ID: 53856
Title: A volumetric approach to change detection in satellite images
Author: Thomas B. Pollard, Ibrahim Eden, Joseph L. Mundy, and David B. Cooper
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 7, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Dense urban areas, volumetric appearance modeling (VAM), ground sampling distance (GSD)
Abstract: The increasing availability of very high resolution satellite imagery has spurred interest in automatically detecting very fine detailed changes in an area over time, a particularly useful tool for analyzing activity in dense urban areas. However, attempting automated change detection at this resolution is difficult due to the motion parallax of elevated structures. This paper presents a comprehensive solution to change detection in areas of significant 3D relief using a new framework called volumetric appearance modeling (VAM). This approach can manage the complications of unknown and changing world surfaces by maintaining a 3D voxel-based model, where probability distributions for surface occupancy and image appearance are stored in each voxel. These distributions are continuously updated as new images are received using an adaptive learning procedure. This representation is demonstrated to produce accurate change detection results under conditions of variable illumination and view point as well as haze conditions present in satellite imagery. The volumetric representation also supports automatic sensor model correction representation also supports automatic sensor model correction to align incoming imagery to a common geographic reference. This registration approach is demonstrated to achieve geo-positioning accuracy on the order of the ground sampling distance (GSD) or better.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53855
Title: Climate and land-use effects on Interannual fAPAR variability from MODIS 250 m data
Author: Marc Linderman, Yu Zeng, and Pedram Rowhani
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 7, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: fraction of Absorbed Photosynthetically Active Radiation (fAPAR), MODIS, Iowa, agriculture, prairies
Abstract: The goals of this research were to examine the effects of climate, land-use, and plot-level characteristics on interannual change of vegetation characteristics. Using mixed effects regression models, we examined the influences of climatic limiting factors and plot-level characteristics on annual fraction of Absorbed Photosynthetically Active Radiation (fAPAR) estimates from MODIS 250 m resolution data across agricultural and restored prairie plots in Iowa. Prairie plots had significantly higher annual fAPAR and less year-to-year variability than highly intensive agriculture. Comparisons between fixed and random effects models show that differential climate responses between land-use types explain approximately 85 percent of between pixel differences. Year-to-year climate differences and pixel scale land use factors explained approximately 48 percent of agriculture within-plot trends and interannual variability and 54 percent of prairie year-to-year variance. Agriculture responses were predominantly influenced by precipitation and prairies were primarily influenced by incident radiation and age since restoration.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53854
Title: Spectral modeling of population density: A study of Utah ' s Wasatch Front
Author: Ryan R. Jensen, Perry J. Hardin, and Mark W. Jackson
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 7, July 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Census Block Group (CBG), Landsat TM ,regression models, network models
Abstract: This study estimated the urban population of the Wasatch Front of Utah, USA by Census Block Group (CBG) using spectral variables derived from Landsat TM reflectance as predictors. Using 353 training CBGs and 446 validation CBGs, five regression models and twenty back-propagation neural network models were built and tested. The median percentage of error in the best and worst models was 25 percent and 50 percent, respectively. Neural network models generally provided better predictions than multiple regression models. The factros most highly related to population density included spectral variance in reflectance;contrast between urban vegetation and dark material (e.g.asphalt); constrast between vegetation and bare soil; total albedo, and thermal temperature.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53853
Title: Reconstruction and texturing of 3D urban terrain from uncalibrated monocular images using L1 splines
Author: Dimitri Bulatov and John E. Lavery
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Optical images, monocular optical cameras,L1 spline
Abstract: We propose a five-step procedure for reconstruction and texturing of 3D urban terrain based on a novel approach for 3D surface reconstruction from optical images produced by monocular optical cameras on small, inexpensive vehicles without external referencing. The approach consists of generation of a nonparametric 2.5D L1-spline surface from a point cloud and iterative creation of parametric 3D L1-spline surfaces based on parametrizations using the previous surface. Computational results for a model house and for Gottesaue Palace in Karlsruhe, Germany are presented. The results presented here are proof of principle results that show that the L1-spline-based procedure is able to reconstruct and texture 3D urban terrain in spite of the large, abrupt changes in density of the point cloud, and that it produces results that are visually competitive with or superior to competing procedures. Future improvements (finer grids, adaptive grids and parameters, reduction of computing time) are outlined.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53852
