【作者】 乔璐；

【导师】 宋瑞清； 陈立新；

【作者基本信息】 东北林业大学 ， 森林保护学， 2013， 博士

【摘要】 土地作为一种不可再生的自然资源,是人类社会生存和发展的最重要条件之一,由于人类对土壤资源认识的不全面性,森林肆意砍伐、土地盲目开发,使的近年来土地耕地面积不断锐减,土壤质量迅速下降,生态环境受到严重破坏。高光谱遥感以其多波段且连续性、高分辨率等特点,及时、准确的获取大面积的土壤环境信息提供了依据,这对土壤质量监测、农业生产、生态环境维护与治理具有现实意义。以黑龙江省大庆地区土壤为研究对象,采用野外调查取样与室内高光谱(350-2500mn)数据测定、MODIS影像相结合的方法,采集126个土壤样本,构建基于偏最小二乘法(PLSR)和BP神经网络(BPNN)建立的土壤有机质SOM、全氮N、全磷P、全钾K、重金属(HM)、盐碱含量的光谱估算模型。同时利用MODIS影像对土壤各成分信息专题制图。研究结果显示：1)按照土壤类型和土地利用方式的不同,采集土样并分析土壤有机质SOM、全氮N、全磷P、全钾K、重金属(Co、Cd、F、Hg、V、Se、Cr、Cu、As、Pb、Ni、Mn、 Zn)、全盐量、总碱度和碱化度的含量。2)土壤机械组成,土壤水分,土壤有机质等是影响土壤光谱曲线特征的重要因素。当土壤中所含水分达到70%1临近饱和状态时,土壤的反射率极低,且1400nm和1900nm的两个水分吸收带随着土壤水分的增加,吸收峰随之变宽。3)土壤光谱预处理对于模型的建立起到决定性的作用,文本采取标准正态变量校正(Standard Normal Variate Transformation,SNV),多元散射校正(Multiplicative Scatter Correction,MSC)、数学运算组合、去包络线法(Continuum Removed)及衍生值等19种处理方式,土壤各指标含量与处理后的光谱指数的相关性显著提高。4)利用偏最小二乘PLSR和BP神经网络建立土壤有机质SOM、全氮N、全磷P、全钾K、重金属(Co、Cd、F、Hg、V、Se、Cr、Cu、As、Pb、Ni、Mn、Zn)全盐量、总碱度,碱化度的高光谱估算模型精度较高,RMSE较低,土壤各指标含量精确的估算是可行的。5)利用高光谱波段模拟MODIS多波段,并建立土壤SOM、全氮N、全磷P、全钾K、重金属(Co、Cd、F、Hg、V、Se、Cr、Cu、As、Pb、Ni、Mn、Zn)盐碱含量的偏最小二乘模型,大多数土壤指标估算精度在0.7以上,可实现精确的估算,全碱度、Hg和P模拟R2较低,只能用于粗略估算。6)根据偏最小二乘模型结果结合MODIS影像,对大庆地区土壤SOM、全氮N、全磷P、全钾K、重金属(Co、Cd、F、Hg、V, Se、Cr、Cu、As、Pb、Ni、Mn、Zn)、全盐量、总碱度和碱化度专题制图,建立较为精细的土壤信息空间分布图。更多还原

【Abstract】 As a non-renewable natural resource, soil is one of the crucial conditions that supports the survival and development of human society. Recent years, over deforesting and over developing with incomplete understanding of soil conditions caused a series of problems such as the declining of farmland, the soil degradation, and environment deterioration. Hyper spectral remote sensing technique with special advantages of high spectral resolution and strong band continuity. It can monitor and analyze crops vigor and soil environmental factors that affect crops production. These possess practical significance for agricultural production and soil quality monitoring, eco-environment management and maintenance.This research is taken place in Daqing of Heilongjiang province. The soil condition in this area is studied by integrating soil spectral characteristic (indoor reflectance measurements among350nm-2500nm and MODIS image. In this research,126soil samples was collected, SOM, total phosphorus (P), potassium (K), nitrogen (N),Heavy Metal(Co、Cd、F、Hg、 V、Se、Cr、C、As、Pb、Ni、Mn、Zn),Total salt,Total Alkalinity,Exchange Sodium Percentage(ESP) concentration were estimated by using the Partial Least Squares Regression (PLSR) and Back-Propagation Neural Network (BPNN) model. After that, MODIS images were used to create spatial distribution maps for soil contents. The results showed:(1) According to the different soil types and land use types, collected soil samples, analysis of SOM, N, P, K Heavy Metals (Co、Cd、F、Hg、V、Se、Cr、Cu、As、Pb、 Ni、Mn、Zn), Total Salt Total Alkalinity and ESP content.(2) Soil mechanical composition and soil moisture, soil organic matter and so on are the important factors that affect soil spectral curve features. When soil moisture content of70%is near saturation, The two absorption peaks of the moisture band width than before in band1400nm and1900nm.(3) Soil spectral preprocess play a decisive role for the establishing model. In the research we choice19kinds of preprocess.including Standard Normal variables, Multiplicative Scatter Correction, Mathematics, Continuum Removed and it’s the derivative value.The correlation index significantly increased between the index content and soil spectral after treatment.(4)Estimated SOM.Total N P K, Heavy Metal(Co、Cd、F、Hg、V、Se、Cr、Cu、 As、Pb、Ni、Mn、Zn),Total Salt, Total Alkalinity, ESP concentration by using the Partial Least Squares Regression (PLSR) and back-propagation neural network (BPNN) model.Model is high precision, low RMSE, it s feasible of accurate estimates for soil content.(5) Using hyper spectral bands to simulate MODIS band,then established SOM, Total N, P K, Heavy Metals (Co、Cd、F、Hg、V、Se、Cr、Cu、As、Pb、Ni、Mn、Zn). Total salt, Total Alkalinity, ESP by PLSR model.Most soil index estimation accuracy above0.7, Total alkalinity, Hg and P estimation accuracy is low, just only be used as a rough estimating.(6)Based on MODIS images and result of SMLR model, creating spatial distribution maps for s SOM, Total NPK, Heavy Metals (Co、Cd、F、Hg、V、Se、Cr、Cu、As、 Pb、Ni、Mn、Zn),Total Salt, Total Alkalinity and ESP in Daqing region.更多还原