对于定量热红外遥感的一些思考

作者根据在热红外遥感工作中的长期实践经验,介绍了热红外遥感的现状,特别指出了定量反演地表温度的难点---地物比辐射率的测定和区域范围内的比辐射率估算。文中提出了定量热红外遥感研究中常见的一些问题。最后,讨论了定量热红外遥感的未来发展趋势和目前现实工作的对策,旨在抛砖引玉,以求得热红外定量遥感的发展。     

陆地卫星TM6波段范围内地表比辐射率的估计

地表比辐射率是用热红外波段遥感数据反演地表温度的关键参数。目前,应用陆地卫星TM6波段数据反演地表温度共有3种算法,即大气校正法、单窗算法和单通道算法。这3种算法都需要TM6波段范围内的地表比辐射率作为地表温度反演参数。本文首先简介这3种反演算法;然后着重探讨TM6波段地表比辐射率估计方法;最后,利用这一方法对山东省陵县附近农田地区进行地表比辐射率估计和地表温度反演。结果表明,该方法能获得较合理的地表温度反演结果。     

用MODIS影像和单窗算法反演环渤海地区的地表温度

在对地观测卫星MODIS的16个热红外波段中,其中有5个波段是针对地表温度来设计的,其中第31(10.78-11、28μm)和32(11．77-12．27μm)与TM的第6波段区间基本相同。运用单窗算法分别对这2个波段建立方程,然后通过对布郎克方程的辐射率和温度计算模拟,发现温度和辐射率近似线性相关,由此建立辐射率与温度T的线性方程,从而可以简化单窗算法的计算过程一最后运用单窗算法对31和32通道分别反演了环渤海地区的温度分布,并对环渤海地区的土地资源环境作了分析.     

一个针对ASTER数据同时反演地表温度和比辐射率的四通道算法

本文利用对地观测卫星多传感器的特点，提出了针对ASTER数据同时反演地表温度和比辐射率的多通道算法。即利用ASTER数据的第11，12，13，14热红外波段建立热辐射传输方程，并通过对于地表比辐射率分析可知，ASTER4个热红外波段的比辐射率可以用近似线性方程表示，得到了6个方程6个未知数，从而形成了针对ASTER数据的同时反演地表温度和比辐射率的多通道算法。对于关键参数大气透过率，则是通过同一颗星的MODIS传感器的3个近红外波段反演大气水汽含量，然后用MODTRAN模拟大气水汽含量与ASTER热红外波段的统计关系，并进而根据这二关系来计算ASTER热红外波段的大气透过率。由于MODIS和ASTER是在同一颗星上。因此这种大气透过率估计方法保证了地表温度反演过程中所需大气参数的同步获取。     

地温敏感波段的遥感图像反演算法研究

针对应用于地表温度反演的航天遥感数据波段选择问题,文章提出了利用波长范围为8~10.5μm的热红外遥感数据反演地表温度的单通道反演算法:从温度敏感性的角度证明了利用波长范围为8~10.5μm的遥感数据反演地表温度的合理性;在此基础上,将仪器光谱响应率引入到基于大气校正原理的单通道反演算法中,提高了地表温度的反演精度。最后通过实验证明了利用此波段的热红外遥感数据反演地表温度的可行性。     

用遗传算法反演连续植被的组分温度

由于热红外多波段数据间具有高度的相关性和混合像元的大量存在，使得多波段陆面温度反演精度难以提高，并且难以得到组分温度信息。在连续植被热辐射方向性规律上的基础上，以喜直型连续植被为例，进行了大量的Monte-Carlo模拟，建立了组分有效比辐射率与土壤表面比辐射率和植被叶面积指数之间的经验函数关系，并以此构造目标函数，采用遗传算法，从热红外多角度数据中，同时反演混合像元组分温度和土壤比辐射率以及叶面积指数。通过对模拟的观测数据进行遗传算法反演的大量试验，结果表明，遗传算法反演组分温度非常稳健，在宽松的先验知识条件下，遗传算法可以解决不确定性反演问题。遗传算法反演结果和野外实测数据作了比较，证实了反演原理的正确性，为基于热红外方向性辐射模型反演组分温度，提供了新方法。     

