基于LST-EVI特征空间的土壤水分含量反演

干旱是人类历史上的重大自然灾害之一,而土壤水分是干旱监测最重要的指标。利用遥感手段反演地表土壤水分,可以充分反映土壤水分的时空变化特征,适合进行大范围动态监测。研究基于Landsat TM数据,运用普适性单通道算法得到地表温度(LST,Land Surface Temperature),然后选用增强型植被指数(EVI,Enhanced Vegetation Index),构建了LST\|EVI特征空间,计算出温度植被干旱指数(TVDI,Temperature\|Vegetation Dryness Index)。在对实测土壤含水量数据和对应TVDI值进行回归分析的基础上,反演出2010年6月14日黄骅市自然地表20 cm深度处的体积含水量。结果表明:TVDI方法在该研究区是完全可行的,拟合精度较高;研究区自然地表土壤体积含水量分布差异明显,中等含水量地区面积最大,西南和部分北部地区含水量较低,而含水量高的区域主要分布在苇洼和沿海地区。     

基于Sentinel-1及 Landsat 8数据的黑河中游农田土壤水分估算

土壤水分是陆地表层系统中的关键变量。利用主动微波遥感,特别是合成孔径雷达(Synthetic Aperture Radar,SAR)的观测,在监测和估计表层土壤水分时空分布方面已开展了诸多研究。然而,SAR土壤水分反演仍存在诸多挑战,特别是地表粗糙度和植被的影响。因此,本文提出了一种结合主动微波和光学遥感的优化估计方案,旨在同步反演植被含水量、地表粗糙度和土壤水分。反演算法首先在水云模型的框架下对模型中的植被透过率因子(与植被含水量密切相关)采用3种不同的光学遥感指数——修正的土壤调节植被指数(Modified Soil Adjusted Vegetation Index,MSAVI)、归一化植被指数(Normalized Difference Vegetation Index,NDVI)和归一化水体指数(Normalized Difference Water Index,NDWI)进行参数化估计,用于校正植被层的散射贡献。在此基础上,构造基于SAR观测和Oh模型的代价函数,利用复型洗牌全局优化算法进行土壤水分和地表粗糙度的联合反演。采用Sentinel-1 SAR和Landsat 8多光谱数据在黑河中游开展了反演试验,并利用相应的地面观测数据对结果进行了验证。结果表明反演结果与地面观测具有良好的一致性,其中基于NDWI的植被含水量反演效果最佳,与地面观测比较,土壤水分决定系数(R 2)在0.7以上,均方根误差(RMSE)为0.073 m^ 3/m^ 3;植被含水量R 2大于0.9,RMSE为0.885 kg/m 2,表明该方法能够较准确地估计土壤水分。同时发现植被含水量的估计结果,以及植被透过率的参数化方案对土壤水分的反演精度有一定的影响,在未来的研究中需要进一步探索。     

归一化植被指数的土壤背景影响去除

植被冠层归一化植被指数(normalized difference vegetation index,NDVI)由于不同土壤背景的混入干扰,导致利用NDVI信息对作物长势监测等应用的有效性降低。以安徽省来安县小麦农田为研究区,以2种土壤类型(水稻土和黄褐土)背景下拔节期冬小麦为研究对象,采用实测小麦冠层光谱及叶面积指数(leaf area index,LAI)数据,利用传统的照相法求算植被覆盖度,基于混合光谱理论,提出2种NDVI土壤背景影响去除模型(NDVIT),对模型进行对比验证。研究结果表明:2种模型均可去除一定的土壤背景影响;采用信噪比的分析方法定量研究2种模型抵抗土壤噪声影响的能力,分析发现NDVI1T提取植被信息抗土壤噪声能力更佳;2种土壤背景影响去除模型和NDVI的拟合关系良好,相关关系R~2均达到0.9以上。     

