面向亚像元级积雪信息提取的MODIS影像波段融合方法研究

MODIS影像因其共享性和时间序列的完整性而成为大区域积雪监测研究广泛使用的数据源,进行MODIS影像波段间融合,能够为积雪研究提供较高分辨率的影像数据源。为了充分利用MODIS影像250 m分辨率波段的空间和光谱信息,提取亚像元级的积雪面积,使用两种具有高光谱保真度的影像融合方法：基于SFIM变换和基于小波变换的融合方法,采取不同的波段组合策略,对MODIS影像bands 1~2和bands 3~7进行融合,并以Landsat TM影像的积雪分类图作为“真值”,对融合后影像进行混合像元分解得到的积雪丰度图的精度进行评价。结果表明：利用基于SFIM变换和小波变换方法融合后影像提取的积雪分类图精度较高,数量精度为75%,比未融合影像积雪分类图的精度提高了6%,表明MODIS影像波段融合是一种提取高精度积雪信息的有效方法。     

NASA系列雪参数反演算法在单像元内的时间序列验证与分析

NASA系列算法(Chang,NASA96和Foster算法)是被动微波遥感反演雪深、雪水当量的简单、实用的经验算法,并经过了很多学者大范围的算法验证和改进。为了进一步评价NASA系列算法在东北地区的时空适用性,于长春净月潭区域选定了一个以农田和森林为主的10km×10km被动微波遥感混合像元,在时间上连续观测整个干雪期(2014年12月至次年2月)的积雪参数和气象数据,结合FY3B卫星搭载的微波成像仪(MWRI)亮温数据,对NASA系列算法精度进行了评价分析。结果表明:对于雪深的反演,Chang算法和NASA 96算法前期反演效果较好,后期随着时间的推进高估雪深的趋势愈加明显。由于考虑了森林覆盖率的影响,NASA 96算法的反演精度更高。两种算法最大高估值分别是24.46和14.62cm,这是因为期间雪性质不断变化,尤其是雪粒径不断增大的缘故。Foster算法也严重高估了雪水当量,可能是由于积雪类型的分类系统未必适合于东北地区的积雪特征。本文的积雪连续观测数据为认识东北地区的积雪特性奠定了基础,对算法的时间序列验证与分析为雪参数反演算法的进一步改进提供了可靠依据。     

Fuzzy modelling of powder snow avalanches

This paper examines powder snow avalanches by introducing a predetermined degree of variation, or fuzziness, in model parameters. Given a value of vagueness in the parameters, fuzzy set theory makes it possible to evaluate the vagueness in the results. The use of a more complex stochastic analysis can be avoided. Six parameters of the model are taken to be affected by a certain amount of uncertainty; the response of the numerical model is calculated by solving the fuzzy equations. In this way, it is possible to evaluate how the results are affected by a given change in the model parameters.The paper first presents a well-known avalanche model and its solution considering the influence of friction. A brief introduction of the fuzzy set is given with regard to the avalanche model mentioned. Later, the fuzzy solution of the model in terms of velocity and average pressure is calculated for three different levels of imprecision in the data. At the end, the results are presented and commented.     

Retrieval of subpixel snow covered area, grain size, and albedo from MODIS

We describe and validate a model that retrieves fractional snow-covered area and the grain size and albedo of that snow from surface reflectance data (product MOD09GA) acquired by NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). The model analyzes the MODIS visible, near infrared, and shortwave infrared bands with multiple endmember spectral mixtures from a library of snow, vegetation, rock, and soil. We derive snow spectral endmembers of varying grain size from a radiative transfer model specific to a scene's illumination geometry; spectra for vegetation, rock, and soil were collected in the field and laboratory. We validate the model with fractional snow cover estimates from Landsat Thematic Mapper data, at 30 m resolution, for the Sierra Nevada, Rocky Mountains, high plains of Colorado, and Himalaya. Grain size measurements are validated with field measurements during the Cold Land Processes Experiment, and albedo retrievals are validated with in situ measurements in the San Juan Mountains of Colorado. The pixel-weighted average RMS error for snow-covered area across 31 scenes is 5%, ranging from 1% to 13%. The mean absolute error for grain size was 51 µm and the mean absolute error for albedo was 4.2%. Fractional snow cover errors are relatively insensitive to solar zenith angle. Because MODSCAG is a physically based algorithm that accounts for the spatial and temporal variation in surface reflectances of snow and other surfaces, it is capable of global snow cover mapping in its more computationally efficient, operational mode.     

