The Pingluo area, as an experimental study area in Yinchuan, has been subjected to major environmental degradation due to soil salinization problems. Soil salinization is one of the main problems of land degradation in arid and semiarid regions. In the present study, remote sensing was integrated with mathematical modeling to evaluate soil salinization adequately. To detect soil salinization, soil water content and electrical conductivity of soil samples were analyzed. The reflectance of soil samples was measured using a spectrometer (SR-3500) with 1024 bands. Indices of soil salinity, vegetation and drought were analyzed using Landsat images over the study area. Based on Landsat images, physicochemical analysis, reflectance of sensitive bands for soil salinization and environmental indices, canopy response salinity index (CRSI), perpendicular drought index (PDI) and enhanced normalized difference vegetation index (ENDVI), a new model was established for simulation and prediction of soil salinization in the study area. Correlation analyses and multiple regression methods were used to construct an accurate model. The results showed that green, blue and near-infrared light was significantly correlated with soil salinity and that the spectral parameters improved this correlation significantly. Therefore, the model was more effective when combining spectral parameters with sensitive bands with modeling. After mathematical transformation of soil reflectance, the correlations of bands sensitive to soil salinization were 0.739 and 0.7 for electrical conductivity and water content, respectively. After transformation of vegetation reflectance, the correlation coefficient of soil salinity became 0.577. After inversion of the model based on soil hyperspectral and water content, the significance became 0.871 and 0.726, respectively, which can be used to predict soil salinity and water content. The spectral soil salinity model had a coefficient of 0.739 for soil salinity prediction. Among the salinity indices, the CRSI was selected as the most significant, with R2 of 0.571, whereas the R2 for PDI reached only 0.484. Among the vegetation indices, the ENDVI had the highest response to soil salinity, with R2 of 0.577. After scale conversion, the correlation percentages between CRSI and measured soil salinity and between ENDVI and measured soil salinity increased to 16.2% and 8.5%, respectively. Following the correlation between PDI and soil water content, the percentage of correlation increased to 11.6%. The integration of hyperspectral remote sensing, ground methods and an inversion method for salinity is a very important and effective technique for rapid and nondestructive monitoring of soil salinization.
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1.
基于冠层反射和植被指数的华东地区叶面指数反演 总被引：4，自引：0，他引：4
1 IntroductionLeaf A rea Index (LA I), defined as half the all-sided leaf or needle surface per unit groundsurface (Chen and Black,1992),is an im portantparam eter to quantify leaf density and m onitorvegetation change.A tthe sam e tim e,LA I is also an i… 相似文献
2.
Remote Sensing Inversion for Simulation of Soil Salinization Based on Hyperspectral Data and Ground Analysis in Yinchuan,China 总被引：2，自引：0，他引：2
Wu Dan Jia Keli Zhang Xiaodong Zhang Junhua Abd El-Hamid Hazem T. 《Natural Resources Research》2021,30(6):4641-4656
3.
The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper. The procedure was: (1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images; (2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated; (3) the relationship models between LAI and biomass were built and annual branch, stem, root and maximum leaf biomass over the landscape were simulated; (4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained. The simulation was based on spatial analysis module GRID in ArcInfo software. The method is also a kind of scaling method from patch scale to landscape scale. A case study of Changbai Mountain Nature Reserve was dissertated. Analysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995. 相似文献
4.
基于遥感和地面数据的景观尺度叶面积指数和生物量的模拟 总被引：3，自引：0，他引：3
The method for simulating the temporal and spatial distribution patterns of leaf area index (LAI) and biomass at landscape scale using remote sensing images and surface data was discussed in this paper,The procedure was:(1) annual maximum normalized difference vegetation index (NDVI) over the landscape was calculated from TM images;(2) the relationship model between NDVI and LAI was built and annual maximum LAI over the landscape was simulated;(3) the relationship models between LAI and biomass were built and annual branch ,stem ,root and maximum leaf biomass over the landscape were simulated;(4) spatial distribution patterns of leaf biomass and LAI in different periods all the year round were obtained.The simulation was based on spatial analysis module GRID in ArcoInfo software ,The method is laso a kind of scaling method from patch scale to landscape scale ,A case study of Changbai Mountain Nature Reserve was dissertated ,Aalysis and primary validation were carried out to the simulated LAI and biomass for the major vegetation types in the Changbai Mountain in 1995. 相似文献
5.
