ID: 58728
Title: Estimating single-tree branch of Norway spruce by airborne laser scanning
Author: Marius Hauglin, Janka Dibdiakova, Terje Gobakken, Erik Nasset.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 147-156 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Forestry, LIDAR, Inventory, Estimation, Accuracy.
Abstract: The use of forest biomass for bioenergy purposes, directly or through refinement processes, has increased in the last decade. One example of such use is the utilization of logging residues. Branch biomass constitutes typically a considerable part of the logging residues, and should be quantified and included in future forest inventories. Airborne laser scanning (ALS) is widely used when collecting data for forest inventories, and even methods to derive information at the single-tree level has been described. Procedures for estimation of single-tree branch biomass of Norway spruce using features derived from ALS data are proposed in the present study. As field reference data the dry weight branch biomass of 50 trees were obtained through destructive sampling. Variables were further derived from the ALS echoes from each tree, including crown volume calculated from an interpolated crown surface constructed with a radial basis function. Spatial information derived from the pulse vectors were also incorporated when calculating the crown volume. Regression models with branch biomass as response variable were fit to the data, and the prediction accuracy assessed through a cross-validation procedure. Random forest regression models were compared to stepwise and simple linear least squares models. In the present study branch biomass equations based on field measurements. An improved prediction accuracy was observed when incorporating information from the laser pulse vectors into the calculation of the crown volume variable, and a linear model with the crown volume as a single predictor gave the best overall results with a root mean square error of 35% in the validation.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58727
Title: Direct stereo radargrammetric processing using massively parallel processing.
Author: Timo Balz, Lu Zhang, Mingsheng Liao.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 137-146 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: High resolution, SAR, Radagrammetry, DSM, Correlation
Abstract: Synthetic Aperture Radar (SAR) offers many ways to reconstruct digital surface models (DSMs). The two most commonly used methods are SAR interferometry (InSAR) and stereo radargrammetry. Stereo radargrammetry is a very stable and reliable process and is far less affected by temporal decorrelation compared with InSAR. It is therefore often used for DSM generatiion in heavilly vegetated areas. However, stereo radargrammetry often produces rather noisy DSMs, sometimes containing large outliers. In this manuscript, we present a new approach for stereo radargrammetric processing, where the homologus points between the images are found by geocoding large amount of points. This offers a very flexible approach. allowing the simultaneous processing of multiple images and of cross-heading image pairs. Our approach relies on a good initial geocoding accuracy of the data and on very fast processing using a massive parallel implementation. The approach is demonstrated using TerraSAR-X images from Mount Song, China, and from Trento, Italy.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58726
Title: Geometric calibration of a terrestrial laser scanner with local additional parameters: An automatic strategy.
Author: D. Garcia-San-Miguel, J L Lerma.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 122-136 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Calibration, Automation, Adjustment, Laser scanning, Parameters, Geometric.
Abstract: Terrestrial laser scanning systems are steadily increasing in many fields of engineering, geoscience and architechture namely for fast data acquistion, 3-D modelling and mapping. Similarly to other precision instruments, these systems provide measursements with implicit systematic errors. Systematic errors are physically corrected by manufacturers before delivery and sporadically afterwards. The approach presented herein tackles the raw observables acquired by a laser scanner with additional parameters, a set of geometric calibration parameters that model the systematic error of the instrument to achieve the most accurate point cloud outputs, implroving eventual workflow owing to less filtering, better registration and best 3D modelling. This paper presents a fully automatic strategy calibrate geometrically terrestrial laser scanning datasets. The strategy is tested with multiple scans taken by a FARO FOCUS 3D, a phase-based terrestrial laser scanner. A calibration with local parameters for datasets is undertaken to improve the raw observables and a weighted mathematical index is proposed to select the most significant set of additional parameters. The improvements achieved are exposed, highlighting the necessity of correcting the terrestrial laser scanner before handling multiple datas ets.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58725
Title: Field-based sub-boundary ectraction from remote sensing imagery using perceptual grouping
Author: Mustafa Turker, Emre Hamit Kok.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 106-121 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Field-based, Boundary detection, Perceptual-grouping, Agriculture, SPOT imagery.
