Sharing and cooperation in geo-information technology

Aziz, T. Lukman

Bibliographic data

Monograph

Persistent identifier:: 856479470

Author:: Aziz, T. Lukman

Title:: Sharing and cooperation in geo-information technology

Sub title:: ISPRS Commission VI Symposium, April 15 - 17, 1999, Bandung, Indonesia

Scope:: 1 Online-Ressource (130 Seiten)

Year of publication:: 1999

Place of publication:: London

Publisher of the original:: RICS Books

Identifier (digital):: 856479470

Illustration:: Illustrationen, Diagramme

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: WG VI/3: INTERNATIONAL COOPERATION AND TECHNOLOGY TRANSFER

Write comment:: Der Aufsatz "Promotion Of The General Understanding And Improvement Of Public Relations, [...] ist im Original nicht enthalten.

Document type:: Monograph

Structure type:: Chapter

Chapter

Title:: SPATIAL AND TEMPORAL DATA HANDLING FOR REMOTE SENSING DATA. R. Venantius Hari Ginardi

Document type:: Monograph

Structure type:: Chapter

70 International Archives of Photogrammetry and Remote Sensing. Vol. XXXII, Part 6. Bandung-lndonesia 1999 SPATIAL AND TEMPORAL DATA HANDLING FOR REMOTE SENSING DATA R. Venantius Hari Ginardi Presented on ISPRS Mid-term Technical Commision VI Symposium, Bandung, 15-17 April 1999 Lecturer on ITS Surabaya (Sepuluh Nopember Institute of Technology - Surabaya), postgraduate student on Msc in Information Tecnology for Natural Resources Management, SEAMEO-BIOTROP, Bogor-Indonesia ABSTRACT Processing multi-satellite imagery with different times of acquisition in image processing software is based on manual image selection by the user. Its efficiency depends on how accurate the user notes the file content, image acquisition dates and file location. Selecting image files based on spatial and temporal criteria is a process that helps the user to retrieve image file(s) more effectively. This paper proposes a Temporal Data Manager Development for Remote Sensed data that enables image data query, based on spatial and temporal information. This model can support development in the real time dynamic modelling using Satellite Imagery. 1. INTRODUCTION Early use of satellite imagery was mainly based on image interpretation. Image processing tools , electromagnetics theory and coordinate system were combined for this purpose. The output was object figure or analysis such as land cover classification, NDVI, clay ratio, shape detection, topographic feature, etc. other programming for the advanced user. In some remote sensing software, this feature is called batch script or user script. The scope of programming is dependent on supported language and predefined object class. Much more customization can be made if remote Sensing software supports C language or .lava programming. 2. SPATIAL AND TEMPORAL DATA HANDLING With a wider choice of sensor type and satellite source, more variation of spatial and spectral satellite imagery becomes available. It is also feasible to collect multisensor data and multitemporal data for certain area. With multitemporal data for specific area, more analysis and modelling based on change detection can be performed, using the advantages of currently cheaper and more detaileds satellite imagery. Current image processing sofware use manual data retrieval. A user should use his/her interpretaion of metadata to select which image file to retrieve. The management of metadata is in the form of text files that are organised depending on user. This paper proposes to develop a Temporal data manager approach for Remote Sensed Data, that enables features for data query based on spatial and temporal information. Basic information stored in remotely sensed data is spectral and spatial information. Managing temporal information is an additional possibilitiy for current remote sensing applications. Although a time stamp for acquisition time information is currently available in Remote Sensed Data, this information is not a part of data processing. The image file format is highly dependent on remote sensing application software. By managing temporal information, some operation can be performed for sequence of satellite imagery like : clouds removal, mosaic, and other image correction using other image information. Spatial information of image consist of information about 'what' feature exist in image file and 'where' is object position relative to other object. Spatial information in vector representation is known as topology. Temporal dimension can be handled in a I time type information format. There are two common time type 1 information format : event time and transaction time. Temporal 1 information systems can be sub-divided into four categories i based on those two type (Worboys, 1994) I s No support for transaction time Support for transaction time No support for event time Static Rollback Support for event time Historic Bitemporal Table 1. Temporal Dimension supported by system types This paper focuses only on historic type of temporal dimension to be applied in Remote Sensed Data since image file from satellite imagery can be considered as an entity with a single \ time stamp. Coversely transaction time is usually used in motion multimedia video that has duration time component. Storing multi-temporal data for one spatial entity, for example NDVI data from NOAA satellite for West Java on 7 consecutive days, has 2 possibilities : The Development of Temporal Database in GIS (called TGIS) is more applicable since GIS and Database Systems are closely related. Adapting a Temporal Database to Remote Sensing application is very difficult because of its different file structure. Remote Sensed data is similar to multimedia data. Since there is existing research to model and retrieve Multimedia data using temporal information, this approach can apply a temporal data manager into current remote rensing application. Some remote sensing software that is widely used supports user defined application development that enables customization and a. Store all 7 layers of temporal information in one dataset. This approach is widely used because it is easy to perform arithmetic modelling, but the independence of each temporal information layer is lost because they are bounded together. b. Store each image layer data of temporal information independently, and manage metadata for each dataset. This approach has a benefit from its independence, but requires manual user retrieval and metadata interpretation. The temporal data handling used in this paper is based on this approach.

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