机载高光谱热红外数据的地表温度和发射率反演与应用

机载高分辨率遥感是高分对地观测的重要部分,其中高分辨率高光谱热红外数据的光谱发射率可以用于矿物识别,是对可见光遥感地物识别的有效补充。机载高光谱热红外传感器TASI（Thermal Airborne Hyperspectral Imager）在8—11.5 μm范围内设置了32个波段,在国内外常被用于地表热辐射信息、矿产资源探测等领域。本文利用2018-10在新疆富蕴县研究区的TASI航空飞行数据,首先基于再分析大气廓线NCEP数据与MODTRAN实现了TASI高光谱热红外数据的大气校正,并在基础上发展了温度与发射率分离方法TES（Temperature and Emissivity Separation method）反演研究区地表温度与发射率,采用多波段热辐射计CE312测量的地面发射率对反演结果进行了有效验证,结果表明波长大于9.6 μm的波段的发射率误差约为0.01。最后,结合反演的TASI发射率光谱曲线,采用光谱角度匹配方法提取了研究区高岭石的空间分布。研究工作涉及的相关算法与应用成果可为星载高分辨率热红外载荷数据的应用提供了相关参考。     

多角度遥感估算稀疏团粒分布型土壤表面粗糙度方法初探

表面粗糙度是影响土壤在微波波段发射和散射辐射的主要因素之一,也是微波遥感研究与应用的重要参量。由于微波后向散射还受介电特性、穿透深度等因素的影响,在微波遥感应用中往往难以单独考虑介质表面粗糙度,给参数估算与反演带来了一定困难。在可见光、近红外波段,粗糙度作为土壤表面重要的结构参数之一,直接影响着土壤的二向反射分布特征。因此,本文尝试利用光学多角度观测信息,反演土壤表面粗糙度。基于地表二向反射几何光学模型,假设裸土像元由随机分布于平坦表面的土壤团粒组成,将团粒近似为半椭球体,建立裸露土壤表面二向反射模型,模拟不同粗糙度条件下土壤表面像元的二向反射分布特征。进一步尝试采用多角度观测数据反演模型,估算土壤团粒的几何结构参数,进而计算土壤表面均方根高度,作为表面粗糙度的衡量指标。地面实测多角度数据的初步验证结果表明,多角度光学遥感估算土壤表面粗糙度的方法是可行的。     

闪电河流域水循环和能量平衡遥感综合试验

遥感试验是进行遥感原理的验证、遥感模型与反演方法的发展、遥感产品的真实性检验,推动卫星计划的论证实施及其观测在地球系统科学中应用的重要途径。闪电河流域水循环和能量平衡遥感综合试验以滦河上游闪电河流域为核心试验区,以地球表层系统的水循环过程和能量平衡为研究对象,旨在通过天—空—地一体化的观测手段,针对不同典型地表类型开展全波段主被动协同遥感观测,研究异质地表和山地条件下像元尺度遥感关键参量的观测方案,研究重要水热参量的遥感方法及其同陆面/水文过程模型的结合,支撑国家民用空间基础设施和空间科学先导专项相关卫星计划的论证实施。其中,航空飞行遥感试验搭载L波段主被动一体化微波载荷、双角度热红外相机、四波段多光谱相机和高光谱成像仪进行协同观测,实现了土壤水分、组分温度、植被含水量、叶面积指数等地表参数以及湖泊、水库、湿地等的遥感监测;地面同步观测试验利用车载微波辐射计、地基雷达和光谱仪进行了典型地物如裸土、植被、水体、人工目标等的遥感观测,并按照样区—样方—样点的多尺度嵌套方案进行了地表参数的同步采样,获取了该地区关键地表参数的短时期时空变化特征;同时配合卫星和机载观测,在闪电河流域完成了土壤温湿度、地表水热通量、地表辐射四分量、降水等气象要素的地面观测网络的建设,为验证地表辐射/散射遥感模型,发展、优化和验证水热参量遥感反演算法,研究地表水热参量尺度效应与尺度转化问题提供了重要平台,将促进陆表能量与水分交换过程的理解及其对全球变化的作用和反馈机制的研究。     

水分含量与红土野外光谱的定量分析

土壤水分含量与土壤光谱关系密切,本文利用实测粤西红土野外光谱数据及其水分含量来分析两者之间的关系。得出以下结论:在0.46-2.5μm波段水分含量与红土光谱反射率呈显著负相关关系,并且随波长的增加其相关性有所增强,在2.22-2.29μm波段两者相关性最强;利用野外红土光谱反射率的倒数与水分含量进行回归分析,得到建模样本修正后的确定系数R2为0.781。这将为利用遥感技术监测土壤水分提供依据。     

