Retrieval of urban land surface component temperature using multi-source remote-sensing data

The components of urban surface cover are diversified,and component temperature has greater physical significance and application values in the studies on urban thermal environment.Although the multi-angle retrieval algorithm of component temperature has been matured gradually,its application in the studies on urban thermal environment is restricted due to the difficulty in acquiring urban-scale multi-angle thermal infrared data.Therefore,based on the existing multi-source multi-band remote sensing data,access to appropriate urban-scale component temperature is an urgent issue to be solved in current studies on urban thermal infrared remote sensing.Then,a retrieval algorithm of urban component temperature by multi-source multi-band remote sensing data on the basis of MODIS and Landsat TM images was proposed with expectations achieved in this work,which was finally validated by the experiment on urban images of Changsha,China.The results show that:1)Mean temperatures of impervious surface components and vegetation components are the maximum and minimum,respectively,which are in accordance with the distribution laws of actual surface temperature;2)High-accuracy retrieval results are obtained in vegetation component temperature.Moreover,through a contrast between retrieval results and measured data,it is found that the retrieval temperature of impervious surface component has the maximum deviation from measured temperature and its deviation is greater than 1℃,while the deviation in vegetation component temperature is relatively low at 0.5°C.

基于多时相热红外遥感的理塘盆地地热资源探测

地热能是地球内部一种环保、可再生的地下热能,热量传导至地表会引起地表温度异常。然而,地表温度受到太阳辐射、周期性变化和降水等诸多因素的影响,可能掩盖由地热引起的温度异常。为了解决这些问题并突出地热引起的地表温度异常,文中提出了一种利用Google Earth Engine(GEE)高效快速计算多时相冬季平均地表温度并提取地热异常的方法,并对理塘盆地的地热资源分布特征进行了研究。该方法综合运用多时相冬季平均地表温度对比分析、水体剔除、地形效应抑制等手段来提取地热异常区。结果表明,文中确定的8处地热异常区与断裂构造关系密切,且区内水资源丰富,具备地热资源形成的良好条件,可以作为未来地热勘探的重点方向。研究认为,在高原恶劣环境中,利用多时相平均冬季地表温度识别地热异常是一种高效且经济的方法。

2023年积石山6.2级地震热红外异常研究

应用卫星遥感数据,采用相对功率谱法和均线差值振幅增强比法,提取甘肃积石山6.2级地震前的热红外信息。结果表明,震前存在显著的热红外异常现象。相对功率谱法提取到的热红外异常现象分为两个阶段:(1)在2023年10月以托莱山断裂和冷龙岭断裂交汇处为核心区,出现了沿北东向展布的热红外异常(功率谱最高值超过8);(2)在2023年11月,冷龙岭断裂和金强河断裂交汇处至日月山断裂和拉脊山断裂交汇处出现了较弱的热红外异常(功率谱最高值不到7),异常的空间演化逐步向震中靠近。均线差值振幅增强比法的计算结果显示出背景性异常的特征,9月在祁连山中东至甘东南段出现了显著的长波辐射异常,两种热红外异常提取方法的结果起到了互相佐证的作用。

Genetic inverse algorithm for retrieval of component temperature of mixed pixel by multi-angle thermal infrared remote sensing data

After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature. Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm (GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA.

Atmospheric correction of Landsat data for the retrieval of sea surface temperature in coastal waters

A mono-window algorithm was introduced to retrieve sea surface temperature （SST） using Landsat data in coastal waters. In this algorithm, the effective mean air temperature and the water vapor content of air column were estimated with the local meteorological parameters of air temperature and relative humidity, based on the facts that in the troposphere, （ 1 ） air temperature decreases linearly with the altitude, and （2） water vapor content lapses exponentially with the altitude. The sea-truth temperature data and MODIS Terra SST product were used to validate the SST retrieved from Landsat TM and ETM ＋ thermal infrared （TIR） data with the algorithm. The results show that the algorithm can improve the spatial temperature contrast which is often masked due to water vapor effects, and the temperature derived from the algorithm is closer to the sea-truth SST. When applying the algorithm, the initial parameters of air temperature and relative humidity can be easily collected from local meteorological stations, and there is no need to identify the model of air profile.

