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
ID: 58713
Title: Partial iterates for symmertrizing non-parametric color correction.
Author: Bruno Vallet, Laman Lelegard.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 93-101 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Mosaic, Color correction. Radiometry, Fusion, Image.
Abstract: Mosaic generation is a central tool in various fields ranging way beyond the scope of photogrammetry and requires the radiometry and color of the images to be corrected. Correction can either be done by a global parametric approach (looking for an optimal gain or gamma for each image of the mosaic), or by iteratively correcting image pairs with a non parametric approach. Such non-parametric approaches allow for much finer correction but are asymmetric, i.e. they require the choice of a source image that will be corrected to match a target image. Thus the result on the whole mosaic will be very dependant on the order in which images are corrected. In this paper, we propose to use partial iterates to symmetrize non-parametric correction in order to solve this problem. Partial iterates formalize what partially applying a bijective function means and we explain how this can be done in both the continuous and discrete domain. This mechanism is applied to a simple non-parametric appraoach (histogram transfer of the luminance) to show its potential.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58712
Title: Evaluating the capabilities of Sentimental-2 for quantitative estimation of biophysical variables in vegetation.
Author: William James Frampton, Jadunandan Dash, Gary Watmough, Edward James Milton.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 83-92 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Vegetation, Sentinel-2, Chlorophyll, Red-Edge, LAI
Abstract: The red edge position (REP) in the vegetation spectral reflectance is a surrogate measure of vegetation chloropyll content, and hence can be used to monitor the health function of vegetation. The Multi-Spectral Instrument (MSI) aboard the future ESA Sentinel-2 (S-2) satellite will provide the opportunity for estimation of the REP at much higher spatial resolution (20m) than has been previously possible with spaceborne sensors such as Medium Resolution Imaging Spectometer (MERIS) aboard ENVISAT. This study aims to evaluate the potential of S-2 MSI sensor for estimation of canopy chloropyll content, leaf area index (LAI) and leaf chlorophyll concentration (LCC) using data from multiple field campaigns are results from SEN3Exp in Barrax. Spain composed of 35 elementary sampling units (ESUs) of LCC and LAI which have been assessed for correlation with simulated MSI data using a CASI airborne imaging spectrometer. Analysis also presents results from SicilyS2EVAL, a campaign consisting of 25 ESU ' s in Sicily, Italy supported by simultaneous Spectim Asia-Eagle data acquisition. In addition, these results were compared to outputs from the PROSAIL model for similar values of biophysical variables using these combined datasets through investigating the performance of the relevant Vegetation Indicies (VIs) as well as presenting the novel Inverted Red-Edge Chlorophyll Index (IRECI) and Sentinel-2 Red Edge Position (S2REP), Results indicated significant relationships between both canopy chlorophyll content and LAI for simulated MSI data using IRECI or the Normalised Difference Vegetation Index (NDVI) while S2REP and the MERIS Terrestial Chlorophyll Index (MTCI) were found to have the strongest correlation for retrieval of LCC.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58711
Title: Analysis of full-waveform LiDAR data for classification of an orange orchard scene.
Author: Karolina D Fieber, Ian J Davenport, James M Ferryman, Robert J Gurney, Jeffrey P Walker, Jorg M Hacker.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 63-82 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Full-waveform, LiDAR, Backscattering coefficient, Classification, Reflectance, Vegetation.
Abstract: Full-waveform laser scanning data acquired with a Riegl LMS-Q560 instrument were used to classify an orange orchard into orange trees, grass and ground using waveform parameters alone. Gaussian decomposition was performed on this data
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58710
Title: Glacier surface velocity estimation using repeat TerraSAR-X images: Wavelet- vs. correlation-based image matching
Author: Adrain Schubert, Annina Faes, Andreas Kaab, Erich Meier.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 49-62 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Image matching, Feature tracking, Glacier surface velocity, Aletsch, TerraSAR-X, Synthetic Aperture Radar, Wavelet decomposition.
