Landsat TM热红外遥感数据定量反演地下水富集带的温度信息——以甘肃河西地区石羊河流域为例

利用ＬａｎｄｓａｔＴＭ６热红外遥感数据定量反演了干旱地区的地表温度,研究结果表明,研究区典型地表覆盖类型的地表亮温比地表真实温度低０．４～１Ｋ,遥感反演的地面真实温度与当地３月下旬的实测温度误差在０．８Ｋ以下,这说明用ＬａｎｄｓａｔＴＭ６定量反演干旱区的地表温度是可行的。研究结果还表明,地下水富集带地表温度具有异常现象,其地表温度比地表水体高５Ｋ左右,而比其它地表类型低７Ｋ以上,据此,可以利用热红外遥感技术有效地探测干旱区地下水富集带的信息。     

TM热红外波段等效比辐射率估算

地表比辐射率是热红外遥感获取地表温度必不可少的参数。目前,实验室或野外实际测量的都是8~14um热红外波段范围内的地表比辐射率,这与Landsat 5 TM热红外波段10.4~12.5um范围内的地表比辐射率还存在着一定的差异。本文将着重探讨TM热红外范围内地表比辐射率的估算方法,然后根据估算出的地表比辐射率,利用覃志豪等提出的单窗算法[1~2],对北京城八区进行地表温度反演。结果表明,该方法能获得较为合理的地表温度反演结果。     

热红外遥感地表温度反演研究现状与发展趋势

从Planck函数和热红外辐射传输方程出发,概述了热红外遥感反演地表温度的基本原理,总结了当前反演地表温度常用到的热红外遥感器及相应波段。将热红外遥感地表温度反演算法分为单通道、劈窗和多通道3大类,分析了每一类中较具代表性算法的原理、适用条件及精确度。从热红外遥感机理、发射率、环境辐射、混合像元、大气影响等方面概述了热红外遥感反演地表温度面临的主要问题,并对热红外遥感地表温度反演的发展趋势进行了展望。     

基于ETM+热红外遥感的武汉市城市地温反演研究

利用ERDAS及ArcGIS软件,通过影像预处理、影像解译,最终提取城区土地分类信息;由单窗算法,以大气辐射传输方程简化的单波段地表温度反演算法为基础,对武汉市2002年ETM+热红外遥感影像及相关气象资料进行地面亮温反演和不同土地利用类型的热效应定量评价研究.研究中采用了基于归一化差值植被指数和基于地表分类相结合的方法确定地表发射率;地温反演引入了热效应贡献度和区域热单元权重指数,对不同地表类型的热贡献度以及植被覆盖与地表温度的关系进行分析.     

基于静止气象卫星数据的地表温度遥感估算

基于分裂窗算法和地表温度日周期变化模型,探讨了利用多时相热红外遥感数据反演地表温度的方法。首先,利用分裂窗算法及地表温度日周期变化形式,推导了多时相遥感数据反演地表温度的方法。其次,利用辐射传输模型(MODTRAN),以2006年夏季在禹城观测的3 d地表温度、气温及大气水汽数据做为输入参数、变化观测角及比辐射率,模拟了一日多个时刻与风云二号(F-2D)波谱响应函数一致的亮温数据,基于此,模拟数据库对所提算法进行了检验。最后,利用2010年9月30日FY-2D多时相热红外数据对新疆区域地表温度进行了反演,并与相应时刻的MODIS地表温度产品进行了比较。结果表明：利用模拟遥感数据反演地表温度,模拟值与估算值的相关系数达0.9,均方根误差在1.5 K以内;利用在轨FY-2D热红外数据反演得到的地表温度与MODIS温度产品趋势基本一致,两者的相关性达到了0.5,均方根误差为4.4 K。需要说明的是,此方法仅满足于晴朗无云的条件。     

