共查询到20条相似文献，搜索用时 500 毫秒
1.
Geostatistical analysis of soil moisture measurements and remotely sensed data at different spatial scales 总被引：1，自引：0，他引：1
The European remote sensing satellite (ERS-2) synthetic aperture radar (SAR) data was used for temporal monitoring of soil moisture at Sukhothai, Thailand. Higher correlations were found between the observed soil moisture and the radar backscattering coefficient. The soil moisture distribution shows great variation in space and time due to its stochastic nature. In order to obtain a better understanding of the nature and causes of spatial variation of soil moisture, the extensive soil moisture measurements observed in Thailand and also remotely sensed ERS-2 SAR data were used for geostatistical analysis. The observed soil moisture shows seasonal variations with mean varying from 3.33 %v/v (dry season) to 33.44 %v/v (wet season). The spatial geostatistical structure also shows clear seasonal variations in the geostatistical characteristics such as range and sill. The sills vary from 1.00 (%v/v)2 for the driest day to 107.57 (%v/v)2 for one of the wet days. The range or the correlation lengths varies between 46.5 and 149.8 m for the wettest and driest periods. The nugget effect does not show strong seasonal pattern or trend but the dry periods usually have a smaller nugget effect than the wet periods. The spherical variogram model fits the sample variograms very well in the case of soil moisture observations while the exponential model fits those of the remotely sensed data. The ranges observed from the observed soil moisture data and remotely sensed data at the same resolution are very similar. Resolution degradation affects the geostatistical structure of the data by reducing the sills, and increasing the ranges. 相似文献
2.
Soil moisture from operational meteorological satellites 总被引：2，自引：0，他引：2
Wolfgang Wagner Vahid Naeimi Klaus Scipal Richard de Jeu José Martínez-Fernández 《Hydrogeology Journal》2007,15(1):121-131
In recent years, unforeseen advances in monitoring soil moisture from operational satellite platforms have been made, mainly due to improved geophysical retrieval methods. In this study, four recently published soil-moisture datasets are compared with in-situ observations from the REMEDHUS monitoring network located in the semi-arid part of the Duero basin in Spain. The remotely sensed soil-moisture products are retrieved from (1) the Advanced Microwave Scanning Radiometer (AMSR-E), which is a passive microwave sensor on-board NASA’s Aqua satellite, (2) European Remote Sensing satellite (ERS) scatterometer, which is an active microwave sensor on-board the two ERS satellites and (3) visible and thermal images from the METEOSAT satellite. Statistical analysis indicates that three satellite datasets contribute effectively to the monitoring of trends in surface soil-moisture conditions, but not to the estimation of absolute soil-moisture values. These sensors, or rather their successors, will be flown on operational meteorological satellites in the near future. With further improvements in processing techniques, operational meteorological satellites will increasingly deliver high-quality soil-moisture data. This may be of particular interest for hydrogeological studies that investigate long-term processes such as groundwater recharge. 相似文献
3.
遥感技术在陆面过程研究中的应用进展 总被引：10，自引：1，他引：10
探讨了当前陆面过程 (LSP)研究的特点 ,指出遥感在陆面过程研究中的应用以及陆面过程国际合作实验是突出的特点 ,进而对遥感技术的陆面参数获取、地表能量通量的计算以及与 LSP模式的结合研究及进展进行了综述。根据不同特征的地表参数选择光学遥感或微波遥感已成共识 ,而综合利用不同遥感数据获取同一种地表参数也已成为研究热点 ,当前及今后发射的携载多种遥感仪器的众多遥感卫星为此项研究提供了条件 ;遥感与 LSP模式的结合研究是遥感在陆面过程研究中深入应用的一个方面 ,国际陆面过程合作实验是这项研究的重要保证。 相似文献
4.
This study examines linear spectral unmixing technique for mapping the surface soil types using field spectroscopy data as the reference spectra. The investigated area is located in North Sinai, Egypt. The study employed data from the Landsat 7 ETM+ satellite sensor with improved spatial and spectral resolution. Mixed remotely sensed image pixels may lead to inaccurate classification results in most conventional image classification algorithms. Spectral unmixing may solve this problem by resolving those into separate components. Four soil type end-members were identified with minimum noise fraction and pixel purity index analyses. The identified soil types are calcareous soils, dry sabkhas, wet sabkhas, and sand dunes. Soil end-member reference spectra were collected in the field using an ASD FieldSpec Pro spectrometer. Constrained sum-to-one and non-negativity linear spectral unmixing model was applied and the soil types map was produced. The results showed that linear spectral unmixing model can be a useful tool for mapping soil types from ETM+ images. 相似文献
5.
