利用遥感瞬时温度场研究云南山地气温直减率

基于MODIS影像反演地表瞬时温度场和气象站点30年平均气温实测数据,结合数字高程模型,研究了云南山地气温随海拔变化的规律。结果表明,降低或消除了坡向与坡度、纬度与经度变化的影响后,在云南全区域尺度上,海拔对气温作用而产生的气温直减率为0.53℃;在典型山地地貌类型区,山地气温直减率由高山区向低山区逐渐增大,滇西北高山区直减率为0.47℃,滇中、滇东中山区为0.51℃,滇南宽谷低山区为0.54℃,滇西北高山峡谷和滇南低山深切沟谷地带为0.54℃;由阳坡、半阴半阳坡至阴坡,山地气温直减率依次增大:阳坡直减率平均为0.52℃,半阴半阳坡平均为0.54℃,阴坡平均为0.55℃。除海拔之外,坡向、坡度等微地形因子亦是微格局气温场的主要地理响应因子。利用遥感数据反演的瞬时温度场研究山地气温直减率,是一种研究山地气温变化规律的新方法。     

4种常用植被指数的地形效应评估

植被指数已经广泛应用于地表植被覆盖监测,但是地形对植被指数的影响难以避免,却经常在大尺度遥感应用时被忽略。本文利用山区森林的Landsat TM数据计算SR、NDVI、RSR、MNDVI4种常用植被指数,评估了地形对这些植被指数的影响,并利用余弦校正和C校正模型分别对它们进行地形校正。结果表明,近红外和短波红外比红光波段的地形影响更为敏感,原因是更强的红光天空漫反射削弱了红光的地形影响。地形强烈影响非波段比值型植被指数(如RSR和MNDVI等),导致阳坡的植被指数相对偏小,阴坡的植被指数相对偏大,这种地形效应随坡度增大而显著增大。因此,利用非波段比值型植被指数反演山区植被参数时必须做严格的地形校正。与之相反,波段比值型植被指数(如SR和NDVI等)可以很大程度上消除地形影响,但是在大坡度情况下,地形影响仍然不能被忽略,而且此时SR比NDVI的地形效应更大。C地形校正效果好于余弦校正效果,特别是大坡度情况下更为明显。     

南方丘陵区植被覆盖度遥感估算的地形效应评估

植被覆盖变化是生态环境领域的核心研究内容之一,但其估算精度常受到地形效应、土壤背景、大气效应等各种因素影响。以Landsat 8 OLI为遥感数据源,基于像元二分模型,分别利用归一化差值植被指数(NDVI)、经Cosine-C校正的归一化差值植被指数(NDVI)和归一化差值山地植被指数(NDMVI)建立植被覆盖度估算模型,以评估南方丘陵区植被覆盖度的地形效应。结果表明,3种植被覆盖度估算模型均能削弱地形效应,但消除或抑制地形效应影响的能力不同。比较而言,基于NDMVI指数构建的植被覆盖度估算模型的地形效应最小,更适合地形复杂区域的植被覆盖度遥感估算;基于Cosine-C校正的NDVI植被指数构建的植被覆盖度估算模型的地形效应次之,但存在一定的过度校正现象;基于NDVI植被指数构建的植被覆盖度估算模型的地形效应最大,尤其当坡度≥10°时,阴坡植被覆盖度比阳坡明显偏低。     

山区地表太阳辐照度随时空变化的模拟分析

在光学遥感数据的应用过程中,地表太阳辐照度的量化问题对于遥感数据的获取和地表地物特性的反演等工作都是一个非常重要的环节,而地表太阳辐照度的定量计算又依赖于辐射源、目标物和传感器三者之间的几何关系以及目标地物的地表特征。利用山区地表太阳辐照度的计算模型,对不同时间、不同山区地形下的地表太阳辐照度进行了定量模拟,用三维图的方式分析了地表太阳辐照度随时间、地形坡度、坡向的变化规律,为光学遥感中地表太阳辐照度随时空变化的量化关系分析提供了更直观的依据。     

