ID: 52357
Title: Estimation of abundance and distribution of two moist tall grasses in the Watarase wetland, Japan, using hyperspectral imagery
Author: Shan Lu, Yo Shimizu, Jun Ishii, Syo Funakoshi, Izumi Washitani, Kenji Omasa
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Hyperspectral, Imagery, Estimation, Vegetation
Abstract: The dominant grasses in a wetland are of critical concern for the wetland ' s ecological integrity, because these species provide the habitats for many small plants and animals. In this study, we used hyperspectral imagery to map the distributions of two dominant tall grasses (Miscanthus sacchariflorus (Maxim) Benth and Phragmites australis (Cav) Trin. ex Stend) in the Watarase wetland, in central Japan. Stepwise multiple linear regression analysis was applied to the hyperspectral data to predict the shoot density and biomass of the two grasses. The independent data sets included original reflectance, band ratios, significant components identified by prinicpal components analysis (PCA), and significant components identified by decision boundary feature extraction (DBFE). The coefficient of determination (R2) and the root-mean-square error (RMSE) of model calibration and validation were used to evaluate the models. The significant DBFE components showed better ability at predicting shoot density of the two grasses than the other variables in the validating areas. The RMSE values were 7.40/m2 for M.sacchariflorus and 13.09/m2 for P.australis, which amounted to errors of around 10.0% and 12.6%, respectively, of the maximum shoot density measured during our surveys. All variables showed similar performance at predicting biomass, but the results were less accurate than those for shoot density. Considering the performance of the DBFE components for both shoot density and biomass prediction, we suggest that these are the best indicators for estimating the abundance of the two grasses.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52356
Title: Evaluating effects of spectral training data distribution on continuous field mapping performance
Author: L.Mathys, A.Guisan, T.W.Kellenberger, N.E.Zimmermann
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Continuous field, Generalised linear model, Spectral space, Mixed pixels
Abstract: Continuous field mapping has to address two conflicting remote sensing requirements when collecting training data. On one hand, continuous field mapping trains fractional land cover and thus favours mixed training pixels. On the other hand, the spectral signature has to be preferablly distinct and thus favours pure training pixels. The aim of this study was to evaluate the sensitivity of training data distribution along fractional and spectral gradients on the resulting mapping performance. We derived four continuous fields (tree, shrubherb, bare, water) from aerial photographs as response variables and processed corresponding spectral signatures from multitemporal Landsat 5 TM data as explanatory variables. Subsequent controlled experiments along fractional cover gradients were then based on generalised linear models. Resulting fractional and spectral distribution differed between single continuous fields, but could be satisfactorily trained and mapped. Pixels with fractional or without respective cover were much more critical than pure full cover pixels. Error distribution of continuous field models was non-uniform with respect to horizontal and vertical spatial distribution of target fields. We conclude that a sampling for continuous field training data should be based on extent and densities in the fractional and spectral, rather than the real spatial space. Consequently, adequate training plots are most probably not systematically distributed in the real spatial space, but cover the gradient and covariate structure of the fractional and spectral space well.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52355
Title: Geostatistical interpolation of SLC-off Landsat ETM+images
Author: M.J.Pringle, M.Schmidt, J.S. Muir
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Landsat, Vegetation, Monitoring, Spatial, Statistics
Abstract: The scan-line corrector (SLC) for the Enhanced Thematic Mapper Plus (ETM+) sensor, on board the Landsat 7 satellite, failed permanently in 2003. The consequence of the SLC failure (or SLC -off) is that about 20% of the pixels in an ETM+image are not scanned. We aim to develop a geostatistical method that estimates the missing values. Our rationale is to collect three cloud-free images for a particular Landsat scene, taken within a few weeks of each other: the middle image is the target whose un-scanned locations we wish to estimate; the earlier and later images are used as secondary information. We visit each un-scanned location in the target image and , for each reflectance band in turn, predict the missing value with cokriging (resorting to kriging when there is not enough local secondary information to justify cokriging). For three Landsat scenes in different bio-regions of Queensland, Australia, we compared the performance of geostatistical interpolation with image compositing. Geostatistics was a generally superior estimator. In contrast to composting, geostatistics was able to estimate accurately values at all un-scanned locations, and was able to quantify the variance associated with each prediction. SLC-off iamges interpolated with geostatistics were visually sensible, although changes in land-use from pixel to pixel affected adversely the accuracy of prediction. The primary disadvantage of geostatistics was its relatively slow computing speed. We recommend the geostatistical method over compositing, but, if speed take priority over statistical rigour, a hybrid technique- whereby composites are corrected to the local means and variances of the banes in the target image, and any un-estimable locations are interpolated geopstatistically-is an adequate compromise.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52354
