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1.
Snow cover is an important variable for climatic and hydrologic models due to its effect on surface albedo, energy, and mass balance. Satellite observations successfully provide a global and comprehensive hemispheric-scale record of the short-term, as well as inter-seasonal variations in snow cover. Passive microwave sensors provide an excellent method to monitor temporal and spatial variations in large-scale snow cover parameters, overcoming problems of cloud cover. Using microwave remote sensing data, snow parameters (snow surface temperature, snow water equivalence, scattering index, emissivity, snow depth) have been retrieved to integrate with the snow cover simulation model developed by SASE for avalanche risk assessment on regional basis. Multispectral and multitemporal brightness temperature data obtained from the Special Sensor Microwave Imager (SSM/I), flown onboard the DMSP satellites, for the period November 2000 to April 2001 and from November 2001 to February 2002 have been analysed. A comparative data set on snow measurements and meteorological observations of a region covering large area of Pir-Panjal and the Greater Himalayan range, available on near real time basis from SASE field observatories were also used. Model calculations were carried out to study the effects of atmospheric transmission on the microwave radiation emitted from the snow covered and snow free ground and atmosphere. The sensitivity of combinations of the SSM/I channels at 19, 37 and 85 GHz, in both horizontal and vertical polarizations, in respect to snow depth, surface temperature of the snowpack have been carried out. Decision rule based algorithms are developed to identify snow cover and non-snow area.  相似文献   

2.
Radar remote sensing has great potential to determine the extent and properties of snow cover. Availability of space-borne sensor dual-polarization C-band data of environmental satellite- (ENVISAT-) advanced synthetic aperture radar (ASAR) can enhance the accuracy in measurement of snow physical parameters as compared with single polarization data measurement. This study shows the capability of C-band synthetic aperture radar (SAR) data for estimating dry snow density over snow covered rugged terrain in Himalayan region. The snow density is an important parameter for the snow hydrology and avalanche forecasting related studies. An algorithm has been developed for estimating snow density, based on snow volume scattering and snow-ground scattering components. The radar backscattering coefficients of both horizontal–horizontal (hh) and vertical–vertical (vv) polarization and incidence angle are used as inputs in the algorithm to provide the snow dielectric constant which can be used to derive snow density using Looyenga's semi-empirical formula. Comparison was made between snow density estimated from algorithm using ENVISAT-ASAR hh and vv polarization data and the measured field value. The mean absolute error between estimated and measured snow density was found to be 0.024 g/cm3.  相似文献   

3.
基于ASTER GED产品的地表发射率估算   总被引:1,自引:0,他引:1  
地表发射率是地表温度反演的重要输入参数,为了解决现有地表发射率估算方法在裸露地表精度较差的问题,本文基于最新的ASTER全球地表发射率产品(ASTER GED)和基于植被覆盖度的方法(VCM),提出了一个改进的地表发射率估算方法。首先,利用ASTER GED产品求解裸土发射率,然后,利用ASTER波谱库中的植被发射率和植被覆盖度结合VCM方法计算地表发射率。利用张掖地区2012年11景ASTER TES算法反演的地表发射率产品和实测地表发射率数据进行了验证,同时利用一景Landsat 8 TIRS数据分析了对地表温度反演精度的影响。结果表明该方法估算的地表发射率整体精度较高,可以有效改进裸露地表的发射率估算精度,用于支持利用多种热红外传感器数据生产高精度的地表温度产品。  相似文献   

4.
A radiative transfer model is used to simulate the sea ice radar altimeter effective scattering surface variability as a function of snow depth and density. Under dry snow conditions without layering these are the primary snow parameters affecting the scattering surface variability. The model is initialized with in situ data collected during the May 2004 GreenIce ice camp in the Lincoln Sea (73/spl deg/W; 85/spl deg/N). Our results show that the snow cover is important for the effective scattering surface depth in sea ice and thus for the range measurement, ice freeboard, and ice thickness estimation.  相似文献   

