黑土养分含量的航空高光谱遥感预测  

Prediction of black soil nutrient content based on airborne hyperspectral remote sensing

作　　者：杨越超 赵英俊[1] 秦凯[1] 赵宁博[1] 杨晨 张东辉[1] 崔鑫 Yang Yuechao;Zhao Yingjun;Qin Kai;Zhao Ningbo;Yang Chen;Zhang Donghui;Cui Xin(National Key Laboratory of Remote Sensing Information and Imagery Analyzing Technology,Beijing Research Institute of Uranium Geology,Beijing 100029,China;College of Urban Design,Wuhan University,Wuhan 430072,China)

机构地区：[1]核工业北京地质研究院遥感信息与图像分析技术国家级重点实验室,北京100029 [2]武汉大学城市设计学院,武汉430072

出　　处：《农业工程学报》2019年第20期94-101,共8页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家自然科学基金项目(41602333);东北黑土地1:25万土地质量地球化学调查(DD20160316);遥感信息与图像分析技术国家级重点实验室基金项目(ZJ2019-1)

摘　　要：为监测黑龙江省黑土典型区土壤的养分元素含量,综合利用统计理论与光谱分析方法,研究建三江农场黑土土壤的3类养分含量与土壤光谱之间的关系,建立土壤全氮、有效磷、速效钾含量高光谱反演模型,实现土壤养分元素含量定量预测。对黑土土壤航空高光谱数据进行处理,应用偏最小二乘回归(PLSR)和BP神经网络方法分别建立土壤养分元素含量的高光谱定量反演模型,结果表明:全氮PLSR和BP神经网络预测模型的RPIQ值(样本观测值第三和第一四分位数之差与均方根误差的比值)分别为2.42和2.80;有效磷PLSR和BP神经网络模预测型的RPIQ值分别为0.83和1.67;速效钾PLSR和BP神经网络模型的RPIQ值分别为2.00和2.33。试验证明土壤全氮和速效钾的光谱定量预测模型具备较好的精度和预测能力。但有效磷的预测效果不是特别理想,仅可达到近似定量预测的要求;全氮、有效磷和速效钾的预测精度,BP神经网络建模相比偏最小二乘建模有更好的精度和预测能力,预测精度分别提高6.5%、10.1%和6.6%。In order to improve the efficiency and accuracy of the quantitative prediction of soil nutrient content in black soil of Heilongjiang province,in this paper,we utilized statistical theory and spectral analysis method,researched the relationship of three kinds of soil nutrient content and soil spectrum to established hyperspectral inversion model of soil total nitrogen,available phosphorus,available kalium content.We acquired the aerial hyperspectral data by using CASI-1500 and SASI-600 linear array push-broom imaging spectrometers.Preprocessing of calibration and atmospheric radiation correction of Airborne Hyperspectral raw radiation data was studied.96 samples were evenly sampled.In order to increase the representativeness of samples,96 groups of samples were collected from 3-5 samples collected from 15 meters around the sampling point,and 1.5 kg was retained after mixing.After air-drying,mixing and grindingetc,it is used for the contents of total nitrogen,available phosphorus and available kalium were obtained through laboratory tests.The content of total nitrogen,available phosphorus and available kalium was determined by NaOH diffusion method,NaHCO3 extraction-molybdenum blue colorimetry and NH4OAC extraction-flame photometry.Referring to Kennard-Stone method,72 groups of representative samples were selected as model samples for nutrient content prediction,and 24 groups were model prediction samples.96 black soil samples were sorted according to nutrient content,and the spectral transformation in the visible near red range was analyzed.The change rule of total nitrogen is that the reflectance decreases with the increase of content.The first order differential spectra at 580 nm were significantly correlated with total nitrogen and available phosphorus content,with a correlation coefficient of-0.43 and-0.36,respectively.The first-order differential spectra at 1730-2200 nm were significantly correlated with K2O,and the maximum correlation coefficient was-0.31.Compared with the original spectral waveform,the cor

关 键 词：土壤 遥感 模型 偏最小二乘法 BP神经网络 

分 类 号：S15[农业科学—土壤学]