Abstract: For the observation and monitoring of glacier surface velocity (GSV), remote sensing is an increasingly suitable tool thanks to the high temporal and spatial resolution of the data. Radar sensors have the specific advantage over optical sensors of being nearly weather and time-independent.
Two image pairs seperated by 11 days, acquired with the high-resolution spotlight (HS) and stripmap (SM) modes of Gernan sensor TerraSAR-X, were used to estimate GSV over Switzerland ' s Aletsch Glacier. The SM mode covers larger ground swaths, making it more suitable for glacier-wide observations, while the HS images cover less area but offer the highest possible spatial resolution, approximately 1?1m on the ground. The images were acquired during the summer to maximise feature visibility by minimal snow cover.
GSV estimation was performed using two methods, the comparison of which was a major goal of this study: traditional cross-correlation optimization and a dense image matching algorithm based on complex wavelet decomposition. Each method was found to have unique advantages and disadvantages, but it was concluded that for GSV monitoring, cross-correlation is probably preferable to the wavelet-based approach. While it generates fewer estimates per unit area, this not necessarily a critical requirement for all glaciological applications, and the method requires less initial "tuning" (calibration) than the wavelet algorithm, making it a slightly better tool in operational contexts. Also, the use of the highest resolution spotlight datasets is recommended over stripmap mode images when large-area coverage is less critical. The comparative lack of visible features at the resolution of the stripmap images made reliable GSV estimation difficult, with the exception of several small areas dominated by large crevasses.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58709
Title: 3-D voxel-based solid modelling of a broad-leaved tree for accurate volume estimation using portable scanning lidar.
Author: Fumiki Hosoi, Yohei Nakai, Kenji Omasa.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 41-48 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Portable ground based scanning lidar, Solid model, Voxel, Woody material volume
Abstract: We developed a method to produce a 3-D voxel based model of a tree based on portable scanning lidar data for accurate estimation of the volume of the woody material. First, we obtained lidar measurements with a high laser pulse density from several measurement positions around the target, a Japanese zelkova tree. Next, we converted lidar-derived point-cloud data for the target in voxels. The voxel size was 0.5cm ? 0.5cm ? 0.5cm. Then, we used differences in the spatial distribution of voxels to seperate the stem and the large branches (diameter > 1cm) from small branches (diameter ? 1cm). We classified the voxels into sets corresponding to the stem and to each large branch and then interpolated voxels to fill out their surfaces and their interiors. We then merged the stem and large branches with the small branches. The resultant solid model of the entire tree was composed of consecutive voxels that filled the outer surfaces and the interior of the stem and large branches, and a cloud of voxels equivalent to small branches that were discretely scattered in mainly the upper part of the target. Using this model, we estimated the woody material volume by counting the number of voxels in each part and multiplying the number of voxels by the unit voxel volume (0.13 cm?). The percentage error of the volume of the stem and the part of a large branch was 0.5%. The estimation error of a certain part of the small branches was 34.0%.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58708
Title: Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data.
Author: A. Ramoelo, A K Skidmore, M A Cho, R Mathieu, I M A, Heitkonig, N Dudeni-Tlhone, M Schlerf, H H T Prins.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 27-40 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: In situ hyperspectral remote sensing, Ecosystem, Partial least square regression, Radial basis neutral network, Nitrogen concentrations, Phosphorus concentrations.