Title: Effect of Sun elevation angle on DSMs derived from Cartosat-1 data
Author: Tapas R. Martha, Norman Kerle, Cees. J.Van Westen, Victor Jetten, and K. Vinod Kumar
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: digital surface models (DSM), Cartosat-1, GPS
Abstract: Along-tract stereoscopic data are increasingly used for automatic extraction of digital surface models (DSM) due to the reduced radiometric variation between the images. Problems remain with the quality of such DSMs, especially in steep terrain. This paper explores the accuracy of DSMs steep terrain. This paper explores the accuracy of DSMs extracted from Cartosat-1 data required under high and low sun elevation angle conditions in High Himalayan terrain. The metric accuracy of the DSM was estimated by comparing it with check points obtained with a differential GPS. Additionally, we used spatial discrepancy of drainage lines to estimate errors in the DSM due to spatial auto-correlation. For valleys perpendicular to the satellite track, the DSM extracted from a low sun elevation angle data showed 45 percent higher spatial accuracy than the DSM extracted from high sun elevation angle data. The results indicate that the sun elevation angle and valley orientation affect the spatial accuracy of the DSM, though metric accuracy remains comparable.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53851
Title: Comparison of airborne and terrestrial Lidar estimates of Seacliff erosion in Southern California
Author: Adam P. Young, M.J.Olsen, N. Driscoll, R.E.Flick, R.Gutierrez, R.T.Guza, E. Johnstone, and F.Kuester
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Seacliff changes, terrestrial lidar, airborne lidar, California
Abstract: Seacliff changes evaluated using both terrestrial and airborne lidar are compared along a 400 m length of coast in Del Mar, California. The many large slides occurring during the rainy, six - month study period (September 2004 to April 2005) were captured by both systems, and the alongshore variation of cliff face volume changes estimated with the airborne and terrestrial systems are strongly correlated (r2 = 0.95). However, relatively small changes in the cliff face are reliably detected only with the more accurate terrestrial lidar, and the total eroded volume estimated with the terrestrial system was 30 percent larger than the corresponding airborne estimate. Although relatively small cliff changes are not detected, the airborne system can rapidly survey long cliff lengths and provides coverage on the cliff top and beach at the cliff base.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53850
Title: Automatic segmentation of lidar data into Coplanar point clusters using an Octree-based split -and -merge algorithm
Author: Miao Wang and Yi-Hsing Tseng
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Lidar (light detection and ranging), spilt-and-merge algorithm
Abstract: Lidar (light detection and ranging) point cloud data contain abundant three-dimensional (3D) information. Dense distribution of scanned points on object surfaces prominently implies surface features. Particularly, plane features commonly appear in a typical lidar dataset of artificial structures. To explore implicitly contained spatial information, this study developed an automatic scheme to segment a lidar point cloud dataset into coplanar point clusters. The central mechanism of the proposed method is a spilt-and -merge segmentation based on an octree structure. Plane fitting serves as an engine in the mechanism that evaluates how well a group of points fits to a plane. Segmented coplanar points and derived parameters of their best-fit plane are obtained through the process. This paper also provides algorithms to derive various geometric properties of segmented coplanar points, including inherent properties of a plane, intersections of planes, and properties of point distribution on a plane. Several successful cases of handling airborne and terrestrial lidar data as well as a combination of the two are demonstrated. This method should improve the efficiency of object modelling using lidar data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53849
Title: Detection of roadway sign condition changes using Multi-scale Sign Image Matching
Author: Yichang (James) Tsai, Zhaozheng Hu, and Chris Alberti
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Roadway signs, Novel algorithm,Multi-Scale Sign Image Matching (M-SIM), Image feature analysis,Sign condition change detection,Sign condition change classification
Abstract: Roadway signs are important for safety, and transportation agencies need to identify sign condition change to perform timely maintenance, including replacement. Currently, sign condition changes are inspected manually in the field, which is time consuming, costly, and some-times dangerous. This paper first proposes a novel algorithm to detect three condition changes: missing, tilted, and blocked signs, using GPS data and video log images. The algorithm consists of three steps: (a) Multi-Scale Sign Image Matching (M-SIM), (b) Image feature analysis, and (c)Sign condition change detection and classification. The algorithm was tested using images with simulated sign condition changes and actual video images taken in Fiscal Year (FY) 2003 and 2005 by the Louisiana Department fo Transporation and Development (LADOTD). The tests demonstrate the algorithm is effective to detect three types of sign condition changes. Out of 34,000 actual video log images, the algorithm detected and classified 100 percent of the missing signs, 72.7 percent of the tilted signs, and 66.7 percent of the blocked signs, for an overall 74.3 percent detection rate. These results show that the alogorithm is useful for developing an intelligent roadway sign condition change detection system.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53848