微地形上太阳辐射模拟及与地表温度关系研究

在微地形上进行太阳辐射模拟对于探讨起伏地表微气候因素分布具有重要意义,为分析微地形对太阳辐射的影响及对地表温度的影响,利用实时动态差分仪(real-time kinematic,RTK)实地测量实验样区的微地形,生成分辨率为0.1 m×0.1 m的分米级高精度数字高程模型(digital elevation model,DEM),模拟微地形下太阳总辐射的时空分布;同时结合地面温度实测数据,建立地表温度与太阳辐射的关系。结果表明:微地形下太阳辐射具有明显的空间分布特征,表现为沟脊大,沟底小;阳坡大,阴坡小;坡度越大接受的太阳辐射量越少;实验样区接受太阳辐射量大小依次为夏季春季秋季冬季;地形遮蔽效应对太阳辐射影响程度依次为冬季秋季春季夏季;地表温度与太阳辐射呈显著相关,相关系数为0.622。     

基于DEM的森林植被空间分析与变化检测

采用1∶10 000地形图等高线地形数据建立内蒙古大兴安岭克一河林业局DEM,用于自动提取地形因子,获得高程、坡度和坡向分级图;并利用2012~2015年高分辨率卫星遥感影像监测森林资源变化情况。结果表明,基于1∶10 000地形图等高线地形数据DEM的地形分类具有可接受的垂直精度,山区植被分布图为遥感树种识别与分类提供了可能,三维可视化空间表达提高了森林资源的空间分析能力,卫星遥感影像判读区划与现地验证是监测林地变化的有效技术手段。     

地表反射率地形校正物理模型与效果评价方法研究进展

地形校正是准确获取地形复杂区遥感反射率的重要步骤,对提高山区地表遥感参数定量化反演精度,扩大遥感产品应用广度具有重要意义。从20世纪80年代开始,国内外学者开始对准确获取山区地表遥感反射率进行研究,建立了多种地形校正模型来减少或消除遥感图像中地形效应影响,减少同种地表类型的反射率差异,并将地形校正模型分为经验模型和物理模型。根据构建物理模型时是否考虑地表非朗伯体特性,将物理模型分为朗伯体假设模型和非朗伯体假设模型,本文分别从朗伯体假设模型和非朗伯体假设校正模型展开叙述。从两类模型构建的理论基础,模型特点,局限性等几方面进行分析和讨论,描述了两类模型的发展历程,系统阐述了朗伯体假设模型和非朗伯体假设模型的适用性和不足,剖析了目前地形校正模型存在的问题与挑战。同时,本文也比较了应用于地形校正的效果评价方法,并展望了地形校正方法和地形校正评价方法的未来主要发展方向。     

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。     

应用多波段合成图像圈定地热异常的初步探索

本文根据地热异常引起的植被效应模式,确定了多波段合成图像地热异常的解译标志,并进行了地面波谱测试及红外辐射测温工作,从遥感基本原理上论证了解译标志的可靠性。圈定的地热遥感异常,已得到证实,应用这一解译标志指导关中地区寻找地热取得了一定的效果     

基于热红外遥感技术的腾冲地区地热异常区温度反演研究

我国云南腾冲地区地热资源丰富,对地热资源进行定量的预测评价势在必行。而以遥感为手段进行地表温度的反演是地热研究的重要方法。本文利用ETM数据的Band6热红外通道,对工作区进行温度反演并通过消除阴影影响对反演温度进行修正使得温度差异较大的情况得到改善,减少了太阳照射造成的温差影响。结果表明,研究区地表温度分布主要有3个区域;通过温度反演结果与已知地热点叠加分析,选取14~21℃为进行地热预测评价的有利区间。     

Geothermal area detection using Landsat ETM+ thermal infrared data and its mechanistic analysis—A case study in Tengchong,China

Thermal infrared (TIR) remote sensing is an important technique in the exploration of geothermal resources. In this study, a geothermal survey is conducted in Tengchong area of Yunnan province in China using TIR data from Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. Based on radiometric calibration, atmospheric correction and emissivity calculation, a simple but efficient single channel algorithm with acceptable precision is applied to retrieve the land surface temperature (LST) of study area. The LST anomalous areas with temperature about 4–10 K higher than background area are discovered. Four geothermal areas are identified with the discussion of geothermal mechanism and the further analysis of regional geologic structure. The research reveals that the distribution of geothermal areas is consistent with the fault development in study area. Magmatism contributes abundant thermal source to study area and the faults provide thermal channels for heat transfer from interior earth to land surface and facilitate the present of geothermal anomalies. Finally, we conclude that TIR remote sensing is a cost-effective technique to detect LST anomalies. Combining TIR remote sensing with geological analysis and the understanding of geothermal mechanism is an accurate and efficient approach to geothermal area detection.     