利用温度植被干旱指数反演三峡库区土壤水分

土壤水分是监测土地退化的一个重要指标,是气候、水文、生态、农业等领域的主要参数,在地表与大气界面的水分和能量交换中起重要作用。传统的监测土壤水分的方法只能得到单点的数据,很难获得大范围地区的土壤湿度。遥感能够快速方便地获取大区域的地表信息,因此使用遥感监测土壤水分意义重大。主要利用了温度指标干旱指数对三峡库区进行土壤水分反演及其验证。利用TM6波段的亮温方程,计算得出地表温度（Ts）,以TM3、TM4波段计算得出归一化植被指数（NDVI）;把Ts和NDVI作为基本参数,根据Ts-NDVI特征空间的形状,取中间范围的NDVI,拟合干湿边方程,确定干湿边参数;根据温度植被干旱指数（TVDI）进行土壤湿度等级划分。结果表明,利用TVDI可以很好地反演出地表的土壤湿度信息。     

基于MODIS数据的渭河流域土壤水分反演

利用MODIS产品数据MOD11A1、MOD13A2和MOD15A2获取地表温度(TS)、昼夜温差(TSD)、表观热惯量(ATI)、归一化植被指数(NDVI)、增强植被指数(EVI)、叶面积指数(LAI),构建渭河流域2006年8月1日、8月6日的TS-NDVI、TS-EVI、TS-LAI、TSD-NDVI、TSD-EVI、TSD-LAI、ATI-NDVI、ATI-EVI、ATI-LAI特征空间,根据TS-NDVI、TS-EVI、TS-LAI、TSD-NDVI、TSD-EVI、TSD-LAI、AI-NDVI、ATI-EVI、ATI-LAI特征空间建立了温度归一化植被指数型干旱指数(TNDI)、温度增强植被指数型干旱指数(TEDI)、温度叶面积指数型干旱指数(TLDI)、温差归一化植被指数型干旱指数(DTNDI)、温差增强植被指数型干旱指数(DTEDI)、温差叶面积指数型干旱指数(DTLDI)、表观热惯量归一化植被指数型干旱指数(ANDI)、表观热惯量增强植被指数型干旱指数(AEDI)、表观热惯量叶面积指数型干旱指数(ALDI),并以这些干旱指数作为土壤水分监测指标,反演了渭河流域2006年8月1日、8月6日的土壤水分.利用TDR实测10cm土壤水分进行相关分析表明: TEDI、TNDI、TLDI在高植被覆盖的地区、低植被覆盖的地区进行土壤水分反演和干旱监测都能取得较好的效果,其中TEDI效果最好;DTNDI、DTEDI、DTLDI、ANDI、AEDI、ALDI比较适合在低植被覆盖的地区进行土壤水分反演和干旱监测,但在高植被覆盖的地区效果较差,不适合进行土壤水分反演和干旱监测.     

NDWI与NDVI指数在区域干旱监测中的比较分析——以2003年江西夏季干旱为例

植被水分指数NDWI是基于短波红外（SWIR）与近红外（NIR）的归一化比值指数。与NDVI相比，它能有效地提取植被冠层的水分含量；在植被冠层受水分胁迫时，NDWI指数能及时地响应，这对于旱情监测具有重要意义。结合2003年夏季MODIS影像数据和地面气象数据，以江西省内一片农田和一片林地为试验区域，分析比较了NDWI与NDVI距平值在短期旱情监测中的有效性。监测结果表明， NDWI对植被冠层水分信息比NDVI更为敏感；在短期干旱监测中，NDWI指数能准确地反映旱情的时空变化。     

利用NOAA数据分析中国地区植被覆盖变化周期

对中国地区连续数年的改进的高解析度传感器（AVHRR）均一化植被指数（NDVI）时间序列数据进行研究，利用时间序列谐波分析（HANTS）算法对NDVI数据进行去云处理，同时计算NDVI时间序列的特征分量，用以分析地表植被覆盖的生长周期性变化特性，从而了解地表植被覆盖情况。研究HANTS之后提取出的NDVI傅里叶特征分量。得知0频率表明了全年植被覆盖率均值，1、2频率谐波分量简明地描述了观测点的全年与半年幅值与相位值；1频率谐波的幅值表明了全年中植被生产率的变化，1频率谐波的相位值表明了植被绿度的时间变化快慢；2频率谐波表示的是半年的植被覆盖强度以及时间变化率。     