Title: Generation and application of rules for quality dependent facade reconstruction
Author: Susanne Becker
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Architecture, Modelling, Interpretation, Building, Three-dimensional
Abstract: Frequently, terrestrial LiDAR and image data are used to extract high resolution building geometry like windows, doors and protrusions for three-dimensional (3D) facade reconstruction. However, such a purely data driven bottom-up modelling of facade structures is only feasible if the available observations meet considerable requirements on data quality. Errors in measurement, varying point densities, reduced accuracies, as well as incomplete coverage affect the achievable correctness and reliability of the reconstruction result. While dependence on data quality is a general disadvantage with data driven botton-up appraoches, model based top-down reconstructions are much more robust. Algorithms introduce knowledge about the appearance and arrangement of objects. Thus, they cope with data uncertainly and allow for a procedural modelling of building structures in a predefined architectural style, which is inherent in grammar or model descriptions.
We aim at a quality sensitive facade reconstruction which is on the one hand robust against erroneous and incomplete data, but on the other hand not subject to prespecified rules or models. For this purpose, we combine bottom-up and top-down strategies by integrating automatically inferred rules into a data driven reconstruction process. Facade models reconstructed during a bottom-up method serve as a knowledge base for further processing. Dominant or repetitive features and regularities as well as their hierarchical relationship are detected from the modelled facade elements and automatically translated into rules. These rules together with the 3D representations of the modelled facade elements constitute a formal grammar. It holds all th information which is necessary to reconstruct facades in the style of the given building. The paper demonstrates that the proposed algorithm is very flexible towards different data quality and incomplete sensor data. The inferred grammar is used for the verification of the facade model produced during the data driven reconstruction process and the generation of synthetic facades for which only partial or no sensor data is available. Moreover, knowledge propagation is not restricted to facades of one single building. Based on a small set of formal grammars derived from just a few observed buildings, facade reconstruction is also possible for whole districts featuring uniform architectural styles.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52353
Title: Improving radiometry of imaging spectrometers by using programmable spectral regions of interest
Author: Francesco Dell ' Endice, Jens Nieke, Benjamin Koetz, Michael E.Schaepaman, Klaus Itten
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Calibration, Algorithms, Pushbroom, Radiometric, Imaging spectrometer
Abstract: Programmable imaging spectrometers can be adjusted to fit specific application requirements that differ from the instrument initial spectral design goals. Sensor spectral characteristics and its signal-to-noise ratio (SNR) can be changed by applying customized online binning patterns. We present a software utility that generates application driven spectral binning patterns by using an SNR dependent sensor model. The utility, named BinGO (BInning patterN Generator and Optimiser), is used to produce predefined binning patterns that either (a) allow an existing imaging spectrometer to optimize its spectral characteristics for a specific application, (b) allow an existing imaging spectrometer to spectral and /or spatially emulate another instrument, or (c) design new multispectral or imaging spectrometer missions (i.e. spaceborne, airborne, terrestrial). We present a variety of BinGO case studies, including the simulation of airborne (APEX) [Itten, K.I.et al., 2008. APEX-The hyperspectral ESA Airborne Prism Experiment. Sensors 8(1), 1-25], spaceborne (SENTINEL III) [Nieke, J.,Frerick,J.,Stroede, J.,Mavrocordatos, C., Berruti, B.,2008. Status of the optical payload and processor development of ESA ' s Sentinel 3 mission. In: Proceedings of the Geoscience and Remote Sensing Symposium IGARSS 2008, pp. 427-430], as well as scientific and performance optimized approaches. We conclude that the presented appraoch can successfully be used to increase the efficiency of spectral information retrieval by using imaging spectroscopy data and to simulate various missions and requirements, finally supporting proper trade-off decisions to be made between performance optimization and scientific requirements. In addition, if specific sensor parameters are known, BinGO can also model other imaging spectrometers.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52352
