Satellite remote sensing and conceptual cloud modeling for convective rainfall simulation

Motivated by the need for rainfall prediction models in data scarce areas, we adapted a simple storage based cloud model to use routinely available thermal infrared (TIR) data. The data is obtained from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) of the Meteosat Second Generation (MSG-2) satellite. Model inputs are TIR cloud top temperatures at 15-min intervals and observations of pressure, temperature, and dew point temperatures from ground-based stations at 30-min intervals. The sensitivity of the parsimonious cloud model to its parameters is evaluated by a regional sensitivity analysis (RSA) which suggests that model performance is sensitive to few parameters. The model was calibrated and tested for four convective events that were observed during the wet season in the source basin of the Upper Blue Nile River. The difference between the simulated and the observed depth of the selected rain events varies between 0.2 and 1.8 mm with a root mean square error of smaller than 0.5 mm for each event. It is shown that the updraft velocity characteristic can provide relevant information for rainfall forecasting. The simulation results suggest the effectiveness of the model approach as evaluated by selected performance measures. The various characteristics of the rainfall events as simulated generally match to observed counter parts when ground-based and remote sensing observations are combined.     

Evaluation of precipitation products over complex mountainous terrain: A water resources perspective

The availability of in situ measurements of precipitation in remote locations is limited. As a result, the use of satellite measurements of precipitation is attractive for water resources management. Combined precipitation products that rely partially or entirely on satellite measurements are becoming increasingly available. However, these products have several weaknesses, for example their failure to capture certain types of precipitation, limited accuracy and limited spatial and temporal resolution. This paper evaluates the usefulness of several commonly used precipitation products over data scarce, complex mountainous terrain from a water resources perspective. Spatially averaged precipitation time series were generated or obtained for 16 sub-basins of the Paute river basin in the Ecuadorian Andes and 13 sub-basins of the Baker river basin in Chilean Patagonia. Precipitation time series were generated using the European Centre for Medium Weather Range Forecasting (ECMWF) 40 year reanalysis (ERA-40) and the subsequent ERA-interim products, and the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis dataset 1 (NCEP R1) hindcast products, as well as precipitation estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN). The Tropical Rainfall Measurement Mission (TRMM) 3B42 is also used for the Ecuadorian Andes. These datasets were compared to both spatially averaged gauged precipitation and river discharge. In general, the time series of the remotely sensed and hindcast products show a low correlation with locally observed precipitation data. Large biases are also observed between the different products. Hydrological verification based on river flows reveals that water balance errors can be extremely high for all evaluated products, including interpolated local data, in basins smaller than 1000 km². The observations are consistent over the two study regions despite very different climatic settings and hydrological processes, which is encouraging for extrapolation to other mountainous regions.     

Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture

This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions of root-zone soil moisture, evapotranspiration, and stream flow within the 341 km² Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthetic twin experiments assimilating surface soil moisture is shown to effectively update SWAT upper-layer soil moisture predictions and provide moderate improvement to lower layer soil moisture and evapotranspiration estimates. However, insufficient SWAT-predicted vertical coupling results in limited updating of deep soil moisture, regardless of the SWAT parameterization chosen for root-water extraction. Likewise, a real data assimilation experiment using ground-based soil moisture observations has only limited success in updating upper-layer soil moisture and is generally unsuccessful in enhancing SWAT stream flow predictions. Comparisons against ground-based observations suggest that SWAT significantly under-predicts the magnitude of vertical soil water coupling at the site, and this lack of coupling impedes the ability of the EnKF to effectively update deep soil moisture, groundwater flow and surface runoff. The failed attempt to improve stream flow prediction is also attributed to the inability of the EnKF to correct for existing biases in SWAT-predicted stream flow components.     