REMOTE SENSING OF CLOUD BOTTOM HEIGHT AND CLOUD TEMPERATURE BY INFRARED RADIOMETER

The feasibility of retrieving cloud bottom height (CBH) and cloud bottom temperature (CBT) by infrared radiometer has been studied by simulations with a large number of historical radiosounding data and field obser- vations.The results show that it is feasible to retrieve CBH and CBT by radiometer observation in infrared band. In this paper we also demonstrate simply that through joint observations by a dual-wavelength (1.35 cm and 8.5mm) microwave radiometer and by infrared radiometer (8.5—12.5μm),it is possible to obtain total water vapor,liquid water content in clouds and CBH and CBT.

Analysis of Thermal Infrared Anomalies for the April16,2013M_W7.8of Khash, Iran Earthquake

After using the "Time-Frequency Relative Power Spectrum"( T-F RPS) method based on the China Geostationary Meteorological Satellite( FY-2 C/FY-2 E) infrared remote sensing brightness temperature data processing,we rapidly and accurately extracted and identified pre-earthquake thermal infrared anomalies for the April 16,2013 MW7. 8 of Khash,Iran Earthquake. Spatial evolution of anomalies showed the distribution and process. The anomalies were mainly distributed in the east of Khash,Iran. The characteristics of process and distribution presented X-Type model of NE and near NS strip which relates to the geological structure of this region. The epicenter was located near the intersection region of the X-Type abnormal migration process. Besides,the results of time series of anomalies showed that,the duration was more than 40 days and the maximum amplitude was about18 times. The earthquake occurred 20 days after the abnormal maximum amplitude which appeared on March 26,2013.

光照与阴影对无人机热红外遥感监测土壤含水率的影响

为探究作物冠层受阳光直射或阴影遮挡对无人机热红外遥感诊断作物水分胁迫、监测土壤含水率的影响,该研究以不同灌溉处理的夏玉米为研究对象,将热红外图像划分为光照冠层、阴影冠层、光照土壤、阴影土壤4个部分,分别提取光照温度与阴影温度后计算了11:00、13:00、15:00的冠气温差(冠层温度与大气温度之差,ΔT)、作物水分胁迫指数(crop water stress index,CWSI)、蒸发比(潜热通量与有效能量的比值,evaporative fraction,EF),并对比了3种指数在不同时刻使用光照温度(ΔT_(L)、CWSI_(L)、EF_(L))与阴影温度(ΔT_(S)、CWSI_(S)、EF_(S))后对土壤含水率的监测效果变化情况。结果表明:1)3种指数的监测效果会随时间发生变化,11:00与15:00时EF监测效果较好,13:00时CWSI监测效果较好,ΔT的监测效果较差但随时间波动最小;2)拔节期在区分光照温度与阴影温度后监测效果在11:00时提升幅度最大,EF、EF_(S)、EF_(L)的R^(2)分别为0.54、0.65、0.78,CWSI、CWSI_(S)、CWSI_(L)的R^(2)分别为0.47、0.64、0.70,抽雄期与灌浆期使用光照温度对监测效果提升不大,但使用阴影温度的指数监测效果有明显降低,在13:00时CWSIS较CWSI有最大降幅,R^(2)降幅分别为0.11、0.06;3)在拔节期与抽雄期使用11:00的EFL,在灌浆期使用13:00的CWSI能取得最好的土壤含水率监测效果,验证期预测土壤含水率的R2分别为0.75、0.75、0.89。该研究可以为无人机热红外监测土壤含水率提供参考。

基于随机森林模型的黑龙江省地表温度降尺度的研究

作为研究地表能量平衡的重要参数,地表温度是研究地表物理过程、监测全球资源环境以及气候变化的重要指标之一。通过降尺度处理提高MODIS LST数据空间分辨率,对LST和气候的研究都具有重要的意义。选取黑龙江省作为研究区,选择MOD11A2数据,通过随机森林算法对MODIS LST(1 000 m空间分辨率)进行降尺度处理,并通过气象数据作为验证。试验结果表明:利用随机森林算法对黑龙江省LST数据进行降尺度,降尺度结果良好,降尺度LST的均方根误差(Root Mean Square,RMSE)为2.13 K。