基于Landsat ETM+遥感数据的组分温度反演方法研究

地表温度在干旱监测和模拟地表热通量中有重要作用。在干旱半干旱地区,双源能量平衡模型(TSEB)通常用于计算地表的热通量。以黑河中游典型灌区为研究区域,选取4个时相的Landsat-7 ETM+遥感影像,通过植被指数与TSEB模型结合的方法反演土壤表面温度和植被冠层温度,并重点讨论土壤表面温度和植被冠层温度的分解算法。结果表明:土壤表面温度和植被冠层温度具有较好的时空一致性;土壤表面温度与植被冠层温度的反演精度通过地表净辐射与地表热通量得到了间接验证。地表净辐射与地表热通量的计算值与观测值相关性好,相关系数大于0.92。地表净辐射与地表热通量的线性回归分析表明拟合精度高。通过地表温度分解的方法获得的土壤表面温度和植被冠层温度,对监测典型区域的干旱和模拟地表热通量是可行的。     

遥感干旱指数在洛川苹果干旱监测中的适用性分析

目前对苹果干旱研究较少且主要运用站点数据,对空间信息表征有限,遥感干旱指数可用于大范围干旱时空动态监测,但在苹果干旱监测中的适用性还有待研究。基于2014~2018年MODIS反射率、地表温度以及地表覆被数据,结合土壤湿度数据和野外调查资料,分析洛川苹果区温度植被干旱指数（TVDI）、归一化植被水分指数（NDWI）、植被供水指数（VSWI）与10 cm深度土壤湿度（SM）的一致性,探索遥感干旱指标对土壤干湿状况表征能力,并进一步研究遥感干旱指标对干旱响应敏感时段。结果表明：①由增强型植被指数（EVI）计算的VSWI与SM的时空一致性最好,其在2014、2017年表现出的干旱特征与实际旱情相符;②VSWI（EVI）和TVDI（EVI）与SM的相关性分别高于VSWI（NDVI）和TVDI（NDVI）与SM的相关性,使用EVI能提高VSWI和TVDI对干旱的表征能力;③TVDI、NDWI、VSWI对SM存在不同时间的反应滞后,滞后3时相（24 d）的VSWI（EVI）与SM的相关性最高,而NDWI对SM滞后时间短,对干旱响应较及时,结合VSWI（EVI）和NDWI可能更有利于监测苹果干旱;④在不同苹果生育期,遥感指标对土壤湿度敏感性不同,VSWI在不同生育期敏感性差异最明显：新梢旺长期（5、6月）对土壤湿度敏感性高于萌芽开花期、果实膨大期、成熟期;该结果符合洛川县苹果不同生育期需水规律和洛川降水、干旱发生特征。研究结果可为遥感监测苹果干旱提供参考依据。     

基于Landsat-5 TM数据的河南省白沙灌区地表温度反演研究

地表温度是土壤水分和植被水分状态的指示计,在干旱遥感监测中有重要作用。应用Landsat-5 TM遥感数据和气象资料,利用归一化植被指数(NDVI)区分地表覆盖类型,采用Van de Griend的经验公式法结合典型地表赋值法计算出地表比辐射率。用单窗算法和单通道算法分别对河南省白沙灌区地表温度进行反演,结果表明:两种方法均能较好地将白沙灌区地表温度分布趋势反映出来,单窗算法的反演精度较高,绝对误差为1.1 ℃,更适宜白沙灌区的地表温度反演,进而可以提高灌区旱情遥感监测精度。     

Associated changes in physiological parameters and spectral reflectance indices in olive (Olea europaea L.) leaves in response to different levels of water stress

