不同空间分辨率热红外数据在近海核电厂温排水监测一致性研究

针对近年来我国核电厂大力发展而引起的核电温排水体污染的问题,该文利用相同日期的环境一号B星(HJ-1B)红外相机与Landsat ETM+热红外波段数据,均采用辐射传输模型法反演出大亚湾区域海表温度,通过同日期MODIS海温产品作为基准,比较HJ-1B数据、Landsat ETM+数据温度反演的差别,在此基础上,基于同一基准温度提取方法,开展HJ-1B数据、Landsat ETM+数据及MODIS反演结果3种不同空间分辨率数据在近海核电站温排水监测的一致性进行了分析与评价。研究表明:ETM+数据温度反演精度高于HJ-1B结果,且更能体现高温升区监测精度;基于劈窗算法的MODIS海温反演精度更高,但不能反映温排水温升分布细节;综合考虑具有较高时间分布率和较大幅宽的HJ-1BIRS数据更能满足业务需求。     

基于MODIS和TM数据的陆面温度反演

陆地表面温度(LST)反演一直是热红外遥感研究中的一大难题。目前,分辨率较高的Landsat5/TM数据是陆地表面温度(LST)反演的常用遥感信息源。然而,由于TM只有一个热通道,大多数情况下由TM6数据得到的都是星上亮度温度,与实际地表温度有较大差距。普适性单通道算法的提出为从TM6数据高精度地反演地表真实温度提供了可能。为寻找一条从TM6数据高精度反演陆地表面温度的有效途径,利用该算法对北京地区的地表温度进行了反演试验,对该算法必需的总大气水蒸汽含量通过MOD IS数据计算获得。同时利用卫星过境时的同步实测数据对反演精度进行了检验,并与用标准大气数据得到的结果进行了比较。其结果表明,该方法具有较高的反演精度,其rmsd值为1.67℃,显示了多源数据结合的优势。     

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。     

天宫二号数据地表温度反演及其在城市群热环境监测中的应用

根据天宫二号宽波段成像仪热红外谱段的特点,提出了一种适用于天宫二号数据的劈窗算法,并以苏南城市群为研究区,进行了地表温度的反演。在此基础上,通过SUHI(Surface Urban Heat Lsland)指标分析了苏南城市群热环境空间分布特征。结果表明:劈窗算法可以有效地应用于天宫二号热红外数据,地表温度反演结果的均方根误差在1K以内;研究区地表温度结果与土地利用类型有较好的一致性,建筑用地温度最高,水体最低,苏锡常城市群形成一个整体热岛效应,SUHI指标能有效监测城市群的热岛强度及其空间分布。     

针对HJ-1B的水表温度反演方法研究

利用HJ-1B热红外波段数据进行了水表温度反演。数据定标后,利用水体指数对HJ-1B热红外数据进行了水体识别,识别后直接对水体区域进行编程处理。在模型方面,考虑了HJ-1B热红外通道波谱响应函数的影响,利用MODTRAN4模型修正了Jimenez-Munoz和Sobrino提出的单通道算法,算法的参数"水汽含量"从MOD05水汽产品中取得。最后利用相同时间段内MODIS的海表面温度产品进行了验证,结果显示在抽取的1211个验证点中相对误差在5%以下的占78.695%,可以认为利用HJ-1B热红外数据进行水表面温度反演是可行的。     

基于Landsat8的地表温度反演算法研究——以滇池流域为例

2013年2月11日Landsat 8在加州范德堡空军基地发射升空,其携带的热红外传感器为反演地表温度提供了一种新的数据,但目前尚没有针对Landsat 8热红外波段反演地表温度的算法。针对Landsat 8第10波段特征,对现有反演地表温度的单窗算法进行了参数修正,得到了用Landsat 8第10波段反演地表温度的单窗算法系数。为了评价修正后算法的精度,用MODTRAN模拟地表温度为20、30和40℃时大气水汽含量分别为1.0、1.5、2.0和2.5g·cm-2传感器高度处的热辐射值,再将模拟数据用修正后的单窗算法反演地表温度,结果表明:地表温度越低、大气水汽含量越低,误差越小;模拟结果的平均误差为0.74℃。说明基于Landsat 8第10波段用修正后的单窗算法反演地表温度是可行的,该方法可为地表温度反演提供一种途径。最后以滇池流域为例,基于2013年4月20日的Landsat 8热红外数据反演了滇池流域的地表温度,并分析了滇池流域地表温度的分布特征。     