Abstract: Grass nitrogen (N) and phosphorous (P) concentrations are direct indicators of rangeland quality and provide imperative information for sound management of wildlife and lifestock. It is challenging to estimate grass N and P concentrations using remote sensing in the savanna ecosystems. These areas area diverse and heterogenous in soil and plant moisture, soil nutrients, grazing pressures, and human activities. The objective of the study is to test the performance of non-linear partial least squares regression (PLSR) for predicting grass N and P concentrations through integrating in situ hyperspectral remote sensing and environment variables (climatic, edaphic, and topographic). Data were collected along a land use gradient environment in the greater Kruger National Park region. The data consisted of: (i) in situ-measured hyperspectral spectra, (ii) environmental variables and measured grass N and P concentrations. The hyperspectral varialbles included published starch, N and protien spectral absorption features, red edge position, narrow-band indicies such as simple ratio(SR) and normalised difference vegetation index (NDVI). The results of the non-linear PLSR were compared to those conventional linear PLSR. Using non-linear PLSR, integrating in situ hyperspectral and environmental variables yielded highest grass N and P estimations accuracy (R?=0.81, root mean square error (RMSE)=0.08, and R?=0.80, RMSE=0.03, respectively) as compared to using remote sensing variables only, conventional PLSR. The study demonstrates the importance of an integrated modelling approach for estimating grass quality which is crucial effort towards effective management and planning of protected and communal savanna ecosystems.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58707
Title: Accurate 3D comparison of complex topography with terrestrial laser scanner: Application to the Rangitikei canyon (N-Z)
Author: Dimitri Lague, Nicolas Brodu, Jerome Leroux
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. 10-26 (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: Terrestrial laser scanner, Point cloud, 3D change detection, Surface roughnes, Self-affinity, Geomorphology.
Abstract: Surveying techniques such as terrestrial laser scanner have recently been used to measure surface changes via 3D point cloud (PC) comparison. Two types of approaches have been pursued : 3D tracking of homologus parts of the surface to compute a displacement field, and distance calculation between two point clouds when homologous parts cannot be defined. This study deals with the second approach typical of natural surface altered by erosion, sedimentation or vegetation between surveys. Current comparison methods are based on a closest point distance or require at least one of the PC to be meshed with severe limitations when surfaces present roughness elements at all scales. To solve these issues, we introduce a new algorithm performing a direct comparison of point clouds in 3D. The method has two steps (1) surface normal estimation and orientation in 3D at a scale consistent with the local surface roughness (2) measurement of the mean surface change along the normal direction with explicit calculation of a local confidence interval. Comparison with existing methods demonstrates the higher accuracy of our approach, as well as an easier workflow due to the absence of surface meshing or Digital Elevation Mode (DEM) generation. Application of the method in a rapidly eroding, meandering bedrock river (Rangtikei River canyon) illustrates its ability to handle 3D differences in complex situations (flat and vertical surfaces on the same scene), to reduce uncertainity related to point cloud roughness by local averaging and to generate 3D maps of uncertainity levels. We also demonstrate that for high precision survey scanner, the total error budget on change detection is dominated by the point clouds registration error and the surface roughness. Combined with mm-range local georeferencing of the point clouds, levels of detection down to 6 mm (defined at 95% confidence) can be routinely attained in situ over ranges of 50 m. We provide evidence for self-affine behaviour of different surfaces. We show how this impacts the calculation of normal vectors and demonstrate the scaling behaviour of different surfaces. We show how this impacts the calculation of normal vectors and demonstrate the scaling behaviour of the level of change detection. The algorithm has been implemented in a freely available open source software package. It operates in complex 3D cases and can also be used as a simpler and more robust alternative to DEM differencing for the 2D cases.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58706
Title: A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data.
Author: Chuanfa Chen, Yanyan Li, Wei Li, Honglei Dai.
Editor: Derek Lichti
Year: 2013
Publisher: Elsevier B. V.
Source: Centre for Ecological Sciences
Reference: ISPRS Journal of Photogrammetry & Remote Sensing Vol. 82, pp. (2013)
Subject: ISPRS Journal of Photogrammetry & Remote Sensing
Keywords: LIDAR, Filtering, Thin plate spine, Accuracy.
Abstract: We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by International Society for Photogrammetry and Remote Sensing (ISPRS) commision, were used to compare the performance of MHC with the average total error and average Cohen ' s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58705
Title: Assessing Lidar Accuracy with Hexagonal Retro-Reflective Targets
Author: Roberto Canavosio-Zuzelski, James Hogarty, Craig Rodarmel, Mark Lee, Aaron Braun.
Editor: Russell G Congalton
Year: 2013
Publisher: ESRI
Source: Centre for Ecological Sciences
Reference: Photogrammetric Engineering & Remote Sensing Vol. 79(no. 7), pp. 663-670 (2013)
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Lidar Accuracy, Hexagonal Retro-Reflective Targets, terrain information.
