Automatic Digital Surface Model Research Articles

Digital surface model generation from aerial imagery using bridge probability relaxation matching

Optical image dense matching is a crucial step in the process of generating digital surface models (DSMs). Many existing dense matching methods have adopted pixelwise matching strategy and have achieved precise matching results; however, the methods are time consuming and have limited efficiency in high surveying and mapping production. We introduce a bridge probability relaxation matching method for automatic DSM generation. The method adopts a coarse-to-fine hierarchical strategy and achieves high matching accuracy and fast processing speed simultaneously. This method builds a self-adaptive disparity surface model in a local area and constrains the disparity surface using the spatial relationship between feature points and adjacent pixels. Finally, the disparity is optimized by calculating the increment of the relaxation iteration probability. Experiments are based on different areas with different textures and terrain types. Compared with the DSMs derived from semi-global matching, our proposed approach achieves high levels of accuracy and efficiency in automatic DSM generation.

Urban Feature Extraction from Merged Airborne LiDAR Data and Digital Camera Data

Until recently, the most highly accurate digital surface models were obtained from airborne lidar. With the development of a new generation of large format digital photogrammetric aerial camera, a fully digital photogrammetric workflow became possible. Digital airborne images are sources for elevation extraction and orthophoto generation. This research concerned with the generation of digital surface models and orthophotos as applications from high-resolution images. In this research, the following steps were performed. A Benchmark data of LIDAR and digital aerial camera have been used. Firstly, image orientation, AT have been performed. Then the automatic digital surface model DSM generation has been produced from the digital aerial camera. Thirdly true digital ortho has been generated from the digital aerial camera also orthoimage will be generated using LIDAR digital elevation model (DSM). Leica Photogrammetric Suite (LPS) module of Erdsa Imagine 2014 software was utilized for processing. Then the resulted orthoimages from both techniques were mosaicked. The results show that automatic digital surface model DSM that been produced from digital aerial camera method has very high dense photogrammetric 3D point clouds compared to the LIDAR 3D point clouds. It was found that the true orthoimage produced from the second approach is better than the true orthoimage produced from the first approach. The five approaches were tested for classification of the best-orthorectified image mosaic using subpixel based (neural network) and pixel-based ( minimum distance and maximum likelihood).Multicues were extracted such as texture(entropy-mean),Digital elevation model, Digital surface model ,normalized digital surface model (nDSM) and intensity image. The contributions of the individual cues used in the classification have been evaluated. It was found that the best cue integration is intensity (pan) +nDSM+ entropy followed by intensity (pan) +nDSM+mean then intensity image +mean+ entropy after that DSM )image and two texture measures (mean and entropy) followed by the colour image. The integration with height data increases the accuracy. Also, it was found that the integration with entropy texture increases the accuracy. Resulted in fifteen cases of classification it was found that maximum likelihood classifier is the best followed by minimum distance then neural network classifier. We attribute this to the fine resolution of the digital camera image. Subpixel classifier (neural network) is not suitable for classifying aerial digital camera images.

Assessment of the Automatic Digital Surface Model from Digital Aerial Camera and from Lidar Point Clouds Data

Assessment of the Automatic Digital Surface Model from Digital Aerial Camera and from Lidar Point Clouds Data

Analysis of Geometric and Spatial Image Quality of KOMPSAT-3A Imagery in Comparison with KOMPSAT-3 Imagery

This study investigates the geometric and spatial image quality analysis of KOMPSAT-3A stereo pair. KOMPSAT-3A is, the latest satellite of KOMPSAT family, a Korean earth observation satellite operating in optical bands. A KOMPSAT-3A stereo pair was taken on 23 November, 2015 with 0.55 m ground sampling distance over Terrassa area of Spain. The convergence angle of KOMPSAT-3A stereo pair was estimated as 58.68˚. The investigation was assessed through the evaluation of the geopositioning analysis, image quality estimation and the accuracy of automatic Digital Surface Model (DSM) generation and compared with those of KOMPSAT-3 stereo pair with the convergence angle of 44.80˚ over the same area. First, geopositioning accuracy was tested with initial rational polynomial coefficients (RPCs) and after compensating the biases of the initial RPCs by manually collected ground control points. Then, regarding image quality, relative edge response was estimated for manually selected points visible from two stereo pairs. Both of the initial and biascompensated positioning accuracy and the quality assessment result expressed that KOMPSAT-3A images showed higher performance than those of KOMPSAT-3 images. Finally, the accuracy of DSMs generated from KOMPSAT-3A and KOMPSAT-3 stereo pairs were examined with respect to the reference LiDAR-derived DSM. The various DSMs were generated over the whole coverage of individual stereo pairs with different grid spacing and over three types of terrain; flat, mountainous and urban area. Root mean square errors of DSM from KOMPSAT-3A pair were larger than those for KOMPSAT-3. This seems due to larger convergence angle of the KOMPSAT-3A stereo pair.