GF-5卫星模拟单通道SST反演

针对国内外热红外数据空间分辨率低、反演温度精度低的问题,提出了基于高分辨率GF-5卫星热红外通道修订的单通道海表温度(sea surface temperature,SST)反演算法。以大气传输模型软件(moderate resolution atmospheric transmittance and radiance code4.0,MODTRAN 4.0)与全球大气廓线数据(thermodynamic initial guess retrieval,TIGR)为基础,采用Jiménez-MuozSobrino's单通道算法和QIN单通道算法对GF-5卫星热红外数据进行SST的模拟反演研究。通过对比不同条件下的反演误差,结果表明,B11通道的反演精度高、效果最好,B12、B10通道次之,B09通道反演精度最低;传感器垂直向下观测即观测天顶角为0°时的SST反演精度最高。由于单通道算法反演误差较大,因此进行了二次修订,修订后效果有明显改善,误差在1K以内。     

基于MODIS的海表面温度反演系统设计与实现

海表面温度(SST)是重要的海洋物理参数,对海洋研究具有重要意义.通过遥感数据反演是目前获取SST数据的主要方法之一.遥感反演数据具有反映大区域尺度的海温连续分布状况,且数据获取及时稳定等特点.本文基于IDL构建了面向EOS/MODIS数据的SST反演系统,讨论了系统的功能和结构,给出了具体的数据反演处理流程,对系统中采用的SST反演算法和云检测方法进行了详细说明.最后以我国东海海域为例,将反演结果与多年观测资料对比,表明系统反演得到的SST分布规律与多年观测资料一致,同时还利用同步观测的浮标数据和NASA MODIS SST产品对反演结果进行验证,结果显示系统反演的SST平均误差为1℃.数据精度满足海洋预报和其他科学研究的需要.     

星载微波遥感观测海表温度的研究进展

随着卫星遥感技术的快速发展,星载微波遥感作为观测海温的手段之一,受到越来越多的关注。总结了国内外星载微波遥感观测海温的发展历程和微波遥感反演海温的理论基础,归纳了多元线性回归算法和非线性迭代算法两种主要的算法类型,在此基础上介绍了国外的TMI和AMSR-E以及国内FY-3和HY-2等卫星上搭载的先进微波传感器仪器的运行参数、通道特征及其相应的反演算法,最后分析了微波遥感反演海温的影响因素,指出了目前研究中存在的问题,并对今后的研究方向进行了展望。     

利用TM6数据反演陆地表面温度新算法研究

陆地表面温度(LST)反演一直是热红外遥感研究中的一大难题。虽然TM 6数据具有较高的空间分辨率(120 m),但由于只有一个热通道,要得到地表真实温度,原来需要利用辐射传输方程的方法,实时资料的缺乏限制了该方法的应用。因而由TM 6数据得到的通常都是星上亮度温度,而星上亮度温度与实际地表温度差距较大,因此,其反演的温度精度不高。而单窗算法和普适性单通道算法的提出为从TM 6数据较高精度地反演陆地表面温度提供了可能。分析和研究了这两个新的单通道温度反演算法,并针对北京市的实际情况,利用2005年5月6日的TM数据对北京市的陆地表面温度进行了反演,并用实地测量数据进行了比较验证。结果表明这两种温度反演算法都取得了较高的精度,它们的rm sd值分别为1.38°和2.18°。     

