, and etc., by procession of multi-source remote sensing data, MODIS NDVI data, DEM, and statistical climate data of the study area. (2) Study the changes of time zone vegetation variation and spatial analysis by applying the difference and linear regression analysis methods to analyzing NDVI time series data of Eastern Jilin Province from 2000 to 2009. (3) Use the correlation analysis method to research the statistcial relation bewteen NDVI indexes and elevation, slope degree, and aspect. Compute the correlation coefficients bewtween NDVI indexes and temperature and precipitation. Analysis the climate factor and the spatial changes of the vegetation by correlation graph analysis of the annual NDVI with respect to the temperature and precipitation sequence data. (4)The author applied spatial analysis methods to study how vegetation coverage affected by the changes of rivers, lakes, and wetlands, and then implemented buffer analysis methods to study urban changes and their affections on the city sorroundings. The author also applied superposition analysis methods to investigate the relationship between vegetation coverage and urban change in different urban-buffering zones and the relationship between the population density and vegetation. Sequentially, the author discussed the affections of human activities on the vegetation. (5)Finaly, the author established quantification theory, correlation analysis, and other statistcial models for prediction of the driving forces of vegetation changes in both the whole study area and its subareas and forecasted the future development direction and the vegetation change rule using Markov Random Procedure model and Grey System theory model. The following conclusions can be drawn on the basis of the author's work.1. Vegetation changes in the study area: The research result of temperal and spatial changes of vegetation coverage of Eastern Jilin Province indicates that the vegetation coverage of the study area changes nothing much but grow slightly from 2000 to 2009. The yearly lowest and highest vegetation changes happened in 2004 and 2007, respectively. The monthly vegetation change, which happened in July, is similar to the yearly vegetation change that happened in the corresponding same year. The spatial distribution of regional vegetation coverage shows that the areas with unchanged vegetation coverage are enlarging, the areas with increased vegetation coverage is mainly distributed in the northeast and north; the areas with decreased vegetation coverage is mainly distributed in the southeast and southwest,and the areas with significantly changed vegetation coverage are comparatively small and scattered throughout the study area. All in all, the areas with increased vegetation coverage is more than the areas with the decreased vegetation coverage.2. Relationship between terrain rules and vegetation changes: The Eastern Jilin Province geomorphologically is a mountainous and hilly region. The eastern areas are topographically higher than the western areas. The east and south of Changbai area are with the comparatively higher topographical fluctuation. These areas are mainly comprised of slops and steep slopes. The micro slopes mainly distribute in the central and western parts. The superposition analysis of elevation, slope degree, slope direction, and the NDVI data shows that vegetation changes occur mainly in the slight slopes and the lower elevation areas, and the vegetation changes are more closely related to the faced-sun slopes than the enfaced-sun slopes.3. Relationship between climate changing rules and vegetation changes: In the study area, the temperatures and precipitations variate fluctuatively and the humidity increases overall in the nearest decade. The temperature increases and changes gradually from north to south. The areas with the largest amount of changes are in the northern Jiaohe and central Antu and Huadian. The areas with the minimum precipitations are the southeastern Jian district, south Changbai county, and the central of Yanbian, etc. The regional rainfalls are increased in most parts of the study area, and changed from southwest to northeast. The areas with gradually decreased rainfall mainly distribute in the north and northeast of the study area. The calculated correlation coefficients between average NDVI sequence data and the corresponding temperature and precipitation sequence data reveals that the climate factors are closely related to vegetation changes, the areas with higher correlation coefficients of temperature and NDVI mainly distribute in northeastern, northwestern, and southeastern regions, the areas with higher correlation coefficients of precipitation and NDVI mainly distribute in northwestern, southwestern, and central regions, and the areas with lower correlation coefficients mainly distribute in central and northeastern regions. The areas with higher positive correlation coefficients coincide with the areas with low temperature and precipitation while the areas with higher negative correlation coefficients coincide with the areas with annual moderate temperature and high rainfall.4. Wetland changes and their influences on vegetation cover: Through statistically analyzing the interpretation results of the remote sensing data of Eastern Jilin Province, the author finds that the wetland area becomes slightly larger in 2007 in comparison with 2000. All the types of wetlands have changed in the study area during the past few years. Swamps decrease while all other types increase in different degrees. Among these changes, artificial and lake-derived wetlands have changed extensively, while rivers and marsh wetlands have changed little or kept relatively stable. The contrast between wetland changes and NDVI changes manifests that vegetation cover is mainly affected by both the area and type changes of wetlands.5. Relationship between human activities and vegetation changes: Human activities in the study area have obvious characteristics. The population is dense in the western plainary areas while relatively sparse in the eastern mountain areas. From west to east, the population becomes sparser and sparser. The highest population density mainly occurs in downtown areas and gradually becomes lower from downtown areas to their outskirts; the lowest population density mainly appears in mountain areas. All of the urban areas, especially the plainary regions with dense population, are obviously expanding in the study area. Obviusely, the population density is negatively related to the NDVI. The vegetation condition is good in sparsely populated areas while relatively worse in densely populated areas. Vegetation condtion is proportional to the distance from a downtown area to its outskirts. The farther away from the downtown area, the better the vegetation condtion. The vegetation coverage usually increases from downtown areas to their surroundings in the study area.6. Driving forces of vegetation changes: The quantification theories and correlation analysis are applied to investigating the driving force of the vegetation in the study area. The results show that, from most to least significant, the impact factors, respectively, are elevation and slope degree, wetland and population densities, the distribution of urban areas, the annual temperature, precipitation, and the direction of slope when the whole study area are analyzed. Dividing the study area into a set of watersheds, we can find that the same impact factor has different affection on the vegetation in different subareas. However, terrain factors are always have relatively larger impact on the vegetation covers in all the watersheds.7. Prediction of vegetation change rules: The author establishes Markov model and the Grey System theory model to forecast the change rule of vegetation coverage of the study area. The results show that these two kinds of models are feasible for vegetation change prediction. According to the predicted results, the vegetation coverage of the study area will raise gradually in the future, and the areas with low NDVI values will decrease while the areas with high NDVI values will continuely increase. |
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