The Potential of Virtual Reality Technology for Analysis of Remotely Sensed Data: A Lidar Case Study

Abstract

Although the GIS community has been quick to exploit the advantages of virtual reality (VR) for display and analysis of spatial data, VR does not appear to have been exploited widely for remote sensing data analysis. A case study of high resolution lidar data acquired over a deciduous forest near Morgantown, WV was used to investigate the potential and limitations of current VR software for remote sensing analysis. The functionality within a standard remote sensing software package was found to provide a good overview of interpolated, smoothed lidar data, but was less useful for gridded data that had not been interpolated. With gridded data, it was possible to drape orthophotographs or other images over the lidar data, providing a useful method for investigating relationships between lidar and other data. Alternatively, using a commercial VR package, it was possible to view the original lidar point data, and thus visualize the multiple returns from within the canopy of each tree. The point data were preferable for identification of surfaces within the data cloud, especially the ground surface. For a fully integrated remote sensing VR package, functionality will be needed to link point and interpolated coverages, and also to enhance the interactive selection of data for further statistical analysis.     

矿区岩溶陷落柱探测中遥感与地理信息系统技术的应用研究

岩溶陷落柱是煤矿生产中严重的地质灾害之一。本文研究了陷落柱的遥感图像特征，从中提取了矿山环形和线性构造及热异常区，并结合实际地质，采矿资料，应用ＡＲＣ／ＩＮＦＯ地理信息系统进行多因素复合分析，预测陷落柱的可能分布区，进而实施探验证，结果表明，这种综合探测技术方案效果好，费用省。     

遥感图像准无损压缩技术的研究

提出了一种基于图像恢复技术的遥感图像压缩技术,在提高遥感图像压缩比的同时,使压缩后的重建图像质量达到准无损的技术要求。对SRTF、TM图像的试验结果表明,该技术是可行的。     

深度学习遥感图像标注系统研究

随着深度学习的发展,遥感影像处理技术也从传统机器学习算法向深度学习转变,然而,用于遥感图像的训练数据集却十分稀少,且数据标注困难。本文将GIS技术与图像标注技术相结合,基于Flask Web框架设计一个可用于海量遥感数据的标注系统。该系统可用于海量遥感数据的数据框标注、数据类别标注,以及目标关键点标注,同时能将标注数据导出为深度学习训练最常用的COCO数据集和VOC2007两种格式。     

GIS辅助下的遥感图像分类与识别

RS与GIS有着紧密的关系和很强的互支持性,RS为GIS提供了最好的一种数据获取手段,而GIS则可以用来辅助进行遥感图像分析,提高分析的精度和可靠性,因此两者的集成是十分必要的。     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

Approaches for delineating landslide hazard areas using different training sites in an advanced artificial neural network model

The current paper presents landslide hazard analysis around the Cameron area, Malaysia, using advanced artificial neural networks with the help of Geographic Information System (GIS) and remote sensing techniques. Landslide locations were determined in the study area by interpretation of aerial photographs and from field investigations. Topographical and geological data as well as satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. Ten factors were selected for landslide hazard including: 1) factors related to topography as slope, aspect, and curvature; 2) factors related to geology as lithology and distance from lineament; 3) factors related to drainage as distance from drainage; and 4) factors extracted from TM satellite images as land cover and the vegetation index value. An advanced artificial neural network model has been used to analyze these factors in order to establish the landslide hazard map. The back-propagation training method has been used for the selection of the five different random training sites in order to calculate the factor’s weight and then the landslide hazard indices were computed for each of the five hazard maps. Finally, the landslide hazard maps (five cases) were prepared using GIS tools. Results of the landslides hazard maps have been verified using landslide test locations that were not used during the training phase of the neural network. Our findings of verification results show an accuracy of 69%, 75%, 70%, 83% and 86% for training sites 1, 2, 3, 4 and 5 respectively. GIS data was used to efficiently analyze the large volume of data, and the artificial neural network proved to be an effective tool for landslide hazard analysis. The verification results showed sufficient agreement between the presumptive hazard map and the existing data on landslide areas.     