Title: A geometric stochastic approach based on marked point processes for road mark detection from high resolution aerial images
Author: O.Tournaire, N. Paparoditis
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Road modelling, Aerial imagery, Road marks, Marked point process, RJMCMC
Abstract: Road detection has been a topic of great interest in the photogrammetric and remote sensing communities since the end of the 70s. Many approaches dealing with various sensor resolutions, the nature of the scene or the wished accuracy of the extracted objects have been presented. This topic remains challenging today as the need for accurate and up-to-date data is becoming more and more important. Based on this context, we will study in this paper the road network from a particular point of view, focusing on road marks, and in particular dashed lines. Indeed, they are very useful clues, for evidence of a road, but also for tasks of a higher level. For instance, they can be used to enhance quality and to improve raod databases. It is also possible to delineate the different circulation lanes, their width and functionality (speed limit, special lanes for buses or bicycles...). In this paper, we propose a new robust and accurate top-down appraoch for dashed line detection based on stochastic geometry. Our approach is automatic in the sense that no intervention from a human operator is necessary to initialise the algorithm or to track errors during the process. The core of our approach relies on defining geometric, radiometric and relational models for dashed lines objects. The model also has to deal with the interactions between the different objects making up a line, meaning that it introduces external knowledge taken from specifications. Our strategy is based on a stochastic method, and in particular marked point processes. Our goal is to find the objects configuration minimising an energy function made-up of a data attachment term measuring the consistency of the image with respect to the objects and a regularising term managing the relationship between neighbouring objects. To sample the energy function, we use Green algorithm ' s; coupled with a simulated annealing to find its minimum. Results from aerial images at various resolutions are presented showing that our approach is relevant and accurate as it can handle the most frequent layouts of dashed lines. Some issues, for instance, such as the relative weighting of both terms of the energy are also discussed in the conclusion.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52351
Title: Spectral discrimination of papyrus vegetation (Cyperus papyrus L) in swamp wetlands using field spectrometry
Author: Elhadi Adam, Onisimo Mutanga
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Papyrus, Greater St. Lucia Wetlands Park, Field spectrometer mesurements, CART, Jeffries-Matusita
Abstract: Techniques for mapping and monitoring wetland species are critical for their sustainable management. Papyrus (Cyperus papyrus L) is one of the most important species-rich habitats that characterize the Greater St. Lucia Wetlands Park (GSWP) in South Africa. This paper investigates whether papyrus could be discriminated from its co-existing species using ASD field spectrometer data ranging from 300 nm to 2500 nm, yielding a total of 2151 bands. Canopy spectral measurements from papyrus and three other species were collected in situ in the Greater St. Lucia Wetlands Park, South Africa. A new hierarchical method based on three integrated analysis levels was proposed and implemented to spectrally discriminated papyrus from other species as well as to reduce and subsequently select optimal bands for the potential discrimination of papyrus. In the first level of the analysis using ANOVA, we found that there were statistically significant differences in spectral reflectance between papyrus and other species on 412 wavelengths located in different portions of the electromagnetic spectrum. Using the selected 412 bands, we further investigated the use of classification and regression trees (CART) in the second level of analysis to identify the most sensitive bands for spectral discrimination. This analysis yielded eight bands which are considered to be practical for upscaling to airborne or space borne sensors for mapping papyrus vegetation. The final sensitivity analysis level involved the application of Jeffries-Matusita (JM) distance to assess the relative importance of the selected eight bands in discriminating papyrus from other species. The results indicate that the best discrimination of papyrus from its co-existing species is possible with six bands located in the red-edge and near-infrared regions of the electromagnetic spectrum. Overall, the study concluded that spectral reflectance of papyrus and its co-existing species is statistically different a promising result for the use of airborne and satellite sensors for mapping papyrus. The three-step hierarchial approach employed in this study could systematically reduce the dimensionality of bands to manageable levels, a move towards operational implementation with band specific sensors.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52350
Title: Analysis at medium scale of low-resolution DInSAR data in slow-moving landslide -affected areas
Author: Leonardo Cascini, Gianfranco Fornaro, Dario Peduto