全球地表热辐射特性数据集构建技术研究

红外遥感成像主要采集地表热辐射特性,具有观测对象动态范围广、能量时空变化度高等特点。为实现高像质、高效率的红外遥感观测,迫切需要研究全球地表热辐射特性的时空分布规律,形成卫星总体设计的重要先验知识库,用于指导卫星面向观测数据质量的智能化设计。针对现有的全球地表热辐射数据集时空覆盖率较低、缺值较严重的问题,文章基于多源卫星遥感数据,通过遥感数据融合技术,构建较为完备的全球地表热辐射数据集,为星上空间相机最佳成像参数自主选取提供有力支撑。

基于FY-3D MERSIⅡ数据的辽宁省作物生长季日平均气温估算方法比较

作为反映气候特征的重要指标之一,日平均气温在农业气象灾害监测和气候变化研究等领域承担着至关重要的作用。与传统日平均气温的监测和估算方式相比,遥感技术具有全方位、宏观、动态等不可比拟的绝对优势,能够准确地描述日平均气温的空间异质性。为提高农业服务质量,保证农业健康、可持续发展,探索作物生长季日平均气温遥感反演方法,提高农业气象灾害监测精确度,以FY-3D MERSIⅡ遥感数据为基础,提取研究区日间地表温度(LST_(day))、夜间地表温度(LST_(night))、归一化植被指数(NDVI),同时还考虑了高程(DEM)、坡度(Slope)两个变量,结合气象站日平均气温数据,分别构建多元线性回归和随机森林日平均气温遥感反演模型,开展辽宁省2021年作物生长季(5—9月)日平均气温遥感监测的应用研究。结果表明:(1)基于多元线性回归模型反演的日平均气温均方根误差(RMSE)为1.71℃,平均绝对误差(MAE)为1.45℃;基于随机森林反演误差RMSE为1.17℃,MAE为0.96℃;整体上,随机森林的日平均气温反演结果更好,适用性更强。(2)实验当天和前1 d的降水总量对日平均气温的估算结果具有很大影响,降水量随时间的变化曲线与日平均气温的反演误差散点分布情况基本一致,呈现降水总量越大,日平均气温的反演误差越大的趋势,日平均气温反演结果受大气水汽含量的影响很大。(3)对输入的气温影响因子的重要性进行动态的统计分析,发现LST_(day)和DEM是日平均气温反演时两个最重要的变量,且LST_(day)对日平均气温反演的影响最为重要,但是随着作物的生长,DEM的重要性也越来越凸显。

遥感方法在宁武煤田煤火识别中的应用

煤火燃烧会对周围地区的环境、经济和安全造成严重影响,准确识别煤田自燃引起的火区范围对于监测与治理煤火具有重要意义。相关学者分别通过提取地表热异常或地表形变信息来识别煤火范围,但由于方法及手段单一,而引起煤火发生因素众多,导致试验结果不够准确。为提高煤火识别准确性,通过实际应用研究,利用融合卫星热红外技术与雷达技术的煤火识别方法,应用于山西省宁武煤田的火区识别。首先采用ASTER–TES(Temperature-Emissivity Separation)算法对ASTER夜间热红外数据进行地表温度反演,同时利用SBAS–InSAR(Small Baseline Subset InSAR)技术对Sentinel-1数据进行地表沉降信息反演,然后通过阈值分割法提取研究区域中的高温异常区域和沉降异常区域,进而融合处理,获得疑似煤田火区范围,最后利用测氡的实地勘测方法所确定的煤火范围对试验结果进行对比验证分析。结果显示:研究提出的方法对宁武煤田火区范围的识别准确率高达93.78%,较单一的温度反演方法与沉降异常方法提高43.29%和62.23%,但有部分火区未被识别,原因在于利用地表形变识别火区的阈值难以获取。结果表明:热红外技术与雷达技术协同识别方法能够有效克服单一识别方法的不足,显著提高煤火范围的识别精度,为准确圈定火区的治理范围提供有力参考,今后应深入研究地表形变探测火区的方法特性,从而获得更加全面准确的煤火范围。