遥感与地理信息系统数据的信息量及不确定性

讨论了遥感、GIS数据的不确定性与信息论中的不确定性间的联系，导出了GIS图形数据与遥感影像数据的信息量估算式，提出了位置疑义度和属性疑义度等概念。在统一的数学基础上，估算几何位置误差和属性正确率不足引起的不确定性，从而建立起遥感影像与GIS图形数据的信息量及不确定性的统一量度。     

遥感地学分析与中国遥感事业——纪念陈述彭先生逝世一周年

作为一代科学宗师,陈述彭先生是我国遥感地学分析的先驱、是遥感应用研究的开创者,陈述彭先生的逝世,不仅是我国遥感界甚至整个科学界的一大损失。值此逝世一年之际,回顾陈先生开创和繁荣遥感事业的历程,深刻缅怀陈述彭院士在推动我国地理学、地图学、遥感应用、地理信息系统等学科发展中的卓越贡献,以表达我们对他的敬意。     

面向农作物监测的遥感信息处理技术研究

以区域性主要农作物种类识别、长势分析与产量估算及农业种植结构现状监测为主要研究对象,开展适于农业管理部门业务化运行的卫星遥感信息处理的关键技术研究。从分析主要作物类型识别的遥感物理依据入手,提出了卫星遥感数据处理及专题信息提取的基本技术框架、主要农作物类型及种植面积信息的提取方法以及主要粮食作物长势分析和产量估算模型,并对结果进行了简要的精度分析。     

ALCM: Automatic land cover mapping

It may be quite important for resource management people to extract single land cover class, at sub-pixel level from multi-spectral remote sensing images of different areas in single step processing. It has been observed, that neural network can be trained to extract single land cover class from multi-spectral remote sensing images, but they have problems in setting various parameters and slow during training stage. This paper present single land cover class water, extraction from mixed pixels present in multiple multi-spectral remote sensing data sets of same bands of AWiFS sensor of Resoursesat-1 (IRS-P6) satellite from different areas. In this work fuzzy logic-based algorithm, which is independent of statistical distribution assumption of data, has been studied at sub-pixel level to handle mixed pixels. It has been found; possibilistic c-means (PCM) algorithm takes the possibilistic view, that the membership of a feature vector in a class has nothing to do with its membership in other classes. Due to this, it was observed that PCM can extract only one class, from remote sensing multi-spectral data and it has produced 93.7% and 97.1% overall sub-pixel classification accuracy for two different data sets of different places using LISS-III (IRS-P6) reference data of same dates as of AWiFS data.     

Electronic Theses and Dissertations (ETDs), GIS,and Remote Sensing: The West Virginia University Example

Abstract

Remote sensing and geographic information system (GIS) scientists and educators in general are utilizing global web sources for information of the latest developments in the use of satellite and GIS approaches, as well as to understand more fully environmental and natural resources processes in various geographic settings. West Virginia University (WVU) has embarked on a pioneering approach (as only the second university worldwide) to archive graduate theses and dissertations in electronic format with worldwide web access. This study illustrates the type of remote sensing and GIS research available through WVU's worldwide web ETD archive, and its potential uses by educators at a variety of levels of the education system for understanding remote sensing and GIS methodologies, as well as environmental and natural resource processes. Keywords: Geographic Information Systems (GIS), remote sensing, West Virginia University, Electronic Thesis and Dissertation (ETD).     

Sustainable Utilisation of Water Resource in Watershed Perspective - A Case Study in Alaunja Watershed, Hazaribagh, Bihar

Alaunja watershed, located on ‘Chotanagpur’ plateau of Bihar, is mainly under single cropping. The area receives more than 1000 mm of rainfall but it has not been utilised properly to increase the agricultural output. The remote sensing, geophysical, DBTM (Digital Basement Terrain Model) and GIS (Geographic information System) techniques were used for providing scientific database for sustainable utilisation of water resources in watershed perspective. The landuse, soil and surface water body maps have been prepared using remotely sensed data. DBTM has been generated based on depth of basement information derived from geophysical data to provide information regarding aquifer geometry, fracture zones and sub-surface basins. Analysis indicated that surface and groundwater resources have potential to irrigate 53 per cent of geographical area of the watershed. But at present, this available potential has been utilised only to irrigate 7.03 per cent area of the watershed. Feasibility for large scale development of groundwater through dugwell is possible only in 2 per cent area of the watershed. The available groundwater potential to irrigate 28 per cent area of watershed can not be utilised through dugwells. The surface water potential is also poorly utilised. The present study also helped in prioritising the water resource development activities.     