Open source tool for DSMs generation from high resolution optical satellite imagery: development and testing of an OSSIM plug-in

ABSTRACTThe fully automatic generation of digital surface models (DSMs) is still an open research issue. From recent years, computer vision algorithms have been introduced in photogrammetry in order to exploit their capabilities and efficiency in three-dimensional modelling. In this article, a new tool for fully automatic DSMs generation from high resolution satellite optical imagery is presented. In particular, a new iterative approach in order to obtain the quasi-epipolar images from the original stereopairs has been defined and deployed. This approach is implemented in a new Free and Open Source Software (FOSS) named Digital Automatic Terrain Extractor (DATE) developed at the Geodesy and Geomatics Division, University of Rome ‘La Sapienza’, and conceived as an Open Source Software Image Map (OSSIM) plug-in. DATE key features include: the epipolarity achievement in the object space, thanks to the images ground projection (Ground quasi-Epipolar Imagery (GrEI)) and the coarse-to-fine pyramidal scheme adopted; the use of computer vision algorithms in order to improve the processing efficiency and make the DSMs generation process fully automatic; the free and open source aspect of the developed code. The implemented plug-in was validated through two optical datasets, GeoEye-1 and the newest Pléiades-high resolution (HR) imagery, on Trento (Northern Italy) test site. The DSMs, generated on the basis of the metadata rational polynomial coefficients only, without any ground control point, are compared to a reference lidar in areas with different land use/land cover and morphology. The results obtained thanks to the developed workflow are good in terms of statistical parameters (root mean square error around 5 m for GeoEye-1 and around 4 m for Pléiades-HR imagery) and comparable with the results obtained through different software by other authors on the same test site, whereas in terms of efficiency DATE outperforms most of the available commercial software. These first achievements indicate good potential for the developed plug-in, which in a very near future will be also upgraded for synthetic aperture radar and tri-stereo optical imagery processing.

UPGRADE OF FOSS DATE PLUG-IN: IMPLEMENTATION OF A NEW RADARGRAMMETRIC DSM GENERATION CAPABILITY

Abstract. Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome “La Sapienza”, and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery.

UPGRADE OF FOSS DATE PLUG-IN: IMPLEMENTATION OF A NEW RADARGRAMMETRIC DSM GENERATION CAPABILITY

Synthetic Aperture Radar (SAR) satellite systems may give important contribution in terms of Digital Surface Models (DSMs) generation considering their complete independence from logistic constraints on the ground and weather conditions. In recent years, the new availability of very high resolution SAR data (up to 20 cm Ground Sample Distance) gave a new impulse to radargrammetry and allowed new applications and developments. Besides, to date, among the software aimed to radargrammetric applications only few show as free and open source. It is in this context that it has been decided to widen DATE (Digital Automatic Terrain Extractor) plug-in capabilities and additionally include the possibility to use SAR imagery for DSM stereo reconstruction (i.e. radargrammetry), besides to the optical workflow already developed. <br><br> DATE is a Free and Open Source Software (FOSS) developed at the Geodesy and Geomatics Division, University of Rome “La Sapienza”, and conceived as an OSSIM (Open Source Software Image Map) plug-in. It has been developed starting from May 2014 in the framework of 2014 Google Summer of Code, having as early purpose a fully automatic DSMs generation from high resolution optical satellite imagery acquired by the most common sensors. <br><br> Here, the results achieved through this new capability applied to two stacks (one ascending and one descending) of three TerraSAR-X images each, acquired over Trento (Northern Italy) testfield, are presented. Global accuracies achieved are around 6 metres. These first results are promising and further analysis are expected for a more complete assessment of DATE application to SAR imagery.