Landsat 9数据的地表温度反演算法优化

地表温度作为地表与大气之间能量交换的关键参数被广泛地用于众多领域。本文针对Landsat 9数据,优化了单窗算法模型和劈窗算法模型,实现了地表温度反演,并结合SURFRAD站点实测数据和地表温度产品进行了精度验证分析。结果表明:两种算法模型的确定系数均大于0.96,其中劈窗算法模型精度较高,误差(RMSE)值为1.45 K左右,单窗算法模型精度较低,误差(RMSE)值为1.61 K左右;劈窗算法模型相较于单窗算法模型对参数的敏感性较低,在高水汽含量范围内,劈窗算法模型的结果要优于单窗算法模型的结果;本文提出的地表温度反演方法结果与官方地表温度产品的误差(RMSE)值均在2.5 K以内,可满足热红外遥感数据生产地表温度产品的应用需求。

热红外遥感对马尾松林松材线虫病早期响应研究

松材线虫病由于传播速度快、致死率高等特点也被称“松树的癌症”,早期监测非常重要。基于Landsat 8 TIRS热红外遥感数据评估绿色攻击阶段的植被温度的异常变化,并探究其监测潜力。应用2018年江西省吉安市万安县的Landsat 8 TIRS遥感数据,通过单窗算法反演地表温度(LST)。以30个100 m×100 m样地的受害马尾松林的枯梢率为指标,分别开展5月(绿色阶段)、7月(绿色攻击阶段)及11月(红褐色-灰色阶段)3个不同月份的LST与枯梢率(SDR)的相关性分析。对比分析热红外和Sentinel-2光学数据在早期监测能力上的差异。结果表明,1)Landsat 8反演的地表温度LST分布合理,对虫害区域有响应;2)LST与枯梢率在5月(0.01<P<0.05)、7月(P<0.01)和11月(P<0.01)均有良好的相关性;联合光谱指数能够提升对SDR的反演结果精度。通过精度结果对比发现,NDVI与LST建立的模型精度最高;3)除NDVI(P<0.01)以外,光学光谱指数与枯梢率的关系在5月与7月不显著。经研究发现通过热红外遥感手段有可能实现对松材线虫病的早期环境变化监测,比光学波段预警时间可以提前约20 d。

热红外遥感对煤矸石山温度的反演研究

为探究利用热红外遥感反演的地表温度对煤矸石山识别情况,基于Landsat TM卫星遥感影像和研究区的气象数据、矢量数据等,采用单窗算法对研究区域的地表温度进行反演,并将反演出的地表温度异常区域与阳泉市实际煤矸石山分布情况做对比,验证利用反演结果识别煤矸石山的准确性。结果表明,阳泉矿区的高温异常区除了与煤矸石分布有关,也与矿区煤炭和工厂分布有关;利用反演结果提取的高温异常区可作为煤矸石山温度精准探测的参考,从而提升判断煤矸石山自燃位置的效率。

Progress in monitoring high-temperature damage to rice through satellite and ground-based optical remote sensing

The occurrence of rice high-temperature damage (HTD) has increased with global warming. Cultivation of rice is seriously affected by the HTD in the middle and lower reaches of the Yangtze River, which directly affects food security in this region and in the whole of China. It is important to monitor and assess crop HTD using satellite remote sensing information. This paper reviews the recent development of monitoring rice HTD using optical remote sensing information. It includes the use of optical remote sensing information to obtain the regional spatial distribution of high temperatures, mixed-surface temperature retrieval for rice fields based on mixed decomposition information, the development of field and thermal infrared testing and modeling, and the satellite/ground-based remote sensing coupled method for monitoring rice HTD. Finally, the prospects for monitoring crop HTD based on remote sensing information are summarized.