Spatial relationships between snow contaminant content, grain size, and surface temperature from multispectral images of Mt. Rainier, Washington (USA)

We use multispectral MODIS/ASTER Airborne Simulator (MASTER) data collected at Mt. Rainier, Washington (USA) to map spatial covariance between snowpack properties and to evaluate techniques for quantitative estimation of reflectance, grain size, and temperature. The late-August MASTER images reveal a distinct pattern of snow contaminant content, grain size, and temperature related to a recent snowfall and late-summer melting. Spatial correlation between grain size and temperature patterns suggests that rapid destructive metamorphism of the fresh snow occurred when temperatures were near 0 °C. We use 10 specific locations to evaluate hemispherical-directional reflectance factor (HDRF), grain size, and temperature retrievals. We map relative snow contaminant content using visible (0.4-0.8 μm) HDRF spectra. Atmospheric correction and topographic modeling limit the accuracy of HDRF estimates. We use MASTER-derived spectra near 1.8 and 2.2 μm to estimate optical grain size (by comparison to modeled layers of ice spheres) and physical grain size (by comparison to measured spectra with known physical grain size and by correlation to ground measurements). Estimated physical grain sizes were less than estimated optical grain sizes. Differing definitions of optical and physical grain sizes could contribute to this discrepancy. Limitations at 1.8 and 2.2 μm, including reduced discrimination between larger grain radii (>∼500 μm physical, >∼200 μm optical) and low signal-to-noise ration with atmospheric effects and decreasing solar irradiance, suggest that grain size retrieval may be improved at other wavelengths (e.g., 1.1 μm). Accounting for uncertainty in emissivity, atmospheric correction, and detector noise, we estimate systematic errors in our radiant temperatures at <1.8 °C. This study shows both strengths and limitations for coregistered visible, short-wave infrared, and thermal infrared images to estimate snowpack properties and reveal their spatial coherence.     

东北-内蒙古地区基于MODIS单、双卫星积雪数据及常规积雪观测结合的积雪日数研究

结合Terra和Aqua卫星的积雪产品,获取2001~2008年东北-内蒙古地区逐年积雪日数分布,并利用此数据对比Terra卫星积雪数据获取的逐年积雪日数。结果表明随海拔的升高,双星与单颗卫星积雪日数差异呈现明显增加的趋势。整个东北-内蒙古地区双星积雪日数平均高出单颗卫星积雪日15 d,但与台站积雪日数对比发现,双星积雪日数平均仍然偏低27 d。这说明,利用Terra和Aqua双卫星积雪监测数据能明显改善山区云对遥感监测的影响,同时也可以减少降雪初期和消融期由于积雪消融较快带来的积雪漏测,但不足以消除云等因素的影响。考虑到获取的2001~2006年台站年积雪日数与MODIS年积雪日数与有良好的统计关系,利用两者建立的线性统计关系修正整个东北-内蒙古地区的MODIS积雪日数,能够很好地消除云等因素带来的MODIS双卫星积雪日数偏小的问题,修正后台站与双星积雪日数之间的绝对误差由原来的27 d减小到18 d。     

一种新型的雨雪视频图像复原方法

针对雨、雪等恶劣天气极易影响视频图像质量的问题,提出了一种新型雨雪视频图像复原方法。该方法在深入研究视频帧序列时域特性的基础上,将R、G、B 3维彩色空间属性数据进行投影降维,通过研究低维数据的散布形状来揭示高维数据的聚类特征,进而依据统计特性进行雨雪去除,实现视频图像复原的目的。该方法依据雨雪区和背景区的数据特性进行分类,能提供更准确的类别中心,尤为关键的是,该方法所需视频序列帧数少,不需要进行数据的彩色空间转换,简化了运算。6个经典视频场景的实验结果表明,复原后的图像清晰度高,具有较强的鲁棒性。     

被动微波遥感在青藏高原积雪业务监测中的初步应用

积雪范围、积雪深度和雪水当量等参数的遥感监测与反演对气候模式的建立以及积雪灾害的评估具有重要意义。被动微波遥感在这些参数的反演方面具有明显优势,但目前尚未应用到青藏高原地区的积雪遥感业务监测上来。2001年10月至2002年4月,利用SSM/I数据对青藏高原地区的积雪范围和积雪深度进行了实时监测,为西藏、青海遥感应用部门提供逐日的雪深分布图。对这次监测的总效果进行了分析和评价,并对发生在青海省内一次较大的降雪过程进行了遥感分析,结果表明:SSM/I反演的积雪范围变化趋势与MODIS结果总体上较为一致;SSM/I的雪深监测结果为当地遥感部门对大于10 cm的雪深做出正确判断提供了重要信息,是对雪灾定位的重要信息源。     

一种新型短壁开采输送设备

介绍了CLY2000/980-10型重叠式连续运输系统的主要技术参数、结构特点及其工作原理,它是为我国煤矿巷道宽度≤4.5m设计的一套短壁机械化开采输送设备。