Abstract: This study presents an approach for the automatic extraction of dynamic sub-boundaries within existing agricultural fields from remote sensing imagery using perceptual grouping. We define sub-boundaries as boundaries, where a chang in crop type takes a place withtin fixed geometry of an agricultural field. To perforn field-based processing and analysis operations, the field boundary data and the satellite are integrated. The edge pixels are detected using Canny edge detector. The edge pixels are then analysed to find the connected edge chains and from these chains the line segments are detected using the graph based vectorization method. The spurious line segments is employed for detecting sub-boundaries and constructing sub-fields within the fixed geometry of agricultural fields. Our strategy for perceptual grouping involves the Gestalt laws of proximity, continuation, symmetry and closure. The processing and analysis operations are carried out on field-by-field basis. For each field, the geometries of sub-boundaries are integrated with the fixed geometry of the field. The experimental validation of the approach was carried out on the SPOT4 multispectral (XS) and SPOT5 XS images that cover an agricultural area located in the north-western section of Turkey. The overall matching percentages between the reference data and tha automatically extracted sub-boundaries were computed to be 82.6% and 76.2% for the SPOT5 and SPOT4 images respectively. The higher matching percentage of the SPOT5 image is due to the fact that some of the boundaries present in the SPOT5 image were not detected in the coarser resolution SPOT4 image. For the SPOT5 image, of the total 292 fields processed, 177 showed a total agreement between the detected segments and the reference dat. For SPOT4 image, 154 fields showed a total agreement between the detected segments and the reference data.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58724
Title: Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska.
Author: Shengli Huang, Suming Jin, Devendra Dahal, Xuexia Chen, Claudia Young, Heping Liu, Shuguang Liu.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 94-105 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Alaska, Fire, Land Surface, Landsat, Image reconstruction, NDVI.
Abstract: Land surface change caused by fires and succession is confounded by many site-specific factors and requires futher study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of wheather variability, seasonal offset, topography, land cover and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987-2004 fire scars for August 5th 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST differences but no absolute trends could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58723
Title: Semi-automated extraction and delineation of 3D roads of street scene from mobile laser scanning point clouds.
Author: Bisheng Yang, Lina Fang, Jonathan Li.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 80-93 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Mobile Laser scanning, Curb detection, 3D road extraction, Scanning lines, Moving windows filtering.
Abstract: Accurate 3D road information is important for applicatiion such as road maintenance and virtual 3D modelling. Mobile laser scanning (MLS) is an efficient technique for capturing dense point clouds that can be used to construct detailed road models for large areas. This paper presents a method for extracting and delineating roads from large-scale MLS point clouds. The proposed method partitions MLS point clouds into a set of consecutive "scanning lines", which each consists of a road cross section. A moving window operator is used to filter out non-ground points line by line, and curb points are detected based on curb patterns. The detected curb points are tracked and redefined so that they are globally consistent and locally similar. To evaluate the validity of the proposed method, experiments were conducted using two types of street-scene point clouds captured by Optech ' s Lynx Mobile Mapper System. The completeness, correctness and quality of the extracted roads are over 94.42%, 91.13%, and 91.3%, respectively which proves the proposed method is a promising solution for extracting 3D roads from MLS point clouds.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58722
Title: Generalization of 3D building texture using image compression and multiple representation data structure
Author: Bo Mao, Yifang Ban.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 68-79 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Three-dimensional builiding model, Texture compression, Multi-resolution Image, Multiple representation data structures, Dynamic visualization.
Abstract: Textures are an essential part of 3D building models and often consume large portions of data volume, thus making visualization difficult. Therefore, we propose a multi-resolution texture generalization methods to compress the textures of 3D building models for dynamic visualization at different scales. It consists of two steps: image compression and text coloring. In the first step, texture images are compressed using wavelet transformation in both the horizontal and the vertical direction. In the second step, a Texture Tree is created to store building texture color for dynamic visualization from different distances. To generate a TextureTree, texture images are iteratively segmented by horizontal and vertical dividing zones, until each section is basically in the same color. Then the texture of each section is represented by their main color and the TextureTree is created based on the color difference between the adjacent sections. In dynamic visualization, the suitable compressed texture images or the TextureTree nodes are selected to generate 3D scenes based on the angle and the distance between the view-point and the building surface. The experimental results indicate that wavelet based image compression and the proposed TextureTree can effectively represent the visual features of the textured buildings with much less data.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58721
Title: Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery
Author: Xiaohua Tong, Xiaofei Lin, Tiantian Feng, Huan Xie, Shijie Liu, Zhonghua Hong, Peng Chen.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 53-67 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Hybrid appraoch, Shadow analysis, Building collapse detection, High-resolustion satellite image, Earthquake-induced damage assessment. Accuracy.
