Ground-based SAR interferometry for monitoring mass movements

An innovative technique for the remote assessment of ground displacements, based on radar interferometry and implemented using ground-based instrumentation (GB-InSAR), has been tested in recent years on a number of selected case sites. The system, known as LISA, developed by the Joint Research Centre (JRC) of the European Commission, is a ground-based radar interferometer specifically designed for field use. It is composed of two radar antennas mounted on a linear rail which horizontally slides to form a synthetic aperture. Coherent SAR processing converts the raw data into an image containing, for each pixel, information on the wave phase, which depends on the target-sensor distance. Consecutive couples of SAR images can be cross-correlated to form interferograms representing phase variations which can be directly related to ground displacement along the sight-line of the radar system, since they are acquired from exactly the same position. Several applications of the system have been conducted on a number of mass movements located in Italy, in order to validate the technique for the monitoring of landslides. GB-InSAR has proved its potential for the measurement of the superficial ground displacements of different landslide types, in terms of failure mechanism, materials involved, kinematics, water content and deformation rates. In particular conditions, such as fast-moving phenomena and inaccessible areas, the technique can be employed directly as a monitoring tool, providing multi-temporal displacement maps of the observed area. Additionally, some applications of the GB-InSAR have provided a fundamental support to decision makers during landslide emergencies, allowing the civil protection authorities to assess the risk and to manage an effective emergency response.     

利用遥感技术复核灾毁耕地面积的试验研究

利用遥感和地理信息技术对县(市)上报的灾毁耕地资料进行复核,能够有效的纠正错报、虚报数据,提高复核工作效率,为做好灾毁耕地的复垦管理工作奠定基础。以福建省漳浦县、建瓯市试验研究为例,探索利用遥感和GIS技术对县(市)上报的灾毁耕地资料进行全面复核的方法,寻求一条快速、及时、准确的复核全省上报的灾毁耕地资料的途径。     

Simple spatially-distributed models for predicting flood inundation: A review

In this paper we review recent progress in the use of reduced complexity models for predicting floodplain inundation. We review the theoretical basis for modelling floodplain flow with simplified hydraulic treatments based on a dimensional analysis of the one-dimensional shallow water equations. We then review how such schemes can be applied in practice and consider issues of space discretization, time discretization and model parameterisation, before going on to consider model assessment procedures. We show that a key advantage of reduced complexity codes is that they force modellers to think about the minimum process representation necessary to predict particular quantities and act as a check on any tendency to reductionism. At the same time, however, the use (compared to standard hydraulic codes) of strong simplifying assumptions requires us to also address the question “how simple can a model be and still be physically realistic?” We show that by making explicit this debate about acceptable levels of abstraction, reduced complexity codes allow progress to be made in addressing a number of long-standing debates in hydraulics.     

唐山地震发震构造的浅层地震探测

利用浅层地震探测方法,研究了唐山地震区１年前出现在卫星图像上的异常现象与发震构造的关系,探讨地震中长期预测的途径。结果表明：唐山地震断层是一条倾向ＮＷ的右旋走滑第四纪同生断裂,它错断了全新统,晚更新统,中更新统,和早更新统地层。     

GIMMS NDVI time series reveal the extent,duration, and intensity of “blooming desert” events in the hyper-arid Atacama Desert,Northern Chile

The “blooming desert”, or the explosive development and flowering of ephemeral herbaceous and some woody desert species during years with abnormally high accumulated rainfall, is a spectacular biological phenomenon of the hyper-arid Atacama Desert (northern Chile) attracting botanists, ecologists, geo-scientists, and the general public from all over the world. However, the number of “blooming deserts”, their geographical distribution and spatio-temporal patterns have not been quantitatively assessed to date. Here, we used NDVI data from the Global Inventory Modeling and Mapping Studies (GIMMS) project to reconstruct the annual land surface phenology (LSP) of the Atacama Desert using a non-parametric statistical approach. From the reconstructed LSP, we detected the “blooming deserts” as positive NDVI anomalies and assessed three dimensions of the events: their temporal extent, intensity of “greening” and spatial extent. We identified 13 “blooming deserts” between 1981 and 2015, of which three (1997–98, 2002–03, and 2011) can be considered major events according to these metrics. The main event occurred in 2011, spanning 180 days between July and December 2011, and spread over 11,136 km² of Atacama dry plains. “Blooming deserts” in Atacama have been triggered by the accumulation of precipitation during a period of 2 to 12 months before and during the events. The proposed three-dimensional approach allowed us to characterize different types of “blooming deserts”: with longer episodes or larger spatial distribution or with different “greening” intensities. Its flexibility to reconstruct different LSP and detect anomalies makes this method a useful tool to study these rare phenomena in other deserts in the world also.     

