中国东北黑土带土壤线空间变异规律

Spatial heterogeneity of soil line parameters of black soil zone in Northeast China

利用遥感影像分析土壤参数和监测植被长势要求准确的土壤线参数。利用MODIS反射率产品计算东北黑土带不同分区土壤线参数,研究其空间分布规律;并利用不同分区土壤线参数计算与土壤线性相关的植被指数,分析不同植被指数与作物叶面积指数、光合有效辐射分量之间的相关关系。结果表明:东北黑土带土壤线斜率的总体趋势是,由北向南先增加后减小,最大值(1.5921)在北纬47°～47.7°之间的黑土带范围(对应行政范围为海伦南部,望奎北部);最低值(1.1319)在德惠南部与九台中部。与土壤线性相关的植被指数与作物两个生理参数的相关关系显著高于归一化植被指数(NDVI);改进的转换型土壤植被指数(ATSAVI)对土壤线参数的敏感性最高,利用分区不同土壤线参数计算的ATSAVI与作物生理参数的相关系数高于利用单一土壤线参数计算的结果;引入土壤线参数可以提高植被指数反演作物生理参数的精度。

Accurate soil line parameters are significant for monitoring vegetation or crop and analyzing soil properties with remote sensing images. Soil line parameters of different areas in black soil zone, Northeast China were calculated with MODIS reflectance products to analyze the spatial distribution of soil line parameters; then the vegetation indices relating to soil line were established, and the correlation coefficients between vegetation indices and crop leaf area index, the fraction of photosynthetically active radiation were analyzed. The results were as follows： the overall distribution of soil line slope in black soil zone was that from north to south, the value increased and reached maximum at south Hailun city and central Wangkui County （47°N-47.7°N）, then decreased, the minimum value lay at south Dehui City and central Jiutai City. The correlation coefficients between vegetation indices relating to soil line and crop leaf area index, the fraction of photosynthetically active radiation were significantly greater than that between Normalized Difference Vegetation Index and crop physiological parameters; the most sensitive vegetation index to soil line parameters was Adjusted Transformed Soil-adjusted Vegetation Index, and the vegetation indices calculated with soil line parameters in different zones showed more significant correlation with leaf area index and the fraction of photosynthetically active radiation than that calculated with single soil line parameter. With the introduction of soil line parameters, the precision of crop physiological parameters predicted with vegetation indices is much better.