This study aimed to determine whether modification of physiological parameters could be detected remotely by monitoring the spectral reflectance of olive leaves in response to different degrees of drought. Three different drought intensities were simulated: (a) a mild drought by feeding abscisic acid to detached branches; (b) a rapid and severe drought by detaching leaves and letting them dry over several hours; (c) a relatively slow drought caused by withholding water to potted olive plants. The three degrees of stress affected gas exchange and chlorophyll fluorescence. When the inhibition of photosynthesis occurred within an hour it was not accompanied by a parallel reduction in chlorophyll concentration in the carotenoid to chlorophyll ratio. Consequently, changes in spectral reflectance in the visible region, e.g. in PRI (photochemical reflectance index) and FRI (fluorescence reflectance indices) were not significantly induced. In contrast, when the inhibition of photosynthesis caused by slow developing drought was prolonged (i.e. more than 24 hours) and led to a decrease in chlorophyll concentration and to a simultaneous increase in carotenoid to chlorophyll ratio, there were significant changes in the visible region of the leaf spectral reflectance and, in turn, in PRI and FRI. We defined 16 new reference wavelengths, from visible to SWIR regions, which are sensitive to both fast‐developing and slow‐developing stresses. These reference wavelengths were used to develop an algorithm, the Relative Reflectance Increment (RRI), that was linearly related to changes in relative water content (RWC, r ² = 0.733). This algorithm showed that the 1455 nm wavelength is highly affected by drought. This wavelength was therefore used to elaborate the water content reflectance index that was inversely related to RWC (r ² = 0.702).     

Observation of flooding and rice transplanting of paddy rice fields at the site to landscape scales in China using VEGETATION sensor data

A unique physical feature of paddy rice fields is that rice is grown on flooded soil. During the period of flooding and rice transplanting, there is a large proportion of surface water in a land surface consisting of water, vegetation and soils. The VEGETATION (VGT) sensor has four spectral bands that are equivalent to spectral bands of Landsat TM, and its mid-infrared spectral band is very sensitive to soil moisture and plant canopy water content. In this study we evaluated a VGT-derived normalized difference water index (NDWI VGT =(B3-MIR)/ (B3+MIR)) for describing temporal and spatial dynamics of surface moisture. Twenty-seven 10-day composites (VGT- S10) from 1 March to 30 November 1999 were acquired and analysed for a study area (175 km by 165 km) in eastern Jiangsu Province, China, where a winter wheat and paddy rice double cropping system dominates the landscape. We compared the temporal dynamics and spatial patterns of normalized difference vegetation index (NDVI VGT ) and NDWI VGT . The NDWI VGT temporal dynamics were sensitive enough to capture the substantial increases of surface water due to flooding and rice transplanting at paddy rice fields. A land use thematic map for the timing and location of flooding and rice transplanting was generated for the study area. Our results indicate that NDWI and NDVI temporal anomalies may provide a simple and effective tool for detection of flooding and rice transplanting across the landscape.     

不同含水量黄棕壤反射光谱特征研究

采用多光谱辐射仪(MSR～16R)对自然条件下不同水分含量黄棕壤光谱特征进行了研究，试验结果表明在可见光部分(460～710nm)，土壤含水量与光谱反射率相关性差，而在红外部分(760～1650nm）土壤含水量与光谱反射率达到极显著负相关，模式方程拟合度都在0．86以上，因此通过测定土壤光谱反射率来推算土壤含水量是可行的。应用地面光谱测量试验的结果，本文讨论了由地面光谱测量来推算土壤含水量向由卫星遥感影像反演土壤含水量过渡的可能性，进而对采用TM遥感影像对黄棕壤分布区土壤水分状况实施遥感监测的可行性作了一些探访。     

Assessing the sensitivity of MODIS to monitor drought in high biomass ecosystems

Drought monitoring is important to analyse the influence of rainfall deficiency patterns on bushfire behaviour. Remote sensing provides tools for spatially explicit monitoring of drought across large areas. The objective of this study was to assess the performance of MODIS-based reflectance spectral indices to monitor drought across forest and woodland vegetation types in the fire prone Sydney Basin Bioregion, NSW, Australia. A time series of eight spectral indices were created from 2000 to 2009 to monitor inter-annual changes in drought and were compared to the Standardized Precipitation Index (SPI), a precipitation deficit/surplus indicator. A pixel-to-weather station paired correlation approach was used to assess the relationship between SPI and the MODIS-based spectral indices at different time scales. Results show that the Normalised Difference Infrared Index—band 6 (NDIIb6) provided the most suitable indicator of drought for the high biomass vegetation types considered. The NDIIb6 had the highest sensitivity to drought intensity and was highly correlated with SPI at all time scales analysed (i.e., 1, 3 and 6-month SPI) suggesting that variations in precipitation patterns have a stronger influence on vegetation water content than vegetation greenness properties. Spatial similarities were also found between patterns of NDIIb6-based drought maps and SPI values distribution. NDIIb6 outperformed the spectral index currently in use for operational drought monitoring systems in the region (Normalised Difference Vegetation Index, NDVI) and its implementation in existing drought-monitoring systems is recommended.     