沿海湿地植被遥感分类研究

沿海湿地植被遥感分类是遥感在土地利用变化研究领域的一项重要内容,本文以江苏盐城沿海湿地核心区为研究区域,探讨了利用遥感技术进行湿地植被分类的方法和技术流程。在此基础上,以Landsat-5TM图像为遥感数据源,以盐城丹顶鹤湿地保护区样点数据为辅助数据,分别用非监督分类法、监督分类法与基于LBV变换的分类法,对研究区进行分类,并对各种分类方法的结果进行精度分析。结果表明,非监督分类的结果最差,特别是对芦苇,其错分误差达到51．65％。监督分类法的精度虽然高于非监督分类,但其制图精度只有66．56％。而基于LBV变换分类法能够有效解决关于米草和芦苇的错分现象,它对其他地物的分类精度也很高,基本上都在90％以上。总体来说,LBV变换法已经达到了核心区分类的精度要求。     

高光谱遥感图像的监督分类

图像分类是高光谱遥感图像分析与应用的重要手段。总结了目前用于高光谱图像监督分类的主要方法,包括最小距离法、最大似然法、神经元网络法和支持向量机法,分析了上述方法的特点,并探讨了高光谱遥感图像分类方法的发展趋势。     

无人机遥感在应对地质灾害中的主要应用

无人机遥感技术在近几十多年取得了巨大发展,从理论研究已经进入了实用化阶段,尤其是在预防与应对自然灾害方面有着明显优势。介绍了无人机遥感系统的组成、数据获取和处理过程,对地质灾害监测、应急救援和灾情评估工作中无人机遥感可提供的的应用进行了分析,并介绍了无人机遥感在重庆市武隆县鸡尾山特大型滑坡救援中的应用;并对无人机遥感系...     

Mechanisms controlling the intra-annual mesoscale variability of SST and SPM in the southern North Sea

Thermal and optical remote sensing data were used to investigate the spatial and temporal distribution of sea surface temperature (SST) and of suspended particulate matter (SPM) in the southern North Sea. Monthly SST composites showed pronounced seasonal warming of the southern North Sea and delineated the English coastal and continental coastal waters. The East-Anglia Plume is the dominant feature of the English coastal waters in the winter and autumn SPM composites, and the Rhine region of freshwater influence (ROFI), including the Flemish Banks, is the dominant feature of the continental waters. These mesoscale spatial structures are also influenced by the evolution of fronts, such as the seasonal front separating well-mixed water in the southern Bight, from the seasonally stratified central North Sea waters. A harmonic analysis of the SST and SPM images showed pronounced seasonal variability, as well as spring-neap variations in the level of tidal mixing in the East Anglia Plume, the Rhine ROFI and central North Sea. The harmonic analysis indicates the important role played by the local meteorology and tides in governing the SST and near-surface SPM concentrations in the southern North Sea. In the summer, thermal stratification affects the visibility of SPM to satellite sensors in the waters to the north of the Flamborough and Frisian Fronts. Haline stratification plays an important role in the visibility of SPM in the Rhine ROFI throughout the year. When stratified, both regions typically exhibit low surface SPM values. A numerical model study, together with the harmonic analysis, highlights the importance of tides and waves in controlling the stratification in the southern North Sea and hence the visibility of SPM.     

基于ETM数据的庞西垌地区断裂信息提取

针对庞西垌地区植被高覆盖特征,主要选用ETM+数据,结合DEM数据,采用正向主成分分析、波段比值、多波段信息合成等处理方法,提取与成矿控矿相关的线状、环状构造信息,结合该区相关地质资料,实现研究区构造综合解译.     

东准噶尔三道岭地区遥感矿化蚀变信息提取及综合信息找矿

遥感矿化蚀变信息提取已被广泛应用于地质找矿中,但直击找矿部位需其他信息佐证.综合运用地质、化探、遥感等方法进行找矿可增大发现新矿产的可能.在新疆东准噶尔巴里坤县三道岭地区以遥感为先导,对ETM数据采用掩膜技术剔除水体、第四系等干扰,再利用Crosta法提取矿化蚀变信息,将遥感异常与地质、化探信息叠合进行分析,据此圈定25处找矿靶区.对其中10处靶区进行野外地质检查,验证地表多处蚀变,发现铜、金矿化点8处.