Abstract: In this paper, we present a hybrid shadow analysis approach that integrates the model and property-based methods for detecting collapsed buildings after an earthquake using high resolution satellite imagery. The framework proposed approach has four main steps. (1) The three-dimensional (3D) building model is established according to its footprint and height data stored in a geographical information system. (2) The theoretical shadow area of the building at the time that the post-seismic image was acquired is calculated. And the polygon of the ground shadow area of the building, which is called the theoretical ground shadow polygon, is extracted. (3) The theoretical ground shadow polygon is overlaid with the casting shadow area of the building, which is called the actual shadow area in the post-seismic satellite image, and the mean value of the digital number values of the post-seismic image pixels within the polygon of the theoretical shadow area is calculated. (4) The calculated mean value is compared with predefined thresholds, which are determined by the training pixels collected from the different types of shadows. On this basis, the shadows of totally collapsed, partially collapsed and uncollapsed buildings can be distinguished. A comprehensive experiment for Dujiangyan city, one of the urban areas most severely damaged in May 2008 Wenchuan Earthquake, was conducted, and the experimental results showed the superiority of the proposed approach to the other existing ones.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58720
Title: Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011
Author: Mirela G Tulbure, Mark Broich.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 44-52 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Optical remote sensing, Surface water body detection, Large area wetland inventory, Swan Coastal Plain, Western Australia, Long term trends.
Abstract: Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands. The Swan Coastal Plain (SCP) with over 1500 wetlands is a global biodiversity hotspot located in the south west of Western Australia, where more than 70% of the wetlands have been lost since European settlement. SCP is located in an area affected by recent climate change that also experiences rapid urban development and ground water abstraction. Landsat TM and ETM+ imagery from 1999 to 2011 has been used to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP. A mapping method based on the Landsat data and a decision tree classification algorithm is described. Two generic classifiers were derived for the Landsat 5 and Landsat 7 data. Several landscape metrics were computed to summarize the intra and interannual patterns of surface water dynamic. Top of the atmosphere (TOA) reflectance of bands 4 and 3 were explanatory variables most important for mapping surface water bodies. Accuracy assessment yielded an overall classification accuracy of 96%, with 89% producer ' s accuracy and 93% user ' s accuracy of surface water bodies. The number, mean size, and total area of water bodies showed high seasonal variability with highest numbers in witner and lowest numbers in summer. The number of water bodies in winter increased until 2005 after which a decline can be noted. The lowest numbers occurred in 2010 which coincided with one of the years with the lowest rainfall in the area. Understanding the spatiotemporal dynamic of surface water bodies on the SCP constitutes the basis for understanding the effect of rainfall, water abstraction and urban development on water bodies in a spatially explicit way.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58719
Title: A generative statistical approach to automatic 3D building roof reconstruction from laser scanning data.
Author: Hai Huang, Claus Brenner, Monika Sester
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 29-43 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Building, LIDAR, point cloud, Urban, Extraction, Reconstruction, Three-dimensional
Abstract: This paper presents a generative statistical approach to automatic 3D building roof construction from airborne laser scanning point clouds. In previous works, bottom-up methods, e.g, points clustering, plane detection, and contour extraction, are widely used. Due to the data artefacts caused by tree clutter, reflection from windows, water features, etc., the bottom-up reconstruction in urban areas may suffer from a number of incomplete or irregular roof parts. Manually given geometric constraints are usually needed to ensure plausible results. In this work we propose an automatic process with emphasis on top-down approaches. The input point cloud is firstly pre-segmented into subzones containing a limited number of buildings to reduce the computational complexity for large urban scenes. For the building extraction and reconstruction in the subzones we propose a pure top-down statistical scheme, in which the bottom-up efforts or additional data like building footprints are no more required. Based on a predefined primitive library we conduct a generative modeling to reconstruct roof models that fit the data, Primitives are assembled into an entire roof with given rules of combination and merging. Overlaps of primitives are allowed in the assembly. The selection of roof primitives, as well as the sampling of their parameters, is driven by a variant of Markov Chain Monte Carlo technique with specified jump mechanism. Experiments are performed on data-sets of different building types (from simple houses, high-rise buildings to combined building groups) and resolutions. The results show robustness despite the data artefacts mentioned above and plausibility in reconstruction.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58718
Title: Commertial tree species discrimination using airborne AISA Eagle hyperspectral imagery and partial least squares discriminant analysis (PLS-DA) in KwaZulu-Natal, South Africa
Author: Kabir Yunus Peerbhay, Onisimo Mutanga, Riyad Ismail .......................................................................