基于卫星影像的自动提取中尺度漩涡方法研究

中尺度漩涡蕴涵着海洋洋流的许多动力学信息。它对我们的海洋研究具有重要意义,如洋流,海洋渔业等。近年来出现许多漩涡提取的方法,例如,采用水文观测的方法(以设立各种浮标收集海洋资料的方法)不仅要耗费昂贵的人力物力且无法覆盖广大区域。本文提出一种借助星载传感器的温度场(SST)数据实现自动提取中尺度漩涡的技术方法。本技术借助漩涡与温度场(具有一定结构的温度场)之间存在的对应关系,通过分析温度场数据的特征获取漩涡的信息,从而实现自动提取漩涡的目标。本方法分为三个步骤:首先对温度场数据进行处理,得到温度等值线并对闭合等值线进行分组;然后就各分组闭合等值线来计算其特征参数;最后利用粗糙集理论对这些闭合等值线分组实现分类。研究中所使用的决策表,是以海洋学家从温度场影像中识别出的多个漩涡作为基础生成的,这样我们就可以利用专家的知识方便地从其他温度场影像中提取出漩涡。本文采用北大西洋湾流实例作为我们研究对象,实验表明本文采用的方法行之有效。     

Locating tuna forage ground through satellite remote sensing

A technique has been developed to assess tuna habitat using satellite derived ocean colour, water transparency and sea surface temperature. The scientific approach is based on the food and feeding habit and the preferential temperature range of tuna. Time series chlorophyll-a images of Indian Remote Sensing Satellite P4-Ocean Colour Monitor (IRS P4-OCM) have been analysed to define the critical phytoplankton patch size, its persistence and the optimal water transparency depth. Sea surface temperature (SST) data derived from National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) have been analysed to study the optimum temperature range in the surrounding waters. Results based on hindcasting indicate that the tuna forage ground derived from satellite data yielded high catch of tuna (>2% hooking rate). Study reveals that a minimum time delay of 5–7 days is required for a phytoplankton patch to mature to the forage ground. In addition, water transparency for facilitating sight feeding should be about 25–30 m depth. The thermal limit and preferential temperature range observed is 26–30°C and 26–28°C, respectively. Preliminary results based on limited validation are highly promising. However, an experimental forecast is being planned to validate this approach.     

A non-regression-coefficients method of sea surface temperature retrieval from space

For several years now NOAA/NESDIS have derived an operational global sea surface temperature (SST) product from the AVHRR instrument on the NOAA satellites. This is done using the MCSST and CPSST algorithms which contain coefficients that are determined from a regression analysis of satellite data against in situ surface data. The current algorithms are used to provide global SST data without taking into account the latitude, climate or location of the satellite data, although the CPSST coefficients do have a weak dependence on the satellite brightness temperatures. Because of this global application the current SST algorithms have inherent errors due to local climate influences. In this paper a new SST algorithm is developed that does not rely on regression analysis to derive its coefficients. By using the spatial variation of the brightness temperatures in a small area (50 km by 50 km) it is possible to derive the appropriate coefficients to use in the algorithm. The SST field can thus be derived at any location without need for prior determination of the algorithm coefficients. In a simulation study, data from twenty-five radiosonde ascents-arc use with an atmospheric transmission model to derive a range of atmospheric transmittances and satellite brightness temperatures. Coincident AVHRR data and ship data are used to assess the accuracy of the new algorithm. The various dependencies of the terms in the SST algorithm are investigated. As with the MCSST and CPSST algorithms, the new method has largest errors when applied in situations of abnormal atmospheric structure. The improvement over the MCSST product may initially be only marginal, but with the advent of the more precise data from the Along Track Scanning Radiometer (ATSR) a more accurate global SST product may be possible.     