利用6S模型结合暗目标法确定TM过境时的最优气象能见度,分别使用MODIS气溶胶产品(MOD04)、最优气象能见度作为TM的气溶胶光学厚度,对黄河源区的Landsat TM数据进行大气校正。以同步野外实测地面数据为标准,比较了两种气溶胶参数输入方法的校正结果,并从光谱曲线、植被指数、草地生物量的估算三方面探讨了大气校正的效果,两种气溶胶参数输入方法均可以对遥感图像进行有效的大气校正,消除因散射增加的辐射能量,同时补偿因吸收而损失的辐射能量。经过大气校正后的TM光谱更接近真实地表光谱,更有助于地物真实光谱信息的提取,同时对与该地区相似气候条件下影像的大气校正有借鉴意义。 相似文献
6.
用TM影像和DEM获取黑河流域地表反射率和反照率 总被引：28，自引：13，他引：15
传统的大气校正方法原理比较复杂,而且有些参数特别是实时的大气剖面资料难以获取。本文利用DEM对TM 影像进行地形校正后,用简便而又实用的方法对TM影像进行了大气校正,较精确地反演出黑河流域河西走廊中段对应于Landsat TM 1~5 和7波段的地表反射率。在此基础上,通过不同波段地表反射率的组合,获得了地表反照率。通过与实地观测数据对比分析,表明对于植被覆盖区用TM 2,4,7波段组合结果较好,而在非植被覆盖区用TM 1~5,7这6 个波段组合结果更佳。 相似文献
7.
8.
热带森林植被生物量与遥感地学数据之间的相关性分析 总被引：14，自引：6，他引：14
以我国云南省西双版纳的热带森林为例,对热带森林植被生物量与遥感地学数据之间的相关性进行了分析。首先,利用森林资源连续清查的林业固定样地数据计算出各样地的森林植被生物量,并建立其GIS数据库。然后,对遥感图像进行几何校正,并对遥感图像进行主成分变换、缨帽变换以及植被指数的计算来产生其派生数据。其次,将样地数据、遥感数据及其派生数据,地形和气象数据转换到统一的坐标系和投影下,并将其内插为30米分辨率的格网数据。最后,进行样地森林植被生物量与其遥感地学数据之间的相关性分析。该分析表明,森林植被的生物量与年降雨量和第二主成分在0·01的水平上相关显著,而与中红外植被指数、LANDSATTM5、缨帽变换的亮度、湿度以及第一主成分在0·05的水平上相关显著。其中,与年降雨量的相关性最高,达到0·308;其次是与第二主成分,达到-0·231;再次是与中红外植被指数和LANDSATTM5,其相关系数分别为0·203和-0·201。 相似文献
9.
归一化水汽指数与地表温度的关系 总被引：7，自引：4，他引：3
城市热岛的遥感研究,传统上主要利用归一化植被指数作为指标来评估地表温度-植被之间的关系。本研究探讨了以归一化水汽指数作为评估其与地表温度关系的适应性,比较了归一化水汽指数和归一化植被指数在表达城市热岛效应方面的效力。利用"单窗算法"和3个不同时段的TM/ETM+数据获取了珠江三角洲核心区域的地表温度分布图,分析了两种指数与地表温度之间的关系。对局部区域逐像元和对区域总体分析的结果表明:不同时段的地表温度与归一化水汽指数之间均存在较强的线性关系,而地表温度与归一化植被指数之间的线性关系相对较弱。说明在城市化的环境下,与传统上常用归一化植被指数作为指标来定量分析地表温度相比,归一化水汽指数提供了一种互补的、甚至更加有效的衡量指标。 相似文献
10.
以渭-库绿洲为例,基于Landsat8 OLI遥感数据,考虑到短波红外特征与土壤水分有很好的关联,将短波红外波段引入可见光-近红外波段构成的传统植被指数中,旨在建立新的植被指数监测土壤水分。基于改进前后共8种植被指数,通过灰色关联分析（GRA）筛选出3种高关联度植被指数,再用偏最小二乘回归（PLSR）进行建模,然后用该模型对研究区土壤水分反演,并对其空间分布格局进一步分析。结果显示：（1）在传统植被指数的基础上引入信息量较大的短波红外,可大幅度降低植被指数间的VIF,消除其多重共线性。（2）通过GRA分析可知,改进后的植被指数与土壤水分之间的关联度均要高于传统植被指数。（3）通过GRA分析筛选出3种高关联度植被指数建立得到精度较高,稳定性较好的PLSR模型,并反演研究区土壤水分分布状况,土壤水分总体上至西向东,由北到南降低,然而土壤水分最小值主要分布在绿洲—荒漠交错带,使得交错带成为“生态裂谷”。研究表明：将短波红外波段引入到可见光-近红外植被指数中,建立的新植被指数可获得较好的土壤水分空间分布反演结果。 相似文献
11.
