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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
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以武汉东湖为研究区域,利用MODIS数据和地面准同步叶绿素a浓度实测数据,建立适合东湖水体的叶绿素a浓度遥感定量估算模型,从而分析MODIS数据应用于内陆湖泊水体叶绿素a浓度反演的可行性。 相似文献
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在综合分析已有研究成果的基础上,选择MODIS遥感影像,借助灰色系统理论,结合观测站实测雪深数据,选择雪深反演特征参数,构建反演模型,并定义多元回归模型的综合评价系数,进而从构建的多个回归模型中,选择出雪深反演最优模型。 相似文献
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基于波谱知识库的MODIS叶面积指数反演及验证 总被引:3,自引:2,他引:3
目前用物理模型反演叶面积指数普遍存在缺少先验知识的状况,如何获得准确的先验知识是遥感走向应用的一个关键环节。中国典型地物标准波谱数据库就是结合国家重大行业中的应用需求,研究制定地物波谱获取与分析的技术规范和数据标准,建立典型地物标准波谱数据库。从波谱数据库提取模型反演所需要的先验知识,实现了基于SAIL模型的MODIS数据(经过几何纠正与大气纠正)叶面积指数的反演。另外,基于TM数据,对MODIS混合像元进行了分解,用纯像元的叶面积指数与实测数据进行对比验证,同时,反演结果与NASA的LAI产品也进行了对比,结果表明基于波谱库的先验知识可以有效的提高叶面积指数的反演精度。 相似文献
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余志飞 《测绘与空间地理信息》2015,(3):80-82
针对MODIS遥感数据采用多波段普间关系算法提取水体容易与阴影混淆,产生提取不精确的问题。作者将对多波段普间关系水体提取算法进行研究,并以鄱阳湖为实验对象,使用改进后的多波段普间关系算法对水体进行提取。实现提升水体提取精度的目标。 相似文献
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基于MODIS数据的上海市热岛效应的遥感研究 总被引:2,自引:0,他引:2
对2000,2005,2011年MODIS L1B数据,采用分裂窗算法定量反演了上海市地表温度,对上海市的热岛空间分布特征及规律,以及季节变化进行研究,分析了植被覆盖指数与地表温度之间的关系。研究结果表明,从2000年到2011年的11年间,上海高温区面积出现先增大后减小的过程。从高温区的四季分布来看,冬季高温区出现面积最小,而春夏高温区的面积最大,约占整个上海面积的一半。上海的春夏秋3季,植被指数与地面温度呈负相关关系,且相关系数大于0.6。因此可以通过增加绿化面积来减缓上海城市热岛效应。 相似文献
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以黄海及东海海域为对象,研究用MOD IS数据提取我国海域悬浮泥沙时空分布的定量遥感方法,建立了基于MOD IS数据的悬浮泥沙定量遥感实用模式。研究表明,用250 m和1 000 m分辨率的MOD IS数据进行悬浮泥沙浓度的定量遥感,可以达到实际应用的精度要求。这说明,MOD IS数据是研究近岸水体中悬浮物输运变化规律的一种经济实用数据源。 相似文献
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MODIS数据的海洋表面温度反演 总被引:4,自引:0,他引:4
以黄海及东海海域为对象,研究用MODIS数据提取我国海域海洋表面温度的方法,建立了适合于我国海域的MODIS海洋表面温度遥感实用模式。研究表明,此算法的反演精度比较高,用这种模式计算的海面温度可较真实地反映海洋表面温度分布状况。由于同一天可以获取同一地区的上午和下午两景MODIS数据,因此MODIS数据在探测海洋现象方面具有独特的优势。 相似文献
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为了提高北疆地区雪深时空分布监测的准确性,以该区域48个气象站点2006年12月—2007年1月的月平均雪深观测数据为基础,通过分析月均雪深空间自相关性及其与经纬度、高程的相关性,结合MODIS雪盖数据构建了多元非线性回归克里金插值方法,插值获得了北疆地区较高精度的雪深空间分布数据。将插值雪深数据与普通克里金插值法、考虑高程为辅助变量的协同克里金插值法的预测结果进行比较,结果表明:1相对普通克里金和协同克里金方法,多元非线性回归克里金法的12月份雪深预测精度分别提高了15.14%和9.54%,1月份的提高了4.8%和6.7%;2由于充分利用了经纬度和地形信息,多元非线性回归克里金法的雪深预测结果可提供更多细节信息;3预测结果客观地表达了雪深随经纬度和地形变化的趋势,反映了积雪深度的空间变异性;4基于不显著相关的协变量高程的协同克里金插值法预测的雪深数据精度劣于普通克里金插值法的预测结果。 相似文献
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The split-window algorithm is the most commonly used method for land surface temperature (LST) retrieval from satellite data. Simplification of the Planck’s function, as an important step in developing the SWA, allows us to directly relate the radiance to the temperature toward solving the radiative transfer equation (RTE) set. In this study, Planck’s radiance relationship between two adjacent thermal infrared channels was modeled to solve the RTE set instead of simplification of the Planck’s function. A radiance-based split-window algorithm (RBSWA) was developed and applied to Moderate Resolution Imaging Spectroradiometer (MODIS) data. The performance of the RBSWA was assessed and compared with three most common brightness temperature-based split-window algorithms (BTBSWAs) by using the simulated data and satellite measurements. Simulation analysis showed that the LST retrieval using RBSWA had a Root Mean Square Error (RMSE) of 0.5 K and achieved an improvement of 0.3 K compared with three BTBSWAs, and the LST retrieval accuracy using RBSWA was better than 1.5 K considering uncertainties in input parameters based on the sensitivity analysis. For application of RBSWA to MODIS data, the results showed that: 1) comparison between LST from MODIS LST product and LST retrieved using RBSWA showed a mean RMSE of 1.33 K for 108 groups of MODIS image covering continental US, which indicates RBSWA is reliable and robust; 2) when using the measurements from US surface radiation budget network as real values the RMSE of the RBSWA algorithm was 2.55 K and was slightly better than MODIS LST product; and 3) through the cross validation using Advanced Spaceborne Thermal Emission and Reflection Radiometer LST product, the RMSE of the RBSWA algorithm was 2.23 K and was 0.28 K less than that of MODIS LST product. We conclude that the RBSWA for LST retrieval from MODIS data can attain a better accuracy than the BTBSWA. 相似文献
