Use of Aerial and Satellite Imagery for DEM Extraction and GIS Applications (original) (raw)
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Int. Journal of Advances in Remote Sensing and GIS, 2016
Abstract: A Digital Elevation Model (DEM) is a representation of a land surface in a 3 dimensional space with elevation as the third dimension along X (horizontal coordinates) and Y (vertical coordinates) dimensions. DEM is a useful data source in hilly areas terrain analysis; DEM plays an important role in various areas like disaster management, hydrology and watershed management, geomorphology, urban development, map creation and resource management etc. Cartosat 1 or IRS P5 (Indian Remote Sensing Satellite) is a state of the art remote sensing satellite developed and launched by ISRO (May 5, 2005). It has been designed for terrain modeling and large scale mapping applications. This high resolution stereo data has great potential to produce high quality DEM. The high resolution Cartosat 1 stereo image data is capable to provide significant impact in topographic mapping and watershed applications. The objective of the present study is to generate high resolution DEM (10 m and 30 m) and ortho rectified image through Cartosat 1 stereo pair, quality evaluation in different elevation strata, generation of terrain parameters. Aglar watershed in Tehri Garhwal and Dehradun district has been used as the test site. The present study reveals that DEM generated (10 m and 30 m) using CARTOSAT 1 stereo pair is of high quality. The derived terrain parameters like slope, aspect, drainage, watershed boundaries etc., are also of good quality. A comparison of the DEM and the parameter derived from it reveals significant improvement in the quality as compared to the freely available DEM in internet. Keywords: ASTER DEM, CARTO DEM, CARTOSAT 1, Digital Elevation Model, Ortho rectified Image, Photogrammetry, Rational Polynomial Coefficient, Stereo Pair, Terrain Parameters.
2011
For the generation of 3D city models from satellite stereo imagery beyond the generation of digital surface models (DSM) from stereo data the next crucial step is the separation of urban 3D objects from ground. To do this the most common method is the derivation of a so called digital terrain model (DTM) from the DSM. The DTM should ideally contain only the surface of the ground on which the urban objects are located. Since only the surface of the objects can be seen from space, sophisticated methods have to be developed to gain information of the bare ground. In this paper selected methods for the extraction of a DTM from a DSM are described and evaluated. The evaluation is done by applying the methods to synthetically generated DSMs. These synthetical DSMs are a combination of ground and typical urban objects put on top of it. The application of the DTM extraction methods should recover in turn the original ground model as good as possible. Also the sum of the obtained DTM and the...
Digital Elevation Model Generation and Retrieval of Terrain Attributes using CARTOSAT-1 Stereo Data
… Journal of Science …, 2012
Terrain analysis is a very important part of the study of surface processes. Although several techniques have been used historically to study terrain, the use of satellite imageries has become one of the optimum methods now. Presently there are lots of satellite imageries available for extraction of elevation features microwave optical etc. The stereo pair images have a great potentiality in the study of terrain analysis. The present study deals with the generation of Digital Elevation Model (DEM) using CARTOSAT-1 stereo data and retrieval of terrain attributes thereof for western Dehradun area. Initially the DEM is generated and the vertical accuracy was analysed. Additionally, contour and primary attributes (slope and aspect) are derived for further analysis. A three dimensional view is also generated in order to visualize the terrain perspective view.
Towards automated DEM generation from high resolution stereo satellite images
International Society for …, 2008
High resolution stereo satellite imagery is well suited for the creation of digital surface models (DSM). In this paper, a system for highly automated DSM and orthoimage generation based on CARTOSAT-1 imagery is presented. The proposed system processes photometrically corrected level-1 stereo scenes using the rational polynomial coefficients (RPC) universal sensor model. The RPC are derived from orbit and attitude information and have a much lower accuracy than the ground resolution of approximately 2.5 m. Ground control points are used to estimate affine RPC correction. Accurate GCP are not always available, especially for remote areas and large scale reconstruction. In this paper, GCP are automatically derived from lower resolution reference images (Landsat ETM+ Geocover and SRTM DSM). It is worthwhile to note that SRTM has a much higher lateral accuracy than the Landsat ETM+ mosaic, which limits the accuracy of both DSM and orthorectified images. Thus, affine RPC correction parameters are estimated by aligning a preliminary DSM to the SRTM DSM, resulting in significantly improved geolocation of both DSM and orthoimages. Robust stereo matching and outlier removal techniques and prior information such as cloud masks are used during this process. DSM with a grid spacing of 10 m are generated for 9 CARTOSAT-1 scenes in Catalonia. Checks against independent ground truth indicate a lateral error of 3-4 meters and a height accuracy of 4-5 meters. Independently processed scenes align at subpixel level and are well suited for mosaicing.