作物蒸散发模型研究中的地表温度反演

针对美国加州Merced县2002年8月9日的ETM+影像,利用单窗温度反演算法反演了遥感蒸散发模型S SEBI中的地表温度参数。选用了ETM+热红外的高增益61波段,对热红外波段反射率较低的植被覆盖研究区进行了地表温度反演,并反演地表温度所需要的几个参数：亮度温度、地表比辐射率、大气透射率。最后得出了研究区域地表温度分布结果：水体地表温度低于植被作物,建筑或道路的地表温度最高。不同地物间地温是不同的,作为蒸散发反演的重要参数,这将影响不同地物蒸散发估算。因此精确反演地表温度,将为今后蒸散发的研究打好基础。     

基于劈窗算法的Landsat 8影像地表温度反演

陆地表面温度（LST）是表征地表能量交换和地面特征的重要指标,目前遥感技术逐渐成为区域和全球尺度上LST反演的一种便捷工具,而采样不同算法及不同影像的热红外遥感LST反演研究层出不穷,其中基于Landsat数据的反演成果尤为突出。文章利用劈窗算法对Landsat 8遥感影像进行地表温度反演,对比探讨了根据经验值与借助MODIS热红外数据两种不同方式的LST反演结果,并进行北京市热红外波段辐射亮度温度比较,针对地表温度分级进行统计,分析了当地地表温度分布趋势。结果表明：劈窗算法下Landsat 8数据的反演温度更接近实际温度,精度较高且优于MODIS产品;北京市地表温度空间分布格局受地物结构与反射率所制约,高温区主要集中分布于中东部,中低温区分布与林地及水体分布结构较为吻合。     

地表温度热红外遥感反演的研究现状及其发展趋势

区域性或全球性的地表温度, 只有通过遥感手段才能获得, 在诸多应用中是一个非常重要的参数。地表温度反演是热红外遥感研究的热点和难点之一, 大气校正、温度与比辐射率的分离是必须考虑的两个重要方面。近年来有关的研究非常多, 主要反演方法可分为5 类: 单通道方法、分裂窗(双波段) 方法、多波段温度- 比辐射率分离方法、多角度温度反演方法和多角度与多通道相结合的方法。这些方法都各有利弊, 如何提高反演的精度和模型的适用性是地表温度热红外遥感的未来发展趋势, 理论和实验相结合的多种信息源的综合应用成为必然的要求。     

基于TES算法的地表温度反演应用研究

温度比辐射率分离算法（TES）是针对高光谱分辨率的热红外测量数据,利用地物热红外光谱的一些共性特点作为先验知识或者约束条件,从一次观测中同时反演温度和光谱发射率的方法。利用这类方法反演地表温度时主要需要较多的光谱波段和较高的信噪此。本研究以长白山火山区为例,首次将温度比辐射率分离算法应用于该区的地表温度反演,通过NEM,RAT和MMD这三种TES方法的迭代逼近,基于ASTEPR多波段热红外数据反演了长白山地区的地表温度。反演结果显示：望天鹅火山区为低地表温度集中分布区;而长白山火山区却表现为高海拔低温背景下的高地表温度集中分布,经过对地表覆盖状况的实地调查发现,该区裸露的大量浮岩是引起这种地表温度异常的主要原因之一。     

一种基于ASTER数据的陆面温度反演方法

陆面温度是地表物体热红外辐射的综合定量形式,是地表热量平衡的结果。陆面温度作为一个重要的基本参数已广泛用于相关模型的计算及生态环境等领域的研究。ASTER数据具有较高的空间分辨率与光谱分辨率,可提供比陆地卫星、NOAA/AVHRR等常见卫星数据更丰富的地表信息,有助于提高陆面温度的反演精度。根据温度/比辐射率分离(TES)的思想,基于ASTER热红外数据的特性,获取了一种反演陆面温度的方法,并以长白山为例进行了试验。结果表明,所用的方法仅依赖ASTER遥感数据便可快速获取地面温度的空间分布特征,对自然地表可取得比较理想的结果,具有较好的应用前景。     

Rainfall and vegetation monitoring in the Savanna Zone of the Democratic Republic of Sudan using the NOAA Advanced Very High Resolution Radiometer

NOAA-6 and NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) global-area coverage (4?km ground resolution) data were obtained at three-day intervals throughout each of the four-month periods covering the 1980, 1983 and 1984 growing seasons, between latitudes 10° and 22° North in the Democratic Republic of Sudan. Daily rainfall data for twelve meteorological stations spanning the Savanna Zone were analysed. Rainfall in Sudan during 1980 was below normal, but in 1983 and 1984 there were moderate and severe droughts. The satellite data were used to calculate normalized difference vegetation index (NDVI) values from the visible and near-infrared bands of the satellite data. These were processed into ten-day composite data sets using the AVHRR thermal-infrared channel as a cloud screen and a temporal compositing procedure that reduces cloud contamination and selects viewing angles closest to nadir.