We present a remotely-sensed degradation assessment technique based on the measurement of landscape heterogeneity (a key determinant of degradation status). The moving standard deviation index (MSDI) is derived by passing a moving standard deviation filter across the Landsat TM band 3 (red band). Degraded/unstable landscapes exhibit higher MSDI values than their undisturbed/stable counterparts. Significant differences in MSDI were detected (p<0·001) across four fence-lines which separated rangeland of contrasting condition. The relationship of the index to normalized difference vegetation index (NDVI) was tested in five different ecosystems and significant correlations were obtained in all cases (p<0·001). We propose the MSDI as a powerful adjunct to vegetation indices. 相似文献
12.
为探索快速提取典型绿洲棉田土壤盐分的有效方法,获取区域尺度的土壤盐渍化特征及空间分布,进而为土壤盐渍化防治提供参考。以新疆兵团农二师31团为研究区域,2019、2021年春季Landsat 8 OLI多光谱影像和野外实测土壤含盐量为数据源,将波段组、光谱指数组和全变量组作为模型输入变量组,采用多元逐步回归（Multiple stepwise regression, MSR）、偏最小二乘回归（Partial least squares regression, PLSR）、极限学习机（Extreme learning machine, ELM）、支持向量机（Support vector machine, SVM）和BP神经网络（Back propagation neural network, BPNN）构建基于3个输入变量组的土壤盐分遥感反演模型,探究输入变量和建模方法对模型精度的影响效果,通过对比确定春季土壤盐分最优反演模型,定量反演地表土壤含盐量。结果表明：（1） 研究区主要为非盐化土和轻度盐化土,总样本变异系数为0.67,呈中等变异性;光谱反射率与土壤盐渍化程度的关系表现为土壤盐渍化越重,光谱反射率越高。（2） 海岸波段（b1）、蓝波段（b2）、绿波段（b3）、红波段（b4）和盐分指数（SI1、SI2、SI3、SI4、S3、S4、S5）均通过显著性检验P<0.01,相关系数均达到0.4以上。（3） 所有模型中,基于全变量组建立的BPNN反演模型精度最高,建模集R2为0.705;验证集R2为0.556。（4） 由反演结果可知,2019、2021年春季耕作区土壤主要为非盐化土,分别占耕作区总面积的55.55%和64.62%,其次为轻度盐化土,分别占44.31%和35.17%;2021年土壤盐渍化程度较2019年有所减轻。 相似文献
13.
地表参数反演及城市热岛时空演变分析 总被引：8，自引：0，他引：8
采用TES算法实现了ASTER地表温度的反演,在对发射率估算方法改进基础上,利用单窗算法反演1989年TM地表温度。结合C地形校正,利用线性光谱模型提取植被覆盖度与城市不透水面密度,利用反射率提取NDVI。从多方面对城市热岛时空演变进行综合研究,研究表明,与等间距法相比,均值-标准差法可以较合理地刻画地表热场的分布,一定程度上可以避开不同时相的差异。最后时空对比及空间统计学分析显示,1989~2004年间福州市城市热岛面积、热岛强度都有所增加,城市热岛总体趋势为西北-东南走向,并逐渐向北-南方向偏移,而且城市热岛重心向东南方向偏移。 相似文献
14.
Hydrocarbon Alteration Characteristics of Soils and Mechanism for Detection by Remote Sensing in East Sichuan Area,China 总被引：1，自引：0，他引：1
The type, strength, and spatial distributions of hydrocarbon alteration of the surface soil are studied in two sections in East Sichuan area through the simultaneous analysis of soil organic geochemistry, soil mineralogy, and soil chemistry. The spectral response and remote-sensing mechanism are studied through the soil spectral analysis in the range of VIS--NIR bands. The results of this study demonstrate that long-time hydrocarbon microseepage can induce mineral and chemical alteration of surface soil, including the increase of clay-mineral content and carbonate-mineral content, the increase of ferrous-iron content, and decrease of ferric-iron content. Soil mineral components related to hydrocarbon alteration have spatial coincidence with soil organic geochemical components. Increase of clay- and carbonate-mineral contents in the soil can cause decrease of reflectance in VIS–NIR bands and increase of Landsat band ratio TM5/TM7. Increase of ferrous-iron content and decrease of ferric-iron content in the soil may cause increase of reflectance in the range of 400 nm to 600 nm, and higher reflectance of Landsat band ratios of TM1/TM3 and TM2/TM3. 相似文献
15.
