Estimation of recent glacial variations in baspa basin using remote sensing technique

The Himalayas has one of the largest concentrations of glaciers outside the Polar Regions. Various reports suggest that significant number of mountain glaciers is shrinking due to climatic variations. Monitoring of these glaciers is important to assess future availability of water resources in the Himalayan region. However, Himalayan glaciers are normally difficult to monitor due to the rugged, mountainous terrain. Therefore, images of Indian Remote Sensing Satellite were used to monitor glaciers in the Baspa basin. Investigations have shown the presence of 30 glaciers in the basin, with areal extent of 167 km2. Out of these, 19 glaciers, with areal extent of 140 km² were selected to estimate retreat. Investigation suggests that almost all glaciers are retreating in the study basin and overall 19% deglaciation has been observed from 1962 to 2001. In general, altitude distribution appears to have significant influence on glacial retreat. Glaciers located around 5000 m altitude range are showing 24% loss as compared to 14% by glaciers located in altitude range higher than 5400 m. In addition, mean altitude of glacier terminus is shifted upward by 88 m, i.e. from 4482 to 4570 m in last 39 years. The glacial volumes were estimated using regression relationship between area and depth. The investigations have suggested that 19.10 km³ of glacial water stored in the 19 glaciers in 1962, has been reduced to 14.71 km³ in 2001, respectively, an overall loss of 23 percent in a period between 1962 and 2001. These investigations suggest that all glaciers in the Baspa Basin are reducing and in long term, such reducing trend can create scarcity of water in the region.     

Artificial Neural Network (ANN) Based Inversion of Benthic Substrate Bottom Type and Bathymetry in Optically Shallow Waters - Initial Model Results

Ocean-colour remote sensing in optically shallow waters is influenced by contribution from the water column depth as well as by the substrate type. Therefore, it is required to include the contribution from the water column and substrate bottom type for bathymetry estimation. In this report we demonstrate the use of Artificial Neural Network (ANN) based approach to spectrally distinguish various benthic bottom types and estimate depth of substrate bottom simultaneously in optically shallow waters. We have used in-water radiative transfer simulation modeling to generate simulated top-of-the-water column reflectance the four major benthic bottom types viz. sea grass, coral sand, green algae and red algae using Hydrolight simulation model. The simulated remote sensing reflectance, for the four benthic bottom types having benthic bottom depth up to 30 m were generated for moderately clear waters. A multi-layer perceptron (MLP) type neural network was trained using the simulated data. ANN based approach was used for classification of the benthic bottom type and simultaneous inversion of bathymetry. Simulated data was inverted to yield benthic bottom type classification with an accuracy of ~98% for the four benthic substrate types and the substrate depth were estimated with an error of 0% for sea grass, 1% for coral sand and 1–3% for green and red algae up to 25 m, whereas for substrate bottom deeper than 25 m depth the classification errors increased by 2–5% for three substrate bottom types except sea grass bottom type. The initial results are promising which needs validation using the in-situ measured remote sensing reflectance spectra for implementing further on satellite data.     

Water Harvesting Structure Positioning by Using Geo-Visualization Concept and Prioritization of Mini-Watersheds Through Morphometric Analysis in the Lower Tapi Basin

Geo-visualization concept has been used for positioning water harvesting structures in Varekhadi watershed consisting of 26 mini watersheds, falling in Lower Tapi Basin (LTB), Surat district, Gujarat state. For prioritization of the mini watersheds, morphometric analysis was utilized by using the linear parameters such as bifurcation ratio (R_b), drainage density (D_d), stream frequency (F_u), texture ratio (T), length of overland flow (L_o) and the shape parameter such as form factor (R_f), shape factor (B_s), elongation ratio (R_e), compactness constant (C_c) and circularity ratio (R_c). The different prioritization ranks were assigned after evaluation of the compound factor. 3 Dimensional (3D) Elevation Model (DEM) from Shuttle Radar Topography Mission (SRTM) and DEM from topo contour were analyzed in ArcScene 9.1 and the fly tool was utilized for the Geo-visualization of Varekhadi mini watersheds as per the priority ranks. Combining this with soil map and slope map, the best feasibility of positioning check dams in mini-watershed no. 1, 5 and 24 has been proposed, after validation of the sites.     

A Hierarchical Hybrid SVM Method for Classification of Remotely Sensed Data

The focus of this work is on developing a new hierarchical hybrid Support Vector Machine (SVM) method to address the problems of classification of multi or hyper spectral remotely sensed images and provide a working technique that increases the classification accuracy while lowering the computational cost and complexity of the process. The paper presents issues in analyzing large multi/hyper spectral image data sets for dimensionality reduction, coping with intra pixel spectral variations, and selection of a flexible classifier with robust learning process. Experiments conducted revealed that a computationally cheap algorithm that uses Hamming distance between the pixel vectors of different bands to eliminate redundant bands was quite effective in helping reduce the dimensionality. The paper also presents the concept of extended mathematical morphological profiles for segregating the input pixel vectors into pure or mixed categories which will enable further computational cost reductions. The proposed method’s overall classification accuracy is tested with IRS data sets and the Airborne Visible Infrared Imaging Spectroradiometer Indian Pines hyperspectral benchmark data set and presented.     

海南国际旅游岛公众版地理信息公共平台设计与实现

简单介绍了海南国际旅游岛公众版地理信息公共平台的总体架构,再从数据集、管理服务软件系统和支撑环境三个方面分别详细介绍了平台数据内容、功能服务以及软硬件、网络部署等内容的设计与实现.     

Recent advances in accessibility research: Representation,methodology and applications

 In this article we examine recent advances in accessibility research and their implications for future studies. We base our discussion on three intersecting dimensions that are useful for evaluating the contribution of recent studies: representation, methodology and applications. Various examples are selected to show that research concerned with representation and methodological problem solving is often applied to issues of broad concern in policy and planning. It is, however, not clear that the simultaneous treatment of representation, methodological and application issues has ever been fully worked out. The questions raised in this article may serve as a foundation for addressing issues pertinent to accurate representation, improved model building, and more rigorous applications in accessibility research. Received: 9 December 2002 / Accepted: 10 February 2003     

GPS导航技术在伊拉克战争中的应用

论述了GPS导航定位技术在伊拉克战争中的作用，着重分析了GPS在精确制导武器中的应用形式和效果，并预测了美国在GPS应用方面未来将要进行的努力。     

Integration and Sharing of Geo-spatial Data Based on Data Engine

Through analyzing the principle of data sharing in the database system, this paper discusses the principle and method for integrating and sharing GIS data by data engine, introduces a way to achieve the high integration and sharing of GIS data on the basis of VCT in VC , and provides the method for uniting VCT into RDBMS in order to implement a spatial database with object-oriented data model.