The ten-day composite NDVI values and the integrals of NDVI for each growing season were found to be closely correlated with rainfall. The constants of regressions between NDVI and rainfall were lower in 1983 and 1984 than in 1980, which suggests there was reduced water-use efficiency by the rangeland vegetation in drought years. It was found that July and August NDVI values were closely related to the integrated NDVI values; hence early- and mid-season NDVI data could be used to predict annual primary production. Images showing the geographical distribution of values of NDVI prepared for the three years clearly illustrate the effects of the 1983 and 1984 droughts, compared with the higher rainfall of 1980. The precision of the relationship between rainfall and the vegetation indices for the meteorological stations encourages the view that NOAA AVHRR GAC composite NDVI values can be used to monitor effective rainfall in the Savanna Zone of the Democratic Republic of Sudan     

The satellite-measured sea surface temperature change in the Gulf of Finland

Climate change in Baltic region and in the Gulf of Finland is an accomplished fact in human brains and in science. The purpose of this research is to retrieve quantitative level of changes for sea surface temperature (SST) of the Gulf of Finland. Two space systems National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) provided satellite data about temperature of the sea surface. SST data covers period 1981–2014 and includes 444 monthly data scenes with spatial resolution about 10 km. Data quality analysis displays high reliability of NOAA/AVHRR and Aqua/MODIS satellite information. The Gulf of Finland’s average annual SST has changed from 6.8°C in 1982 up to 8.2°C in 2014. Its mean speed of warming is about 0.04°C year^–1. The growth of the temperature was irregular, in the middle of 80th year, the temperature dropped down to 5.0°C, and then sharply increased up to 7.3°C in 1989. SST growth in the Gulf of Finland coincides with air temperature and sea temperature growth. The climate change in the Gulf of Finland has special significance due to the fragility of the northern ecosystems and high anthropogenic load.     

Deriving the operational nonlinear multichannel sea surface temperature algorithm coefficients for NOAA-15 AVHRR/3

The National Oceanic and Atmospheric Administration (NOAA) currently uses Nonlinear Sea Surface Temperature (NLSST) algorithms to estimate sea surface temperature (SST) from NOAA satellite Advanced Very High Resolution Radiometer (AVHRR) data. In this study, we created a three-month dataset of global sea surface temperature derived from NOAA-15 AVHRR data paired with coincident SST measurements from buoys (i.e. called the SST matchup dataset) between October and December 1998. The satellite sensor SST and buoy SST pairs were included in the dataset if they were coincident within 25 km and 4 hours. A regression analysis of the data in this matchup dataset was used to derive the coefficients for the operational NLSST equations applicable to NOAA-15 AVHRR sensor data. An independent matchup dataset (between January and March 1999) was also used to assess the accuracy of these day and night operational NLSST algorithms. The bias was found to be 0.14°C and 0.08°C for the day and night algorithms, respectively. The standard deviation was 0.5°C or less.     

雪盖卫星遥感信息的提取方法探讨

着重论述了从卫星遥感资料中提取雪盖信息的一些方法,结果表明,利用积雪阈值参数从ＮＯＡＡ／ＡＶＨＲＲ图象中提取雪盖信息方法和利用积雪指数（ＮＤＳＩ）从陆地卫星ＴＭ图象中提取雪盖面积的技术,以及利用ＮＯＡＡ／ＡＶＨＲＲ和ＴＭ信息复合的技术,可提高信息获取的精度,具有实用价值。     

Determination of land surface spectral reflectances using Meteosat and NOAAA/AVHRR Shortwave Channel Data

Abstract

A method to derive surface spectral reflectances from currently available Meteosat geostationary and NOAA/AVHRR polar orbiting satellite data is described. Broadband reflectance was derived from Meteosat measurements while NOAA/AVHRR vegetation index provided a spectral weighting which enabled the spectral reflectances on either side of 0-7 μm to be estimated. The method takes into account satellite calibrations, viewing geometry, and correction of some atmospheric effects. Conversion from narrow-band to broadband reflectances is discussed. The method was applied to a month of data to obtain the surface spectral reflectances of Africa which are compared with some data sets used by climate modellers, in order to assess them and to monitor their seasonal and interannual changes on a global scale.     