土壤有机物质对土壤介电常数的影响

土壤介电常数是开展微波土壤水分和冻融状态的监测的基础,也是植被和积雪的下垫面边界条件,然而目前已有的介电常数研究都没有对高有机质含量的土壤开展系统观测。本文将土壤中的自然有机物质分为腐殖质和植物性残留物两类。采用控制变量实验方法,通过测量5种不同有机质含量的东北黑土和加入不同比例毛白杨碎屑的扁都口草甸土,研究了腐殖质和植物性残留物的对土壤介电常数的影响。结果表明,腐殖质会降低干燥土壤的容重,从而发挥间接作用,使介电常数降低;而对于相同容重下观测的潮湿土壤,腐殖质含量较多的土壤介电常数更大。与Dobson模型的比较显示,在29℃室温下,腐殖质对25%重量含水量潮湿土壤实部的影响在±2左右,虚部能达到1。与腐殖质相比,植物性残留物对风干土壤和潮湿土壤的影响都十分明显。植物性残留物能有效地疏松土壤并代入植物组分的介电特征。当重量含水量为30%时,含毛白杨含量为20%的混合土壤比纯扁都口土壤在实部平均减小3—7左右,虚部减小 1—3左右。因此,根据实验观测以及和模型的比较,土壤中的有机物质会改变土壤介电性质,对微波遥感造成影响。     

Remote detection of bare soil moisture using a surface-temperature-based soil evaporation transfer coefficient

An approach for estimating soil moisture is presented and tested by using surface-temperature-based soil evaporation transfer coefficient (h_a), a coefficient recently proposed through the equation h_a = (T_s − T_a)/(T_sd − T_a), where T_s, T_sd, and T_a are land surface temperature (LST), reference soil (dry soil without evaporation) surface temperature, and air temperature respectively. Our analysis and controllable experiment indicated that h_a closely related to soil moisture, and therefore, a relationship between field soil moisture and h_a could be developed for soil moisture estimation. Field experiments were carried out to test the relationship between h_a and soil moisture. Time series Aqua-MODIS images were acquired between 11 Sep. 2006 and 1 Nov. 2007. Then, MODIS derived h_a and simultaneous measured soil moisture for different soil depths were used to establish the relations between the two variables. Results showed that there was a logarithmic relationship between soil moisture and h_a (P < 0.01). These logarithmic models were further validated by introducing another ground-truth data gathered from 46 meteorological stations in Hebei Province. Good agreement was observed between the measured and estimated soil moisture with RMSE of 0.0374 cm³/cm³ and 0.0503 cm³/cm³ for surface energy balance method at two soil depths (10 cm and 20 cm), with RMSE of 0.0467 cm³/cm³ and 0.0581 cm³/cm³ for maximum temperature method at two soil depths. For vegetated surfaces, the ratio of h_a and NDVI suggested to be considered. The proposed approach has a great potential for soil moisture and drought evaluation by remote sensing.     

Estimating soil salinity in Pingluo County of China using QuickBird data and soil reflectance spectra

Soil salinization is a worldwide environmental problem with severe economic and social consequences. In this paper, estimating the soil salinity of Pingluo County, China by a partial least squares regression (PLSR) predictive model was carried out using QuickBird data and soil reflectance spectra. At first, a relationship between the sensitive bands of soil salinity acquired from measured reflectance spectra and the spectral coverage of seven commonly used optical sensors was analyzed. Secondly, the potentiality of QuickBird data in estimating soil salinity by analyzing the correlations between the measured reflectance spectra and reflectance spectra derived from QuickBird data and analyzing the contributions of each band of QuickBird data to soil salinity estimation Finally, a PLSR predictive model of soil salinity was developed using reflectance spectra from QuickBird data and eight spectral indices derived from QuickBird data. The results indicated that the sensitive bands covered several bands of each optical sensor and these sensors can be used for soil salinity estimation. The result of estimation model showed that an accurate prediction of soil salinity can be made based on the PLSR method (R² = 0.992, RMSE = 0.195). The PLSR model's performance was better than that of the stepwise multiple regression (SMR) method. The results also indicated that using spectral indices such as intensity within spectral bands (Int1, Int2), soil salinity indices (SI1, SI2, SI3), the brightness index (BI), the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) as independent model variables can help to increase the accuracy of soil salinity mapping. The NDVI and RVI can help to reduce the influences of vegetation cover and soil moisture on prediction accuracy. The method developed in this paper can be applied in other arid and semi-arid areas, such as western China.     

