基于遥感和地面实测水分数据的小流域土壤水分模拟
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摘要
水是制约黄土高原植被建设的关键自然因素,黄土高原土层深厚,地下水埋藏深,植物难以利用,所需水分主要来自土壤水,土壤水分作为水量平衡和水循环与土壤资源的重要因素已经受到了广泛的研究。土壤水分也决定了生态建设中植被类型和结构,它是植物生长、植被恢复、土壤侵蚀的主要影响因素。因此,监测和掌握土壤水分状况对于黄土高原的农业生产和土地的合理利用具有重要的指导意义。
本论文以陕西安塞县沿河湾乡桑塌村为土壤水分采样区,借助遥感数字图像处理技术和GIS地形分析方法,首先根据遥感影像提取地表温度(Ts)和植被指数(NDVI),由Ts和NDVID组成的特征空间拟合干边和湿边方程,从而计算得到温度植被干旱指数(TVDI)。其次,根据野外实测土壤水分数据分析TVDI和土壤水分的相关性,建立TVDI模型反演土壤水分,利用未参与推演模型的野外实测数据进行模型检验。利用GIS的地形分析功能,对坡向和土地利用类型对土壤水分的影响做分析,利用DEM提取地形湿度指数。在已建立的TVDI模型的基础上,考虑地形因子对土壤水分的作用情况下加入坡向、土地利用类型和地形湿度指数作为土壤水分的影响因子,建立一个土壤水分反演的综合模型,以此方法反演土壤水分含量,再利用未参与推演模型的土壤水分实测数据进行检验。最后根据TVDI模型和综合模型对土壤水分的空间分布制作了预测图。为黄土高原地区快速获取土壤水分含量提供了可借鉴的方法,同时也为小流域土壤侵蚀模型提供了基础数据。
Water is the key natural factor to restricting the construction of the natural vegetation. The natural vegetation in the Loess Plateau mainly depends on soil moisture, because water is buried deep underground, which is difficult to use by the vegetation. As the important factor in water balance and cycle and soil resource, soil moisture has received extensive research. Meanwhile, soil moisture is the main factor affecting the plant growth, vegetation restoration and soil erosion. Therefore, monitoring soil moisture has an important significance to the agricultural production and the rational use of land for the Loess Plateau.
In this paper, based on Sangta village soil moisture sampling experimental area in Ansai County of Shaanxi Province, using Remote sensing digital image processing and GIS methods. At first, extracts Surface temperature (Ts) and Normalized difference vegetation index (NDVI) based on remote sensing. We can calculate the Temperature Vegetation Dryness Index (TVDI) by equation formed by Ts and NDVI. Second, establishes soil moisture retrieval model according to the relevance of TVDI and soil moisture. Using the terrain analysis capabilities of GIS, analyses the slope and land influence on soil moisture and extracts the Topographic Wetness Index based on the Xiannangou DEM. Checks the TVDI model utilizing other data not involved model inference. Taking into account the topographic fators influence on soil moisture, establishes an integrated model to inverse the soil moisture. At last, products soil moisture distribution according to the TVDI model and integrated model. Provide a feasible method collecting soil moisture content quickly. Furthermore, supplies the basic data for the soil erosion model.
本论文以陕西安塞县沿河湾乡桑塌村为土壤水分采样区,借助遥感数字图像处理技术和GIS地形分析方法,首先根据遥感影像提取地表温度(Ts)和植被指数(NDVI),由Ts和NDVID组成的特征空间拟合干边和湿边方程,从而计算得到温度植被干旱指数(TVDI)。其次,根据野外实测土壤水分数据分析TVDI和土壤水分的相关性,建立TVDI模型反演土壤水分,利用未参与推演模型的野外实测数据进行模型检验。利用GIS的地形分析功能,对坡向和土地利用类型对土壤水分的影响做分析,利用DEM提取地形湿度指数。在已建立的TVDI模型的基础上,考虑地形因子对土壤水分的作用情况下加入坡向、土地利用类型和地形湿度指数作为土壤水分的影响因子,建立一个土壤水分反演的综合模型,以此方法反演土壤水分含量,再利用未参与推演模型的土壤水分实测数据进行检验。最后根据TVDI模型和综合模型对土壤水分的空间分布制作了预测图。为黄土高原地区快速获取土壤水分含量提供了可借鉴的方法,同时也为小流域土壤侵蚀模型提供了基础数据。
Water is the key natural factor to restricting the construction of the natural vegetation. The natural vegetation in the Loess Plateau mainly depends on soil moisture, because water is buried deep underground, which is difficult to use by the vegetation. As the important factor in water balance and cycle and soil resource, soil moisture has received extensive research. Meanwhile, soil moisture is the main factor affecting the plant growth, vegetation restoration and soil erosion. Therefore, monitoring soil moisture has an important significance to the agricultural production and the rational use of land for the Loess Plateau.
In this paper, based on Sangta village soil moisture sampling experimental area in Ansai County of Shaanxi Province, using Remote sensing digital image processing and GIS methods. At first, extracts Surface temperature (Ts) and Normalized difference vegetation index (NDVI) based on remote sensing. We can calculate the Temperature Vegetation Dryness Index (TVDI) by equation formed by Ts and NDVI. Second, establishes soil moisture retrieval model according to the relevance of TVDI and soil moisture. Using the terrain analysis capabilities of GIS, analyses the slope and land influence on soil moisture and extracts the Topographic Wetness Index based on the Xiannangou DEM. Checks the TVDI model utilizing other data not involved model inference. Taking into account the topographic fators influence on soil moisture, establishes an integrated model to inverse the soil moisture. At last, products soil moisture distribution according to the TVDI model and integrated model. Provide a feasible method collecting soil moisture content quickly. Furthermore, supplies the basic data for the soil erosion model.
引文
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