共查询到20条相似文献，搜索用时 578 毫秒
1.
针对MODIS影像的劈窗算法研究 总被引：27，自引：3，他引：27
在分析热红外遥感和现有的劈窗算法的理论基础上,针对MODIS数据对劈窗算法进行了推导。通过对热辐射强度和温度之间的关系计算,对Planck函数进行了线性简化,同时分析了MODIS的波段设置特点。MODIS的近红外波段适宜于反演大气水汽含量,而大气透过率主要从MODIS的近红外波段数据反演得到大气水汽含量,并进而根据水汽含量与大气透过率的关系来进行估算。通过MODIS的可见光波段、近红外和中红外波段数据,完全可以获得地表温度反演所需要的基本参数,从而形成了针对MODIS数据的地表温度反演的劈窗算法。最后以环渤海地区为实验区,对本文提出的方法进行了实际应用分析。 相似文献
2.
《International Journal of Digital Earth》2013,6(6):476-494
In recent years, algorithms have been developed to derive land surface temperature (LST) from geostationary and polar satellite systems. However, few works have addressed the intercomparison between Geostationary Operational Environmental Satellites (GOES) and the available suite of polar sensors. In this study, differences in LSTs between GOES and MODerate resolution Imaging Spectroradiometer (MODIS) have been compared and also evaluated against ground observations. Due to the lack of split-window (SW) channels in the GOES M (12)-Q era, a dual-window algorithm using a mid-infrared 3.9 µm channel is compared with traditional SW algorithm. It is found that the differences in LST between different platforms are bigger during daytime than those during nighttime. During daytime, LSTs from GOES with the dual-window algorithm are warmer than MODIS LSTs, while LSTs from the SW algorithm are close to MODIS LSTs. The difference during daytime is found to be related to anisotropy in satellite viewing geometry, and land surface properties, such as vegetation cover and especially surface emissivity at middle infrared (MIR) channel. When evaluated against ground observations, the standard deviation (precision) error (2.35 K) from the dual window algorithm is worse than that (1.83 K) from the SW algorithm, indicating the lack of split-window channel in the GOES M(12)-Q era may degrade the performance of LST retrievals. 相似文献
3.
为了探讨特定城市在热岛效应中的地表温度反演的有效方法,本文分别基于TM与MODIS影像并采用了目前较为成熟的单窗和劈窗算法对泰安市的地表温度进行反演,将泰安市各气象观测站的实测温度数据与两种算法的温度反演结果进行验证,通过反演结果对比分析,证明劈窗算法精度更高。并且,采用10年间的多期MODIS影像对泰安市热岛效应分析的劈窗算法的可行性和优势进行了普适性验证。实验结果证明,针对处于山区且地势起伏较大的泰安地区,劈窗算法能较好地减弱或消除上空大气含水量高对温度反演的影响,同时还能更好地获取地表比辐射率和大气透过率,而且反演温度的分布规律也符合研究区地貌和类型要素特征。最后,本文就分析结果给出了泰安市产生热岛效应的主要原因,并认为该区域城市化过程中的城市热岛效应正在进一步加剧。 相似文献
4.
针对Terra/MODIS数据的改进分裂窗地表温度反演算法 总被引：1，自引：0，他引：1
针对Terra/MODIS数据提出改进的分裂窗地表温度反演算法。充分考虑了传感器观测角度(VZA)的影响,并对地表和有效大气辐射按照不同的亮度温度区间分别进行Planck函数简化。利用TIGR3大气廓线库中的875条晴空大气廓线,ASTER波谱库中的106条地物发射率波谱,结合MODTRAN4大气辐射传输模型模拟得到分裂窗算法系数。利用MODTRAN4模拟数据对算法精度进行验证,结果表明本文的改进算法和原算法的均方根误差RMSE分别为0.34K和0.65K。敏感性分析表明,在中等湿润的大气条件下,算法对大气水汽含量并不敏感。该算法降低了传感器观测角度带来的地表温度反演误差。利用2009年6月美国SURFRAD辐射观测网6个站点的实测数据对改进算法、原算法以及MOD11_L2地表温度产品进行了对比验证,RMSE分别是0.93K、1.49K和1.0K,表明本文算法可以提高反演精度。 相似文献
5.