Confirmation of soil physiographic units through soil mineralogy studies in Yamuna alluvial plain,India

A confirmatory study of soil physiographic units identified through aerial photo interpretation technique, in Yamuna alluvial plain, Haryana is presented here. The area under study is part of Yamuna alluvial plain in Sonepat district, Haryana. Shanwal and Malik (1980) studied and mapped this area (semi-detailed) on 1:25,000 scale through areial photo interpretation technique. The soil profile samples of major soil physiographic units of the area were fractionated into sand, silt and clay. Detail mineralagical studies were carried out through electron microscopic and X-ray diffractometer studies in order to know their nature and origin of the parent material. X-ray diffraction data shows that mineralogy of different fractions (Sand, silt and clay) of soils samples, of different physiographic units were similar except Lavee. In this area mica is the dominant day mineral in the soils followed by Kaolinite, chlorite, vermiculite and smectite in decreasing order of their abundances. The occurance of fibrous minerals in coarse clay and silt fraction of soil samples of Lavee physiographic unit is the interesting feature of this area. The presence of fibrous minerals indicates that this overlain material designated as natural Levee in this area is not the alluvium brought down by the river Yamuna but is aeolian material flown from adjoining deseret of Rajasthan and deposited as stabilized sand dune. The fibrous minerals have been reported earlier in the desert of Rajasthan.     

土壤含盐量反演的研究

运用Hyperion数据,以黑龙江省大庆市某一实验区为例,开展对土壤含盐量定量提取的研究,通过对图像预处理、特征提取、建立BP神经网络模型（Back Propagation Network）等研究工作,探讨反演土壤含盐量的方法。研究结果表明：神经网络模型具有极强的线性和非线性拟合能力,模拟遥感影像特征与土壤盐分之间比较复杂的关系上有很大优势。研究结果不但为利用Hyperion数据反演土壤含盐量提供理论依据,而且还为其它地表参数的反演提供参考。     

钙质结核土细观结构定量分析研究

钙质结核土的结构特征对于其宏观力学性质和工程特性具有重要的影响。利用空间统计分析和分形维数计算方法,对钙质结核土的细观结构进行了定量分析,提取并计算了其颗粒形态、定向性等分形维数。结果表明,钙质结核的分布具有良好的分形特征和统计自相关性特点。     

土壤有机质光谱特征研究(英文)

The study on soil spectral reflectance features is the physical basis for soil remote sensing. Soil organic matter content influences the soil spectral reflectance dramatically. This paper studied the spectral curves between 400 nm∼2500 nm of 174 soil samples which were collected in Hengshan county and Yixing county. Fourteen types of transformations were applied to the soil reflectance R to remove the noise and to linearize the correlation between reflectance (independent variable) and soil organic matter (SOM) content (dependent variable). Then, the methods such as derivative spectrum technology and stepwise regression analysis, were applied to study the relationship between these soil spectral features and soil organic matter content. It shows that order 1 derivative of the logarithm of reflectance (O1DLA) is the most sensitive to SOM among the various transform types of reflectance in consideration. The regression model whose coefficient of determination reaches 0.885 is built. It predicted the soil organic matter content with higher effect. Supported by the National Natural Science Foundation of China (No. 40271007).     

An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil

Ground-reflected global positioning system signals measured by a geodetic-quality GPS system can be used to infer temporal changes in near-surface soil moisture for the area surrounding the antenna. This technique, known as GPS-interferometric reflectometry, analyzes changes in the interference pattern of the direct and reflected signals, which are recorded in signal-to-noise ratio (SNR) data, as interferograms. Temporal fluctuations in the phase of the interferogram are indicative of changes in near-surface volumetric soil moisture content. However, SNR phase is also highly sensitive to changes in overlying vegetation, and thus, the effects of seasonal vegetation changes on the ground-reflected signal must be considered. Here a method is described for determining whether SNR data are significantly corrupted by vegetation and for correcting these effects. Absolute soil moisture content must be determined for each site using ancillary data for the residual moisture content. Accounting for vegetation effects significantly improves the agreement between GPS-derived soil moisture and in situ measurements.     

污染场地土壤的光谱特征分析

随着经济发展与城市化进程的加速,随之带来的土壤污染等环境问题呼之欲出。传统的土壤环境监测方法依赖于定点采样分析,耗时长,成本高;而遥感技术凭借监测范围广、速度快、成本低和便于进行长期动态监测等优势,已广泛应用于环境地球化学和土壤科学等领域。文章以天津某农药厂为研究对象,在地面土壤光谱实测以及土壤中农药类污染物化学分析的基础上,开展农药类污染物的土壤光谱响应特征研究,分析不同农药类污染物对土壤光谱特征的影响,为进一步应用遥感技术进行土壤地球化学填图、土壤质量评价等提供参考。     

Variations in soil spectral reflectance related to soil moisture,organic matter and particle size

Spectral reflectance measurements in the visible and near infrared wavelengths of alluvial, black cotton and lateritic soils under different conditions show that reflectance has negative association withsoil moisture and organic matter in all the three soils. In lateritic soils reflectance increases with decrease of particle size. Variations in reflectance due to changes in concentrations of parameters were generally restricted to certain concentration levels. The generally superior discriminant capability of band 4 (0.8 to 1.1 urn) is indicative of its utility in soil and soil characteristics mapping.