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 19-28 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Commercial forest species, Partial least squares discriminant analysis (PLS-DA), Variable importance in projection (VIP)
Abstract: Discriminating commercial tree species using hyperspectral remote sensing techniques is critical in monitoring the spatial distributions and compositions of commercial forests. However, issues related to data dimensionality and multicolinearity limit the successful application of the technology. The aim of this stufy was to examine the utility of the partial least squares discriminant analysis (PLS-DA) technique in accurately classifying six exotic commercial forest species (Eucalyptus grandis, Eucalyptus nitens, Euculyptus smithii, Pinus patula, Pinus ellioti and Acacia mearnsii) using airborne AISA Eagle hyperspectral imagery (393-900 nm). Additionally, the variable importance in the projection (VIP) method was used to identify subsets of bands that could successfully discriminate the forest species. Results indicated that the PLS-DA model that used all the AISA Eagle bands (n=230) produced an overall accuracy of 80.61% and a kappa value of 0.77, with user ' s and producer ' s accuracies ranging from 50% and 100%. In comparison, incorporating the optimal subset of VIP selected wavebands (n=78) in the PLS-DA model resulted in an improved overall accuracy of 88.78% and a kappa value of 0.87, with user ' s and producer ' s accuracies ranging from 70% to 100%. Bands located predominantly within the visible region of the electromagnetic spectrum (393-723 nm) showed the most capability in terms of discriminating between the six commercial forest species. Overall, the research has demonstrated the potential of using PLS-DA for reducing the dimensionality of hyperspectral datasets as well as determining the optimal subset of bands to produce the highest classification accuracies.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58717
Title: Feasibility of employing a smartphone as the payload in a photogrammetric UAV system
Author: Jinsoo Kim, Seongkyu Lee, Hoyong Ahn, Dongju Seo, Soyoung Park, Chuluong Choi.
Editor: Derek Lichti
Year: 1800
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 79, pp. 1-18 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Smartphone, Photogrammetric UAV system, Accuracy, Camera calibration, Ontho-Images.
Abstract: Smartphones can be operated in a 3G network environment at any time or location, and they also cost less than existing photogrmmetric UAV systems, providing high-resolution images and 3D location and attitude data from a variety of built-in sensors. This study aims to assess the feasibility of using a smartphone as the payload for a photogrammetric UAV system. To carry out the assessment, a smartphone based photogrammetric UAV system was developed and utilized to obtain image, location, and attitude data under both static and dynamic conditions. The accuracy of the the location and the attitude data obtained and sent by this system was then evaluated . The smartphone images were converted into ortho-images via image triangulation, which was carried out both with and without consideration of the interior orientation (IO) parameters determined by camera calibration. In the static experiment, when the IO parameters were taken into account, the triangulation results were less than 1.28 pixels (RMSE) for all smartphone types, an improvement of at least 47% compared with the case when IO parameters were not were not taken into account. In the dynamic experiment, on the other hand, the accuracy of smartphone image triangulation was not significantly improved by considering IO parameters. This was because the electronic rolling shutter within the complementary metal-oxide semiconductor (CMOS) sensor built into the smartphone and the actuator for the voice coil motor (VCM)-type-auto-focusing affected by the vibration and the speed of the UAV, which is likely to have a negative effect on image-based digital elevation model (DEM) generation. However, considering that these results were obtained using a single smartphone, this suggests that a smartphone is not only feasible as the payload for a photogrammetric UAV system but it may also play a useful role when installed in existing UAV systems.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58716
Title: Advances in Geographic Object-Based Image Analysis with ontologies: A review of main contributions and limitations from a remote sensing perspective.
Author: Damien Arvor, Laurent Durieux, Samuel Andres, Marie-Angelique Laporte
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 125-137 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Ontology, GEOBIA, Knowledge representation, Land cover, Interoperability.
Abstract: Geographic Object-Based Image Analysis (GEOBIA) represents the most innovative new trend for processing remote sensing images that has appeared during the last decade. However, its application is mainly based on expert knowledge, which consequently highlights important scientific issues with respect to the robustness of the methods applied in GEOBIA. In this paper, we argue that GEOBIA would benefit from another technical enhancement involving knowledge representation techniques such as ontologies. Although the role of ontologies in Geographical Information Sciences (GISciences) is not new topic, few works have discussed how ontologies, considered from the perspective of a remotes sensing specialists, can contribute to advance remote sensing science. We summarize the main application of ontologies in GEOBIA, especially for data publication. Finally, we discuss the major issues related to the construction of ontologies suitable for remote sensing applications and outline long-term future advances that can be expected for the remote sensing community.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58715
Title: Multi-feature based boresight self-calibration of a terrestrial mobile mapping system.
Author: Ting On Chan, Derek D Lichti, Craig L Glennie.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 112-124 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: boresight self-calibration, terrestrial mobile mapping system, least-square adjustment, geometric model.