Refinement of urban digital elevation models from very high resolution stereo satellite images
ISPRS. IPI-Workshop, 2009
Digital elevation models (DEM) of high resolution and high quality are required for many applications like urban modeling, readiness for catastrophes or disaster assessment. A good source for the derivation of such DEMs from any place in the world are very high resolution (VHR) satellite stereo images as provided e.g. by Ikonos, QuickBird or WorldView. In this paper a method for the generation and refinement of urban high resolution DEMs from VHR imagery is presented and evaluated. Urban DEMs generated from very high resolution satellite imagery of ground sampling distances of about one meter are normally of resolutions of about three to ten meters. For the above mentioned applications of urban DEMs such results are often too coarse. In this paper an advanced method for the generation of dense digital elevation models is presented and discussed. The method is mainly based on dense stereo algorithms developed for computer vision applications. It is adapted and optimized to earth observation requirements. In the paper the DEM generation together with the additional refinement steps is presented and evaluated using very high resolution stereo imagery from Munich and Athens. The generated DEMs are compared to ground truth data where available and the quality and efficiency of the algorithms are analyzed and discussed.
GI_Forum, 2021
High-resolution digital elevation models of urban areas can support humanitarian organisations in their work; especially the 3D reconstruction of buildings is desirable because it can be used for population estimation and damage analysis after crises and disaster events. In this paper, we test the quality of multi-date DEMs with 15 Pléiades images from Port-au-Prince, Haiti using the automatic stereo pipeline s2p. We focus on triplet combinations with images taken from different dates. This study investigates the metaparameters satellite azimuth and incident angle to understand which recording geometry yields a good result in terms of completeness and accuracy. It is assumed that the closer the multi-date constellation gets to an in-orbit triplet, the better the quality of the DEM.
ISPRS International Journal of Geo-Information, 2017
Very high spatial resolution (VHSR) stereo-imagery-derived digital surface models (DSM) can be used to generate digital elevation models (DEM). Filtering algorithms and triangular irregular network (TIN) densification are the most common approaches. Most filter-based techniques focus on image-smoothing. We propose a new approach which makes use of integrated object-based image analysis (OBIA) techniques. An initial land cover classification is followed by stratified land cover ground point sample detection, using object-specific features to enhance the sampling quality. The detected ground point samples serve as the basis for the interpolation of the DEM. A regional uncertainty index (RUI) is calculated to express the quality of the generated DEM in regard to the DSM, based on the number of samples per land cover object. The results of our approach are compared to a high resolution Light Detection and Ranging (LiDAR)-DEM, and a high level of agreement is observed-especially for non-vegetated and scarcely-vegetated areas. Results show that the accuracy of the DEM is highly dependent on the quality of the initial DSM and-in accordance with the RUI-differs between the different land cover classes.
Image and Vision Computing, 2003
This paper addresses the problem of generating digital elevation models from satellite images taken by linear pushbroom cameras. Since there exist unique geometric properties for linear pushbroom images, we argue that the conventional DEM generation schemes developed for perspective images are not suitable for satellite images. Using the geometric properties of linear pushbroom images, we design a new matching strategy optimized for linear pushbroom image in three aspects: conjugate search method, correlation patch design and match sequence determination. We will discuss in what aspect conventional approaches and our new approach differ and show how performance has improved by hiring proper techniques. A series of experiments using SPOT panchromatic stereo pairs showed that our approach outperformed conventional approaches in terms of accuracy and processing time.