基于ASAR-APP影像数据和光学影像数据,根据水云模型研究了小麦覆盖下地表土壤含水量的反演方法。利用TM和MODIS影像构建的植被生物、物理参数与实测小麦含水量进行回归分析,发现TM影像提取的归一化水分指数(NDWI)反演精度较好,相关系数达到0.87。根据这一关系,结合水云模型并联立裸露地表土壤湿度反演模型,建立了基于多源遥感数据的土壤含水量反演模型和参数统一求解方案。反演结果表明:该方案可得到理想的土壤水分反演精度,并可控制参数估计的误差。反演土壤含水量和准同步实测数据的相关系数为0.9,均方根误差为3.83%。在此基础上,分析了模型参数的敏感性,并制作了研究区土壤缺水量分布图。 相似文献
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The relationship between drought activity and vegetation cover in Northwest China from 1982 to 2013 总被引：1，自引：0，他引：1
Yelin Jiang Ranghui Wang Qing Peng Xiaoquan Wu Husen Ning Cheng Li 《Natural Hazards》2018,92(1):145-163
We investigated drought activity and the relationship between drought and vegetation in Northwest China over the period 1982–2013 using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI). The indexes were, respectively, calculated from ground-based meteorological data and from remotely sensed satellite data. The spatial and temporal distributions of drought (SPEI) and of vegetation cover (NDVI) were compared using annual trends, and the relationships between these trends were analyzed. The results are: (1) Overall, Northwest China had a drought trend during the study period, although some a few regions show a significant wetness trend; (2) the mean annual NDVI fluctuates, but overall shows an increasing trend, particularly in some mountainous areas that have at least adequate water and vegetation cover, while unused land becomes degraded; (3) most regions show a positive correlation between SPEI and NDVI, although the western parts of the Tarim basin, Qaidam basin, and some regions in the southeastern part of study area show a negative correlation; and (4) the various regions respond differently to global climate change, but in general regions with more vegetation cover show increased vegetation growth, while regions with less vegetation cover are becoming degraded and thus more vulnerable to the adverse effects of climate change. 相似文献
9.
为了揭示中国表层土壤湿度的时空分布特征及主要影响因子,通过SMAP、SMOS、AMSR2、FY3B和FY3C 5个卫星平台的遥感信息,采用集合平均法合成了2015-2016年中国25 km、逐日表层土壤湿度信息,通过比较5套产品之间的差异来分析卫星产品的不确定性,分析了中国土壤湿度的空间和季节分布特征以及同降雨量和蒸散发量的关联。结果表明:中国表层土壤湿度呈较明显带状分布,与干湿气候带的分布基本一致,总体由西北向东南和东北增加;土壤湿度在大部分地区呈现明显季节变化,主要表现为夏高冬低,不同地区的季节变化特征有所不同;中国60%以上地区,土壤湿度受同步和前期降雨量的强控制影响;中国87.5%的地区土壤湿度和蒸散发呈显著正相关和强依存关系。 相似文献
10.
Defining the surface hydrological parameters represents a crucial factor for the sustainable development purposes. In areas with heavy precipitation and rugged topography, these parameters control the occurrence of some natural hazards, from which the flash flood gets the most attention. Traditional methods for the assessment of the surface hydrological parameters are costly, time-consuming and provide information for limited geographic extent. On the other hand, remotely sensed data provide a cost-effective, rapid and wide aerial coverage with adequate accuracy. Geospatial analysis of these remotely sensed data provides a suitable and effective method for the reconnaissance determination of the surface hydrological parameters. In this work, digital elevation models, Landsat 8 satellite images as well as digital maps of soil and land use for Kyushu Island were acquired and analyzed using geographic information system. Surface hydrological parameters were determined in terms of watershed boundaries, soil moisture, initial abstraction as well as flash flood potentiality. Results of this research show a great correlation with historical flash flood events that occurred in the island. The northern parts of the island are subjected to the threat of flash floods. A follow-up is recommended in some areas on the island. As a conclusion, the geospatial analysis performs an accurate reconnaissance method for hydrological analysis at regional scale, which in turn guides the detailed field observation saving time and cost.
相似文献11.
