• Title/Summary/Keyword: remote sensing and GIS

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ANALYSIS OF SPATIAL FACTORS AFFECTING DENGUE EPIDEMICS USING GIS IN THAILAND

  • Nakhapakorn Kanchana;Tripatht Nitin;Nualchawee Kaew;Kusanagt Michiro;Pakpien Preeda
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.774-777
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    • 2005
  • Dengue Fever(DF) and Dengue haemorrhagic fever(DHF) has become a major international public health concern. Dengue Fever(DF) and Dengue haemorrhagic Fever (DHF) is also still the major health problem of Thailand, although many campaigns against it have been conducted throughout the country. GIS and Remotely Sensed data are used to evaluate the relationships between socio-spatial, environmental factors/indicators and the incidences of viral diseases. The aim of the study is to identify the spatial risk factors in Dengue and Dengue Haemorrhagic Fever in Sukhothai province, Thailand using statistical, spatial and GIS Modelling. Preliminary results demonstrated that physical factors derived from remotely sensed data could indicate variation in physical risk factors affecting DF and DHF. The present study emphasizes the potential of remotely sensed data and GIS in spatial factors affecting Dengue Risk Zone analysis. The relationship between land cover and the cases of incidence of DF and DHF by information value method revaluated that highest information value is obtained for Built-up area. A negative relationship was observed for the forest area. The relations between climate data and cases of incidence have shown high correlation with rainfall factors in rainy season but poor correlation with temperature and relative humidity. The present study explores the potential of remotely sensed data and GIS in spatial analysis of factors affecting Dengue epidemic, strong spatial analysis tools of GIS. The capabilities of GIS for analyst spatial factors influencing risk zone has made it possible to apply spatial statistical analysis in Disease risk zone.

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Change Detection of Buildings Using High Resolution Remotely Sensed Data

  • Zeng, Yu;Zhang, Jixian;Wang, Guangliang
    • Proceedings of the KSRS Conference
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    • 2002.10a
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    • pp.530-535
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    • 2002
  • An approach for quickly updating GIS building data using high resolution remotely sensed data is proposed in this paper. High resolution remotely sensed data could be aerial photographs, satellite images and airborne laser scanning data. Data from different types of sensors are integrated in building extraction. Based on the extracted buildings and the outdated GIS database, the change-detection-template can be automatically created. Then, GIS building data can be fast updated by semiautomatically processing the change-detection-temp late. It is demonstrated that this approach is quick, effective and applicable.

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REMOTE SENSING AND GIS INTEGRATION FOR HOUSE MANAGEMENT

  • Wu, Mu-Lin;Wang, Yu-Ming;Wong, Deng-Ching;Chiou, Fu-Shen
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.551-554
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    • 2006
  • House management is very important in water resource protection in order to provide sustainable drinking water for about four millions population in northern Taiwan. House management can be a simple job that can be done without any ingredient of remote sensing or geographic information systems. Remote sensing and GIS integration for house management can provide more efficient management prescription when land use enforcement, soil and water conservation, sewage management, garbage collection, and reforestation have to be managed simultaneously. The objective of this paper was to integrate remote sensing and GIS to manage houses in a water resource protection district. More than four thousand houses have been surveyed and created as a house data base. Site map of every single house and very detail information consisting of address, ownership, date of creation, building materials, acreages floor by floor, parcel information, and types of house condition. Some houses have their photos in different directions. One house has its own card consists these information and these attributes were created into a house data base. Site maps of all houses were created with the same coordinates system as parcel maps, topographic maps, sewage maps, and city planning maps. Visual Basic.NET, Visual C#.NET have been implemented to develop computer programs for house information inquiry and maps overlay among house maps and other GIS map layers. Remote sensing techniques have been implemented to generate the background information of a single house in the past 15 years. Digital orthophoto maps at a scale of 1:5000 overlay with house site maps are very useful in determination of a house was there or not for a given year. Satellite images if their resolutions good enough are also very useful in this type of daily government operations. The developed house management systems can work with commercial GIS software such as ArcView and ArcPad. Remote sensing provided image information of a single house whether it was there or not in a given year. GIS provided overlay and inquiry functions to automatically extract attributes of a given house by ownership, address, and so on when certain house management prescriptions have to be made by government agency. File format is the key component that makes remote sensing and GIS integration smoothly. The developed house management systems are user friendly and can be modified to meet needs encountered in a single task of a government technician.

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Object-oriented Information Extraction and Application in High-resolution Remote Sensing Image

  • WEI Wenxia;Ma Ainai;Chen Xunwan
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.125-127
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    • 2004
  • High-resolution satellite images offer abundance information of the earth surface for remote sensing applications. The information includes geometry, texture and attribute characteristic. The pixel-based image classification can't satisfy high-resolution satellite image's classification precision and produce large data redundancy. Object-oriented information extraction not only depends on spectrum character, but also use geometry and structure information. It can provide an accessible and truly revolutionary approach. Using Beijing Spot 5 high-resolution image and object-oriented classification with the eCognition software, we accomplish the cultures' precise classification. The test areas have five culture types including water, vegetation, road, building and bare lands. We use nearest neighbor classification and appraise the overall classification accuracy. The average of five species reaches 0.90. All of maximum is 1. The standard deviation is less than 0.11. The overall accuracy can reach $95.47\%.$ This method offers a new technology for high-resolution satellite images' available applications in remote sensing culture classification.