Title: A Modified PSO algorithm for Remote Sensing image template matching
Author: Ru An, Peng Gong, Huilin Wang, Xuezhi Feng, Pengfeng Xiao, Qi Chen, Qing Zhang, Chunya Chen, and Peng Yan]
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Cross-correlation algorithms, particle swarm optimization (PSO),mutual information (MI)
Abstract: Image template matching is essential in image analysis and computer vision tasks. Cross-correlation algorithms are often used in practice, but they are sensitive to nonlinear changes in image intensity and random noise, and are computationally expensive. In this paper, we propose a template-matching algorithm based on a modified particle swarm optimization (PSO) procedure with a mutual information (MI) similarity measure. The influence of MI on the performance of template matching, calculated by different histogram bins, is analyzed first. A modified PSO method (CRI-PSO) is then presented. The proposed algorithm is tested with remote sensing imagery from different sensors and for different seasons. Our experimental results indicate that the proposed approach is robust in practical scenarios and outperforms the standard PSO, multi-start PSO, and cross-correlation algorithms in accuracy and efficiency with our test data. The proposed method can be used for position estimation of aircraft, object recognition, and image retrieval.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53847
Title: A multi-scale approach for delineating individual tree crowns with very high resolution imagery
Author: Le Wang
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 4, April 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: ndividual tree crowns (ITC)
Abstract: This paper presents a muti-scale approach for delineating individual tree crowns (ITC) from high spatial resolution imagery. By analyzing the evolution of image gradients over the scale-space constructed with orthogonal wavelets, tree crown boundaries are effectively strengthened while the textures resulted from tree branches and twigs are largely suppressed. Two scale consistency checks, a scale and a geometric consistency check, were devised to account for tree crown ' s radiometric and geometric characteristic. After an edge-enhanced image was acquired, a previously developed marker-controlled watershed segmentation method was adopted to delineate ITC. An experiment was carried out in a study site in California. Field measurements of crown size of 58 trees were compared with those derived from aerial imagery. An R square value of 0.68 was achieved. It was found that crown size was underestimated from the photo interpretation compared to that from the ground survey. The result can be attributed to the fact that pixels lying on the tree crown boundaries are poorly represented in the image.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53846
Title: Point set topology extraction for branch and crown-level species classification
Author: Andrew Niccolai, Melissa Niccolai, and Chadwick Dearing Oliver
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 3, March 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: eastern hemlock (Tsuga canadensis) ,eastern white pine (Pinus strobus),Getis (Gi*) statistic contour analysis
Abstract: Contextually-based distance and proximity functions derived from the axioms of point set topology are applied at the branch and crown-level for species differentiation between). Point set topology is a branch of mathematics that offers methods to describe the connectivity and orientation of spatial objects and therefore allows object grouping based on spatial characteristic metrics unlike traditional fixed distance measures imposed from a global metric. Local neighborhood membership functions based on topological space are robust to variation in object sizes within a fixed image resolution and are therefore useful for describing spatial characteristics in highly variable objects such as tree morphology. We investigated the utility of topological space for describing branch-level needle orientations and crown-level patterns of high and low spectral intensity clusters. Branch-level measures of orientations within topologically-derived neighborhoods resulted in a classification accuracy of 96 percent for hemlock and pine; this represents a 23 percentage point (pp) improvement over traditional spectral feature classification. A crown-level species feature extraction and classification methodology that incorporated a local Getis (Gi*) statistic contour analysis produced species dicrimination results that were improved by 8 pp for an overall accuracy of 85 percent over traditional color and shape-based feature classification.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53845
Title: Co-registration of surfaces by 3D least squares matching
Author: Devrim Akca