Development of spectral band cloning techniques for soil nutrients estimation

Satellite‐based monitoring is an indispensable tool to guide soil‐specific crop management. However, it has attained little success in the estimation of soil nutrients due to the limitations incurred from inherent spectral characteristics. In this study, spectral band cloning (SBC) is developed and proposed to augment the soil nutrient predictive capabilities of broadband satellite data. Fine‐spectral channels of spectrometers were synchronized with coarse resolution of IRS satellite data to generate nutrient‐sensitive cloned IRS bands. Soil samples, collected at the time of satellite image acquisition in Lop Buri, Thailand, were analyzed both spectrally and chemically, viz., soil organic matter (OM), phosphorus, potassium and iron. The resulting SBC‐based models showed acceptable correlations, which otherwise were unattainable from raw IRS bands through prevailing models. Accuracy and validation measures showed good agreements between the measured and estimated nutrient surfaces. It is concluded that the SBC is a promising method of quantitative soil nutrient mapping, and could further be used for identification and mapping of other indiscernible biophysical parameters.     

Geometric correction and radiometric normalisation of NOAA AVHRR data for fisheries applications

Sea surface temperature (SST) has been found useful for locating potential fishing grounds (PFGs). Thermal data of the National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) was acquired using a microcomputer (PC/AT 486) based Direct Reception and Processing Terminal (DRPT) developed in-house to map surface thermal fronts. Geometric correction using orbital ephemeris and ground control points (GCPs) resulted in locational accuracy of 1·73 km by 2·1 km. Besides, the corrections for artificially lowering SST in case of passes with large satellite zenith angles (LSZA) through a radiance normalization based on the mean vectors and dispersion matrices to make it comparable with small satellite zenith angle (SSZA) pass is presented in this letter.     

AVHRR satellite remote sensing and shipboard measurements of the thermal plume from the Daya Bay, nuclear power station, China

The 1800 MW Daya Bay Nuclear Power Station (DNPS), China's first nuclear power station, is located on the coast of the South China Sea. DNPS discharges 29 10×10⁵ m³ year⁻¹ of warm water from its cooling system into Daya Bay, which could have ecological consequences. This study examines satellite sea surface temperature data and shipboard water column measurements from Daya Bay. Field observations of water temperature, salinity, and chlorophyll a data were conducted four times per year at 12 sampling stations in Daya Bay during January 1997 to January 1999. Sea surface temperatures were derived from the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) polar orbiting satellites during November 1997 to February 1999. A total of 2905 images with 1.1×1.1 km resolution were examined; among those images, 342 have sufficient quality for quantitative analysis. The results show a seasonal pattern of thermal plumes in Daya Bay. During the winter months (December to March), the thermal plume is localized to an area within a few km of the power plant, and the temperature difference between the plume and non-plume areas is about 1.5 °C. During the summer and fall months (May to November), there is a larger thermal plume extending 8-10 km south along the coast from DNPS, and the temperature change is about 1.0 °C. Monthly variation of SST in the thermal plume is analyzed. AVHRR SST is higher in daytime than in nighttime in the bay during the whole year. The strong seasonal difference in the thermal plume is related to vertical mixing of the water column in winter and to stratification in summer. Further investigations are needed to determine any other ecological effects of the Daya Bay thermal plume.     

Temporal and spatial variability of satellite sea surface temperature and ocean colour in the Japan/East Sea

Temporal and spatial variability of Sea Surface Temperature (SST) and ocean colour in the Japan/East Sea (JES) are examined during winter and spring using satellite data from Advanced Very High Resolution Radiometer (AVHRR) and Sea-viewing Wide Field of view Sensor (SeaWiFS). The timing of the spring phytoplankton bloom and the locations of the chlorophyll fronts are related to changes in the thermal fields and the locations of the temperature fronts. Daily images of SST and chlorophyll concentration show both differences and similarities of bio-optical and thermal front location, depending on region and season. Four sub-regions in the JES were defined and SST and chlorophyll values were extracted from weekly and monthly composite images to derive summary statistics. SST at the Subpolar Front increased about 7°C over a 1.5-month period from late April to early June in 1999. During this same period, elevated chlorophyll values near the Korean coast and in the southern basin decreased sharply as the phytoplankton bloom that first developed in the southern basin progressed to the front and northward. The SST/chlorophyll relationship is complex and seasonal. Near the Subpolar Front, SST and chlorophyll were positively related in April. In May, highest chlorophyll values corresponded to mixing regimes (such as areas of convergence and divergence at the edges of meanders) and, by June, SST and chlorophyll near the front were inversely related.     