支持多源遥感数据格式的抽象库DFAL

针对当前遥感数据缺乏统一文件格式标准,多源遥感产品的生产使用涉及多种文件格式的现状,在研究多种遥感数据格式及对应库GDAL、HDF4、HDF5的基础上,参考国家气象局的NOAA AVHRR 1B格式标准,利用工厂模式,设计和实现了一个具有统一操作接口的多源遥感数据格式抽象库DFAL,在更高的抽象层次解决了GDAL和HDF4、HDF5库不能一致使用的问题。使用DFAL库进行不同文件格式的读写,专家无需了解这些文件格式的差别,以便从繁杂的遥感数据格式中解放出来,将更多精力投入到遥感科学研究的层面上。在DFAL库的基础上实现了两类常用遥感数据格式Geo TIFF和HDF5之间的转换工具,方便工程应用。DFAL库及转换工具在国家高技术研究发展计划《星机地综合定量遥感系统与应用示范》的多尺度按需定量遥感产品生产系统中进行了应用测试,取得了很好的实际效果,证明了DFAL库稳定性和可用性,并大大减少了多源数据协同使用时多种文件格式读写的工作量。     

光学遥感三维计算机模拟模型的研究进展与应用

三维计算机模拟模型是遥感辐射传输机理研究的重要内容,在复杂地表正向模拟和遥感反演中扮演着重要角色.经过最近20年的发展,三维计算机建模研究取得了显著进展,在地表辐射传输过程分析、模型和算法的验证及遥感反演等方面应用广泛.为了更加充分理解三维计算机模拟模型的发展和模型间的差异,及探讨如何将其更好的应用于生活、生产,本文对...     

The transfer of remote sensing technology in Asia ‐ the ITC experience

For forty years, ITC has been involved in institution building, manpower development, technical assistance and applied research. A major effort has taken place in Asia, where ITC has trained some 4000 remote sensing and related disciplines scientists. In addition, three regional sister institutes have been established in Asia. This paper describes and discusses some of ITC's experiences in transferring remote sensing technology to the Asian region, giving examples from various countries, and stressing the need for long‐term institutional support, and the value of conbining training, advisory services and applied reseach, as each provides spin‐offs and benefits to the other forming an inter‐related loop in the transfer of technology process.     

基于数据挖掘的GIS专业课程体系研究

运用关联规则和人工神经网络数据挖掘方法对GIS专业毕业生成绩进行数据挖掘,用SQL Server数据挖掘服务建立毕业设计成绩与各类课程、GIS专业课程与毕业设计成绩、GIS专业实习课程与毕业设计成绩等的数据挖掘模型,将数据挖掘结果应用于GIS专业培养方案的制订中。结果表明,GIS专业毕业生的成绩受理科类课程、计算机类课程的影响较大;GIS专业毕业生成绩受遥感数字图像处理、GIS设计与开发课程设计等实践类课程的影响较大。在新一轮的专业培养方案的修订中增加了计算机类课程、遥感数字图像处理与GIS设计、开发课程的实习学时。     

1996-2000年中国摄影测量与遥感进展

本文总结了从1996年到2000年中国摄影测量与遥感以及地理信息系统等方面的成就，内容涉及，数据获得取与数据管理，航空航天遥感系统及其软硬件，GIS软硬件，摄影测量，遥感及空间信息系统的原理与算法，摄影测量，遥感及空间信息的应用等。     

Lidar遥感基本原理及其发展

介绍了航空激光扫描(Airborne laser scanning)或者Lidar遥感信息获取系统的基本原理、系统的组成、数据获取的方法及其步骤;对近数十年来应用激光扫描遥感信息获取地形表面模型方面取得的主要成果、应用现状做了简要回顾和评述;结合GIS和影像融合方法对Lidar遥感技术未来发展趋势进行了展望。     

Integrated approach of using remote sensing and GIS to study watershed prioritization and productivity

Soil data obtained from soil resource inventory, land and climate were derived from the remote sensing satellite data (Landsat TM, bands 1 to 7) and were integrated in GIS environment to obtain the soil erosion loss using USLE model for the watershed area. The priorities of different sub-watershed areas for soil conservation measures were identified. Land productivity index was also used as a measure for land evaluation. Different soil and land attribute maps were generated in GIS, and R,K,LS,C and P factor maps were derived. By integrating these soil erosion map was generated. The mapping units, found not suitable for agriculture production, were delineated and mapped as non-arable land. The area suitable for agricultural production was carved out for imparting the productivity analysis; the land suitable for raising agricultural crops was delineated into different mapping units as productivity ratings good, fair, moderate and poor. The analysis performed using remote sensing and GIS helped to generate the attribute maps with more accuracy and the ability of integrating these in GIS environment provided the ease to get the required kind of analysis. Conventional methods of land evaluation procedures in terms of either soil erosion or productivity are found not comparable with the out put generated by using remote sensing and GIS as the limitations in generating the attribute maps and their integration. The results obtained in this case study show the use of different kinds of data derived from different sources in land evaluation appraisals.