Stationary spatially modulated fourier transform spectro-radiometer

Journal of the Indian Society of Remote Sensing - A stationary, compact, spatially modulated Fourier Transform spectro-radiometer based on triangular, common path Sagnac interferometer has been...     

Variation in tree mortality and regeneration affect forest carbon recovery following fuel treatments and wildfire in the Lake Tahoe Basin, California, USA

Background

Forest fuel treatments have been proposed as tools to stabilize carbon stocks in fire-prone forests in the Western U.S.A. Although fuel treatments such as thinning and burning are known to immediately reduce forest carbon stocks, there are suggestions that these losses may be paid back over the long-term if treatments sufficiently reduce future wildfire severity, or prevent deforestation. Although fire severity and post-fire tree regeneration have been indicated as important influences on long-term carbon dynamics, it remains unclear how natural variability in these processes might affect the ability of fuel treatments to protect forest carbon resources. We surveyed a wildfire where fuel treatments were put in place before fire and estimated the short-term impact of treatment and wildfire on aboveground carbon stocks at our study site. We then used a common vegetation growth simulator in conjunction with sensitivity analysis techniques to assess how predicted timescales of carbon recovery after fire are sensitive to variation in rates of fire-related tree mortality, and post-fire tree regeneration.

Results

We found that fuel reduction treatments were successful at ameliorating fire severity at our study site by removing an estimated 36% of aboveground biomass. Treated and untreated stands stored similar amounts of carbon three years after wildfire, but differences in fire severity were such that untreated stands maintained only 7% of aboveground carbon as live trees, versus 51% in treated stands. Over the long-term, our simulations suggest that treated stands in our study area will recover baseline carbon storage 10?C35?years more quickly than untreated stands. Our sensitivity analysis found that rates of fire-related tree mortality strongly influence estimates of post-fire carbon recovery. Rates of regeneration were less influential on recovery timing, except when fire severity was high.

Conclusions

Our ability to predict the response of forest carbon resources to anthropogenic and natural disturbances requires models that incorporate uncertainty in processes important to long-term forest carbon dynamics. To the extent that fuel treatments are able to ameliorate tree mortality rates or prevent deforestation resulting from wildfire, our results suggest that treatments may be a viable strategy to stabilize existing forest carbon stocks.     

Performance of rate detector algorithms for an integrated GPS/INS system in the presence of slowly growing error

In the Global Positioning System, there is no provision for real-time integrity information within the Standard Positioning Service, by design. However, in safety critical sectors like aviation, stringent integrity performance requirements must be met. This can be achieved using the special augmentation systems or RAIM (Receiver Autonomous Integrity Monitoring) or both. RAIM, the most cost-effective method relies on data consistency, and therefore requires redundant measurements for its operation. An external aid to provide this redundancy can be in the form of an Inertial Navigation system. This should enable continued performance even when no redundant satellite measurements are available. An algorithm presented in previous papers by the authors detects the rate of slowly growing errors. The algorithm was shown to be effective for early detection of slowly growing errors that belong to the class of most difficult to detect errors. Firstly, rate detector is tested for varying faults. Secondly, real data are used to validate the rate detector algorithm. The data are extensively analyzed to ascertain whether it is suitable for integrity and fault diagnostics. A modification to the original rate detector algorithm is suggested by addition of a bias state to the dynamic model. The performance is then compared with the existing techniques and substantial improvement is shown.     

Modelling and Remote Sensing of Land Surface Temperature in Turkey

This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26?C45°E and 36?C42°N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, Eski?ehir, ?stanbul, ?zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LST_ANN) and Becker and Li temperature(LST_B-L) method values have been found as 0.077?K and 0.091?K (training stations), 0.045?K and 0.003?K (testing stations), respectively.     

Web环境下SVG地图浏览器的设计与实现

SVG是近年来发展起来的基于XML的用于描述矢量图形、图像的标准规范，该规范的制定对网上矢量地图数据的共享具有十分重要的意义，基于SVG的矢量地图十分有利于地理空间数据的传播。文中首先分析了目前Web环境下矢量地图发布存在的问题，之后介绍了SVG的有关情况，最后基于Adobe的SVG Vie—wer2．0设计并实现了一个SVG地图浏览器，着重研究了3个问题，即矢量地图数据在SVG文档中的组织与编码，地图浏览器界面的设计以及若干地图操作功能的实现。     

Use of the L2C signal for inversions of GPS radio occultation data in the neutral atmosphere

Results from processing FORMOSAT-3/COSMIC radio occultations (RO) with the new GPS L2C signal acquired both in phase locked loop (PLL) and open loop (OL) modes are presented. Analysis of L2P, L2C, and L1CA signals acquired in PLL mode shows that in the presence of strong ionospheric scintillation not only L2P tracking, but also L1CA tracking often fails, while L2C tracking is most stable. The use of L2C improves current RO processing in the neutral atmosphere mainly by increasing the number of processed occultations (due to significant reduction in the number of L2 tracking failures) and marginally by a reduction in noise in statistics. The latter is due to the combination of reduced L2C noise (compared to L2P) and increased L1CA noise in those occultations where L2P would have failed. This result suggests application of OL tracking for L1CA and L2C signals throughout an entire occultation to optimally acquire RO data. Two methods of concurrent processing of L1CA and L2C RO signals are considered. Based on testing of individual occultations, these methods allow: (1) reduction in uncertainty of bending angles retrieved by wave optics in the lower troposphere and (2) reduction in small-scale residual errors of the ionospheric correction in the stratosphere.     

EXPERIENCE IN COMPILING LARGE-SCALE MAPS OF EROSION-PRONE AREAS

Specific criteria used in the compilation of large-scale maps of erosion-prone areas are defined and evaluated for tracts of land representing a number of different agricultural cover types. Formulas are derived which facilitate the mapping of such areas based on such readily observable morphometric characteristics as slope length and steepness. Translated by Edward Torrey, Alexandria, VA 22308 from: Vestnik Moskovskogo Universiteta, geografiya, 1988, No. 5, pp. 25-31.     

基于多智能体技术的实时网络制图研究

为解决实时网络地图制图中产生的空间冲突问题,笔者应用多智能体技术,并结合创新性渐进式地图综合兴趣层理论,以旅游网络地图实时制图为例,将不同级别的空间数据分配到四种类型的智能体上,经过一系列空间转换,消除地图生成过程中产生的空间冲突。实践表明,这项研究一定程度上增强了地图的可读性,可以帮助用户更好地理解地理空间信息。     

地震灾害现象模式分析与识别

在介绍典型震后地质灾害现象的基础上,设计了利用遥感影像进行震后地质灾害模式识别的整体方案,以震后滑坡造成的道路损毁现象为例,分析其表现出的独有模式,提出了先对影像进行目视解译并利用纹理特征对分类结果进行再分类的识别方法。