Short-arc analysis of intersatellite tracking data in a gravity mapping mission

 A technique for the analysis of low–low intersatellite range-rate data in a gravity mapping mission is explored. The technique is based on standard tracking data analysis for orbit determination but uses a spherical coordinate representation of the 12 epoch state parameters describing the baseline between the two satellites. This representation of the state parameters is exploited to allow the intersatellite range-rate analysis to benefit from information provided by other tracking data types without large simultaneous multiple-data-type solutions. The technique appears especially valuable for estimating gravity from short arcs (e.g. less than 15 minutes) of data. Gravity recovery simulations which use short arcs are compared with those using arcs a day in length. For a high-inclination orbit, the short-arc analysis recovers low-order gravity coefficients remarkably well, although higher-order terms, especially sectorial terms, are less accurate. Simulations suggest that either long or short arcs of the Gravity Recovery and Climate Experiment (GRACE) data are likely to improve parts of the geopotential spectrum by orders of magnitude. Received: 26 June 2001 / Accepted: 21 January 2002     

Ecological Effects of Remote Smallsand Descending on Urban Area: Deduced from the "Mud - Snow" in Changchun City

IntroductionContinued sandstorms occurring in North Chinaeally this year have attracted close attention of manyscientists from different aspects. It is recorded thatserious sandstorms occurred eight times in China in1960' s, thirteen times in 1970, s, fou…     

基于WebGIS的智能手机远程监控系统的设计与实现

提出了一套基于WebGIS的智能手机远程监控系统,介绍了系统的总体结构与设计思路。分析发生无线通信粘包现象的原因及后果并提出了解决方法;针对以往基于Web的实时监控系统的实时性不足,利用GPS信息及Ajax技术,实现了Web页面中的数据实时动态更新。     

Capturing the fugitive: Applying remote sensing to terrestrial animal distribution and diversity

Amongst many ongoing initiatives to preserve biodiversity, the Millennium Ecosystem Assessment again shows the importance to slow down the loss of biological diversity. However, there is still a gap in the overview of global patterns of species distributions. This paper reviews how remote sensing has been used to assess terrestrial faunal diversity, with emphasis on proxies and methodologies, while exploring prospective challenges for the conservation and sustainable use of biodiversity. We grouped and discussed papers dealing with the faunal taxa mammals, birds, reptiles, amphibians, and invertebrates into five classes of surrogates of animal diversity: (1) habitat suitability, (2) photosynthetic productivity, (3) multi-temporal patterns, (4) structural properties of habitat, and (5) forage quality. It is concluded that the most promising approach for the assessment, monitoring, prediction, and conservation of faunal diversity appears to be the synergy of remote sensing products and auxiliary data with ecological biodiversity models, and a subsequent validation of the results using traditional observation techniques.     

Assessing changes in the above ground biomass and carbon stocks of Lidder valley,Kashmir Himalaya,India

The changes in the land use and land cover (LULC), above ground biomass (AGB) and the associated above ground carbon (AGC) stocks were assessed in Lidder Valley, Kashmir Himalaya using satellite data (1980–2013), allometric equations and phytosociological data. Change detection analysis of LULC, comprising of eight vegetation and five non-vegetation types, indicated that 6% (74.5 km²) of the dense evergreen forest has degraded. Degraded forest and settlement increased by 20 and 52.8 km², respectively. Normalized difference vegetation index was assessed and correlated with the field-based biomass estimates to arrive at best-fit models for remotely sensed AGB estimates for 2005 and 2013. Total loss of 1.018 Megatons of AGB and 0.5 Megatons of AGC was estimated from the area during 33-year period which would have an adverse effect on the carbon sequestration potential of the area which is already facing the brunt of climate change.