Precipitation is a key input variable for hydrological and climate studies. Rain gauges can provide reliable precipitation measurements at a point of observations. However, the uncertainty of rain measurements increases when a rain gauge network is sparse. Satellite-based precipitation estimations SPEs appear to be an alternative source of measurements for regions with limited rain gauges. However, the systematic bias from satellite precipitation estimation should be estimated and adjusted. In this study, a method of removing the bias from the precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping of gauge and satellite measurements over several climate zones as well as inverse-weighted distance for the interpolation of gauge measurements. Seven years (2010–2016) of daily precipitation estimation from PERSIANN-CCS was used to test and adjust the bias of estimation over Saudi Arabia. The first 6 years (2010–2015) are used for calibration, while 1 year (2016) is used for validation. The results show that the mean yearly bias is reduced by 90%, and the yearly root mean square error is reduced by 68% during the validation year. The experimental results confirm that the proposed method can effectively adjust the bias of satellite-based precipitation estimations. 相似文献
12.
C K Unnikrishnan John P George Abhishek Lodh Devesh Kumar Maurya Swapan Mallick E N Rajagopal Saji Mohandas 《Journal of Earth System Science》2016,125(5):935-944
Surface level soil moisture from two gridded datasets over India are evaluated in this study. The first one is the UK Met Office (UKMO) soil moisture analysis produced by a land data assimilation system based on Extended Kalman Filter method (EKF), which make use of satellite observation of Advanced Scatterometer (ASCAT) soil wetness index as well as the screen level meteorological observations. Second dataset is a satellite soil moisture product, produced by National Remote Sensing Centre (NRSC) using passive microwave Advanced Microwave Scanning Radiometer 2 measurements. In-situ observations of soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil moisture products. The difference between these datasets over India is minimum in the non-monsoon months and over agricultural regions. It is seen that the NRSC data is slightly drier (0.05%) and UKMO soil moisture analysis is relatively wet during southwest monsoon season. Standard AMSR-2 satellite soil moisture product is used to compare the NRSC and UKMO products. The standard AMSR-2 and UKMO values are closer in monsoon season and AMSR-2 soil moisture is higher than UKMO in all seasons. NRSC and AMSR-2 showed a correlation of 0.83 (significant at 0.01 level). The probability distribution of IMD soil moisture observation peaks at 0.25 m3/m3, NRSC at 0.15 m3/m3, AMSR-2 at 0.25 m3/m3 and UKMO at 0.35 m3/m3 during June–September period. Validation results show UKMO analysis has better correlation with in-situ observations compared to the NRSC and AMSR-2 datasets. The seasonal variation in soil moisture is better represented in UKMO analysis. Underestimation of soil moisture during monsoon season over India in NRSC data suggests the necessity of incorporating the actual vegetation for a better soil moisture retrieval using passive microwave sensors. Both products have good agreement over bare soil, shrubs and grassland compared to needle leaf tree, broad leaf tree and urban land cover types. 相似文献
13.
地表土壤湿度影响着陆-气能量交换和水循环,是泥石流、冻土冻融等灾害的重要因子,获取川藏交通廊道沿线地区土壤湿度有助于研究铁路沿线气候变化和冰冻圈灾害风险.基于CYGNSS(cyclone global navigation satellite system)星载GNSS-R(global navigation satellite system reflectometry)信号,结合土地覆盖分类、归一化差分植被指数NDVI(normalized differential vegetation index)和粗糙度等地表土壤湿度影响因子,利用人工神经网络方法建立了地表土壤湿度多参数反演模型,生成了2018—2019年连续两年的川藏交通廊道沿线地区36 km空间分辨率的地表土壤湿度日产品.经土壤水分主被动探测卫星数据检验,生成的地表土壤湿度相关系数R为0.8,均方根误差RMSE(root mean square error)为0.032 cm3/cm3,偏差Bias为0.014 cm3/cm3,可为川藏交通廊道沿线气候变化和地表灾害研究提供高连续性和可靠性的数据. 相似文献
14.
遥感数据专题分类不确定性评价研究：进展、问题与展望 总被引：7，自引：1，他引：7
从遥感数据中提取专题类别信息是当前遥感数据最主要的应用领域之一。由于遥感分类专题信息广泛应用于各种领域，其数据质量受到越来越多的关注。不确定性是评价分类专题类别数据质量最主要的方面。回顾了遥感数据专题分类不确定性评价方法的历史，总结了当前各种评价方法及其指标体系，将这些方法归结为基于误差矩阵的方法、模糊评价方法、像元尺度上的不确定性评价方法和其它方法四大类。对每一类不确定性评价方法及其指标体系的优点和缺点进行了分析和总结，指出从理论方法研究方面，需要优先发展独立于分类方法的像元尺度上的遥感分类不确定性评价模型与指标体系，以及统一的遥感数据分类不确定性评价模型体系研究；在应用研究方面，需要加强优化空间采样设计和不确定性评价过程标准化研究。 相似文献
15.