GIS-Based Estimation of Potential Solar Energy on Flat Roofs in Maadi, Cairo, using True Ortho World View Image and Digital Surface Model

This research is concerned with the use of remotely sensed data in the estimation of the solar energy potentiality of the flat roofs in El Maadi District, Cairo. A solar radiation model was applied using a digital surface model (DSM) generated from two Worldview stereo satellite images using the digital photogrammetric workstation (Leica Photogrammetric Suite) LPS. The procedures included applying orientation with Rational Polynomial Coefficients (RPC) with and without GCPs, tie point measurements, aerial triangulation, automatic DSM and editing, true ortho-rectification. The accuracy of the DSM has been assessed and reported for both methods. The ortho-rectification, of stereo satellite images has been performed. A PAN true ortho-images with 0.5 m resolution resulted from applying orientation with rational polynomial coefficients (RPCs) refined with four accurate differential ground control points (DGCPs) and a high accurate DSM derived from stereo images were generated. Two classification methods were conducted (SVM and ANN) on the true ortho-image. First method without utilizing texture, the second utilizing texture features of Grey Level Co-occurrence Matrix (GLCM) as inputs. The SVM of the ortho-image and texture features overall accuracy was 93.4%, kappa coefficient was 0.92 and ANN of ortho-image and texture features overall accuracy of 91.2% and kappa coefficient was 0.90. Using the generated DSM as input, the area solar radiation model in ESRI ArcGIS was run. The model resulted in an annual total radiation grid for year 2015 which was converted to average daily radiation in kilowatt hour/square meters per day. A sample of 265 buildings footprints was extracted from the classification and used for the estimation. Assuming that 50% roof areas are available for solar Photovoltaic (PV), 12% PV grid conversion efficiency and 0.6 performance ratio and using ESRI zonal statistics tool, the technical potentiality for solar PV electricity generation for the sample buildings was calculated, classified into five classes and mapped.

Automatic digital surface model generation from Pléiades stereo images

We propose a fully automated stereo pipeline for producing digital elevation models from Pléiades satellite images. The agility of the Pléiades satellites allows them to capture multiple views of the same target in a single pass, enabling new applications that exploit these quasi-simultaneous high-resolution images. Concretely the tri-stereo acquisition modality permits to reduce the occlusions and to cross-validate the observed points. This paper gives an overview of our pipeline, named s2p, and presents some digital elevation models and 3D point clouds built from Pléiades tri-stereo datasets. The data was provided by Airbus DS and the CNES through the RTU program. The particularity of the s2p algorithm is that it permits to use conventional stereo correlation tools, by performing a very precise image rectification of each stereo pair. Although the acquisition system does not fit the pinhole camera model, which is necessary to make the rectification possible, the errors due to the pinhole assumption were shown to be negligible for small enough image sizes. Thus, the whole image can be treated by cutting it into small tiles that are processed independently.

Radiometric and geometric evaluation of GeoEye-1, WorldView-2 and Pléiades-1A stereo images for 3D information extraction

Today the use of spaceborne Very High Resolution (VHR) optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM) unit of the Bruno Kessler Foundation (FBK) in Trento (Italy) has collected VHR satellite imagery, as well as aerial and terrestrial data over Trento for creating a complete testfield for investigations on image radiometry, geometric accuracy, automatic digital surface model (DSM) generation, 2D/3D feature extraction, city modelling and data fusion. This paper addresses the radiometric and the geometric aspects of the VHR spaceborne imagery included in the Trento testfield and their potential for 3D information extraction. The dataset consist of two stereo-pairs acquired by WorldView-2 and by GeoEye-1 in panchromatic and multispectral mode, and a triplet from Pléiades-1A. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project, dataset characteristics and achieved results.

REGION BASED FOREST CHANGE DETECTION FROM CARTOSAT-1 STEREO IMAGERY

Abstract. Tree height is a fundamental parameter for describing the forest situation and changes. The latest development of automatic Digital Surface Model (DSM) generation techniques allows new approaches of forest change detection from satellite stereo imagery. This paper shows how DSMs can support the change detection in forest area. A novel region based forest change detection method is proposed using single-channel CARTOSAT-1 stereo imagery. In the first step, DSMs from two dates are generated based on automatic matching technology. After co-registration and normalising by using LiDAR data, the mean-shift segmentation is applied to the original pan images, and the images of both dates are classified to forest and non-forest areas by analysing their histograms and height differences. In the second step, a rough forest change detection map is generated based on the comparison of the two forest map. Then the GLCM texture from the nDSM and the Cartosat-1 images of the resulting regions are analyzed and compared, the real changes are extracted by SVM based classification.