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APPLICATION OF LOGISTIC REGRESSION MODEL AND ITS VALIDATION FOR LANDSLIDE SUSCEPTIBILITY MAPPING USING GIS AND REMOTE SENSING DATA AT PENANG, MALAYSIA

  • LEE SARO
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.310-313
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    • 2004
  • The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and from field surveys. Topographical and geological data and satellite images were collected, processed, and constructed into a spatial database using GIS and image processing. The factors chosen that influence landslide occurrence were: topographic slope, topographic aspect, topographic curvature and distance from drainage, all from the topographic database; lithology and distance from lineament, taken from the geologic database; land use from TM satellite images; and the vegetation index value from SPOT satellite images. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by logistic regression model. The results of the analysis were verified using the landslide location data and compared with probabilistic model. The validation results showed that the logistic regression model is better prediction accuracy than probabilistic model.

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Developing application system of forest information using digital photogrammetry and GIS

  • Jo, Myung-Hee;Heo, Young-Jin;Kim, Joon-Bum;Kim, In-Ho
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.911-913
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    • 2003
  • Recently in order to process forest official task more effectively and scientifically the previous of that which is focused on document and inventory, should be applied with the spatial information technology. Especially, the forest information remote sensing system has to be developed using digital photogrammetry and GIS. In this study the forest information remote sensing system is implemented to manage forest resource and forest official effectively especially by constructing database of forest environment information and cadastral information, overlaying various thematic maps, and performing spatial analysis using GIS and aerial photograph. For this, the attribute data and spatial data of aerial photograph, digital topography map, forest cadastral map, forest type map, forest use map should be reprocessed and stored in Oracle. Also, the user interface is developed by using Visual Basic 6.0 and MapObjects 2.1 of ESRI based on CBD(Component Based Development).

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Remote sensing and GIS technologies for route selection of 'West-East Nature Gas pipeline'

  • Zhu Xiaoge;Zhang Yaoyan;Zhang Yiming;Van Hu;Shihong Wang
    • Proceedings of the KSRS Conference
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    • 2004.10a
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    • pp.28-30
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    • 2004
  • The West-East Nature Gas Pipeline is a great project in China. Advanced remote sensing technology combined with GIS and GPS is used to select the favorable plan from various possible routes through interpreting the information of topographic landform, regional geology, disaster geology, traffic conditions and nature environment from remote sensing images. There are a lot of changes in geographical and environmental factors along such pipelines due to the rapid development in China. Image maps produced from new satellite data can identify these changes and be used successfully not only on route-selection studies but also on in situ investigation, together with GPS. Results from detail analysis provide necessary information and parameters for plan, design and construction of the pipeline and they are also the basic data for the pipeline database. The set of techniques has been applied on planning and designing several pipelines successfully.

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Open Source Remote Sensing of ORFEO Toolbox and Its Connection to Database of PostGIS with NIX File Importing

  • Lee, Ki-Won;Kang, Sang-Goo
    • Korean Journal of Remote Sensing
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    • v.26 no.3
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    • pp.361-371
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    • 2010
  • In recent, interests regarding open source software for geo-spatial processing are increasing. Open source remote sensing (OSRS) is regarded as one of the progressing and advanced fields in remote sensing. Nevertheless, analyses or application cases regarding OSRS are not enough for general uses or references. In this study, three kinds of OSRS software in consideration of international popularity, types of functionalities, and development environments are taken into account: OSSIM, Opticks, and ORFEO Toolbox (OTB). First, functional comparison with respect to these is carried out on the level of the preliminary survey. According to this investigation, OTB is chosen as the most applicable OSRS software in this study. Running on OTB, NIX format importing module and database connecting module are implemented for widely general uses and further application. As for an example case, airborne image of NIX format is used to region growing segmentation algorithm in OTB, and then the results are stored and retrieved in PostGIS database to test implemented modules. Conclusively, local customization and algorithm development using OSRS software are necessary to build on-demand applications from the developers' viewpoint.

Disaster Assessment, Monitoring, and Prediction Using Remote Sensing and GIS (원격탐사를 이용한 재난 감시 및 예측과 GIS 분석)

  • Jung, Minyoung;Kim, Duk-jin;Sohn, Hong-Gyoo;Choi, Jinmu;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.37 no.5_3
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    • pp.1341-1347
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    • 2021
  • The need for an effective disaster management system has grown these days to protect public safety as the number of disasters causing massive damage increases. Since disaster-induced damage can develop in various ways, rapid and accurate countermeasures must be prepared soon after disasters occur. Numerous studies have continuously developed remote sensing and GIS (Geographic Information System)-based techniques for disaster monitoring and damage analysis. This special issue presents the research results on disaster prediction and monitoring based on various remote sensors on different platforms from ground to space and disaster management using GIS techniques. The developed techniques help manage various disasters such as storms, floods, and forest fires and can be combined to achieve an integrated and effective disaster management system.

Core Habitat Zonation for Selected Endangered Species using Remote Sensing and GIS

  • Khant, Aung Pyeh;Tripathi, Nitin K.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.15-17
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    • 2003
  • One of the most serious problems that the world is facing is the loss of biodiversity and habitats as a result of environmental degradation. There are several strategies to protect the habitats and biodiversity within a certain region such as establishing protected areas; monitoring the remaining forests and managing the landscape within limits have been employed. In this study, Predicted Habitat Distribution Model (simple spatial modeling) was developed using vegetation types, land use and land cover, DEM, slope, drainage, roads, human settlement areas and minimum habitat requirements of each species. Then, based on the checklist of presence and absence of each species, the final habitat maps for selected endangered species are generated. Integration of Remote Sensing (RS) and Geographical Information System (GIS) has proven a very effective tool to generate wildlife habitat maps at various levels. An effecting mapping could be performed based on satellite remote sensing and modeling biodiversity indicators in GIS.

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