中国陆地区域陆表温度业务化遥感反演算法及产品运行系统 总被引：7，自引：0，他引：7
地表温度反演的裂窗算法已成功应用于NOAA系列卫星热红外遥感数据。目前，裂窗算法中应用较为广泛的一种是Becker等人于1990年提出的局地裂窗算法，主要是通过辐射传输模型模拟不同地表条件和大气状况下，地表温度和发射率对红外辐射亮温的影响，从而发展出一个利用AVHRR4，5通道亮温数据反演地表温度的线性模型。在晴空无云和地表比辐射率能精确估算的情况下，Becker算法反演地表温度的精度在1K以内。Becker算法用Lowtran程序模拟计算地表辐射量，且模型中参数主要针对NOAA-9传感器特性得到。本文在Becker算法的基础上，针对NOAA-16／17传感器热红外通道光谱响应函数特性，利用最新的、计算光谱分辨率更高的MODTRAN程序模拟不同大气状况下，不同地表温度和发射率对NOAAAVHRR4，5通道辐射亮温响应特性的影响，改进Becker算法中模型参数，使之能适用于NOAA-16／17热红外数据。同时，本文利用植被指数NDVI，在中国陆地区域lkm分辨率最新地表分类数据的基础上，得到模型中需要的地表比辐射率参数，将改进的模型应用于1km分辨率NOAA17数据，得到了旬合成中国陆地区域范围地表温度，通过地面气象台站实测数据对比验证．取得了较好的结果。 相似文献
6.
地表温度LST（Land Surface Temperature）是城市热环境研究的重要参数之一,城市下垫面极为复杂,LST空间差异性较高。高空间分辨率LST对精细化城市热环境监测和缓解具有重要意义。目前大部分城市遥感LST降尺度研究仍以二维角度为主,缺乏建筑三维结构的考虑。本研究同时考虑地表二维和三维指标,构建基于随机森林方法的降尺度模型,开展MODIS 1 km LST降尺度研究（100 m）,并探讨二维和三维建筑形态对LST影响的空间尺度效应。另外,为了弥补随机森林模型缺乏物理基础的不足,参考热辐射传输方程,将方程中传感器接收的辐亮度和与大气透过率相关的大气可降水量,加入降尺度模型构建中。为了更好利用真实观测的MODIS 1 km LST验证降尺度结果,故将MODIS LST和所有指标因子升尺度至5 km,开展5 km LST降尺度至1 km研究,进一步研究探讨大气顶层辐亮度和大气可降水量对LST降尺度的影响。研究结果表明：（1）随机森林模型中增加辐亮度和大气可降水量前后,通过将5 km LST降尺度后1 km LST与原始MODIS 1 km LST相比,RMSE和R2分别由3.1 K和0.5提高至0.38 K和0.94。（2）当随机森林模型中增加建筑形态指标后,模型的袋外分数OOB_score由0.46提高至0.49,模拟的100 m LST与ASTER LST产品比较,R2有所降低,可能的原因是ASTER 和MODIS LST的反演方法和传感器不同,造成两者在100 m尺度下的对比性差一些。但是当驱动因子中增加MOD02和MOD05后,RMSE和R2由2.4 K和0.29提高至1.2 K和0.68,进一步说明MOD02和MOD05在1 km LST降至100 m过程中,起到至关重要作用。（3）在1 km和100 m尺度下,增加建筑形态后,模型OOB_score均有提高,并且建筑形态指标的重要性有所不同,在100 m尺度下独立建筑形态的影响程度有所增加。综上,MODIS LST在城市地区降尺度研究中需要考虑大气顶层辐亮度、大气可降水量和建筑形态的影响,并且不同的建筑形态对LST的重要性存在空间尺度效应。 相似文献
7.
