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.

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IMPROVED TOPOGRAPHIC MODELS VIA CONCURRENT AIRBORNE LIDAR AND DENSE IMAGE MATCHING

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-2-w4-259-2017 ◽

2017 ◽

Vol IV-2/W4 ◽

pp. 259-266 ◽

Cited By ~ 7

Author(s):

G. Mandlburger ◽

K. Wenzel ◽

A. Spitzer ◽

N. Haala ◽

P. Glira ◽

...

Keyword(s):

Spatial Resolution ◽

Image Matching ◽

Point Cloud ◽

Laser Scanning ◽

Point Clouds ◽

Airborne Lidar ◽

Surface Model ◽

3D Point Clouds ◽

Dense Image ◽

Surface Models

Modern airborne sensors integrate laser scanners and digital cameras for capturing topographic data at high spatial resolution. The capability of penetrating vegetation through small openings in the foliage and the high ranging precision in the cm range have made airborne LiDAR the prime terrain acquisition technique. In the recent years dense image matching evolved rapidly and outperforms laser scanning meanwhile in terms of the achievable spatial resolution of the derived surface models. In our contribution we analyze the inherent properties and review the typical processing chains of both acquisition techniques. In addition, we present potential synergies of jointly processing image and laser data with emphasis on sensor orientation and point cloud fusion for digital surface model derivation. Test data were concurrently acquired with the <i>RIEGL</i> LMS-Q1560 sensor over the city of Melk, Austria, in January 2016 and served as basis for testing innovative processing strategies. We demonstrate that (i) systematic effects in the resulting scanned and matched 3D point clouds can be minimized based on a hybrid orientation procedure, (ii) systematic differences of the individual point clouds are observable at penetrable, vegetated surfaces due to the different measurement principles, and (iii) improved digital surface models can be derived combining the higher density of the matching point cloud and the higher reliability of LiDAR point clouds, especially in the narrow alleys and courtyards of the study site, a medieval city.

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APPLICATION OF DSM IN OBSTACLE CLEARANCE SURVEYING OF AERODROME

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xli-b2-227-2016 ◽

2016 ◽

Vol XLI-B2 ◽

pp. 227-233 ◽

Cited By ~ 1

Author(s):

X. Qiao ◽

S. H. Lv ◽

L. L. Li ◽

X. J. Zhou ◽

H. Y. Wang ◽

...

Keyword(s):

Digital Elevation Model ◽

Satellite Imagery ◽

Primary Objective ◽

Considerable Improvement ◽

Surface Model ◽

Digital Surface Model ◽

Horizontal Position ◽

Obstacle Clearance ◽

Digital Elevation ◽

Elevation Model

Compared to the wide use of digital elevation model (DEM), digital surface model (DSM) receives less attention because that it is composed by not only terrain surface, but also vegetations and man-made objects which are usually regarded as useless information. Nevertheless, these objects are useful for the identification of obstacles around an aerodrome. The primary objective of the study was to determine the applicability of DSM in obstacle clearance surveying of aerodrome. According to the requirements of obstacle clearance surveying at QT airport, aerial and satellite imagery were used to generate DSM, by means of photogrammetry, which was spatially analyzed with the hypothetical 3D obstacle limitation surfaces (OLS) to identify the potential obstacles. Field surveying was then carried out to retrieve the accurate horizontal position and height of the obstacles. The results proved that the application of DSM could make considerable improvement in the efficiency of obstacle clearance surveying of aerodrome.

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Assessment of Changes in a Viewshed in the Western Carpathians Landscape as a Result of Reforestation

Land ◽

10.3390/land9110430 ◽

2020 ◽

Vol 9 (11) ◽

pp. 430

Author(s):

Michał Sobala ◽

Urszula Myga-Piątek ◽

Bartłomiej Szypuła

Keyword(s):

Digital Elevation Model ◽

Forest Succession ◽

Western Carpathians ◽

Surface Model ◽

Digital Surface Model ◽

Mountainous Areas ◽

Viewshed Analysis ◽

Digital Elevation ◽

Elevation Model ◽

The Impact

A viewshed analysis is of great importance in mountainous areas characterized by high landscape values. The aim of this research was to determine the impact of reforestation occurring on former pasturelands on changes in the viewshed, and to quantify changes in the surface of glades. We combine a horizontal and a vertical approach to landscape analysis. The changes in non-forest areas and the viewshed from viewpoints located in glades were calculated using historical cartographic materials and a more recent Digital Elevation Model and Digital Surface Model. An analysis was conducted using a Visibility tool in ArcGIS. The non-forest areas decreased in the period 1848–2015. The viewshed in the majority of viewpoints also decreased in the period 1848–2015. In the majority of cases, the maximal viewsheds were calculated in 1879/1885 and 1933 (43.8% of the analyzed cases), whereas the minimal ones were calculated in 2015 (almost 57.5% of analyzed cases). Changes in the viewshed range from 0.2 to 23.5 km2 with half the cases analyzed being no more than 1.4 km2. The results indicate that forest succession on abandoned glades does not always cause a decline in the viewshed. Deforestation in neighboring areas may be another factor that has an influence on the decline.

