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Determination of main climate and ground factors controlling vegetation cover regrowth along oil and gas pipelines using multiple, spatial and geographically weighted regression procedures

机译:使用多重,空间和地理加权回归程序确定控制油气管道沿线植被覆盖生长的主要气候和地面因素

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The goal of this research was to determine the primary climate and ground factors controlling Normalize Difference Vegetation Index (NDVI) of grasslands and croplands along the disturbed Right of Way of Baku-Tbilisi-Ceyhan and South Caucasus Pipelines for revege-tation planning purposes. The climate factors considered in this research were annual precipitation (PRECIP), annual evapotranspiration (ET), land surface temperature (LST), annual minimum air temperature (T_(min)), annual maximum air temperature (T_(max)) and solar radiation (SOLRAD). The ground factors considered were elevation, aspect, ground-water, and topsoil depth. A standard multiple regression model detected and eliminated SOLRAD and (T_(max)) as the independent variables causing the multi-collinearity in the regression models for grasslands and croplands. The spatial autocorrelation of errors in the regression models was detected using the semi-variogram modeling of regression residuals. This required the use of the global spatial regression model (GSRM) based on the maximum likelihood model of spatial errors. GSRM determined for grasslands that PRECIP, ET, and LST were the most significant factors controlling NDVI. In the case of croplands, PRECIP,ET, and T_(min) were observed to be the strongest controlling factors, and LST was not significant. Geographically weighted regression (GWR) determined the ranges of variable regression coefficients predicting NDVI of grasslands and croplands on the local level along the corridor of pipelines. Although no strong correlation was observed between elevation and NDVI, the largest vegetation distribution was identified in the areas with an elevation higher than 150 m. The percentage of high NDVI spatial coverage within the aspect categories was decreasing in the southern directions of slope faces. The threshold of groundwater depth controlling NDVI of grasslands was 1-12 m in the areas lower than 100 m in elevation. Topsoil depth was determined as one of the main ground factors having direct control of NDVI of grassland and croplands. Precipitation was also identified as one of the main factors controlling formation of topsoil depth. The results of GSRM and GWR were validated using low- and high-resolution remotely sensed data.
机译:这项研究的目的是确定受干扰的巴库-第比利斯-杰伊汉和南高加索管道通行权的草原和农田的归一化植被指数(NDVI)的主要气候和地面因素,以进行植被规划。本研究中考虑的气候因素是年降水量(PRECIP),年蒸散量(ET),地表温度(LST),年最低气温(T_(min)),年最高气温(T_(max))和太阳能辐射(SOLRAD)。考虑的地面因素包括海拔,纵横比,地下水和表土深度。一个标准的多元回归模型检测并消除了SOLRAD和(T_(max))作为导致草地和农田回归模型中多重共线性的自变量。使用回归残差的半变异函数模型检测回归模型中误差的空间自相关。这需要基于空间误差的最大似然模型使用全局空间回归模型(GSRM)。 GSRM确定草原的PRECIP,ET和LST是控制NDVI的最重要因素。在农田中,PRECIP,ET和T_(min)被认为是最强的控制因素,而LST并不显着。地理加权回归(GWR)确定了可变回归系数的范围,该系数可预测沿管道走廊局部地区的草地和农田的NDVI。尽管没有观察到海拔与NDVI之间有很强的相关性,但在海拔高于150 m的区域中,植被分布最大。在坡面的南部,纵横比类别内高NDVI空间覆盖率的百分比在下降。海拔低于100 m的地区,控制地下水深度的NDVI阈值为1-12 m。确定表土深度是直接控制草地和农田NDVI的主要地面因素之一。降水也被确定为控制表土深度形成的主要因素之一。使用低分辨率和高分辨率遥感数据验证了GSRM和GWR的结果。

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