Land surface temperature (LST) is an important indicator of global ecological environment and climate change. The Sea and Land Surface Temperature Radiometer (SLSTR) onboard the recently launched Sentinel-3 satellites provides high-quality observations for estimating global LST. The algorithm of the official SLSTR LST product is a split-window algorithm (SWA) that implicitly assumes and utilizes knowledge of land surface emissivity (LSE). The main objective of this study is to investigate alternative SLSTR LST retrieval algorithms with an explicit use of LSE. Seventeen widely accepted SWAs, which explicitly utilize LSE, were selected as candidate algorithms. First, the SWAs were trained using a comprehensive global simulation dataset. Then, using simulation data as well as in-situ LST, the SWAs were evaluated according to their sensitivity and accuracy: eleven algorithms showed good training accuracy and nine of them exhibited low sensitivity to uncertainties in LSE and column water vapor content. Evaluation based on two global simulation datasets and a regional simulation dataset showed that these nine SWAs had similar accuracy with negligible systematic errors and RMSEs lower than 1.0 K. Validation based on in-situ LST obtained for six sites further confirmed the similar accuracies of the SWAs, with the lowest RMSE ranges of 1.57–1.62 K and 0.49−0.61 K for Gobabeb and Lake Constance, respectively. While the best two SWAs usually yielded good accuracy, the official SLSTR LST generally had lower accuracy. The SWAs identified and described in this study may serve as alternative algorithms for retrieving LST products from SLSTR data. 相似文献
8.
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。 相似文献
9.
地表温度LST（Land Surface Temperature）是全球气候变化研究的关键参数,遥感是获取全球和区域尺度地表温度的一种切实可行手段,但现有的单一传感器无法提供高时空分辨率的LST数据,限制了遥感地表温度数据的深入广泛应用。现有的降尺度方法难以生成无缝高时空分辨率的地表温度数据,且降尺度效果易受高空间分辨率LST数据缺失及有效时刻分布影响。本文提出了一种基于地表温度日变化模型DTC（Diurnal Temperature Cycle）偏差系数解算的地表温度降尺度方法,采用FY-4A、MODIS和Landsat 8的LST数据生成晴空及多云条件下逐小时100 m的无缝LST数据。方法主要包含4部分：（1）利用空值重建方法获取无缝的FY-4A的LST数据;（2）建立FY-4A LST数据的DTC模型;（3）采用时空融合模型对MODIS的LST数据进行空间降尺度;（4）解算DTC模型偏差系数,获取逐小时100 m分辨率的无缝LST数据。实验结果表明,本文提出的方法具有较高的降尺度精度,可获得晴空及多云条件下无缝高时空地表温度数据,且高空间分辨率的地表温度数据缺失和有效时刻分布对本文方法降尺度结果影响较小。 相似文献
10.
Angular effect of MODIS emissivity products and its application to the split-window algorithm 总被引：1，自引：0，他引：1
Huazhong RenGuangjian Yan Ling ChenZhaoliang Li 《ISPRS Journal of Photogrammetry and Remote Sensing》2011,66(4):498-507
The angular effects of emissivity are ignored in current land surface temperature (LST) products. As a result, the directionality of these LST products limits their further application in many fields. Accurate correction of the angular problem of LST products requires explicit understanding of the angular effects of emissivity at the pixel scale. Currently, nearly ten years of global emissivity products of MODIS are available. However, the pixel-scale directionality of emissivity has never been analyzed. By performing a statistical analysis of 5-year MODIS emissivity products over most of East Asia, we generated the empirical relationships between the directional emissivity, land cover, and seasonal variations. Two look-up tables (LUTs) of directional emissivity were created for typical land cover types and applied to the generalized split-window algorithm to modify the MODIS LST. The results showed that the angular effect of emissivity could introduce a significant bias of −1-3 K to the 1 km resolution LST. Finally, the spatial scale effects of emissivity were analyzed, and it was found that the temperature differences caused by scale effects fell within +/−0.5 K for most pixels if 5 km emissivity was used in 1 km LST retrieval. Therefore, wide use of the LUTs can be expected. 相似文献
11.
