Researching the pattern of vegetation cover is of great significance for the sustainable development of eco-environment.In this article, the characteristics of vegetation cover pattern and its driving mechanism were investigated and analyzed using geographically weighted regression (GWR) model based on vegetation cover index data of 30m resolution.Fujian Province and Jiangxi Province were selected as study area, and natural and human factors were considered in the analysis. Research results revealed that 1) in Fujian and Jiangxi provinces, topography is a main factor affecting the vegetation cover degree which has the strongest correlation with elevation within the range of [100,300) m and [300,500) m respectively, and weak correlation with slope gradient, above 25 ℃ and 10 ℃ respectively; 2) the correlation between vegetation cover degree and distance from river for the two provinces differ greatly. In Jiangxi Province, the mainstream is surrounded by towns and cropland, while in Fujian Province, the mainstream is surrounded by towns and woodland; 3) the distance to residence at 5 km and 4 km has the weakest correlation with vegetation cover degree in Jiangxi and Fujian, respectively.
Key words
geographically weighted regression model /
Fujian and Jiangxi Provinces /
vegetation index /
natural vegetation cover pattern /
driving mechanism
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
References
[1] TIAN X, WANG X, KG K, et al. Land Use/cover Dynamic Change and Landscape Pattern Analysis in Kayrakkum Reservoir Area during Past 40 Years[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(6): 232-241.
[2] 刘殿伟, 宋开山, 王丹丹,等. 近50年来松嫩平原西部土地利用变化及驱动力分析[J]. 地理科学, 2006, 26(3):277-283.
[3] BIAN L, WALSH S J. Scale Dependencies of Vegetation and Topography in a Mountainous Environment of Montana[J]. The Professional Geographer, 1993, 45(1): 1-11.
[4] DENG S F, YANG T B, ZENG B, et al. Vegetation Cover Variation in the Qilian Mountains and Its Response to Climate Change in 2000-2011[J]. Journal of Mountain Science, 2013, 10(6): 1050-1062.
[5] QIU B, ZENG C, CHEN C, et al. Vegetation Distribution Pattern along Altitudinal Gradient in Subtropical Mountainous and Hilly River Basin, China[J].Journal of Geographic Science, 2013, 23(2): 247-257.
[6] ISIK O, PINARCIOGLU M M. Geographies of a Silent Transition: A Geographically Weighted Regression Approach to Regional Fertility Differences in Turkey[J]. European Journal of Population, 2006, 22(4): 399-421.
[7] ZHAO N, YANG Y, ZHOU X. Application of Geographically Weighted Regression in Estimating the Effect of Climate and Site Conditions on Vegetation Distribution in Haihe Catchment, China[J]. Plant Ecology, 2010, 209(2): 349-359.
[8] 邵一希, 李满春, 陈振杰,等. 地理加权回归在区域土地利用格局模拟中的应用——以常州市孟河镇为例[J]. 地理科学, 2010, 30(1): 92-97.
[9] QIU B W, ZENG C Y, TANG Z H, et al. Identifying Scale-location Specific Control on Vegetation Distribution in Mountain-hill Region[J]. Journal of Mountain Science, 2013, 10(4): 541-552.
[10]王 情, 刘雪华, 吕宝磊. 基于SPOT-VGT数据的流域植被覆盖动态变化及空间格局特征——以淮河流域为例[J]. 地理科学进展, 2013, 32(2): 270-277.
[11]BRUNSDON C, FOTHERINGHAM S, CHARLTON M. Geographically Weighted Regression-Modelling Spatial Non-stationarity[J]. Journal of the Royal Statistical Society Series D:the Statistician, 1998, 47(2): 431-443.
[12]OSBORNE P E, FOODY G M, SUáREZ-SEOANE S. Non-stationarity and Local Approaches to Modelling the Distributions of Wildlife[J]. Diversity & Distributions, 2007,13(3):313-323.
[13]BRUNSDON C, FOTHERINGHAM A, CHARLTON M. Geographically Weighted Summary Statistics:A Framework for Localised Exploratory Data Analysis[J]. Computers, Environment and Urban Systems, 2002, 26(6): 501-524.
[14]刘 斌, 孙艳玲, 王中良,等. 华北地区植被覆盖变化及其影响因子的相对作用分析[J]. 自然资源学报, 2015, 30(1): 12-23.
[15]齐师杰, 张行南, 夏达忠,等. 嘉陵江流域土地利用/覆被变化特征及其驱动力分析[J]. 长江科学院院报, 2013, 30(1): 1-7.