ID: 54066
Title: Automatic detection of residential buildings using LiDAR data and multispectral imagery
Author: Mohammad Awrangjeb, Mehdi Ravanbakhsh, Clive S. Fraser
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 5, September 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Building detection, LiDAR, Point cloud, Multispectral imagery, Fusion
Abstract: This paper presents an automatic building detection technique using LIDAR data and multispectral imagery. Two masks are obtained from the LIDAR data: a ' primary building mask ' and a ' secondary building mask ' . The primary building mask indicates the void areas where the laser does not reach below a certain height threshold. The secondary building mask indicates the filled area, from where the laser reflects, above the same threshold. Line segments are extracted from around the void areas in the primary building mask. Line segments around trees are removed using the nomalized difference vegetation index derived from teh orthorectified multispectral images. The initial building positions are obtained based on the remaining line segments. The complete buildings are detected from their initial positions using the two masks and multispectral images in the YIQ colour system. It is experimentally shown that the proposed technique can successfully detect urban residual buildings, when assessed in terms of 15 indices including completeness, correctness and quality.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54065
Title: A unified approach to self-calibration of terrestrial laser scanners
Author: Yuriy Reshetyuk
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 5, September 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Terrestrial laser scanning, Calibration, Correlation
Abstract: In recent years, the method of self-calibration widely used in photogrammetry has been found suitable for the estimation of systematic errors in terrestrial laser scanners. Since high correlations can be present between the estimated parameters, ways to reduce them have to be found. This paper presents a unified approach to self-calibration of terrestrial laser scanners, where the parameters in a least-squares adjustment are treated as observations by assigning apporpriate weights to them. The higher these weights are the lower the parameter correlations are expceted to be. Self-calibration of a pulsed laser scanner Leica Scan Station was performed with the unified approach. The scanner position and orientation were determined during the measurements with the help of a total station, and the point clouds were directly georeferenced. The significant systematic errors were zero error in the laser rangefinder and vertical circle index error. Most parameter correlations were comparatively low. In part, precise knowledge of the hortizontal coordinates of the scanner centre helped greatly to achieve low correlation between these parameters and the zero error. The approach was shown to be advantageous to the use of adjustment with stochastic (weighted) inner constraints where the parameter correlations were higher. At the same time, the collimation error could not be estimated reliably due to its high correlation with the scanner azimuth because of a limited vertical distribution of the targets in the calibration field. While this problem can be solved for a scanner with a nearly spherical field-of-view, it will complicate the calibration of scanners with limited vertical field-of-view. Investigations into the influence of precision of the scanner position and levelling on the adjustment results lead to two important findings. First, it is not necesary to level the scanner during the measurements when using the unified approach since the parameter correlations are relatively low anyway. Second, the scanner position has to be known with a precision of about 1 mm in order to get a reliable estimate of the zero error.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54064
Title: Photogrammetric modeling of underwater environments
Author: Gili Telem, Sagi Filin
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 5, September 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Underwater photogrammetry, Close-range, Calibration, Estimation
Abstract: Underwater photogrammetry provides an efficient nondestructive means for measurement in environments with limited accessibilit. With the growing use of consumer cameras, its application is becoming easier, thus benefiting a wide variety of disciplines. However, utilizing cameras for underwater photogrammetry poses some nontrivial modeling problems due to refraction effect and the extension of the imaging system into a unit of both the camera and the protecting housing device. This paper studied the effect that the underwater environment has on the photogrammetric process, and proposes a model for describing the geometric distorations and for estimating the additional parameters involved. The proposed model accounts not only for the multimedia effect, but also for inaccuracies related to the setting of the camera and housing device. The paper shows that only a small number of additional parameters is needed to model both elements and to preserve the collinearity relation. The results show that no unique setup is needed for estimating the additional parameters and that the estimation is insensitive to noise or first approximations. Experiments show that high levels of accuracy can be achieved.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54063
Title: Backscatter coefficient as an attribute for the classification of full-waveform airborne laser scanning data in urban areas
Author: Cici Alexander, Kevin Tansey, Jorg Kaduk, David Holland, Nicholas J. Tate
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 5, September 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: LIDAR, Laser scanning, Calibration, Point cloud, Classification, Comparison