On the basis of simplification of the Planck function in a low temperature range, this paper revises the practical split-window algorithm and presents a method for retrieving snow surface temperature （Ts） based on MODIS data in the middle-latitude region. The application of this method in Qinghai Lake region reveals that it is feasible for the retrieval of Ts. Results of correlation analysis indicate that there was strong negative relationship between Ts and altitude. By analyzing three typical areas in which land cover was relatively homogenous, this paper discusses the relationship between Ts and normalized difference snow index （NDSI） and then presents a new concept named ＂NDSI-Ts space＂. 相似文献
12.
Indian geostationary satellite Kalpana-1 (K1) offers a potential to capture the diurnal cycle of land surface temperature (LST) through thermal infrared channel (10.5–12.5 μm) observations of the Very High Resolution Radiometer (VHRR) sensor. A study was carried out to retrieve LST by adapting a generalized single-channel (SC) algorithm (Jiménez-Muñoz and Sobrino, 2003) for the VHRR sensor over India. The basis of SC algorithm depends on the concept of Atmospheric Functions (AFs) that are dependent on transmissivity, upwelling and downwelling radiances of the atmosphere. In the present study AFs were computed for the VHRR sensor through the MODTRAN simulations based upon varying atmospheric and surface inputs. The AFs were fitted with the atmospheric columnar water vapour content and a set of coefficients was derived for LST retrieval. The K1-LST derived with the SC algorithm was validated with (a) in situ measurements at two sites located in western parts of India and (b) the MODIS LST products. Comparison of K1-LST with the in situ measurements demonstrated that SC algorithm was successful in capturing the prominent diurnal variations of 283–332 K in the LST at desert and agriculture experimental sites with a rmse of 1.6 K and 2.7 K, respectively. Inter comparison of K1-LST and MODIS LST showed a reasonable agreement between these two retrievals up to LST of 300 K, however a cold bias up to 7.9 K was observed in MODIS LST for higher LST values (310–330 K) over the hot desert region. 相似文献
13.
为了减少近地表大气逆温对地表温度遥感反演精度的影响,提出在晴空的地表温度"通用劈窗算法"模型中增加一个温度改正项来实现。在建立该误差改正项时,利用正常条件下的通用劈窗算法系数和具有不同逆温强度的逆温廓线,并结合大气辐射传输模型MODTRAN计算,得到近地表大气逆温条件下的地表温度反演误差,并在分析了该误差值与相应的逆温强度的关系后,发现该温度改正项可以表示为近地表大气逆温强度的二次项函数。为了进一步提高地表温度的反演精度,将地表温度和大气水汽含量进行分组,分别针对每个分组来确定温度改正项方程的系数。模拟结果表明,在逆温强度为1.7 K/100m时,该温度改正项可以使地表温度的反演精度提高0.44 K。利用内蒙古海拉尔试验站的实测数据对地表温度反演结果进行了验证,在近地表大气存在逆温的条件下,该方法能提高地表温度的遥感反演精度0.47K。但是,由于本文提出的方法需要已知大气温度廓线来计算大气逆温强度,因此在实际应用中该方法受到了一定的限制。 相似文献
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15.
基于MODIS数据的雪面温度遥感反演 总被引：3，自引：0，他引：3
通过对Planck函数在低温范围内进行线性化,改进了针对MODIS数据的实用性分裂窗算法,建立了基于MODIS数据的中纬度地区雪面温度遥感反演方法。以环青海湖地区为研究区进行了算法应用,取得了较理想的效果。验证并分析了雪面温度与海拔高度的负相关关系。通过对下垫面相对均一的3个样区进行分析,讨论了雪面温度与归一化积雪指数的关系,并提出了"NDSI-Ts空间"的概念。 相似文献
16.
