ID: 53873
Title: Combining Aerial photogrammetry and Terrestrial Lidar for reservior Analog modelling
Author: Simon J. Buckley, Ernesto Schwarz, Viktor Terlaky, John A. Howell, and R.W.(Bill) Arnott
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Terrestrial lidar, geocellular model
Abstract: High-resolution aerial photography was captured covering a geological outcrop at Castle Creek, British Columbia, Canada. Here, for the purpose of hydrocarbon analog modeling, the outcrop was required to be accurately surveyed, so that key stratigraphic surfaces could be mapped in three dimensions. Becasue the outcrop strata were vertically orientated, these surfaces could be tracked over a wide area; however, to provide a true reconstruction of the geology, it was necessary to also model localized vertical cliffs providing a cross-section through the stratigraphy. Terrestrial lidar was utilized to cover these cliff sections which were poorly represented in the 2.5D aerial data. The integrated outcrop surface was textured with metric aerial and terrestrial imagery providing a photorealistic model that could be used for interpretation by geologists. This formed the basis for building a geocellular model of the geological volume, which was used to assist in the understanding of subsurface reservoirs where data are often limited.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53872
Title: Training algorithm performance for image classification by Neural networks
Author: Libin Zhou and Xiaojun Yang
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Artificial neural networks (ANNS), multi-layer-perceptron (MLP), Landsat Enhanced Thematic Mapper Plus (ETM+) image
Abstract: Adaptive training is critical for image classification by artificial neural networks (ANNS). While the machine learning community has been enthusiastic in developing various training algorithms, little research has been conducted to evaluate the performance of these algorithms in image classification by neural networks. We introduce and evaluate nine commonly-used training algorithms in terms of their performance in land-cover classification from remotely sensed data by the multi-layer-perceptron (MLP) neural networks. MLP has been considered as the most popular neural network architecture. The taining algorithms we consider are Steepest Grandient Descent, Gradient Descent with Momentum, Resilient Propagation, Feltcher-Reeves, Polak-Ribiere, Powell-Beale, Scaled Conjugate Gradient, BFGS (Broyden, Fletcher, Goldfarb, and Shanno), and Levenberg- Marquardt. We use each algorithm to train the MLP networks multiple times using identical training samples, and then apply each of the resultant network models to derive land cover information from a Landsat Enhanced Thematic Mapper Plus (ETM+) image. The training algorithms are further evaluated according to their training efficiency, capability of convergence, classification accuracy, and stability of the classification accuracy. It is found that the performance of these algorithms varies substantially and selecting an appropriate algorithm can lead to a fast and efficient training and an increase in land-cover classification accuracy by artificial neural networks.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53871
Title: An assessment of WorldView-1 positional accuracy based on fifty contiguous stereo pairs of imagery
Author: John Dolloff and Reuben Settergren
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: WorldView-1, Metric Information Network (MIN) , GPS
Abstract: This paper presents an assessment of WorldView-1 3D positional extraction accuracy based on 50 overlapping and contiguous stereo pairs of WorldView-1 imagery covering approximately 50,000 square kilometers of the earth ' s surface. Absolute accuracy is both predicted using error propagation and measured using reference points. Shear, a form of relative accuracy, is also assessed between each overlapping stereo pair of images. Accuracy is assessed for two different processing approaches: extraction from individual stereo pairs, and extraction from stereo pairs following the fusion of information across all overlapping stereo pairs. The latter approach was implemented with Metric Information Network (MIN) processing, an efficient process with results equivalent to a simultaneous block adjustment. Both approaches used no ground control, although in a separate sub-experiment, MIN processing was supplemented with a spars set of ground control (GPS surveyed ) points.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53870
Title: Assessment of geo-positioning capability of high resolution satellite imagery for densely populated high buildings in Metropolitan Areas
Author: Gang Qiao, Weian Wang, Bo Wu, Chun Liu, and Rongxing Li
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: QuickBird stereo images, GPS, Ground Control Points (GCPs) , Independent Check Points (ICPs), RFM