Abstract: Airborne laser scanning (ALS) data are increasingly being used for land cover classification. The amplitudes of echoes from targets, available from full-waveform ALS data, have been found to be useful in the classification of land cover. However, the amplitude of an echo is dependent on various factors such as the range and incidence angle, which makes it difficult to develop a classification method which can be applied to full-waveform ALS data from different sites, scanning geometrices and sensors. Additional information available from full-waveform ALS data, such as range and echo width, can be used for radiometric calibration, and to derive backscatter cross section. The backscatter cross section of a target is the physical cross sectional area of an idealised isotropic target, which has the same intensity as the selected target. The backscatter coefficient is the backscatter cross section per unit area. In this study, the amplitude, backscatter cross section and backscatter coefficient of echoes from ALS point cloud data collected from two different sites are analysed based on urban land cover classes. The application of decision tree classifiers developed using data from the first study area on the second demonstrates the advantage of using the backscatter coefficient in classification methods, along with spatial attributes. It is shown that the accuracy of classification of the second study area using the backscatter coefficient (kappa coefficient 0.89) is higher than those using the amplitude (kappa coefficient 0.67) or backscatter cross section (kappa coefficient 0.68). This attribute is especially useful for separating road and grass.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54062
Title: Radiometric stability assessment of an airborne photogrammetric sensor in a test field
Author: Lauri Markelin, Eija Honkavaara, Teemu Hakala, Juha Suomalainen, Jouni Peltoniemi
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Radiometric calibration, Quality, Test field, Stability, Aerial images
Abstract: Radiometric stability is a desired property of digital photogrammetric large-format sensors. This article presents a methodology for determining the radiometric stability of airborne imaging sensors in operational conditions in a test field and the results of stability evaluation of a large-format photogrammetric frame sensor DMC, from Intergraph. The imagery was collected in two days using nine different exposure settings, and images collected with variable exposure time and aperture were compared. The results showed promising stability in many cases, up to a level of 2% of the radiance, but less favorable results also appeared. Possible reasons for the unfavorable results could be the limitations of the experimental set-up or the instability of the sensor. DMC showed high radiometric performance potential, but high sensitivity to the exposure settings. Based on the results, recommendations for the future test field calibration and validation procedures were given. One limitation of the analysis was the insufficient information about the sensor stability potential; proposals were given to sensor manufacturers concerning the necessary information.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54061
Title: Knowledge-based building reconstruction from terrestrial video sequences
Author: Yixiang Tian, Markus Gerke, George Vosselman, Qing Zhu
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Facade, Reconstruction, Knowledge, Image sequence
Abstract: The paper presents an automatic method for the reconstruction of building models from video image sequences. These videos may be recorded using a hand-held camera or a camera mounted on a moving car. Such terrestrial video sequences are economic and flexible. Presenting buildings as geometric models -rather than for instance a representation from a single meshing of 3D points-enables one to perform a wide range of analyses. However, sparse 3D points and 3D edges do not contain topological relations. Therefore, integrating building structure knowledge into the reconstruction steps plays an important role in our method. First, some rules are applied to reasonably group the extracted features. Then, a suitable outline and normal direction are specified for each surface patch. Based on these surface patches, a hybrid model- and data-driven method is used to recover a building model from both the extracted surface patches and hypothesized parts. Using the building structure knowledge leads to a simple and fast reconstruction method, and also enables one to obtain the main structures of buildings. The results show that this method correctly sets up topological relationships between generated surface patches and also obtains reasonable structure models in occluded areas. Therefore, the reconstructed models satisfy requirements for both visualization and analysis.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54060
Title: Generation of three-dimensional deformation maps from InSAR data using spectral diversity techniques
Author: E. Erten, A Reigber, O. Hellwich
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Spectral diversity, DInSAR, 3D deformation analysis, Weighted least squares
Abstract: The capability of DInSAR (Differential Interferometric SAR) for precise large-scale deformation analysis has been shown in various case studies. Generally, DInSAR possesses a high potential for monitoring deformation, but only the velocity component parallel to the line-of-sight direction can be measured. An alternative approach, capable to retrieve the deformation velocity in both range and azimuth direction, is the so-called spectral diversity technique. Spectral diversity is based on a phase comparison between different sub-aperture interferograms of the scene and can generally be regarded as a high-performance technique for estimating the mis-registration between complex SAR images.