TESTFIELD TRENTO: GEOMETRIC EVALUATION OF VERY HIGH RESOLUTION SATELLITE IMAGERY

Abstract. Today the use of spaceborne Very High Spatial Resolution (VHSR) optical sensors for automatic 3D information extraction is increasing in the scientific and civil communities. The 3D Optical Metrology (3DOM) Unit of the Bruno Kessler Foundation (FBK) in Trento (Italy) has collected stereo VHSR satellite imagery, as well as aerial and terrestrial data over Trento, with the aim to create a complete data collection with state-of-the-art datasets for investigations on image analysis, automatic digital surface model (DSM) generation, 2D/3D feature extraction, city modelling and data fusion. The testfield region covers the city of Trento, characterised by very dense urban (historical centre), residential and industrial areas, and the surrounding hills and steep mountains (approximate height range 200-2100 m) with cultivations, forests and bare soil. This paper reports the analysis conducted in FBK on the VHSR spaceborne imagery of Trento testfield for 3D information extraction. The data include two stereo-pairs acquired by WorldView-2 in August 2010 and by GeoEye-1 in September 2011 in panchromatic and multispectral mode, together with their original Rational Polynomial Coefficients (RPC), and the position and description of well distributed ground points. For reference and validation, a DSM from airborne LiDAR acquisition is used. The paper gives details on the project and the dataset characteristics. The results achieved by 3DOM on DSM extraction from WorldView-2 and GeoEye-1 stereo-pairs are shown and commented.

Comparison of Automatic DSM Generation Modules by Processing IKONOS Stereo Data of an Urban Area

This study deals with the evaluation of four different image-processing software modules for the generation of digital surface models from very high-resolution stereo satellite data. The analysis was done in an urban area due to the growing interest in 3-D information over built-up areas. Depending on the different geometric model approaches used by the different software packages, shifts between 3.06-3.27 m between the digital surface models (DSMs) and the reference DSM were measured. The vertical RMSE of the four tested software packages range between 2.96-14.01 m. However, the visual evaluation resulted in a different ranking and does not confirm the quantitative results entirely. The results show that, depending on the building type to be extracted, the choice of software package may vary. The challenges of automatic DSM extraction in urban areas and the performance of current software package modules to address them are discussed. Potential improvements for automatic DSM extraction in urban areas are identified.

Analysis of Cartosat‐1 images regarding image quality, 3D point measurement and DSM generation

AbstractThe Institute of Geodesy and Photogrammetry (IGP) at ETH Zurich is participating in the Cartosat‐1 evaluation programme, a common initiative of ISRO (India) and ISPRS. Within this programme various test sites with reference data have been established and Cartosat‐1 images have been acquired over these sites. Here, investigations at the Rome (Italy) and Maussane‐les‐Alpilles (France) test sites are reported. First, radiometric problems encountered with the images and pre‐processing for their improvement are reported. Examples are shown, together with pre‐processing methods that can be employed in order to improve image quality, aimed especially at automatic generation of a digital surface model (DSM) with fewer blunders and more matched points. Then, georeferencing is discussed and the 3D point measurement accuracy that can be achieved is introduced, as well as problems encountered with the rational polynomial coefficients (RPCs). The georeferencing results were produced using various options regarding image pre‐processing, the mathematical model used for georeferencing, the number and distribution of ground control points (GCPs) and the GCP image mensuration methods. The best results led to a planimetric and height accuracy (RMSE) of about 1·3 m. Use of an affine transformation after the RPCs, with about six well‐distributed GCPs transferred with matching to the second image, is suggested. Finally, the results of automatic DSM generation using the SAT‐PP program package developed at the IGP are presented. Various DSMs were generated with 10 m grid spacing. The results were checked visually and were also compared to the reference data provided. In the best case, the accuracy achieved is about 2·7 m without any manual editing, in spite of a 3‐year difference between the matching and reference DSMs. Although some aspects regarding image quality and RPC generation could be improved, Cartosat‐1 is a useful sensor for mapping and especially for the generation of DSMs. However, owing to its poor absolute geolocation accuracy, Cartosat‐1 cannot be used for the generation of a global DSM without GCPs.