中国东南地区及近海海域气溶胶反演遥感研究

大气气溶胶在很多生物地球化学循环中具有重要作用,但是由于它的来源广泛并且具有很大的时空变化性,难以在全球范围内精确、实时确定气溶胶的性质、组成及时空分布,因而对大气气溶胶的研究依赖于监测手段的发展。地基试验能获取点源的大气气溶胶光学厚度(AOD)的地面测量数据,得到的气溶胶光学厚度用于卫星数据的预处理以及气溶胶光学厚度反演的精度验证。而经过地基校验后的卫星遥感数据,可以反映大范围内实时动态的气溶胶信息。利用MODIS资料和地基探测的太阳光度计资料,对中国东南地区及近海海域的大气气溶胶光学特性进行了分析,讨论了适用于中国东南地区的大气气溶胶模型;利用连续的太阳光度计数据对MODIS资料的反演结果进行校验,结果表明：改进气溶胶模型和采用连续波段太阳光度计探测数据,可以提高MODIS AOD的校验结果。     

Reconstruction of sea surface temperature by means of DINEOF: a case study during the fishing season in the Bay of Biscay

The Spanish surface fishery operates mainly during the summer season in the waters of the Bay of Biscay. Sea surface temperature (SST) data recovered from satellite images are being used to improve the operational efficiency of fishing vessels (e.g. reduce search time and increase catch rate) and to improve the understanding of the variations in catch distribution and rate needed to properly manage fisheries. The images used for retrieval of SST often present gaps due to the existence of clouds or satellite malfunction periods. The data gaps can totally or partially affect the area of interest. Within this study, an application of a technique for the reconstruction of missing data called DINEOF (data interpolating empirical orthogonal functions) is analysed, with the aim of testing its applicability in operational SST retrieval during summer months. In this case study, the Bay of Biscay is used as the target area. Three months of SST Moderate Resolution Imaging Spectroradiometer (MODIS) images, ranging from 1 May 2006 to 31 July 2006, were used. The main objective of this work is to test the overall performance of this technique, under potential operational use for the support of the fleet during the summer fishing season. The study is designed to analyse the sensitivity of the results of this technique to several details of the methodology used in the reconstruction of SST, such as the number of empirical orthogonal functions (EOFs) retained, the handling of the seasonal cycle or the length (number of images) of the SST database used. The results are tested against independent SST data from International Comprehensive Ocean–Atmosphere Data Set (ICOADS) ship reports and standing buoys and estimations of the error of the reconstructed SST fields are given.

Conclusions show that over this area three months of data are enough for efficient SST reconstruction, which yields four EOFs as the optimal number needed for this case study. An extended EOF experiment with SST and SST with a lag of one day was carried out to analyse whether the autocorrelation of the SST data allows better performance in the SST reconstruction, although the experiment did not improve the results. The validation studies show that the reconstructed SSTs can be trusted, even when the amount of missing data is very high. The mean absolute deviation maps show that the error is greatest near to the coast and mainly in the upwelling areas close to the French and north-western Spanish coasts.     

Comparison between satellite and ship measurements of sea surface temperature in the north-east Atlantic Ocean

Abstract

A comparison is made between in situ measurements of sea surface temperature (SST) in the north-east Atlantic Ocean, obtained during Cruise 145 of RRS Discovery, and SSTs derived from several overpasses of the Advanced Very High Resolution Radiometer on the NOAA-7 satellite during the same period in March 1984. The objective of the analysis was to test the ability of the satellite to map the detailed features of SST structure and to examine the performance of atmospheric correction and temperature calibration procedures in this context. Gross comparison between all the cloud-free ship and satellite data confirms agreement normally within 1 degC. More detailed comparison of SST structure along the cruise tracks shows that the satellite data are able to identify features with a resolution of 0.3°C.