In this paper, the following questions will be discussed: how to implement the spectral diversity technique for achieving the most accurate results; how to extract the full 3D deformation vector from a combination of ascending /descending passes and how to extract a surface deformation map if the data sets are not perfectly coherent. Finally, a statistical analysis of every individual processing step and an error propagation anlaysis is undertaken. In order to make a quantitative analysis of the technique, ENVISAT data sets of the Bam earthquake in Iran are used.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54059
Title: Early-season crop area estimates for winter crops in NE Australia using MODIS satellite imagery
Author: A.B.Potgieter, A. Apan, G. Hammer, P. Dunn
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Early-season, Crop area estimates, Simple metric, Multi-temporal, Shire-scale
Abstract: To data, industry and crop forecasters have had a good idea of the potential crop yield for a specific season, but early-season information on crop area for a shire or region has been mostly unavailable. The question of " how early and with what accuracy?" area estimates can be determined using multi-temporal Moderate Resolution Imaging Spectroradiometer (MODIS) enhanced vegetation index (EVI) imagery was investigated in this paper. The study was conducted for two shires in Queensland, Australia for the 2003 and 2004 seasons, and focused on deriving total winter crop area estimates (including wheat, barley and chickpea). A simple metric (?E), which measures the green-up rate of the crop canopy, was derived. Using the unsupervised k-means classification algorithm, the accumulated difference of two consecutive images (one month apart) for three EVI threshold cut-offs (?Ei, where i = 250,500 and 750) at monthly intervals from April to October was calculated. July showed the highest pixel accuracy with percent correctly classified for all thresholds of 94% and 98% for 2003 and 2004, respectively. The differences in accuracy between the three cut-offs were minimal and the T500 threshold was selected as the preferred cut-off to avoid measuring too small or too large fluctuations in the differential EVI values. When compared to the aggregated shire data (surveyed) on crop area across shires and seasons, average percent differences for the ?ET500 for July and August ranged from -19% to 9%. To capture most of the variability in green-up within a region, the average ?ET500 for July and August was used for the early-season prediction of total winter crop area estimates. This resulted in high accuracy (R2=0.96; RMSE=3157 ha) for predicting the total winter crop from 2000 to 2004 across both shires. This result indicated that this simple multi-temporal remote sensing approach could be used with confidence in early-season crop area prediction at least one to two months ahead of anthesis.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54058
Title: Range and AGC normalization in airborne discrete-return LiDAR intensity data for forest canopies
Author: Iikka Korpela, Hans Ole Orka, Juha Hyyppa, Ville Heikkinen, Timo Tokola
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Vegetation, Forestry, Radiometry, Laser scanning, Classification
Abstract: Recently, the intensity characteristics of discrete-return LiDAR sensors were studied for vegetation classification. We examined two normalization precedure affecting LiDAR intensity through the scanning geometry and the system settings, namely, range normalization and the effects of the automatic gain control (AGC) in the Optech ALTM3100 and Leica ALS50-II sensors. Range normalization corresponds to weighting of the observed intensities with the term (R/RRef)a , where R is the range, RRef is a mean reference range, and a ? [2,4] is the exponent that is, according to theory, dependent on the target geometry. LiDAR points belonging to individual tree crowns were extracted for 13 887 trees in southern Finland. The coefficient of variation (CV) of the intensity was analyzed for a range of values of exponent a. The tree species classification performance using 13 intensity variables was also used for sensitivity analysis of the effect of a. The results were in line with the established theory, since the optimal level of a was lower (a?2) for trees with large or clumped leaves and higher (a?3) for diffuse coniferous crowns. Different echo groups also showed varying responses. Single-return pulses that represented strong reflections had a lower optimal value of a than the first and all echoes in a pulse. The gain in classification accuracy from the optimal selection of the exponent was 2%-3%, and the optimum for classification was different from that obtained using the CV analysis. In the ALS50-II sensor, the combined and optimized AGC and R normalizations had a notably larger effect (6%-9%) on classification accuracy. Our study demonstrates the ambiguity of R normalization in vegetation canopies.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54057
Title: An integrated bundle adjustment approach to range camera geometric self-calibration
Author: Derek D. Lichti, Changjae Kim, Sonam Jamtsho
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Range camera, Calibration, Error, Modelling, Correlation
Abstract: This paper describes a new method for integrated range camera system self-calibration in which both traditional camera calibration parameters and rangefinder systematic error parameters are estimated simultaneously in a free-network bundle adjustment of observations to signalised targets. Its mathematical basis is collinearity and range observation equations augmented with correction models for systematic error sources identified in the data. The self-calibration results from datasets captured with two different range cameras, a SwissRanger SR 3000 and a SwissRanger SR 4000, are presented and analysed in detail. The method ' s effectiveness is demonstrated in terms of systematic error removal and independent accuracy assessment. Up to a 54% reduction in the residual RMS was achieved by inclusion of the proposed error models in the self-calibration adjustment. An improvement of at least 74% in the RMS of object point co-ordinate differences, over that achieved without calibration or provided by the manufacturer ' s software ( in the case of the SR 3000), was realised in an independent accuracy assessment . In addition, the effects of several influencing variables, including the range stochastic error model, the network geometry and the range measurements themselves, on key correlation mechanisms are analysed in detail.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54056
Title: 3D road marking reconstruction from street-level calibrated stereo pairs
Author: Bahman Soheillian, Nicolas Paparoditis, Didier Boldo
