赤水河流域生态环境状况遥感监测分析

利用多源卫星遥感数据,对贵州赤水河流域2021年生态环境状况进行监测,定量评估赤水河流域的生态环境状况。结果表明：1）赤水河流域生态环境状况EI指数为68.15,生态环境状况综合评价为良;2）赤水河流域贵州段的土地利用类型主要以林地和耕地为主,流域监测区内生境质量为I级,生物多样性丰富;3）流域NDVI平均值0.42,植被覆盖度高,固土护坡、水源涵养能力较强;4）流域雨水充沛,河网密布,水网密度高达6.8;5）流域土地坡度起伏大,监测区内中度以上土地侵蚀强度的土地面积约占49%。相比,流域污染负荷指数较低,生态环境治理成效持续显现。     

神经网络敏感性分析及其在遥感影像分类中的应用

针对基于连接权的神经网络敏感性分析方法中求取敏感性系数的不稳定性,提出一种优化连接权的神经网络敏感性分析方法。首先采用遗传算法根据误差最小化原则对神经网络进行优化,在优化的神经网络模型上进行基于连接权的敏感性分析。以1个数值模拟实例和华盛顿广场地区的遥感图像地物分类为例,验证所提方法的有效性。实验结果表明,所提方法求取输入变量的敏感性系数是稳定有效的,能有效筛选出遥感图像中对分类贡献较大的特征波段,达到降维的同时提高分类精度。     

阜新市海州露天矿区开采对空气质量的影响

利用遥感技术可快速、准确、大范围地监测矿山开发状况和了解矿区生态环境现状。以Landsat TM和CBERS卫星影像为主要数据来源,采用栅格数据、遥感数据与统计数据相结合的内业处理与外业调查相结合的技术路线,通过目视解译、人机交互解译、计算机自动识别等遥感信息提取技术和遥感影像处理,分析近20 a阜新市海州露天矿矿区面积变化趋势及近5a来对当地空气质量的影响。结果表明:阜新市海州露天矿矿区面积逐年减小,当地空气质量逐年优化。由此可见,露天矿矿区面积的减小对于当地空气质量的改善起到了一定的推动作用。     

A land surface data assimilation framework using the land information system: Description and applications

The Land Information System (LIS) is an established land surface modeling framework that integrates various community land surface models, ground measurements, satellite-based observations, high performance computing and data management tools. The use of advanced software engineering principles in LIS allows interoperability of individual system components and thus enables assessment and prediction of hydrologic conditions at various spatial and temporal scales. In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms. These capabilities are demonstrated here in a suite of experiments that use the ensemble Kalman filter (EnKF) and assimilation through direct insertion. In a soil moisture experiment, we discuss the impact of differences in modeling approaches on assimilation performance. Provided careful choice of model error parameters, we find that two entirely different hydrological modeling approaches offer comparable assimilation results. In a snow assimilation experiment, we investigate the relative merits of assimilating different types of observations (snow cover area and snow water equivalent). The experiments show that data assimilation enhancements in LIS are uniquely suited to compare the assimilation of various data types into different land surface models within a single framework. The high performance infrastructure provides adequate support for efficient data assimilation integrations of high computational granularity.     