Remotely sensed Land Surface Temperature (LST) is a key parameter for studying the global climate changes and the exchanges of water and energy. Acquiring LST accurately is important to diagnose the change of environment on earth. Quantifying the uncertainty of remotely sensed LST is the first step of its application. However, due to the difficulties in obtaining the ground truth of LST at the pixel scale, it is difficult to validate the remotely sensed LST. Here, methods for simulating the LST at the pixel scale based on ground measurements over heterogeneous area were reviewed. From the way to construct the ground scene, these methods were classified into three types, including the Modified Geometric Projection model (MGP), realistic structural three-dimensional model, and other model. The advantages and disadvantages of these models were examined and compared. Finally, some issues in simulating LST at the pixel scale over heterogeneous area needed to be solved and on-going directions in the future were summarized. 相似文献
16.
遥感图像异常识别是遥感应用领域一个颇受关注的研究课题,在军事目标识别和自然环境保护等许多领域都有潜在应用价值。不妨假设遥感图像背景像素分布于随空间位置缓慢变化的一系列高斯超椭球体内,异常像素则分布于超椭球体之外。在这种假设前提下,首先应用Weiszfeld方法估算遥感图像中一系列高斯超椭球体的重心和波段协方差矩阵;然后,计算各像素到对应的超椭球体重心的马氏距离,并用直方图法确定马氏距离的异常下限;最后,把马氏距离高于异常下限的像素作为异常像素识别出来。在GDAL遥感图像数据输入输出函数库基础上,用VC++语言开发了遥感图像像素级异常识别的算法程序;用美国亚特兰大TM图像进行了方法的应用实验研究。结果表明,该方法对遥感图像中的局部异常具有很好的识别效果。 相似文献
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基于MODIS遥感影像和表观热惯量法,以新疆为研究区,建立了适用于干旱半干旱区1 m土体的土壤含水量反演模型。模型根据高表观热惯量,高土壤含水量,低表观热惯量,低土壤含水量这一理论,通过日地表温差和宽波段反照率确定土壤含水量的时空变化。假设通过1 m土体的土壤水通量正比于上下底层土壤含水量的差值,利用水平衡方程建立土壤表面和底层土壤含水量关系方程,并利用中国土壤类型特点确定优化模型。通过验证结果表明,壤土和壤质粘土这两类土壤含水量接近真实值,砂土在区域验证中,模拟与实测差值为2.16%,整个模型模拟精度较好,能够准确地从时空上反演干旱半干旱地区1 m土体的土壤水分情况。 相似文献
19.
Donglian Sun Menas Kafatos Guido Cervone Zafer Boybeyi Ruixin Yang 《Natural Hazards》2007,43(2):273-284
Sea surface temperature (SST) from the remotely sensed infrared measurements, like the GOES, AVHRR, and MODIS, etc., show
missing values of SST over the cloudy regions associated with hurricanes. While satellite microwave measurements, like the
Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI), can provide SST even under cloudy conditions. Both satellite
microwave measurements and buoy observations show SST increase in advance of significant hurricane intensification. Moreover,
hurricane intensification may also be related to the location of high SST. Our results indicate pre-existing high SST anomaly
(SSTA) located at the right side of the storm track for Hurricane Katrina. Numerical simulations also confirm the important
impacts of SSTA location on hurricane intensification. Similar situations are also found for Hurricanes Rita and Wilma. In
contrast, if there is no high SSTA at the right location, hurricane may not undergo further intensification. This may explain
why not all tropical cyclones associated with warm waters can attain peak intensity (categories 4 and 5) during their life
cycle, and partially explains why hurricanes do not reach the maximum potential intensity as calculated only according to
the magnitude of SST. 相似文献
20.
ALUN C. JONES 《Geology Today》1993,9(5):191-196
The attractiveness of remotely sensed data to aid in the interpretation of global and local environmental processes has been widely recognized. However, some of the most common and frustrating, yet simple, questions that are asked by potential users of remotely sensed data are what images are available, from whom, and, most importantly, how much do t h q cost? As cost is often critical in deciding whether satellite imagery is to be used in a project, it is important to determine what benefits can be obtainedfrom the use of such data. These questions are examined here in the context of obtaining remotely sensed Landsat and SPOT imagery for monitoring a spectral and spatial dynamic geological feature, namely, an active volcano, Mt Etna, Sicily. 相似文献