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: DInSAR, Multipass DInSAR, Landslides, Visibility mapping, Natural hazards
Abstract: Landslide studies over large areas call for multidisciplinary analyses supported by accurate ground displacement measurements. At present, conventional techniques can be valuably complemented by innovative satellite techniques such as Differential SAR Interferometry (DInSAR), furnishing huge amounts of data at competitively affordable costs. This work investigates the remote sensed data potential in landslide studies starting from the awareness of the present constraints of the technique. To this end, with reference to a sample area-within the territory of the National Basin Authority of Liri-Garigliano and Volturno rivers (Central-Southern Italy)-for which detailed base and thematic maps are available, quantitative examples of DInSAR data coverage on both different land-uses and landslide-affected areas are shown. Then, an original tool for "a priori DInSAR landslide visibility zoning" is proposed to address the choice of the most suitable image datasets. Finally, referring to the visible zones, the outcomes of DInSAR data for checking/updating landslide inventory maps at 1:25,000 scale highlight appealing perspectives, also holding the promise of obtaining relevant information in the landslide hazard evaluation.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52349
Title: Change of spatial information under rescaling: A case study using multi- resolution image series
Author: Weirong Chen, Geoffrey M Henebry
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: High spatial resolution imagery, Semivariogram analysis, Spatial structure, Rescaling
Abstract: Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187m to 1m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low -pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52348
Title: The influence of topography on the forest surface temperature retrieved from Landsat TM, ETM + and ASTER thermal channels
Author: Martin Hais, Tomas Kucera
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Landsat, ASTER, Surface temperature, Topography, Spruce forest
Abstract: The objective of this study was to assess the influence of topography on the surface temperature (ST) of spruce forest in the central part of the Sumava Mountains, Czech Republic. The aim was to design a method for surface temperature normalisation of forest stands in rugged relief. In this study, two Landsat scenes, ETM + and TM, and one TERRA ASTER scene were used. The different spatial (60m- 90m-120m) and /or radiometric (8-12 bits) resolutions of these scenes enabled the assessment of the influence of these parameters on the accuracy of surface temperature models at the mesoscale landscape context. These models are based on the effects of complex topography (digital elevation model-DEM, and illumination - Hillshade) on surface temperature. Only homogeneous spruce forest stands were used for surface temperature modeling. The influence of topography on surface temperature in spruce forest was confirmed in all types of satellite data used. Three different sampling approaches were used to increase the accuracy of the models. Predictability increased with forest content in the thermal pixel (sampling approach 1). The resulting R2 values (0.47-0.49) were similar between all three scenes. Sampling approach 2 is based on the weighting of thermal pixels by the forest content (R2:0.32-0.39). We also assessed the influence of spruce forest edge effect on the accuracy of thermal models (sampling approach 3). Removing forest buffer zones resuted in greater statistical significance (approximately by 25%-40%). The optimal width of forest edge removed was determined to be 90m. The resulting explained variability (R2) improved by forest edge removal was 0.57, 0.52, 0.47 in the case of ETM +, ASTER and TM, respectively. These values correspond with te spatial resolution. However, the differences are not significant indicating that all these data are useful for ST modeling of spruce forest. The potential use of ST modeling is to identify temperature anomalies caused by different types of forest disturbance (e.g. harvesting, disease, insect attack) or changes in the condition of stands (e.g.water stress)
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52347
Title: Knowledge based reconstruction of building models from terrestrial laser scanning data
Author: Shi Pu, George Vosselman
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Building reconstruction, Terrestrial laser scanning, Feature extraction
Abstract: This paper presents an automatic method for reconstruction of building facade models from terrestrial laser scanning data. Important facade elements such as walls and roofs are distinguished as features. Knowledge about the features ' sizes, positions, orientations, and topology is then introduced to recognize these features in a segmented laser point cloud. An outline polygon of each feature is generated by least squares fitting, convex hull fitting or concave polygon fitting, according to the size of the feature. Knowledge is used again to hypothesise the occluded parts from the directly extracted feature polygons. Finally, a polyhedron building model is combined from extracted feature polygons and hypothesised parts.The reconstruction method is tested with two data sets containing various building shapes.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52346