Estimating uncertainty associated with water stages from a single SAR image

It is the goal of remote sensing to infer information about objects or a natural process from a remote location. This invokes that uncertainty in measurement should be viewed as central to remote sensing. In this study, the uncertainty associated with water stages derived from a single SAR image for the Alzette (G.D. of Luxembourg) 2003 flood is assessed using a stepped GLUE procedure. Main uncertain input factors to the SAR processing chain for estimating water stages include geolocation accuracy, spatial filter window size, image thresholding value, DEM vertical precision and the number of river cross sections at which water stages are estimated. Initial results show that even with plausible parameter values uncertainty in water stages over the entire river reach is 2.8 m on average. Adding spatially distributed field water stages to the GLUE analysis following a one-at-a-time approach helps to considerably reduce SAR water stage uncertainty (0.6 m on average) thereby identifying appropriate value ranges for each uncertain SAR water stage processing factor. For the GLUE analysis a Nash-like efficiency criterion adapted to spatial data is proposed whereby acceptable SAR model simulations are required to outperform a simpler regression model based on the field-surveyed average river bed gradient. Weighted CDFs for all factors based on the proposed efficiency criterion allow the generation of reliable uncertainty quantile ranges and 2D maps that show the uncertainty associated with SAR-derived water stages. The stepped GLUE procedure demonstrated that not all field data collected are necessary to achieve maximum constraining. A possible efficient way to decide on relevant locations at which to sample in the field is proposed. It is also suggested that the resulting uncertainty ranges and flood extent or depth maps may be used to evaluate 1D or 2D flood inundation models in terms of water stages, depths or extents. For this, the extended GLUE approach, which copes with the presence of uncertainty in the observed data, may be adopted.     

Time–space continuity of daily maps of fractional snow cover and albedo from MODIS

Using reflectance values from the seven MODIS “land” bands with 250 or 500 m resolution, along with a corresponding cloud product, we estimate the fraction of each 500 m pixel that snow covers, along with the albedo of that snow. The daily products have data gaps and errors because of cloud cover and sensor viewing geometry. Rather than make users interpolate and filter these patchy daily maps without completely understanding the retrieval algorithm and instrument properties, we use the daily time series to improve the estimate of the measured snow properties for a particular day. We use a combination of noise filtering, snow/cloud discrimination, and interpolation and smoothing to produce our best estimate of the daily snow cover and albedo. We consider two modes: one is the “predictive” mode, whereby we estimate the snow-covered area and albedo on that day using only the data up to that day; the other is the “retrospective” mode, whereby we reconstruct the history of the snow properties for a previous period.     

Passive L-band microwave soil moisture retrieval error arising from topography in otherwise uniform scenes

Soil moisture is an important component of the water cycle and will be measured for the first time on a global scale by a dedicated passive L-band microwave radiometer that is planned for launch in 2008. Here, the contribution of topography to the error budget is examined for a vegetated scene with uniform microwave emission. Dual-polarization brightness temperature curves were generated over a range of look angles for 1-D scenes with simple geometrical features, and the soil moisture was retrieved assuming a flat surface. The errors were small for the scenarios considered. Theoretical errors were tested for realistic topography with a DEM transect of a mountainous region, and were found to be comparable. Knowledge of the mean slope from high-resolution DEM data can be used to improve the accuracy of the retrieval.     

Emergency Seismic Damage Assessment of the M_S8.0 Great Wenchuan Earthquake Based on Remote Sensing Imagery

The fast processing, seismic damage data extraction and loss evaluation from RS imagery acquired immediately after a destructive earthquake occurs, are important means for compen-sating the insufficiency of seismic damage information from ground-based investigations and provide an important basis for emergency command and rescue. The paper introduces the method of emergency seismic damage assessment using remote sensing data and its application to the great Wenchuan earthquake of magnitude 8.0 occurring in southwest Sichuan Province on May 12, 2008. The practical effectiveness of the method is also evaluated in the paper.     

汶川8.0级地震震害遥感定量化初步研究以都江堰城区破坏为例

随着遥感技术的飞速发展, 遥感在地震应急救援、 灾害调查和损失评估中的作用越来越显著。 然而由于缺乏系统的遥感震害定量研究, 使得遥感的实用性常常受到质疑。 文中叙述了遥感震害定量研究的基本思路, 提出了遥感震害指数的概念与定量分析的基本模型, 并以2008年汶川8.0级地震造成的都江堰城区震害为例, 依据建筑物震害遥感解译结果和地面震害调查结果, 进行了都江堰城区部分街区的建筑物遥感震害指数和地面调查震害指数的统计分析, 并建立了两者之间的统计关系。 初步研究结果表明, 依据高分辨率航空遥感影像和卫星雷达图像建立的建筑物遥感震害指数与地面调查震害指数及房屋倒塌率存在显著的对应性。 因此, 通过遥感震害定量化研究, 将为地震震害调查、 损失评估提供有力的方法和工具。