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 3, March 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Least Squares 2D image matching, 3D surface matching, 3D surface matching
Abstract: A method for the automatic co-registration of 3D surfaces is presented. The method utilizes the mathematical model of Least Squares 2D image matching and extends it for solving the 3D surface matching problem. The transformation parameters of the search surfaces are estimated with respect to a template surface. The solution is achieved when the sum of the squares of the 3D spatial (Euclidean) distances between the surfaces are minimized. The parameter estimation is achieved using the Generalized Gauss-Markov model. Execution level implementation details are given. Apart from the co-registration of the point clouds generated from spaceborne, airborne and terrestrial sensors and techniques, the proposed method is also useful for change detection, 3D comparison, and quality assessment tasks. Experiments using terrain data examples show the capabilities of the method.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53844
Title: A mathematical expression for stereoscopic depth perception
Author: Humberto Rosas, Watson Vargas, Alexander Ceron, Dario Dominguez and Adriana Cardenas
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 3, March 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Stereoscopic depth perception, Geometric model, Perceptual model
Abstract: The metric nature of stereoscopic depth perception has remained an enigma. Several mathematical formulations proposed for measuring the stereoscopic effect have not shown to be reliable. This may be due to the lack of a conceptual distinction between the 3D model geometrically obtained by intersection of visual rays (geometric model), and the 3D model perceived in the observer ' s mind (perceptual model). Based on the assumption that retinal parallax is the only source of information on depth available to the brain. We developed an equation that shows real and perceptual space to be connected by a logarithmic function. This relationship has allowed us to formulate the vertical exaggeration for all sorts of stereoscopic conditions, including natural stereo-vision. The obtained formulations might involve possibilities of technological applications, such as the artificial recreation of a natural stereo-vision effect, and the design of stereoscopic instruments with a desired degree of vertical exaggeration.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53843
Title: Accuracy assessment measures for object-based image segmentation goodness
Author: Nicholas Clinton, Ashley Holt, James Scarborough, Li Yan and Peng Gong
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 3, March 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Parsimonious parameters, ranked segmentation results
Abstract: To select an image segmentation from sets of segmentation results, measures for ranking the segmentation relative to a set of reference objects are needed. We review selected vector-based measures designed to compare the results of object-based image segmentation with sets of training objects extracted from the image of interest. We describe and compare area-based and location-based measures that measure the shape similarity between segments and training objects. By implementing the measures in two object-based image porcessing software packages, we illustrate their use in terms of automatically identifying parsimonious parameter combinations from arbitrarily large sets of segmentation results. The results show that the measures have divergent performance in terms of the identification of parameter combinations. Clustering of the results in measure space narrows the search. We illustrate combination schemes for the measures for generating rankings of segmentation results. The ranked segmentation results are illustrated and described.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53842
Title: Evaluation for damaged degree of vegetation by forest fire using Lidar and a digital aerial photograph
Author: Doo-Ahn Kwak, Jinwon Chung, Woo-Kyun Lee, Menas kafatos, Si Young Lee, Hyun-Kook Cho, and Seung-Ho Lee
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 3, March 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: lidar (Light Detection And Ranging), Normalized Difference Vegetation Index (NDVI), serious physical damage (SPD), light physical damage (LPD)
Abstract: The amount of vegetation physically damaged by forest fire can be evaluated using lidar (Light Detection And Ranging) data because the loss of canopy height and width by forest fire can be relevant to the nubmer of points transmitted to the ground through the canopy of the damaged forest. On the other hand, the biological damage of vegetation caused by forest fire can be obtained from the Normalized Difference Vegetation Index (NDVI), which determines the vegetation vitality. In this study, the degree of physical damage from the lidar data was classified into serious physical damage (SPD) and light physical damage (LPD). The degree of biological damage using NDVI was likewise classified into serious bilogical damage (SBD) and light biological damage (LBD). Finally, the damaged area was graded into four categories: (a) SPD and SBD, (b) LPD and SBD, (c) SPD and LBD, and (d) LPD and LBD. The accuracy assessment for the area classified into four grades showed an overall accuracy of 0.74, and a kappa value of 0.61 which provides improvement over previous works.
Location: 231
Literature cited 1: None
Literature cited 2: None