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Three-Dimensional Reconstruction of Structural Surface Model of Heritage Bridges Using UAV-Based Photogrammetric Point Clouds

Remote Sensing ◽

10.3390/rs11101204 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1204 ◽

Cited By ~ 17

Author(s):

Yue Pan ◽

Yiqing Dong ◽

Dalei Wang ◽

Airong Chen ◽

Zhen Ye

Keyword(s):

Classification Tree ◽

Three Dimensional ◽

Point Clouds ◽

3D Models ◽

Surface Model ◽

Reconstruction Method ◽

3D Point Clouds ◽

Surface Models ◽

Structural Surface ◽

Better Than

Three-dimensional (3D) digital technology is essential to the maintenance and monitoring of cultural heritage sites. In the field of bridge engineering, 3D models generated from point clouds of existing bridges is drawing increasing attention. Currently, the widespread use of the unmanned aerial vehicle (UAV) provides a practical solution for generating 3D point clouds as well as models, which can drastically reduce the manual effort and cost involved. In this study, we present a semi-automated framework for generating structural surface models of heritage bridges. To be specific, we propose to tackle this challenge via a novel top-down method for segmenting main bridge components, combined with rule-based classification, to produce labeled 3D models from UAV photogrammetric point clouds. The point clouds of the heritage bridge are generated from the captured UAV images through the structure-from-motion workflow. A segmentation method is developed based on the supervoxel structure and global graph optimization, which can effectively separate bridge components based on geometric features. Then, recognition by the use of a classification tree and bridge geometry is utilized to recognize different structural elements from the obtained segments. Finally, surface modeling is conducted to generate surface models of the recognized elements. Experiments using two bridges in China demonstrate the potential of the presented structural model reconstruction method using UAV photogrammetry and point cloud processing in 3D digital documentation of heritage bridges. By using given markers, the reconstruction error of point clouds can be as small as 0.4%. Moreover, the precision and recall of segmentation results using testing date are better than 0.8, and a recognition accuracy better than 0.8 is achieved.

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Can 3D Point Clouds Replace GCPs?

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-ii-5-347-2014 ◽

2014 ◽

Vol II-5 ◽

pp. 347-354 ◽

Cited By ~ 2

Author(s):

G. Stavropoulou ◽

G. Tzovla ◽

A. Georgopoulos

Keyword(s):

Point Cloud ◽

Laser Scanning ◽

Large Scale ◽

Point Clouds ◽

Field Work ◽

Surface Model ◽

Control Points ◽

3D Point Clouds ◽

Surface Models

Over the past decade, large-scale photogrammetric products have been extensively used for the geometric documentation of cultural heritage monuments, as they combine metric information with the qualities of an image document. Additionally, the rising technology of terrestrial laser scanning has enabled the easier and faster production of accurate digital surface models (DSM), which have in turn contributed to the documentation of heavily textured monuments. However, due to the required accuracy of control points, the photogrammetric methods are always applied in combination with surveying measurements and hence are dependent on them. Along this line of thought, this paper explores the possibility of limiting the surveying measurements and the field work necessary for the production of large-scale photogrammetric products and proposes an alternative method on the basis of which the necessary control points instead of being measured with surveying procedures are chosen from a dense and accurate point cloud. Using this point cloud also as a surface model, the only field work necessary is the scanning of the object and image acquisition, which need not be subject to strict planning. To evaluate the proposed method an algorithm and the complementary interface were produced that allow the parallel manipulation of 3D point clouds and images and through which single image procedures take place. The paper concludes by presenting the results of a case study in the ancient temple of Hephaestus in Athens and by providing a set of guidelines for implementing effectively the method.

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Development on Filtering Algorithms of Airborne LiDAR Point Clouds

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.226-228.1892 ◽

2012 ◽

Vol 226-228 ◽

pp. 1892-1898

Author(s):

Jian Qing Shi ◽

Ting Chen Jiang ◽

Ming Lian Jiao

Keyword(s):

Remote Sensing ◽

Laser Scanning ◽

Three Dimensional ◽

Point Clouds ◽

Airborne Lidar ◽

Filtering Algorithms ◽

Filtering Algorithm ◽

Digital Elevation ◽

City Model ◽

Elevation Model

Airborne LiDAR is a new kind of surveying technology of remote sensing which developed rapidly during recent years. Raw laser scanning point clouds data include terrain points, building points, vegetation points, outlier points, etc.. In order to generate digital elevation model (DEM) and three-dimensional city model,these point clouds data must be filtered. Mathematical morphology based filtering algorithm, slope based filtering algorithm, TIN based filtering algorithm, moving surface based filtering algorithm, scanning lines based filtering algorithm and so on several representative filtering algorithms for LiDAR point clouds data have been introduced and discussed and contrasted in this paper. Based on these algorithms summarize the studying progresss about the filtering algorithm of airborne LiDAR point clouds data in home and abroad. In the end, the paper gives an expectation which will provides a reference for the following relative study.