5.
Snow physical properties, snow cover and glacier facies are important parameters which are used to quantify snowpack characteristics, glacier mass balance and seasonal snow and glacier melt. This study has been done using C-band synthetic aperture radar (SAR) data of Indian radar imaging satellite, radar imaging satellite-1 (RISAT)-1, to estimate the seasonal snow cover and retrieve snow physical properties (snow wetness and snow density), and glacier radar zones or facies classification in parts of North West Himalaya (NWH), India. Additional SAR data used are of Radarsat-2 (RS-2) satellite, which was used for glacier facies classification of Smudra Tapu glacier in Himachal Pradesh. RISAT-1 based snow cover area (SCA) mapping, snow wetness and snow density retrieval and glacier facies classification have been done for the first time in NWH region. SAR-based inversion models were used for finding out wet and dry snow dielectric constant, dry and wet SCA, snow wetness and snow density. RISAT-1 medium resolution scan-SAR mode (MRS) in HV polarization was used for first time in NWH for deriving time series of SCA maps in Beas and Bhagirathi river basins for years 2013–2014. The SAR-based inversion models were implemented separately for RISAT-1 quad pol. FRS2, for wet snow and dry snow permittivity retrieval. Masks for layover and shadow were considered in estimating final snow parameters. The overall accuracy in terms of R2 value comes out to be 0.74 for snow wetness and 0.72 for snow density based on the limited ground truth data for subset area of Manali sub-basin of Beas River up to Manali for winter of 2014. Accuracy for SCA was estimated to be 95 % when compared with optical remote sensing based SCA maps with error of ±10 %. The time series data of RISAT-1 MRS and hybrid data in RH/RV mode based decompositions were also used for glacier radar zones classification for Gangotri and Samudra Tapu glaciers. The various glaciers radar zones or facies such as debris covered glacier ice, clean or bare glacier ice radar zone, percolation/refreeze radar zone and wet snow, ice wall etc., were identified. The accuracy of classified maps was estimated using ground truth data collected during 2013 and 2014 glacier field work to Samudra Tapu and Gangotri glaciers and overall accuracy was found to be in range of 82–90 %. This information of various glacier radar zones can be utilized in marking firn line of glaciers, which can be helpful for glacier mass balance studies.  相似文献   

6.
金亚秋 《遥感学报》1998,2(1):19-25
国家遥感应用工程技术研究中心NationalEngineeringResearchCenterforGeomatics(NCG)国家遥感应用工程技术研究中心于1996年12月25日由国家科委正式批准组建(国科发计字[1996]603号文件)。中国科学...  相似文献   

7.
The Swiss Federal Institute for Snow and Avalanche Research in Davos (SLF) provides snow depth maps for Switzerland on a spatial resolution of 1 km × 1 km. These snow depth maps are derived from snow station measurements using a spatial interpolation method based on the dependency of snow depth and altitude. During a winter season the number of operating snow stations varies and the area-wide snow depth interpolation becomes increasingly difficult in spring. The objective of the study is to develop an operational and near-real time method to calculate snow depth maps using a combination of in situ snow depth measurements and the snow cover extent provided from space borne observations. The operational daily snow cover product obtained from the polar-orbiting NOAA-AVHRR satellite is used to gain an additional set of virtual snow stations to densify the in situ measurements for an improved spatial interpolation. The capacity of this method is demonstrated on selected days during winter 2005. Cross-validation tests are conducted to examine the quantitative accuracy of the synergetic interpolation method. The error estimators prove the decrease in error variance and increase of overall accuracy pointing out the high capacity of this new interpolation method that can be run in near real-time over a large horizontal domain at high horizontal resolution. A solid method for snow–no snow classification in the processing of the satellite data is essential to the quality of the snow depth maps.  相似文献   

8.
An inversion technique based on the merging of microwave remotely sensed data is applied to ground-based radiometer and scatterometer data acquired for the same area. The purpose of this technique is to retrieve the dielectric constant of bare soils. The algorithm is based on a Bayesian approach and combines prior information on the dielectric constant and surface roughness with observed data, in order to obtain a marginal posterior probability density function. The function describes how the probability is distributed within the range of the dielectric constant values, given the measured values of emissivity and backscattering coefficient. The algorithm allows for the incorporation of all the available sources of information, such as multipolarization and multifrequency data. Several criteria, which have been used to compare the predicted and the observed values, show that for dielectric constant values higher than 10 the best performance is achieved when data with one polarization and one or two frequencies are exploited. For dielectric constant values of less than 10, the configuration with two polarizations produces the best estimates.  相似文献   