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This study maps the geographic extent of intermittent and seasonal snow cover in the western United States using thresholds of 2000–2010 average snow persistence derived from moderate resolution imaging spectroradiometer snow cover area data from 1 January to 3 July. Results show seasonal snow covers 13% of the region, and intermittent snow covers 25%. The lower elevation boundaries of intermittent and seasonal snow zones increase from north-west to south-east. Intermittent snow is primarily found where average winter land surface temperatures are above freezing, whereas seasonal snow is primarily where winter temperatures are below freezing. However, temperatures at the boundary between intermittent and seasonal snow exhibit high regional variability, with average winter seasonal snow zone temperatures above freezing in west coast mountain ranges. Snow cover extent at peak accumulation is most variable at the upper elevations of the intermittent snow zone, highlighting the sensitivity of this snow zone boundary to climate conditions. 相似文献
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《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
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基于MODIS数据的湖北省油菜种植分布信息提取 总被引:1,自引:0,他引:1
MODIS归一化差值植被指数(MODIS-normalized difference vegetation index,MODIS-NDVI)时间序列产品能够连续反映植被的覆盖情况,是农作物遥感测量的重要数据源。为研究基于MODIS数据的油菜种植分布信息提取技术,选取湖北省为研究区,利用2008—2013年75个时相的MODIS-NDVI时序数据,结合农作物物候和地面调查样本等辅助资料,通过建立油菜种植面积提取模型,采用多次阈值比较方法提取了2009—2013年湖北省油菜种植分布信息,与统计数据比较,总体提取精度为85%左右。最后利用环境小卫星HJ-1A CCD数据进行精度验证,证明了MODIS-NDVI时序数据及本文方法在油菜种植面积提取中的可靠性,对掌握油菜种植面积和产量信息、加强农业生产管理、调整农业结构及辅助政府有关部门制定科学合理的农业政策具有重要意义。 相似文献
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以成都市为研究区,定量分析了各地表特征参数与地表温度之间的线性关系。通过对地表温度与归一化植被指数(NDVI)、归一化建筑指数(NDBI)、归一化水汽指数(NDMI)进行局部区域逐像元分析和总体区域统计分析,结果表明NDVI,NDMI,NDBI与地表温度间都存在明显的线性关系,可用于说明地表温度的动态变化,在3月份,NDMI与地温的相关性更优于NDVI。对传统城市热现象研究中,NDMI与NDBI能够用来以NDVI作为分析地表温度随季节而变化的互补的度量标准。 相似文献
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通过优化劈窗算法,建立适合长江口水域的海表温度反演模型,利用2000年至2012年的Terra-MODIS LIB晴空数据进行海表温度反演,得到长江口13年海表温度数据集,分析长江流域进入河口的水沙变化后河口水域海表温度的年际变化和季节性变化。结果表明:长江口海表温度主要受太阳辐射影响,温度场的空间分布由口内至外海呈现阶梯性变化。受海域潮流上溯和径流下泄的影响,口内口外的海表温度表现出不同的季节性变化特征:冬季,口外高口内低;夏季,则口外低,口内高。伴随着冬季流域进入河口的径流量增加,长江口口外海域的冬季海表温度也出现下降趋势。 相似文献
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Snow cover mapping is important for snow and glacier-related research. The spatial and temporal distribution of snow cover area is a fundamental input to the atmospheric models, snowmelt runoff models and climate models, as well as other applications. Daily snow cover maps from Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite were retrieved for the period between 2004 and 2007, and pixels in these images were classified as cloud, snow or snow-free. These images have then been compared with ground snow depth (SD) measurements from the four observatories located at different parts of Himalayas. Comparison of snow maps with in situ data showed good agreement with overall accuracies in between 78.15 and 95.60%. When snow cover was less, MODIS data were found to be less accurate in mapping snow cover region. As the SD increases, the accuracy of MODIS snow cover maps also increases. 相似文献