基于NoSREx实验的积雪演化及微波辐射分析研究

在被动微波雪水当量反演中,积雪物理参数随时间的变化特征影响着反演精度,为理解积雪随时间演化的特征及其对微波辐射亮温的影响,本研究选用2009—2013年北欧积雪实验（Nordic Snow Radar Experiment, NoSREx）积雪地面观测和微波辐射测量数据,通过雪深和温度把雪期分为积累期（10月—次年2月）、稳定期（2—4月）和消融期（4—5月）,发现各个雪期的积雪演化特征为：雪颗粒形状在积累期前期以融态颗粒（Melt Forms, MF）为主,积累期后期和稳定期以圆形颗粒、片状颗粒、深霜为主,消融期以MF为主;整个雪季底层雪粒径从小变大再变小的过程,粒径最大值出现在稳定期的2至3月,约为2.5~4.0 mm,均出现在近地表雪层,而表层粒径较小且较为稳定。通过雪深和微波亮度差（18~37 GHz）的关系分析,表明亮温差在不同雪期对于雪深的依赖关系不同,在积累期和稳定期,雪深变化与亮温差变化具有明显的正相关;在消融期由于积雪融化的影响,其相关性较差;基于多层积雪微波辐射模型（MEMLS）构建了一维微波辐射模拟环境,模拟表明MEMLS模型在3个雪期的垂直极化10.65 GHz和18.7 GHz模拟结果较37 GHz和90 GHz更好;10.65 GHz V极化在入射角为50°且稳定期时,微波亮温模拟均方根误差（RMSE）结果最小,为2.49 K。3个雪期90 GHz模拟结果水平极化优于垂直极化,由于受表层积雪变化影响,90 GHz模拟结果较不稳定,尤其是消融期时,RMSE最小也达到了42.7 K。本研究有助于理解积雪随时间演化的特征及其对微波辐射模拟的影响,表明在被动微波雪水当量反演算法中,针对不同积雪期需要考虑积雪演化动态过程。     

Integrating climate and local factors for geomorphological distribution models

Earth surface processes (ESPs) drive landscape development and ecosystem processes in high‐latitude regions by creating spatially heterogeneous abiotic and biotic conditions. Ongoing global change may potentially alter the activity of ESPs through feedback on ground conditions, vegetation and the carbon cycle. Consequently, accurate modeling of ESPs is important for improving understanding of the current and future distributions of these processes. The aims of this study were to: (1) integrate climate and multiple local predictors to develop realistic ensemble models for the four key ESPs occurring at high latitudes (slope processes, cryoturbation, nivation and palsa mires) based on the outputs of 10 modern statistical techniques; (2) test whether models of ESPs are improved by incorporating topography, soil and vegetation predictors to climate‐only models; (3) examine the relative importance of these variables in a multivariate setting. Overall, the models showed high transferability with the mean area under curve of a receiver operating characteristics (AUC) ranging from 0.83 to 0.96 and true skill statistics (TSS) from 0.52 to 0.87 for the most complex models. Even though the analyses highlighted the importance of the climate variables as the most influential predictors, three out of four models benefitted from the inclusion of local predictors. We conclude that disregarding local topography and soil conditions in spatial models of ESPs may cause a significant source of error in geomorphological distribution models. Copyright © 2014 John Wiley & Sons, Ltd.     

Radiometric stability assessment of an airborne photogrammetric sensor in a test field

Radiometric stability is a desired property of digital photogrammetric large-format sensors. This article presents a methodology for determining the radiometric stability of airborne imaging sensors in operational conditions in a test field and the results of stability evaluation of a large-format photogrammetric frame sensor DMC, from Intergraph. The imagery was collected in two days using nine different exposure settings, and images collected with variable exposure time and aperture were compared. The results showed promising stability in many cases, up to a level of 2% of the radiance, but less favorable results also appeared. Possible reasons for the unfavorable results could be the limitations of the experimental set-up or the instability of the sensor. DMC showed high radiometric performance potential, but high sensitivity to the exposure settings. Based on the results, recommendations for the future test field calibration and validation procedures were given. One limitation of the analysis was the insufficient information about the sensor stability potential; proposals were given to sensor manufacturers concerning the necessary information.     