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Photogrammetric computer vision, Mobile mapping system, Edge matching, Shape from stereo,3D road marking extraction
Abstract: This paper presents an automatic approach to road marking reconstruction using stereo pairs acquired by a mobile mapping system in a dense urban area. Two types of road markings were studied: zebra crossings (crosswalks) and dashed lines. These two types of road markings consist of strips having known shape and size. These geometric specifications are used to constrain the recognition of strips. In both cases (i.e. zebra crossings and dashed lines), the reconstruction method consists of three main steps. The first step extracts edge points from the left and right images of a stereo pair and computes 3D linked edges using a matching process. The second step comprises a filtering process that uses the known geometric specifications of road marking objects. The goal is to preserve linked edges that can plausibly belong to road markings and to filter others out. The final step uses the remaining linked edges to fit a theoretical model to the data. The method developed has been used for processing a large number of images. Road markings are successfully and precisely reconstructed in dense urban areas under real traffic conditions.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54055
Title: Expanding global mapping of the foliage clumping index with multi-angular POLDER three measurements: Evaluation and topographic compensation
Author: Jan Pisek, Jing M. Chen, Roselyne Lacaze, Oliver Sonnentag, Krista Alikas
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Multi-angle remote sensing, Vegetation clumping index, POLDER, BRDF
Abstract: The clumping index measures the spatial aggregation (clumped, random and regular) of foliage elements. The global mapping of the clumping index with a limited eight-month multi-angular POLDER 1 dataset is expanded by integrating new, complete year-round observations from POLDER 3. We show that terrain-induced shadows can enhance bi-directional reflectance distribution function variation and negatively bias the clumping index (i.e. indicating more vegetation clumping) in rugged terrain. Using a global high-resolution digital elevation model, a topographic compensation function is devised to correct for this terrain effect. The clumping index reductions can reach up to 30% from the topographically non-compensated values, depending on terrain complexity and land cover type. The new global clumping index map is compared with an assembled set field measurements from 32 different sites, covering four continents and diverse biomass.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54054
Title: Modeling and querying approximate direction relations
Author: Shihong Du, Luo Guo
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Geographical information system, Direction relations, Uncertain regions, Spatial data query
Abstract: Existing models of direction relations are mainly designed to handle crisp regions. To accommodate uncertain spatial data, it is necessary to investigate the formalization, uncertain semantics, and composition operators for uncertain direction relations. In this study, direction relations about uncertain regions, i.e., approximate direction relations, are modeled as the combinations of four crisp direction relations. The approximate relations can be interpreted from two aspects: the lower part (only including crisp relations about uncertain region) and the uncertain part (the uncertain directions about uncertain regions). The uncertain semantics of uncertain directions are formalized, such as possibly north, possibly south, possibly southeast, etc. Both crisp and uncertain parts are used to simplify and handle the composition and the query of uncertain direction relations. Approximate direction relations are helpful to model directions concerned with both crisp and uncertain regions; they therefore can play important roles in handling uncertain data (in our case, querying uncertain data).
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54053
Title: An efficient stochastic approach for building foot print extraction from digital elevation models
Author: O. Tournaire, M. Bredif, D. Boldo, M. Durupt
Editor: George Vosselman
Year: 2010
Publisher: Elsevier, Vol 65, Issue 4, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote Sensing
Keywords: Digital Elevation Model, Building footprint, Energetic modeling, Marked point processes, RJMCMC
Abstract: In the past two decades, building detection and reconstruction from remotely sensed data has been an active research topic in the photogrammetric and remote sensing communities. Recently, effective high level approaches have been developed, i.e., the ones involving the minimization of an energetic formulation. Yet, their efficiency has to be balanced by the amount of processing power required to obtain good results.
In this paper, we introduce an original energetic model for building footprint extraction from high resolution digital elevation models (< 1 m) in urban areas. Our goal is to formulate the energy in an efficient way, easy to parametrize and fast to compute, in order to get an effective process still providing good results.
Our work is based on stochastic geometry, and in particular on marked point processes of rectangles. We therefore try to obtain a reliable object configuration described by a collection of rectangular building footprints. To do so, an energy function made up of two terms is defined: the first term measures the adequacy of the objects with respect to the data and the second one has the ability to favour or penalize some footprint configuration based on prior knowledge (alignment, overlapping...). To minimize the global energy, we use a Reversible Jump Monte Carlo Markov Chain (RJMCMC) sampler coupled with a simulated annealing algorithm, leading to an optimal configuration of objects. Various results from different areas and resolutions are presented and evaluated. Our work is also compared with an already existing methodology based on the same mathematical framework that uses a much more complex energy function. We show how we obtain similarly good results with a high computational efficiency (between 50 and 100 times faster) using a simplified energy that requires a single data-independent parameter, compared to more than 20 inter-related and hard-to-tune parameters.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 54052
Title: Strategy for Conservation of Sacred Groves
Author: None
Editor: C. Kunhikannan, B. Gurudev Singh
Year: 2005
Publisher: Institute of Forest Genetics and Tree Breeding,
Source: Centre for Ecological Sciences
Reference: None
Subject: Strategy for Conservation of Sacred Groves
Keywords: None
Abstract: None
Location: 109
Literature cited 1: None
Literature cited 2: None