Abstract: This paper analyzes the geo-positioning capability of high-resolution satellite images in a very special metropolitan environment where within a relatively small region there are a large number of densely populated skyscrapers and high buildings. A pair of QuickBird stereo images covering down-town Shanghai were used for analysis. Multi-source data including GPS survey data, aerial images, and lidar data collected in the same area were used for Ground Control Points (GCPs) and Independent Check Points (ICPs) measurements and accuracy analysis. The vendor-provided Rational Function Model followed by a translation and scale correction model in image space was used to introduce the ground control and improve geo-positioning accuracy. The experimental results revealed that there is a clear dependency of geo-positioning accuracy on elevation where the GCPs are placed. Using the vendor-provided RFM and several GCPs across all the elevation ranges the overall geo-positioning accuracy.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53869
Title: Predicting Southeastern forest canopy heights and fire fuel models using GLAs data
Author: Andrew Ashworth, David L Evans, William H. Cooke, Andrew Londo, Curtis Collins, and Amy Neuenschwander
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Geoscience Laser Altimeter System (GLAS), Ice, Cloud, and Elevation Satellite (ICESat),Logistic regression, fuel model
Abstract: The Geoscience Laser Altimeter System (GLAS) is a waveform lidar system carried on board the Ice, Cloud, and Elevation Satellite (ICESat). This study tested the use of GLAs data, from the L3e and L3g campaigns, to estimate total canopy height. GLAS footprint locations were sampled for reference data. The GLAS-derived and field -derived canopy heights portrayed good correlation (R2=0.8354). This study also examined two representative fire fuel models within forests in East-Central Mississippi. GLAS waveforms were compared with field data for fire fuel models 9 and 10 of the fire fuel models described by Anderson (1982). GLAs data intensities were extracted and averaged to create predictive variables. Two variables were applied in Logistic regression to predict the probability of belonging to either fuel model (overall accuracy = 0.6875).
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53868
Title: Geographic object-based delineation of neighborhoods of Accra, Ghana using QuickBird Satellite imagery
Author: Douglas A. Stow, Christopher D. Lippitt, and John R. Weeks
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 8, August 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Geographic Object-based Image Analysis (GEOBIA), QuickBird multispectral imagery, enumeration areas (EAs),slum index values
Abstract: The objective was to test Geographic Object-based Image Analysis (GEOBIA) techniques for delineating neighborhoods of Accra, Ghana using QuickBird multispectral imagery. Two approaches to aggregaing census enumeration areas (EAs) based on image-derived measures of vegetation objects were tested: (a) merging adjacent EAs according to vegetation measures, and (b) image segmentation. Both approaches exploit readily available functions within commerical GEOBIA software. Image-derived neighborhood maps were compared to a reference map derived by spatial clustering of slum index values (from census data), to provide a relative assessment of potential map utility. A size-constrained iterative segmentation approach to aggregation was more successful than standard image segmentation or feature merge techniques. The segmentation approaches account for size and shape characteristics, enabling more realistic neighborhood boundaries to be delineated. The percentage of vegetation patches within each EA yielded more realistic delineation of potential neighborhoods than mean vegetation patch size per EA.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53867
Title: Analysis of user and producer risk when applying the ASPRS standards
Author: Francisco Javier Ariza Lopez, Alan D.J.Atkinson, Jose Luis Garcia Balboa, and Jose Rodriguez Avi
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Accuracy Standards for Large Scale Maps (ASLSM), root mean squared eror, Class1 maps, Class 2 maps
Abstract: Using a statistical simulation process, the behavior of the Accuracy Standards for Large Scale Maps (ASLSM) of the American Socity for Photogrammetry and Remote Sensing is analyzed according to the sample size, as well as the relation between the limiting errors (thresholds), stated by the standard as a root mean squared error, and the actual root mean squared error of the product. When the root mean squared error of the product equals the threshold of the standard the simulation results show the ASLSM is very restrictive, classifying 75 percent of products as Class 2 maps instead of Class 1 maps. If the variability of the product is greater or lesser than this threshold, results can be depicted by a family of acceptance curves. These curves can be employed by users to detemine the sample size needed to limit their acceptance risk, but alos by producers to analyze their rejection risk.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53866
Title: Generation of complex polyhedral building models by integrating Stereo-Aerial iamgery and Lidar data
Author: Ayman F. Habib, Ruifang Zhai, and Changiae Kim
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Rooftops, DBM