9.
阚希  张永宏  曹庭  王剑庚  田伟 《测绘学报》2016,45(10):1210-1221
青藏高原积雪对全球气候变化十分重要,针对已有积雪遥感判识方法中普遍采用的可见光与红外光谱数据易受复杂地形与高海拔影响,导致青藏高原地区积雪判识精度较低的问题,提出了一种基于多光谱遥感与地理信息数据特征级融合的积雪遥感判识方法:以风云三号卫星可见光与红外多光谱遥感资料与多要素地理信息作为数据源,由地面实测雪深数据与现有积雪产品交叉筛选出样本标签,构建并训练基于层叠去噪自编码器(SDAE)的特征融合与分类网络,从而有效辨识青藏高原遥感图像中的云、积雪以及无雪地表。经地面实测雪深数据验证,该方法分类精度显著高于使用相同数据源的FY-3A/MULSS积雪产品,略高于国际主流积雪产品MOD10A1与MYD10A1,并且年均云覆盖率最低。试验结果表明该方法可有效地减少云层对积雪判识的干扰,提升分类精度。  相似文献   

10.
To determine land surface emissivity from satellite microwave measurements, the surface is usually assumed to be specular. Questions about the validity of this approximation to estimate emissivity from nadir viewing radiometers were raised. This work aims to examine the validity of the specular assumption by evaluating errors induced when deriving emissivities from near-nadir measurements over snow-free areas. Brightness temperature simulations near nadir above both a specular and a Lambertian surface are compared. Errors on the retrieved emissivity introduced by the specular assumption are also quantified. The results show that the impact of the specular assumption when the surface is Lambertian is limited: less than 1% error in most atmospheric situations over natural snow-free surfaces.  相似文献   

11.
满浩然  臧淑英  李苗  张鑫 《测绘科学》2021,46(3):124-132
针对无源微波遥感时间分辨率高可以克服云层影响获取地表温度的问题,该文应用AMSR-E微波亮度温度数据,分别选取了基于发射率估计的单通道反演法和多通道线性拟合法反演东北地区地表温度。在原有方法的基础上提出算法改进:对单通道反演法按照植被生长周期在生长季与非生长季分别建立发射率估计方程,探究各微波通道在每种地表覆被类型的反演能力并组合反演精度最高的通道,将微波极化差异指数作为表征发射率参数加入多通道拟合方程。结果显示,获取的地表温度剔除水体和冰雪无效像元后可用性达到100%,改进后的单通道反演法均方根误差由3.58~4.6降低至2.0~3.1,在75%的区域的误差小于2 K;多通道拟合法的最终均方根误差为2.6~3.5,同样有较高精度且只使用微波亮温数据就能获取地表温度。  相似文献   

12.
基于被动微波遥感的青藏高原雪深反演及其结果评价   总被引:21,自引:0,他引:21  
采用修正的张氏雪深反演算法,用SSM/I37GHz和19GHz水平极化亮温值计算了青藏高原及其毗邻地区的积雪深度,对其精度进行了评价,并对误差来源进行了分析,结果显示,此算法能够较好地反映研究区的雪深分布,但局部地区误差较大,总体上雪深被高估,其误差主要来源于冻土,深霜层,植被以及雪层中液态水含量,雪粒的形状和粒径的变化带来的影响,SSM/I数据较低的分辨率和研究区复杂的地形使反演的雪深与观测的雪深缺少可比性,给精度的评价带来影响。  相似文献   

13.
Terrestrial brightness temperatures measured from satellites have been used to determine the surface emissivity. The results not only depend on surface temperature and on atmospheric properties, but also on the type of surface scattering. For otherwise identical conditions (same emissivity, same nonscattering atmosphere), the radiation above the Lambertian surface is larger than for a specular surface if the incidence angle is smaller than about 55/spl deg/. The opposite is true for larger angles. The effect leads to overestimates of emissivity for observations especially near nadir with the use of algorithms assuming specular reflection. The problem may be solved by the introduction of a specularity parameter to characterize realistic surfaces by a combination of specular and Lambert scattering. A simple solution lies in the use of conically scanning radiometers at a constant incidence angle near 55/spl deg/. Although the topic applies to all ranges of thermal radiation, the present discussion concentrates on the microwave spectrum in the Rayleigh-Jeans approximation.  相似文献   