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Accuracy assessment of TanDEM-X IDEM using airborne LiDAR on the area of Poland

Geodesy and Cartography ◽

10.1515/geocart-2017-0007 ◽

2017 ◽

Vol 66 (1) ◽

pp. 137-148 ◽

Cited By ~ 3

Author(s):

Małgorzata Woroszkiewicz ◽

Ireneusz Ewiak ◽

Paulina Lulkowska

Keyword(s):

Digital Elevation Model ◽

Laser Scanning ◽

Accuracy Assessment ◽

Shuttle Radar Topography Mission ◽

Reference Points ◽

Airborne Lidar ◽

Surface Model ◽

Digital Elevation ◽

Elevation Model ◽

German Aerospace

Abstract The TerraSAR-X add-on for Digital Elevation Measurement (TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.

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Konversi DSM Menjadi DTM Menggunakan Filter Berbasis Kelerengan Untuk Pemetaan Genangan Banjir Rob Di Kecamatan Tirto

10.31219/osf.io/cu84m ◽

2020 ◽

Author(s):

Trida Ridho Fariz ◽

Nur Rokhayati

Keyword(s):

Digital Terrain Model ◽

Surface Model ◽

Digital Surface Model ◽

Model Data ◽

Alos Palsar ◽

Terrain Model ◽

Digital Terrain ◽

Digital Elevation ◽

Elevation Model ◽

Digital Elevation Model Data

Salah satu data penginderaan jauh yang penting adalah DEM (Digital Elevation Model). Data DEM memberikan informasi ketinggian suatu permukaan bumi dimana dikelompokkan menjadi 2 yaitu DSM (Digital Surface Model) yang menyajikan informasi ketinggian permukaan tutupan lahan dan DTM (Digital Terrain Model) yang menyajikan informasi ketinggian tanah. Pemetaan banjir rob secara umum menggunakan data DTM. Tetapi untuk mendapatkan data DTM sangatlah sulit. Salah satu data DEM yang tersedia secara gratis adalah data DEM terkoreksi hasil ekstraksi dari ALOS PALSAR yang memiliki resolusi spasial 12,5 meter, tidak terlalu bagus untuk digunakan sebagai data untuk pemetaan genangan banjir rob mengingat itu hanyalah DSM. Sedangkan menggunakan data titik ketinggian yang di interpolasi tidak terlalu merepresentatifkan kondisi ketinggian medan suatu wilayah kecuali jika jumlah titiknya banyak. Penelitian ini menggunakan metode slope based filtering untuk mengkonversi data DEM dari ALOS PALSAR menjadi DTM.Hasil dari metode ini dilakukan uji statistik berupa korelasi dengan data titik ketinggian dan mempunyai nilai korelasi yang sangat tinggi yaitu sebesar 0,80 dan nilai RMSE sebesar 1,402. Selanjutnya dibuat pemodalan spasial genangan banjir rob dari DTM. Hasil pemodelan spasial genanngan banjir rob kemudin diuji akurasi dengan uji statistik korelasi dan penghitungan RMSE dengan data hasil survey lapangan. Hasil pemodelan memiliki korelasi sebesar 0,78 dengan nilai RMSE tinggi genangan banjir rob sebesar 0,763. Yang berarti bahwa rata-rata selisih nilai ketinggian genangan banjir rob dari peta dan dilapangan adalah sebesar 0,763m. Wilayah genangan banjir rob meliputi Desa Jeruksari, Desa Tegaldowo, Desa Mulyorejo dan Desa Karangjompo.

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Automatic digital surface model generation from Pléiades stereo images

Revue Française de Photogrammétrie et de Télédétection ◽

10.52638/rfpt.2014.136 ◽

2014 ◽

pp. 137-142

Author(s):

Carlo De Franchis ◽

Enric Meinhardt-Llopis ◽

Julien Michel ◽

Jean-Michel Morel ◽

Gabriele Facciolo

Keyword(s):

Satellite Images ◽

Digital Elevation Models ◽

Point Clouds ◽

Surface Model ◽

Stereo Pair ◽

Camera Model ◽

3D Point Clouds ◽

Digital Elevation ◽

High Resolution Images ◽

New Applications

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.

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