The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVITHM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is significantly larger in the derived LST products than the corresponding radiant temperature images. 相似文献
17.
Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city,Eastern Algeria 总被引：1，自引：0，他引：1
In this study, we presented a mono-window (MW) algorithm for land surface temperature retrieval from Landsat 8 TIRS. MW needs spectral radiance and emissivity of thermal infrared bands as input for deriving LST. The spectral radiance was estimated using band 10, and the surface emissivity value was derived with the help of NDVI and vegetation proportion parameters for which OLI bands 5 and 4 were used. The results in comparison with MODIS (MOD11A1) products indicated that the proposed algorithm is capable of retrieving accurate LST values, with a correlation coefficient of 0.850. The industrial area, public facilities and military area show higher surface temperature (more than 37 °C) in comparison with adjoining areas, while the green spaces in urban areas (34 °C) and forests (29 °C) were the cooler part of the city. These successful results obtained in the study could be used as an efficient method for the environmental impact assessment. 相似文献
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Lei Lu Valentijn Venus Andrew Skidmore Tiejun Wang Geping Luo 《International Journal of Applied Earth Observation and Geoinformation》2011
The retrieval of land-surface temperature (LST) from thermal infrared satellite sensor observations is known to suffer from cloud contamination. Hence few studies focus on LST retrieval under cloudy conditions. In this paper a temporal neighboring-pixel approach is presented that reconstructs the diurnal cycle of LST by exploiting the temporal domain offered by geo-stationary satellite observations (i.e. MSG/SEVIRI), and yields LST estimates even for overcast moments when satellite sensor can only record cloud-top temperatures. Contrasting to the neighboring pixel approach as presented by Jin and Dickinson (2002), our approach naturally satisfies all sorts of spatial homogeneity assumptions and is hence more suited for earth surfaces characterized by scattered land-use practices. Validation is performed against in situ measurements of infrared land-surface temperature obtained at two validation sites in Africa. Results vary and show a bias of −3.68 K and a RMSE of 5.55 K for the validation site in Kenya, while results obtained over the site in Burkina Faso are more encouraging with a bias of 0.37 K and RMSE of 5.11 K. Error analysis reveals that uncertainty of the estimation of cloudy sky LST is attributed to errors in estimation of the underlying clear sky LST, all-sky global radiation, and inaccuracies inherent to the ‘neighboring pixel’ scheme itself. An error propagation model applied for the proposed temporal neighboring-pixel approach reveals that the absolute error of the obtained cloudy sky LST is less than 1.5 K in the best case scenario, and the uncertainty increases linearly with the absolute error of clear sky LST. Despite this uncertainty, the proposed method is practical for retrieving the LST under a cloudy sky condition, and it is promising to reconstruct diurnal LST cycles from geo-stationary satellite observations. 相似文献
20.
与混合像元的地表温度相比,植被和土壤的组分温度具有更明确的物理意义。因此,本文提出了一种从具有广泛应用的极轨卫星地表温度产品中分离出植被和土壤组分温度的算法。该算法使用温度日变化模型作为桥梁连接极轨卫星一日内的两次观测,利用多像元数据进行模型求解,从而得到过境时刻的地表植被和土壤组分温度。论文针对MODIS数据开展了地表组分温度的反演,并利用实测站点数据和高分辨率卫星数据对反演结果进行了验证。结果表明,该算法可以提供合理的植被和土壤组分温度信息,反演温度的误差变化范围为1.4 K到2.5 K。此外,对观测时刻组合方式的分析表明该算法只需要一次白天观测和一次夜晚观测就可以得到精度较好的分离结果,并且两次观测可以来自于不同传感器,进一步表明了算法具有良好的可操作性。 相似文献