Title: 3D segmentation of single trees exploiting full waveform LIDAR data
Author: J. Reitberger, Cl.Schnorr, P.Krzystek, U.Stilla
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: LIDAR, Segmentation, Aerial survey, Clustering, Forestry
Abstract: This paper highlights a novel segmentation approach for single trees from LIDAR data and compares the results acquired both from first/last pulse and full waveform data. In a first step, a conventional watershed-based segmentation procedure is set up, which rebustly interpolates the canopy height model from the LIDAR data and identifies possible stem positions of the tallest trees in the segments calculated from the local maxima of the canopy height model. Secondly, this segmentation approach is combined with a special stem detection method. Stem positions in the segments of the watershed segmentation are detected by hierarchically clustering points below the crown base height and reconstructing the stems with a robust RANSAC-based estimation of the stem points. Finally, a new three-dimensional (3D) segmentation of single trees is implemented using normalized cut segmentation. This tackles the problem of segmenting small trees below the canopy height model. The key idea is to subdivide the tree area in a voxel space and to set up a bipartite graph which is formed by the voxels and similarity measures between the voxels. Normalized cut segmentation divides the graph hierarchically into segments which have a minimum similarity with each other and whose members (=voxels) have a maximum similarity. The solution is found by solving a corresponding generalized eigenvalue problem and an appropriate binarization of the solution vector. Experiments were conducted in the Bavarian Forest National Park with conventional first/last pulse data and full waveform LIDAR data. The first/last pulse data were collected in a flight with the Falcon II system from TopoSys in a leaf-on situation at a point density of 10 points /m2. Full waveform data were captured with the Riegl LMS-Q560 scanner at a point density of 25 points/m2 (leaf-off and leaf-on) and at a point density of 10 points /m2 (leaf-on). The study results prove that the new 3D segmentation approach is capable of detecting small trees in the lower forest layer. So far, this has been practically impossible if tree segmentation techniques based on the canopy height model were applied to LIDAR data. Compared to a standard watershed segmentation procedure, the combination of the stem detection method and normalized cut segmentation leads to the best segmentation results and is superior in the best case by 12%. Moreover, the experiments show clearly that using full waveform data is superior to using first/last pulse data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52345
Title: Co-registration and correlation of aerial photographs for ground deformation measurements
Author: Francois Ayoub, Sebastien Leprince, Jean-Philippe Avouac
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Aerial, Photography, Change detection, Registration, Correlation
Abstract: We describe and test a procedure to accurately co-register and correlate multi-temporal aerial images. We show that this procedure can be used to measure surface deformation, and explore the performance and limitations of the technique. The algorithms were implemented in a software package, COSI-Corr (available from the Caltech Tectonics Observatory website). The technique is validated on several case examples of co-seismic deformation. First, we measure co-seismic ground deformation due to the 1992, Mw 7.3, Landers, California, earthquake from 1m resolution aerial photography of the National Aerial Photography Program (United States Geological Survey). The fault ruptures are clearly detected, including small kilometric segments with fault slip as small as a few tens of centimeters. We also obtained similar performance from images of the fault ruptures produced by the 1999 Mw 7.1 Hector Mine, California, earthquake. The measurements are shown to be biased due to the inaccuracy of the Digital Elevation Model, film distortions, scanning artifacts, and ignorance of ground displacements at the location of the tie points used to co-register the multi-temporal images. We show that some of these artifacts can be identified and corrected.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52344
Title: The application of GPS precise point positioning technology in aerial triangulation
Author: Xiuxiao Yuan, Jianhong Fu, Hongxing Sun, Charles Toth
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: GPS precise point positioning (PPP), GPS camera stations, GPS-supported bundle block adjustment, Error, Accuracy
Abstract: In traditional GPS-supported aerotriangulation, differential GPS (DGPS) positioning technology is used to determine the 3-dimensional coordinates of the perspective centers at exposure time with an accuracy of centimeter to decimeter level. This method can significantly reduce the number of ground control points (GCPs). However, the establishment of GPS reference stations for DGPS positioning is not only labor-intensive and costly, but also increases the implementation difficulty of aerial photography. This paper proposes aerial triangulation supported with GPS precise point positioning (PPP) as a way to avoid the use fo the GPS reference stations and simplify the work of aerial photography.
