广西中南部耕地土壤有机质和全氮变化的遥感监测

Monitoring changes of soil organic matter and total nitrogen in cultivated land in Guangxi by remote sensing

以1981年、2011年土壤数据为基础,以AVHRR和MODIS遥感影像为数据源,通过研究广西中南部土壤有机质、全氮及其变化与归一化差异植被指数(NDVI)、植被覆盖度、植被净初级生产力(NPP)等遥感因子之间的耦合关系,建立表层土壤有机质、全氮含量变化的遥感监测模型。研究表明:近30年来,研究区土壤有机质、全氮变化均呈极显著上升趋势,分别增加了5.43g/kg和0.21g/kg;1981—2011年间,NDVI、植被覆盖度和NPP 3个遥感因子变化趋势一致,均呈现缓慢上升趋势,且遥感因子变化与有机质、全氮变化均具有显著正相关关系;利用逐步线性回归方法,建立土壤有机质、全氮变化的遥感监测模型,分别能够解释有机质、全氮变化的16.9%和20.3%;根据所建模型对研究区耕地土壤有机质、全氮变化可进行空间预测制图。结果表明,研究区内耕地土壤表层有机质、全氮分别上升了6.65g/kg和0.31g/kg,验证结果显示遥感模型能够反映出不同区域土壤有机质和全氮长期变化的空间特征。

Based on soil data in 1981 and 2011, and AVHRR and MODIS remote sensing data, models for predicting the changes of the topsoil organic matter and total nitrogen were built by studying the relationships between soil organic matter, total nitrogen and these remote sensing parameters, such as normalized difference vegetation index （ NDVI ） , vegetation coverage and net primary productivity （NPP）. The study showed that soil organic matter and total nitrogen in the study area had changed significantly during the past 30 years with an increase of 5.43 g/kg and 0.21 g/kg respectively, while the three remote sensing parameters （NDVI, vegetation coverage and NPP ） showed a gentle rising trend between 1981 and 2011. Positive correlation was found between the changes of remote sensing parameters and the change of soil organic matter and total nitrogen. A model was built to predict the change of soil organic matter content and the change of total nitrogen respectively by stepwise multiple linear regression analysis by using those parameters. The models can explain 16.9% and 20.3% of their changes respectively. Then the models were employed to map the spatial variations of the changes organic matter content and total nitrogen content in the cultivated land of the region, the results showed that soil matter and total nitrogen had an increase of 6.65 g/kg and 0.31 g/kg in the cultivated land. The validation results of soil organic showedthat the models could well reflect the spatial distribution features of changes of soil organic matter and total nitrogen content in the study area.