Detection of geothermal anomalies using Landsat 8 TIRS data in Tulu Moye geothermal prospect,Main Ethiopian Rift

Despite the high geothermal potential of the Main Ethiopian Rift (MER), risks associated with the industry and the difficulty of identifying possible targets using ground surveys alone continue to impede the development of geothermal power diligence in Ethiopia. In this paper, we investigate the geothermal potential of the Tulu Moye prospect area in the MER using Landsat 8, which is an important and cost-effective method of detecting geothermal anomalies. Data with a path/row of 168/054 were obtained from the Landsat 8 Operational Land Imager (OLI) and Thermal Infrared (TIR) sensors for October 17, 2014. Based on radiometric calibration, atmospheric correction (with the 6S model) and an NDVI-based threshold method for calculating land surface emissivity, a split-window algorithm was applied to retrieve the land surface temperature (LST) of the study area. Results show LST values ranging from 292.2 to 315.8 K, with the highest values found in barren lands. A comparison of LST between the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 8 shows a maximum difference of 1.47 K. Anomalous areas were also discovered, where LST was about 3-9 K higher than the background area. We identified seven of these as areas of high geothermal activity in the Tulu Moye prospective geothermal area. Auxiliary data and overlay analysis tools eliminated any non-geothermal influences. The research reveals that the distribution of highy prospective geothermal areas is consistent with the development and distribution of faults in the study area. Magmatism is the thermal source and faults provide conduits for the heat to flow from earth’s interior to the surface, facilitating the presence of geothermal anomalies. Finally, TIR remote sensing methods prove to be a robust and cost-effective technique for detecting LST anomalies in the geologically active area of MER. Moreover, combining TIR remote sensing with knowledge of the structural geology of the area and geothermal mechanisms is an efficient approach to detecting geothermal areas.     

Landsat卫星热红外数据地表温度遥感反演研究进展

作为驱动地表与大气之间能量交换的关键物理量,地表温度在众多领域中都发挥着重要作用,包括气候变化、环境监测、蒸散发估算以及地热异常勘探等。Landsat热红外数据因其时间连续性和高空间分辨率等特点被广泛应用于地表温度反演中。本文详细地介绍了Landsat热红外传感器及其可用的数据与产品的现状,梳理了2001年—2020年20年间基于Landsat热红外数据的地表温度遥感反演与应用的相关文献发表及互引情况,系统地综述了基于Landsat热红外数据的地表温度反演算法,包括基于辐射传输方程的算法、单窗算法、普适性单通道算法、实用单通道算法和分裂窗算法等。在此基础上,进一步介绍了每种算法的参数化方案,包括地表比辐射率和大气参数的估算方法。最后针对Landsat热红外数据地表温度遥感反演提出了未来可能的发展趋势与研究方向。     

The application of day and night time ASTER satellite imagery for geothermal and mineral mapping in East Africa

There is considerable interest in optimizing geothermal exploration techniques via the mapping of alteration and evaporate mineralisation, as well as of thermal emissions associated with geothermally active areas on the Earth’s surface. Optical and thermal satellite sensor technologies, improvements in processing algorithms and the means for large scale (e.g. 1:250,000) spatial data distribution are required for detecting both these attributes. The extensive visible, -near, -shortwave and thermal infrared (VNIR-SWIR-TIR) data archive acquired by the multi-spectral Advanced Spaceborne Thermal Emission Reflectance Radiometer (ASTER) provides a rich source of geoscience related imagery for geothermal exploration. Examples of generating large scale mosaicked ASTER imagery to provide province to continental mineral mapping have been undertaken in areas including such as Australia, western USA, Namibia and Zagros Mountains Iran. In addition, ASTER’s thermal infrared imagery also provides night time land surface temperature (LST) estimates relevant for detecting possible geothermal related anomalies.This study outlines existing methods for the application of ASTER data for geothermal exploration in East Africa. The study area encompasses a section of the East African Rift System across the Tanzanian and Kenyan border. The area includes rugged volcanic terrain which has had geological mapping of limited coverage at detailed scales, from various heritages and mapping agencies. This study summarizes the technology, the processing methodology and initial results in applying ASTER imagery for such compositional and thermal anomaly mapping related to geothermal activity. Fields observations have been used from the geothermal springs of Lake Natron, Tanzania, and compared with ASTER derived spectral composition and land surface temperature results. Published geothermal fields within the Kenyan portion of the study area have also been incorporated into this study.     