Firstly, we present the algorithm for GPS PPP in aerial triangulation applications. Secondly, the error law of the coordinate of perspective centers determined using GPS PPP in analyzed. Thirdly, based on GPS PPP and aerial triangulation software self-developed by the authors, four sets of actual aerial images taken from surveying and mapping projects, different in both terrain and photographic scale, are given as experimental models. The four sets of actual data were taken over a flat region at a scale of 1:2500, a mountainous region at a scale of 1:3000, a high mountainous region at a scale of 1:32000 and an upland region at a scale of 1:60000 respectively. In these experiments, the GPS PPP results were compared with results obtained through DGPS positioning and traditional bundle block adjustment. In this way, the empirical positioning accuracy of GPS PPP in aerial triangulation can be estimated. Finally, the results of bundle block adjustment with airborne GPS controls from GPS PPP are analyzed in detail.
The empirical results show that GPS PPP applied in aerial triangulation has a systematic error of half meter level and a stochastic error within a few decimeters. However, if a suitable adjustment solution is adopted, the systematic error can be eliminated in GPS-supported bundle block adjustment. When four full GCPs are emplaced in the corners of the adjustment block, then the systematic error is compensated using a set of independent unknown parameters for each strip, the final result of the bundle block adjustment with airborne GPS controls from PPP is the same as that of bundle block adjustment with airborne GPS controls from DGPS. Although the accuracy of the former is a little lower than that of traditional bundle block adjustment with dense GCPs, it can still satisfy the accuracy requirement of photogrammetric point determination for topographic mapping at many scales.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 52343
Title: Monocular 3D scene reconstruction at absolute scale
Author: Christian Wohler, Pablo d Angelo, Lars Kruger, Annika Kuhl, Horst-Michael GroB
Editor: George Vosselman
Year: 2009
Publisher: Elsevier, Vol 64, Issue 6, November 2009
Source: Centre for Ecological Science,Indian Institute of Science, Bangalore-12
Reference: None
Subject: ISPRS Journal of Photogrammetry and Remote sensing
Keywords: Close-range photogrammetry, Reconstruction, Metrology, Bundle adjustment, Industry
Abstract: In this article we propose a method for combining geometric and real-aperture methods for monocular three-dimensional (3D) reconstruction of static scenes at absolute scale. Our algorithm relies on a sequence of images of the object acquired by a monocular camera of fixed focal setting from different viewpoints. Object features are tracked over a range of distances from the camera with a small depth of field, leading to a varying degree of defocus for each feature. Information on absolute depth is obtained based on a Depth-from-Defocus approach. The parameters of the point spread functions estimated by Depth-from-Defocus are used as a regularisation term for Structure-from-Motion. The reprojection error obtained from bundle adjustment and the absolute depth error obtained from Depth-from-Defocus are simultaneously minimised for all tracked object features. The proposed method yields absolutely scaled 3D coordinates of the scene points without any prior knowledge about scene structure and camera motion. We describe the implementation of the proposed method both as an offline and as an online algorithm. Evaluating the algorithm on real-world data, we demonstrate that it yields typical relative scale errors of a few percent. We examine the influence of random effects, i.e. the noise of the pixel grey values, and systematic effects, caused by thermal expansion of the optical system or by inclusion of strongly blurred images, on the accuracy of the 3D reconstruction result. Possible applications of our approach are in the field of industrial quality inspection; in particular, it is preferable to stereo cameras in industrial vision systems with space limitations or where strong vibrations occur.
Location: 231
Literature cited 1: None
Literature cited 2: None