Abstract: The integration of lidar data and aerial imagery is a pormising approach for accurate building model generation. In this research, lidar data and stereo-aerial imagery are incorporated in the generation of complex polyhedral building models whose rooftops are bounded by straight lines. The process starts by utilizing lidar data for deriving building hypotheses and the initial boundaries of the planar patches consituting the buildings rooftops. The boundaries of these patches are then refined through the incorporation of stereo-aerial imagery while utilizing 3D geometric and spectral constraints. Precise building boundaries are derived through resolving feature matching problems and fully utilizing spectral information. Finally, an efficient manual monoplotting procedure is introduced to remove incorrect and add missing boundaries. The performance of the developed procedures is evaluated through experimental results from real data where the correctness, completeness, and accuracy of the derived building models are evaluated through comparison with a manually generated DBM.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53865
Title: Positional accuracy evaluation of declassified hexagon KH-9 mapping camera imagery
Author: Arzhan Surazakov and Vladimir Aizen
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Ground Control Points (GCPs), KH-9 Hexagon imagery, IceSAT laser, DEM RMSE
Abstract: This paper examines the positional accuracy of the declassified KH-9 Hexagon imagery and derived DEM. Aimed at geodesy and and mapmaking, the KH-9 program (1973 to 1980) resulted in an image archive with world wide stereo coverage at 6 to 9 m. We used six KH-9 images acquired in 1980 over two testfields in Central Asia. Using reseau marks on the scanned KH-9 frames, we found and corrected image distortions. In bundle orientation with Ground Control Points (GCPs) from QuickBird images, we achieved horizontal accuracies below 6 m for a flat terrain testfield and approximately 10 m for a mountainous terrain testfield. WIth three GCPs the image orientation horizontal accuracy degreaded by only 20 percent. We generated a DEM from the KH-9 images and estimated its vertical accuracy using IceSAT laser altimetry data and an additional DEM from 1:25 000 topographic maps. The DEM RMSE was 6.18 m over flat terrain and 20.0 m over mountainous terrain.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53864
Title: The forward propagation of integrated system component errors within airborne Lidar data
Author: Tristan Goulden and Chris Hopkinson
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: General Law of Propagation of Variances (GLOPOV),global positioning system
Abstract: Error estimates of lidar observations are obtained by applying the General Law of Propagation of Variances (GLOPOV) to the direct georeferencing equation. Within the formulation of variance propagation, the most important consideration is the values used to describe the error of the hardware component observations including the global positioning system, inertial measurement unit, laser ranger, and laser scanner (angular encoder noise and beam divergence). Data tested yielded in general, pessimistic predictions as 85 percent of residuals were within the predicted error level. Simulated errors for varying scan angles and altitudes produced horizontal errors largerly influenced by IMU subsystem error as well as angular encoder noise and beam divergence. GPS subsystem errors contribute the largest proportion of vertical error only at shallow scan angles and low altitudes. The transformation of the domination of GPS related error sources to total vertical error occurs at scan angles of 230, 130, and 80 at flying heights of 1,200 m, 2,000m and 3,000m AGL, respectively.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53863
Title: Detection of sinkhole hazards using airborne lase scanning data
Author: Sagi Filin and Amit Baruch
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Airborne laser scanning technology, geohazards, collapse sinkholes
Abstract: Airborne laser scanning technology is primarily perceived as a means for gathering detailed three-dimensional information about the surface and objects on it. The dense 3D data contain information about surface features adn geohazards, some of which are of subtle form. Geohazards are usually embedded within the terrain, and scarcely form distinct shape-transition to their surroundings; therefore their detection is challenging.We address in this paper detection of subtle terrain features and demonstrate it on collapse sinkholes. Collapse sinkholes are surface depressions whose formation has severe effect on the environment and on regional development. We present an autonomous model for their extraction and characterization. Sinkholes within the studied regions appear in various size, forms, from their embryonic to a well developed formation. The level of sinkhole detection is high, and as demonstrated, the model performs well under varying landforms and surface texture, with little influence on the correctness of the extracted sinkholes. As the results show, features of approximately 20 cm deep can be identified and separated from their surroundings in the data.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53862
Title: Comparing classification approaches for mapping cut-leaved teasel in highway environments
Author: Cuizhen Wang, Diego J. Bentivegna, Reid J. Smeda, and Randy E. Swanigan
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Cut-leaved teasel, Spectral angle mapping (SAM), maximum likelihood classifier (MLC),spectral information divergence (SID)