Using Thermal Remote Sensing in Environmental Studies

Thermovision is a relatively new method of remote sensing with applications in areas such as military operations, residential monitoring, technological process control and emergency management. Surprisingly, it has not seen much application in environmental studies. The article presents a method of using thermovision for topoclimatic studies. The method is based on the spatial distribution of land surface temperature (LST). The LST distribution indicates the amount of solar energy reaching the Earth surface and depends primarily on terrain shape and land cover types. By analyzing the LST distribution, one can determine spatial topoclimatic variability. The LST derived topoclimatic classification was compared with the theoretical topoclimatic classification based on heat balance. New classes of topoclimates were created and some of the existing types were diversified into more detailed subtypes. The analysis of selected lowland areas in north‐western Poland revealed that both land cover and terrain shape characteristics had a significant impact on the LST distribution, contrary to the expectation of land cover characteristics being more important than terrain shape. The article demonstrates the possibilities of using thermovision in environmental research and presents a new method of topoclimate delimitation based on thermal remote sensing data and geographical information systems (GIS) techniques comparing. The LST classification method with conventional methods based on DEM and land cover analysis.     

Land surface temperature and its impact factors in Western Sichuan Plateau,China

The understanding influence of multiple factors variations on land surface temperature (LST) remains elusive. LST was retrieved by the atmospheric correction algorithms. Based on the correlation coefficients, stepwise regression analysis was developed to examine how multiple factors variability led to LST variations. The differences in LST between impact factors vary depending on time in a day. The elevation and land use types significantly affect the LST in sunny slope or shadow areas has a significantly quadratic curve correlation or a negative linear correlation with it, the influence of slope and aspect is not very significant. LST for forestland, grassland and bare land in the sunny slope and shadow area was the cubic polynomial related to its elevation. Normalized difference vegetation index (NDVI) and normalized difference moisture index (NDMI) effectively express LST in mountainous. LST and NDMI or NDVI have a significantly negative correlation, NDMI is more effective and more applicable for the expression of LST.     

长春地区地表温度异常遥感分析

热红外遥感是一项探测地热资源、植被覆盖、农作物估产等生态环境评价研究的重要技术。本次使用Landsat 7/ETM＋热红外波段（band 6）,基于单通道算法,对长春地区地表温度应用反演,从而为研究该区地热资源、土地覆盖、城市热岛效应及环境评价提供可靠的依据。研究表明,热红外遥感能够有效探测到地表温度异常,而引起其异常的原因有待我们就一步验证和深入研究。     

基于遥感技术的长白山火山区地热预测研究

在长白山火山区地热调查研究中,基于ASTER遥感数据,运用比辐射率归一化方法,定量反演了区域地表温度,并在此基础上,通过对地质构造的遥感解译,结合对水热活动及深源气体释放特征等资料的关联分析,预测长白山火山区地热资源存在的有利区.研究发现,六道沟-长白山天池-甑峰山北东向断裂的天池段和长白山火山环形断裂的长白聚龙段是地热勘探的有利区,也是火山监测的最佳场所.     

基于DEM的遥感数据复原方法研究

介绍了一种基于数字高程模型（DEM）的遥感数据复原新方法。此方法将地形因子作为最主要的作用因子，不考虑卫星传感过程中的随机影响。首先，根据基础地理数据，按其等高线层生成DEM； 然后，利用DEM，通过实测样点、DEM和经过纠正的遥感数据的信息融合，进行遥感数据中像元样点的坡度、坡向分析，建立DEM与遥感信息的相关关系模型，以数学统计方法描述地形因子对遥感数据的作用机理； 最后，进行逐像元的遥感信息复原(归一化)。结果表明，该方法具有较好的信息复原效果，可消除或减少地形对遥感数据的影响，增强遥感技术在山区复杂地形下的实用性。     

山地遥感主要研究进展、发展机遇与挑战

山地遥感是研究在山地这一特定环境中的遥感基本原理、方法及其应用的科学技术。从山地遥感研究的基本内涵出发,总结面临的若干前沿科学问题,指出当前主要研究内容:(1)电磁波与山地地表相互作用机理及建模理论;(2)山地遥感数据时—空—谱归一化处理方法;(3)山地地表信息遥感建模、反演与同化方法;(4)山地遥感尺度效应与算法/产品验证;(5)山地遥感信息综合应用等。从山地遥感研究的基础理论方法以及山地遥感应用两个层面回顾了近年来山地遥感研究取得的进展,并就新时代背景下山地遥感研究面临的机遇与挑战进行了分析,最后对山地遥感研究前景进行了展望。