Spatial interpolation of monthly climate data for Finland: comparing the performance of kriging and generalized additive models

The Finnish Meteorological Institute has calculated statistics for the new reference period of 1981–2010. During this project, the grid size has been reduced from 10 to 1 km, the evaluation of the interpolation has been improved, and comparisons between different methods has been performed. The climate variables of interest were monthly mean temperature and mean precipitation, for which the spatial variability was explained using auxiliary information: mean elevation, sea percentage, and lake percentage. We compared three methods for spatial prediction: kriging with external drift (KED), generalized additive models (GAM), and GAM combined with residual kriging (GK). Every interpolation file now has attached statistical key figures describing the bias and the normality of the prediction error. According to the cross-validation results, GAM was the best method for predicting mean temperatures, with only very small differences relative to the other methods. For mean precipitation, KED produced the most accurate predictions, followed by GK. In both cases, there was notable seasonal variation in the statistical skill scores. For the new reference period and future interpolations, KED was chosen as the primary method due to its robustness and accuracy.     

Demonstration of a virtual active hyperspectral LiDAR in automated point cloud classification

In this paper, a measurement system for the acquisition of a virtual hyperspectral LiDAR dataset is presented. As commercial hyperspectral LiDARs are not yet available, the system provides a novel type of data for the testing and developing of future hyperspectral LiDAR algorithms. The measurement system consists of two parts: first, backscattered reflectance spectra are collected using a spectrometer and a cutting-edge technology, white-light supercontinuum laser source; second, a commercial monochromatic LiDAR system is used for ranging. A virtual hyperspectral LiDAR dataset is produced by data fusion. Such a dataset was collected on a Norway spruce (Picea abies) sample. The performance of classification was tested using an experimental hyperspectral algorithm based on a novel combination of the Spectral Correlation Mapper and a region growing algorithm. The classifier was able to automatically distinguish between needles, branches and background, in other words, perform a difficult task using only traditional TLS data.     

A 22 GHz receiver with high phase stability for radioastron space-VLBI-mission

A space-qualified low-noise 22 GHz receiver for the international space-VLBI mission Radioastron has been constructed. The microwave electronics is realized by using thermally matched hybrid circuits. The most important properties of the receiver are phase stability, sensitivity and reliability. The high sensitivity is due to a cooled low noise HEMT amplifier (LNA). The measured receiver noise temperature is less than 100 K. The phase stability is achieved by compact structure and thermal stabilization. Phase stabilities of better than 0.13°/°C and 0.2°/°C for the receiver and the LNA units are measured, respectively. The calculated reliability of the receiver exceeds the requirement of 0.97 for the three year mission.     

Management of transboundary water resources: lessons from international cooperation for conflict prevention

Tensions over freshwater resources may become more frequent as pressures on water resources grow due to increased demand and variability of rainfall. Conflicts may take place between or within countries or between competing sectoral users. This paper focuses on institutional approaches for enhancing cooperation between countries for sustainable development of transboundary freshwater bodies and contributing basins. It is assumed that instead of being zones of conflict, shared water resources can provide a basis for cooperation and benefit–sharing provided that threats to the international waters are recognized and collaborative structures are created. The paper draws upon experiences gained within the international waters focal area of the Global Environment Facility, the main funding mechanism for countries to support the environmental management of transboundary water resources. Lessons for promoting peaceful cooperation for environmental management, benefit–sharing and sustainable use of transboundary freshwater resources are highlighted through examples from Africa, Central Asia and Latin America. Experience shows the importance of processes that bring together all sectors and actors whose actions affect the transboundary waterbody at regional, national and local levels. The development of a science–based diagnostic analysis is essential to identify the threats to the transboundary ecosystem and to break down the issues into manageable parts with the aim of developing a strategic action programme. Ensuring political commitment that can result in institutional, policy and legal reforms in the countries concerned is the key to sustainable development of the transboundary resource.