Abstract: This paper presents a multi feature based system calibration method for estimating the boresight angles of a land-based mobile mapping system (MMS) comprised of multiple two dimensional (2D) scanners. The method invokes a least-squares adjustment (LSA) to simultaneously estimate several sets of boresight angles for multiple laser scanners incorporated in an MMS as well as the parameters associated with one or more types of geometric features. This is achieved by constraining the groups of feature point clouds captured by multiple runs to fit their corresponding geometric models in such a way that the weighted sum of squares of adjustment residuals is minimized. The method is particularly suitable for in situ calibration because the geometric features involved are commonly occuring structures (e.g. builiding facades, bridge surfaces, highway signs and hanging power cables) that are usually captured during the actual survey. In addition to using a planar feature model for calibration, a novel and rigorous three-dimensional (3D) catenary curve model is proposed for geometric modelling in hanging cables to augument the calibration. The proposed calibrations were examined with several different combinations of groups of planar and catenary features and the resulting analysis suggests that the in-situ calibrations are effective when compared to the manufactures ' s dedicated calibration, with the overall point cloud accuracies for plane fitting being 5.5cm and 5.4cm for the vertical and horizontal directions, respectively. It has been successfully demonstrated that the proposed method can be used in a scene having no builiding facedes but only some long hanging cables and horizontal ground surfaces. This is particularly useful for rural areas or inter-city/provincal highways where building facades cannot commonly be captured. Parameter correlations in the calibrations were also addressed. It has also been shown that using centenary features in addition to planar features for the calibration can help de-correlate some parameters and improve the overall accuracy. The in situ nature and the high flexibility of integrating different features of the calibration make the proposed method straight forward for most end-users.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58714
Title: Applications of ALOS PALSAR for monitoring biophysical parameters of a degraded black mangrove (Avicennia germinans) forest
Author: J M Kovacs, X X Lu, F Flores-Verdugo, C Zhang, F Flores de Santiago, X Jiao.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 102-111 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Biophysical parameters, Degraded mangrove, PALSAR, SAR backscatter, SAR texture
Abstract: Within the last few decades mangrove forests worldwide have been experiencing high annual rates of loss and many of those that remain have undergone considerable degradation. To understand the condition of these forests, various optical remote sensing platforms have been used to map and monitor these wetlands, including the use of these data for biophysical parameter mapping. For many mangrove forests a reliable source of optical imagery is not possible given their location in quasi-pernanent cloud cover or smoke covered regions. In such cases it is recommended that Synthetic Aperture Radar (SAR) be considered. The purpose of this investigation was to examine the relationships between various ALOS-PALSAR modes, acquired from eight images, and mangrove biophysical parameter data collected from a black mangrove (Avicennia germinans) dominated forest that has experienced considerable degradation. In total, structural data were collected from 61 plots representing the four common stand types found in this degraded forest of the Mexican Pacific: tall healthy mangrove (n=17), dwarf healthy mangrove (n=15), poor condition mangrove (n=13), and predominantly dead mangrove (n=16).
Based on backscatter coefficients, significant negative correlation coefficients were observed between filtered single polarization ALOS PALSAR (6.25m) HH backscatter and Leaf Area Index (LAI). When the dead stands were excluded (n=45) the strength of these relationships increased. Moreover, significant negative correlation coefficients were observed with stand height, Basal Area (BA) and to a lesser degree with stem density and mean DBH. With the coarser spatial resolution dual-polarization and quad polarization data (12.5 m) only a few, and weaker, correlation coefficients were calculated between the mangrove parameters and the filtered HH backscatter. However, significant negative values were once again calculated for the HH when the 16 dead mangrove stands were removed from the sample. Conversely, strong positive significant correlation coefficients were calculated between the cross-polarization HV backscatter and LAI when the dead mangrove stands were considered. Although fewer in comparison to the HH correlations, a number of VV backscatter based relationships with mangrove parameters were observed from the quad polarization mode and, to a lesser extent, with the one single VV polarization data.
In addition to backscatter coefficients, stepwise multiple regression models of the mangrove biophysical parameter data were developed based on texture parameters derived from the grey level co-occurence matrix (GLCM) of the ALOS data. A similar pattern to the backscatter relationships was observed for models based on the single polarization unfiltered data, with fairly strong coefficients of determination calculated for LAI and the stem height when the dead stands were excluded. In contrast, similar coefficients of determination with biophysical parameters were observed for the dual and quad polarization multiple regression models when the dead stands were both included and excluded from the analyses. An estimated mangroove LAI map of the study area, derived from a multiple regression model of the quad polarization texture parameters, showed comparable spatial patterns of degradation to a map derived from higher spatial resolution optical satellite data.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None