TVDI在冬小麦春季干旱监测中的应用

应用冬小麦春季生长期的NOAA/AVHRR资料,反演归一化植被指数（NDVI）、土壤调整植被指数（SAVI）和下垫面温度（T_s）,分析了植被指数和下垫面温度空间特征,采用温度植被旱情指数（TVDI）,研究了河北省2005年3~5月的冬小麦旱情状况。结果表明：基于SAVI的温度植被旱情指数与土壤表层相对湿度的相关性好于基于NDVI的温度植被旱情指数。通过与气象站土壤水分观测资料进行相关性分析,表明温度植被旱情指数与10 cm土壤相对湿度关系最好,20 cm次之,50 cm较差。因此,基于SAVI的温度植被旱情指数更适于监测冬小麦春季的旱情。     

A re‐examination of perpendicular drought indices

In this letter, the performance of newly developed drought indices, the perpendicular drought index (PDI) and modified perpendicular drought index (MPDI), are further explored for regional surface dryness monitoring to provide clear guidance on appropriate implementation of these indices over different eco‐systems through in‐depth analysis of their advantages and constraints. Spatio‐temporal patterns of surface drought derived by MODerate Resolution Imaging Spectroradiometer (MODIS)‐based PDI and MPDI are compared against field‐measured soil moisture (SM), rainfall, and regional hydrological conditions. Results indicate that there are significant negative correlations between the PDI, the MPDI, and mean 0–20 cm SM content and rainfall. The PDI and the MPDI provide similar results at the early stage of vegetation growth, but a greater agreement between the drought information extracted by the MPDI and field measurements is observed for vegetated surfaces where the PDI fails. Therefore, it is recommended that PDI be used for bare soil applications, since it does not require calculation of additional information such as the fraction of vegetation which may contain some uncertainties, but the MPDI should be used for vegetated regions.     

麦田土壤水分NOAA/AVHRR遥感监测方法研究

本文立足于河南省农业遥感业务服务实际,在系统研究麦田土壤水分NOAA/AVHRR遥感监测理论、模型、资料处理、指标及应用技术的基础上,针对这一领域中存在的问题,在GIS技术的支持下,重点探讨了不同土壤质地和风速对遥感干旱监测的影响、用遥感表层土壤水分耦合深层土壤水分的方法与模型、用单时相遥感资料反演土壤水分的方法等,并最终建立了河南省冬小麦干旱遥感监测应用服务系统。     

Precision Evaluation of Drought Index based on CCI Soil Moisture Products and Its Effect on Grain Yield in Northeast China

Soil moisture is the basic factor for monitoring crop drought. Based on the microwave remote sensing soil moisture products of ESA from 1978 to 2014, the statistical database of China's economic and social development and meteorological data, combined with the Soil Moisture Deficit Index (SWDI), the relationship between the degree of drought in Northeast China and corn yield was analyzed. The results show that: (1) the drought level of the three provinces is increasing from northeast to southwest; (2) the SWDI drought index calculated based on CCI (Climate Change Initiative) soil moisture products has a good correlation with rainfall and temperature, which can be used to evaluate the severity of drought; (3) the correlation between SWDI and maize yield is the best in the key water demand period (July), and R2 of Heilongjiang, Jilin and Liaoning provinces are 0.43, 0.78 and 0.38 respectively, which is very suitable for quantifying the effect of drought on maize yield. This conclusion has important guiding significance for the study of the influence of soil moisture content on crop yield and the relevant agricultural decision-making.