Abstract: Cut-leaved teasel is an invasive weed thriving in roadside environments and needs to be detected for implementation of management programs. This study tested several commonly applied classifiers to map teasel with an aerial hyperspectral image along the Interstate Highway 70 in central Missouri. A teasel/non-teasel mask was first built to exclude dominant land-covers that had distinct spectral differences from teasel. The spectral angle mapping (SAM) had the best results of delineating teasel from herbaceous background with its user ' s and producer ' s accuracies of 80 to 90 percent. Large commission errors of teasel were observed in the probability-based maximum likelihood classifier (MLC) and spectral information divergence (SID) methods. Compared with a regular land-use/land-cover classification in an unsupervised/supervised hybrid method, the post-masking SAM had much easier process of training data collection and achieved similar accuracies. It could be an optimal approach for mapping teasel and other weeds in highway environments.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53861
Title: Analysis of impervious surface and its impact on urban heat environment using the Normalized Difference Impervious Surface Index (NDISI)
Author: Hanqiu Xu
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Normalized difference impervious surface index (NDISI), Landsat ETM, Fuzhou City, ASTER, land surface temperature (LST)
Abstract: The fast urban expansion has led to replacement of natural vegetation-dominated land surfaces by various impervious materials. This has a significant impact on the environment due to modification of heat energy balance. Timely understanding of spatiotemporal information of impervious surface has become more urgent as conventional methods for estimating impervious surface are very limited. In response to this need, this paper proposes a new index, normalized difference impervious surface index (NDISI), for estimating impervious surface. The application of the index to the Landsat ETM + image of Fuzhou City and the ASTER image of Xiamen City in China has shown that the new index can efficiently enhance and extract impervious surfaces from satellite imagery, and the normalized NDISI can represent the real percentage of impervious surface. The index was further used as an indicator to investigate the impact of impervious surface on urban heat environment by examination of its quantitative relationship with land surface temperature (LST), vegetation, and water using multivariate statistical analysis. The result reveals that impervious surface has a positive exponential relationship with LST rather than a simple linear one. This suggests that the areas with high percent impervious surface will accelerate LST rise and urban heat island development.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53860
Title: Vegetation dynamics in Yellowstone ' s Northern range: 1985 to 1999
Author: Shannon L. Savage and Rick L. Lawrence
Editor: Russell G. Congalton
Year: 2010
Publisher: Asprs, Vol 76, No 5, May 2010
Source: Centre for Ecological Sciences
Reference: None
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Ranglands, Northern range (NR), Yellowstone National Park
Abstract: An inexpensive and reproducible method for monitoring rangelands over the northern range (NR) of Yellowstone National Park was developed utilizing Landsat imagery. A 1999 map of rangeland vegetation communities was created using boosted classification tree analysis. The 1999 map and a 1985 image were utilized in a change vector analysis resulting in a classified map for 1985. Classification accuracies ranged from 72.30 percent to 83.65 percent for the 1999 map and 72.60 percent to 88.73 percent for the 1985 map, depending upon level of class detail, demonstrating that Landsat-class data can be effectively used for efficient change analysis that maintains accuracy while reducing compound error. Spatial patterns of change were compared to theories from other studies related to change in the NR and were found to be consistent with effects from fire suppression, precipitation, and urban growth but not with trophic cascade from wolves or beaver effects.
Location: 231
Literature cited 1: None
Literature cited 2: None
ID: 53859
Title: Evaluation of the influence of local fuel homogeneity on fire hazard through Landsat-5 TM texture measures
Author: cristina Vega-Garcia, Jaime Tatay-Nieto, Ricardo Blanco, and Emilio Chuvieco
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: Landscape homogeneity, Fire hazard,Logit models, Landsat-5
Abstract: This study analyzed the relationship between landscape homogeneity and fire hazard for a certain area and time period (1984 to 1995), by using logit models. Homogeneity was measured though eight texture measurements computed on visible and NIR bands of Landsat -5 TM data with vaying kernel sizes. Several significant models could be developed to predict future burning at the pixel level for the study period. The best spectral band for detecting proneness to burn was TM1, the blue band, and best results were achieved with large window sizes and the Homogeneity texture measure.
Location: 231
Literature cited 1: None
Literature cited 2: None