14.
For a satellite sensor with only one or two thermal infrared channels, it is difficult to retrieve the surface emissivity from the received emissive signal. Empirical linear relationship between surface emissivity and red reflectance are already established for deriving emissivity, but the inner physical mechanism remains unclear. The optical constants of various minerals that cover the spectral range from 0.44 to 13.5 μm in conjunction with modern radiative transfer models were used to produce corresponding surface reflectance and emissivity spectra. Compared to the commonly used empirical linear relationship, a more accurate multiple linear relationship between Landsat TM5 emissivity and optical reflectances was derived using the simulated data, which indicated the necessity of replacing the empirical relationship with the new one for improving surface emissivity estimate in the single channel algorithm. The significant multiple linear relationship between broadband emissivity (BBE, 8–13.5 μm) and MODIS spectral albedos was also derived using the same data. This paper demonstrates that there is a physical linkage between surface emissive and reflective variables, and provides a theoretical perspective on estimating surface emissivity for sensors with only one or two thermal infrared channels.  相似文献   

15.
The knowledge of the surface temperature is important to a range of issues and themes in earth sciences central to urban climatology, global environmental change and human-environment interactions. The study analyses land surface temperature (LST) estimation using temporal ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) datasets (day time and night time) over National Capital Territory Delhi using the surface emissivity information at pixel level. The spatial variations of LST over different land use/land cover (LU/LC) at day time and night time were analysed and relationship between the spatial distribution of LU/LC and vegetation density with LST was developed. Minimum noise fraction (MNF) was used for LU/LC classification which gave better accuracy than classification with original bands. The satellite derived emissivity values were found to be in good agreement with literature and field measured values. It was observed that fallow land, waste land/bare soil, commercial/industrial and high dense built-up area have high surface temperature values during day time, compared to those over water bodies, agricultural cropland, and dense vegetation. During night time high surface temperature values are found over high dense built-up, water bodies, commercial/industrial and low dense built-up than over fallow land, dense vegetation and agricultural cropland. It was found that there is a strong negative correlation between surface temperature and NDVI over dense vegetation, sparse vegetation and low dense built-up area while with fraction vegetation cover, it indicates a moderate negative correlation. The results suggest that the methodology is feasible to estimate NDVI, surface emissivity and surface temperature with reasonable accuracy over heterogeneous urban area. The analysis also indicates that the relationship between the spatial distribution of LU/LC and vegetation density is closely related to the development of urban heat islands (UHI).  相似文献   

16.
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   

17.
This paper proposes an applicable approach for snow information abstraction in northern Xinjiang Basin using MODIS data. Linear spectral mixture analysis (LSMA) was used to calculate snow cover fractions (SF) within a pixel, which was used to establish a regression function with NDSI. In addition, 80 snow depths samples were collected in the study region. The correlation between image spectra reflectance and snow depth as well as the comparison between measured snow spectra and image spectra was analyzed. An algorithm was developed for snow depth inversion on the basis of the correlation between snow depth and snow spectra in the region. The results indicated that the model of SF had a high accuracy with the mean absolute error 0.06 tested by 26 true measured values and the validation for snow depth model using another dataset with 50 sampling sites showed an RMSE of 1.63. Our study showed that MODIS data provide an alternative method for snow information abstraction through development of algorithms suitable for local application. Supported by the National Natural Science Foundation of China (No.70361001).  相似文献   

18.
采用基于质能平衡的积雪过程模型—雪热力模型(Snow Thermal Model, SNTHERM.89)来描述和模拟2008年中国甘肃省黑河实验冰沟流域的积雪过程与积雪特性参数,并将模型模拟的雪水当量与高级微波扫描辐射计(AMSR-E)的雪水当量产品进行了对比。模型验证结果表明,SNTHERM模型能准确模拟黑河冰沟流域的积雪变化过程和积雪特性,对积雪的演变特征作出合理的描述,表明SNTHERM在中国黑河冰沟流域有较好的适用性。对SNTHERM模型进行不同驱动气象参数和初始输入参数的敏感性分析的结果表明,积雪特性参数对辐射通量最敏感;各积雪特性参数对各自的初始输入比较敏感,密度则对初始输入的雪深、密度和颗粒大小都比较敏感,表明在需要准确模拟密度的情况下以及进行雪水当量同化工作时,初始输入的雪层深度、密度和颗粒都必须比较准确。  相似文献   

19.
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   

20.
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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