Correction of the effect of Sun-sensor-target geometry in NOAA AVHRR data

Models of determining the effects of the bidirectional reflectance distribution function (BRDF) of different surfaces and of eliminating the effect of Sun-sensor-target geometry from the remotely sensed satellite data are actual. The objective of this study is to develop a simple relation between the Sun-sensor-target geometry and the remotely sensed vegetation index. In this investigation 238 National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) images were used over Hungary during the period 1996-98. The greenness vegetation index (the difference between the reflectance values of near-infrared and visible channels) was used between days of the year 140-200, because the greenness values can be considered as constant in this period over the agricultural areas. The so-called 'hot spot effect' can be observed in the variation of reflectance values with different viewing zenith angles of the sensor. A simple quadratic relation was found between the raw AVHRR greenness values and the angle enclosed by the Sun-target and target-sensor directions over the agricultural areas, forests and grasslands. A correction method was developed to eliminate the effect of the Sun-sensor-target geometry, which it is hoped will improve the accuracy of yield forecasting and estimation procedures using NOAA AVHRR data.     

NOAA卫星云检测和云修复业务应用系统的研制和建立

介绍了NOAA气象卫星云检测、云替补的光谱原理、技术模型以及基于VB5.0版本的业务系统的基本功能。系统经过试验运行和实况验证,取得了良好的运行效率与精度较高的云检测和替补效果,从而为NOAA卫星的遥感应用提供了可靠的数据源保证。     

Determination of land surface temperature and its lapse rate in the Satluj River basin using NOAA data

Temperature lapse rate (TLR), an essential parameter for snowmelt runoff analysis, was determined for the Satluj River basin in the Western Himalayas. National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data sets were used to determine the land surface temperature (LST) of the region using the split‐window algorithm proposed by Coll and Caselles (Journal of Geophysical Research, 1997, 102, pp. 16697–16713). The LST was correlated with the elevation values obtained from a US Geological Survey digital elevation model (USGS‐DEM) of the same area and the trend showed an inverse relationship between LST and elevation. The TLRs for the study area on 2 February, 1 March, 26 March, 16 October, 1 November and 20 November 2004 were in the range 0.6–0.74°C/100 m. The results obtained were compared with lapse rates determined using Moderate Resolution Imaging Spectroradiometer (MODIS) LST maps. TLR determination in the past was based on air temperature data available from meteorological stations that are sparsely located in rugged terrain such as the Himalayas. As these measurements were point data and had been measured manually, they may have led to erroneous results. Satellite data, however, provide continuous and potentially unbiased recording provided an accurate radiometric calibration and atmospheric correction can be achieved. A previous TLR calculation using air temperature from meteorological stations for the western Himalayan region was found to be 0.65°C/100 m. Air temperature and LST from NOAA‐AVHRR and MODIS‐Terra data were found to be in good agreement. This type of study will be useful for snowmelt runoff modelling studies for the Himalayan region.     

Estimating bidirectional angles in NOAA AVHRR images

In studies concerning the surface bidirectional reflectance distribution function (BRDF) and thermal-infrared multiangular emissions, Sun-sensor geometry must be known. This Letter provides a potential and simple method for NOAA Advanced Very High Resolution Radiometer (AVHRR) users to estimate the imaging configuration of each pixel in a geometrically corrected image. Our formulas were tested with example AVHRR data and their precision was shown to be comparatively high with a maximum error of either the satellite zenith or azimuth angle less than 4°. The standard deviation for the zenith is 2.07° and azimuth is 2.47°.