Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure
| dc.contributor.author | Abdelrahim, Mohamed | |
| dc.date.accessioned | 2023-03-01T18:30:37Z | |
| dc.date.available | 2023-03-01T18:30:37Z | |
| dc.description.abstract | The integration between remote sensing imagery and GIS vector data has been a major research concern for more than two decades. This integration facilitates monitoring and analyzing of spatial phenomena. Within the existing situation, two main integration approaches are being used. The first approach depends on processing remotely sensed data and transferring the results to a GIS. Existing GIS vector data can also be processed and used within the image processing techniques to extract better results. Second, remote sensing imagery can be used as a backdrop for the vector layers for better visualization and for vector layer updating purposes. In both approaches, remote sensing imagery is playing a passive role in the spatial query and analysis process; either as a source of information and/or a background to the vector layers. As remote sensing imagery continues to improve in terms of spatial resolution (<1 m), it has the potential to provide a closer, clearer, and sharper representation of real-world phenomena and promise a reliable medium if used actively and directly to query and explore these real world phenomena. Although existing integration techniques satisfy the needs of several spatial applications, they are not optimum for either direct/on-the-fly usage of GIS vector layers as a base in interpreting the image content or active involvement of high quality imagery in spatial query analysis. These techniques degrade the quality of the image scene, disturb the analysis performance, and may hide important spatial patterns that appear within the image. In this research, and “Intelligent Imagery System Prototype” (IISP) was developed. IISP is an integration tool that facilitates the environment for active, direct, and on-the-fly usage of high resolution imagery, internally linked to hidden GIS vector layers, to query the real world phenomena and, consequently, to perform exploratory types of spatial analysis based on a clear/undisturbed image scene. The IISP was designed and implemented using the software components approach to verify the hypothesis that a fully rectified, partially rectified, or even unrectified digital image can be internally linked to a variety of different hidden vector databases/layers covering the end user area of interest, and consequently may be reliably used directly as a base for “on-the-fly” querying of real-world phenomena and for performing exploratory types of spatial analysis. Within IISP, differentially rectified, partially rectified (namely, IKONOS GEOCARTERRA [superscript TM]), and unrectified imagery (namely, scanned aerial photographs and captured video frames) were investigated. The system was designed to handle four types of spatial functions, namely, pointing query, polygon/line-based image query, database query, and buffering. The system was developed using ESRI MapObjects 2.0a as the core spatial component within Visual Basic 6.0. When used to perform the pre-defined spatial queries using different combinations of image and vector data, the IISP provided the same results as those obtained by querying pre-processed vector layers even when the image used was not orthorectified and the vector layers has different parameters. IN addition, the real-time pixel location orthorectification technique developed and presented within the IKONOS GEOCARTERRA [superscript TM]) case provided a horizontal accuracy (RMSE) of +/- 2.75 meters. This accuracy is very close to the accuracy level obtained when purchasing the IKONOS PRECISION products (RMSE of +/- 1.9 meter). The latter cost approximately four time as much as the IKONOS GEOCARTERRA [superscript TM] products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. | |
| dc.description.copyright | As with any copyrighted material, permission to reprint or quote extensively from this report must be received from the author. | |
| dc.identifier.uri | https://unbscholar.lib.unb.ca/handle/1882/15005 | |
| dc.rights | http://purl.org/coar/access_right/c_abf2 | |
| dc.subject.discipline | Geodesy and Geomatics Engineering | |
| dc.title | Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure | |
| dc.type | technical report |
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