洪河自然保护区乌拉苔草生物量高光谱遥感估算模型 总被引：6，自引：0，他引：6
尝试用不同方法构建洪河自然保护区湿地植被乌拉苔草(Carex meyeriana)的高光谱植被指数,建立水上鲜/干生物量高光谱估算模型,并比较了不同模型的反演精度。通过实测不同覆盖度和水深状况下乌拉苔草的冠层高光谱反射率与水上生物量的数据,采用高光谱可见光—近红外波段及其微分光谱波段(350~1 050 nm)逐波段构建FNDVI、FRVI、FDVI、FDNDVI、FDRVI、FDDVI植被指数,分别找出与水上鲜生物量和干生物量具有最佳相关性波段组合的植被指数,建立乌拉苔草水上生物量的最佳估算模型,并对比分析了反射率光谱植被指数(FNDVI、FRVI、FDVI)模型和微分光谱植被指数(FDNDVI、FDRVI、FDDVI)模型的反演精度。结果显示,微分光谱与乌拉苔草水上生物量的相关性比反射率光谱好;微分光谱植被指数与乌拉苔草水上生物量的相关性比反射率光谱植被指数好,尤其以微分光谱植被指数FDRVI与FDNDVI建立的二次函数模型反演乌拉苔草的水上鲜生物量和干生物量的效果最好,精度分别达74.9%、71.4%,其均方根误差分别为0.074 4和0.026 2,通过了p<0.01极显著验证。这表明,采用微分光谱植被指数FDRVI、FDNDVI对乌拉苔草水上鲜生物量和干生物量的估算可以取得较高的预测精度。 相似文献
16.
绿洲植被覆盖度遥感信息提取——以敦煌绿洲为例 总被引：1，自引：0，他引：1
以敦煌绿洲为研究区,利用Landsat TM遥感数据,通过归一化植被指数(NDVI)和混合像元分解两种方法,提取了敦煌绿洲的植被覆盖度信息。在基于NDVI提取植被覆盖度时,选取了基于NDVI的像元二分模型; 在混合像元分解过程中,对遥感影像进行波段反射率归一化处理和最小噪声变换(MNF),确定了3个类型端元:植被、不透水表面/土壤、水体/阴影; 最后利用高分辨率遥感影像验证对比了两种提取方法的精度。结果表明:混合像元分解更能准确地提取敦煌地区植被覆盖度信息,其线性相关系数为0.8915,均方根误差为0.0882,而且提取结果更符合实际情况,可以为敦煌植被状况监测及生态环境保护提供科学建议。 相似文献
17.
棉花叶面积指数（LAI）是描述其长势的重要指标,准确获取冠层结构参数是叶面积指数反演的必要条件。以ScoutB-100油动单旋翼无人机为飞行平台,搭载RIEGL VUX-1激光雷达,精确获取棉花高密度点云数据,得到研究区棉田数字表面模型（DSM）和数字高程模型（DEM）,通过差值运算获得其冠层高度模型（CHM）,进而提取有效的冠层结构参数。利用相关性分析法选取相关系数大于0.2的激光穿透力指数（LPI）、回波点云密度（D）、孔隙率（fgap）、归一化高程值（VnDSM）构建棉花LAI反演模型,并与实测叶面积指数进行精度验证与评价。实验结果表明：模型估算的LAI与实测LAI之间的决定系数为0.824,均方根误差为0.072,验证了模型的可靠性。 相似文献
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19.
基于遥感技术的银川市土地利用/覆被研究 总被引：1，自引：2，他引：1
为消除地形复杂地区不同地物的同谱异物现象,在遥感(RS)和地理信息系统(GIS)技术的支持下,采用分区分类方法对宁夏银川市1991和1999年的Landsat TM/ETM 影像进行解译,得到了银川市两期土地利用/覆被变化数据。在此基础上,通过转移矩阵和土地利用/覆被变化幅度、动态度及状态指数模型,对银川市土地利用/覆被变化的状况和变化过程进行了研究。结果表明,在研究期内,银川市各土地利用/覆被变化类型都有不同程度的变化。林地、耕地和城市用地转入大于转出,朝着规模增加的方向发展,而草地和水体转出大于转入,朝着规模缩小的方向发展,未利用地虽然转入大于转出,但变化缓慢;土地利用/覆被年变化率最大的是草地,其次为耕地,未利用地的最小。 相似文献
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