Performance of the Large Field of View Airborne Infrared Scanner and its application potential in land surface temperature retrieval

The Large Field of View Airborne Infrared Scanner is a newly developed multi-spectral instrument that collects images from the near-infrared to long-wave infrared channels.Its data can be used for land surface temperature(LST)retrieval and environmental monitoring.Before data application,quality assessment is an essential procedure for a new instrument.In this paper,based on the data collected by the scanner near the Yellow River in Henan Province,the geometric and radiometric qualities of the images are first evaluated.The absolute geolocation accuracy of the ten bands of the scanner is approximately 5.1 m.The ground sampling distance is found to be varied with the whisk angles of the scanner and the spatial resolution of the images.The band-to-band registration accuracy between band one and the other nine bands is approximately 0.25 m.The length and angle deformations of the ten bands are approximately 0.67%and 0.3°,respectively.The signal-to-noise ratio(SNR)and relative radiometric calibration accuracy of bands 4,9,and 10 are relatively better than those of the other bands.Secondly,the radiative transfer equation(RTE)method is used to retrieve the LST from the data of the scanner.Measurements of in situ samples are collected to evaluate the retrieved LST.Neglecting the samples with unreasonable retrieved LST,the bias and RMSE between in situ LST measured by CE312 radiometer and retrieved LST are−0.22 K and 0.94 K,and the bias and RMSE are 0.27 K and 1.59 K for the InfReC R500-D thermal imager,respectively.Overall,the images of the Large Field of View Airborne Infrared Scanner yield a relatively satisfactory accuracy for both LST retrieval and geometric and radiometric qualities.

水体温度无人机热红外遥感监测研究——以辽河七星湿地为例

以辽河七星湿地内部分水域为研究区域,选用Flir T660热红外成像仪和大疆多旋翼无人机,搭建了热红外无人机遥感平台,获取了研究区域的热红外遥感数据,研究了用无人机获取的Flir热红外影像的处理和拼接方法,生成了监测区域的热红外温度分布图,分析了利用热红外遥感技术进行水体温度监测的可行性。

无人机热红外遥感技术对矿区煤火探测识别研究

提出了1套高效的卫星和无人机遥感煤火快速探测方法,以陕蒙交界煤炭资源开发强度最大的国能神东煤炭集团有限责任公司石圪台煤矿为研究区,采用卫星热红外大范围圈定煤火靶区,通过无人机高分辨率热红外和光学遥感精细探测煤火的具体位置和温度,并分析其存在的问题和提出改进措施。研究发现,利用卫星热红外遥感反演地表温度来进行煤火识别的准确性不够,因卫星数据分辨率较低,各种因素影响导致温度计算误差较大,反演温度普遍偏低,但能够将卫星反演数据作为研究靶区圈定的依据;无人机热红外探测地表分辨率达厘米级,可以准确探测煤火发生的具体位置、范围以及温度,获得了煤火燃烧顶点温度326.2℃,超过300℃的有9处,其他高温火区也符合矿区采掘和煤火发育规律;卫星和无人机结合的煤火探测模式充分发挥了各自的优势,能够做到高效、便捷、准确地识别煤火信息,结合多源数据的综合解译能够为小尺度矿区煤火探测形成一套完整的操作技术流程。

基于多源遥感数据的森林火灾应急监测

针对目前森林火灾应急救援工作中火情监测手段单一、实时性、全面性不够的问题。本文总结了一种基于多源遥感监测数据的复杂地形森林火灾应急监测工作方法,解决了宏观尺度下森林火灾应急监测不够实时和全面的问题。研究结果表明:①空天地联合监测的火情信息获取方法具有全面、机动性和实时性等优势,可有效辅助于森林火灾现场指挥救援工作;②以吉林一号和高分一号为主的国产卫星载荷下的光学监测和夜光遥感监测可对火灾区域进行宏观尺度的持续观测;③无人机载荷的热红外探测和激光测距传感器可以实时获取夜间和小范围区域内的火点信息,助力火灾打早打小。本文研究成果可为森林火灾应急指挥部在火场地形地貌分析、救援力量部署、火灾实时追踪监测和灾后复燃隐患防控等工作提供科学决策支撑。