Abstract: Airborne lidar systems have the potential to produce extremely accurate terrain information at high spatial densities. However, to meet stringent accuracy requirements and minimize systematic errors, proper calibration of the lidar system is required. "Boresighting" is a technique used to correct for some of the these systematic errors and improve the spatial alignment of lidar passes. One challenge with boresighting is the mensuration accuracy to which a known point can be located in overlapping low density lidar strips. To address this issue, a raised Hexagonal Retro-Reflective Lidar ground Target (HRRT) is introduced. The target was optimized for precise mensuration at low point densities. The mensuration model is based on a least squares hexagon fitting approach and is proven to produce mensuation accuracies of 5cm horizontal and 4cm vertical (1-sigma) at ~2 pts/m?. To demonstrate a practical application, the HRRT ' s are used as tie points in a rigorous boresight adjustment to compute lidar strip misalignment parameters (roll, pitch, heading, and range bias). The adjustment results show that accurate boresight parameters are recovered along with their associated uncertainities.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58704
Title: Utility of a Wavelet Transform for LAI Estimation Using Hyperspectral Data.
Author: Asim Banskota, Randoiph H Wynne, Shawn P Serbin, Nilam Kayastha, Valerie A Thomas, Philip A Townsend.
Editor: Russell G Congalton
Year: 2013
Publisher: ESRI
Source: Centre for Ecological Sciences
Reference: Photogrammetric Engineering & Remote Sensing Vol. 79(no. 7), pp. 653-662 (2013)
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Utility, Wavelet Transform, LAI Estimation, Hyperspectral Data.
Abstract: We employed the discrete wavelet transform to reflectance spectra obtained from hyperspectral data to improve estimation of LAI in temperate forests. We estimated LAI for 32 plots across a range of forest types in Wisconsin using hemispherical photography. Plot spectra were extracted from AVIRIS data and transformed into wavelet features using the Haar wavelet. Separately, subsets of spectral bands and the Haar features selected by a genetic algorithm were used as independent variables in linear regressions. Models using wavelet coefficients explained the most variance for both broadleaf plots (R?=0.90 for wavelet features versus R?=0.80 for spectral bands) and all plots independent of forest type (R?= 0.79 for wavelet features vs. R?=0.58 for spectral bands). The forest-type specific models were better than the models using all plots combined. Overall, wavelet features appear superior to band reflectances alone for estimating temperate forest LAI using hyperspectral data.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None
ID: 58703
Title: Land Subsidence Characteristics in Banding City, Indonesia as Revealed by Spaceborne Geodetic Techniques and Hydrogeological Observations.
Author: R S Chatterjee, Moh. Fifik Syafiuddin, Hasanuddin Z Abidin
Editor: Russell G Congalton
Year: 2013
Publisher: ESRI
Source: Centre for Ecological Sciences
Reference: Photogrammetric Engineering & Remote Sensing Vol. 79(no. 7), pp. 639-652 (2013)
Subject: Photogrammetric Engineering & Remote Sensing
Keywords: Land Subsidence Characteristics, Banding City, Indonesia, Spaceborne Geodetic Techniques, Hydrogeological Observations.
Abstract: Bandung, the capital city of West Java Province, Indonesia has been subsiding as reported by a series of Global Positioning Systems (GPS) observations and field evidence. In this work, an integrated satellite-based approach has been adopted using DINSAR and GPS observations to spatially delineate the subsidence-affected areas and cross-validate the subsidence rates using two collateral geodetic techniques. Multi-frequency DINSAR using C- and L-band SAR data facilitates to monitor land subsidence scenario in totality. C-band DINSAR has been found particularly useful to identify slowly subsiding areas with a sub-centimeter level of precision. Furthermore, the initial hypothesis that land subsidence in Bandung Basin has been occuring due to excessive ground water withdrawal has been established in this study. A predictive modelling approach has been adopted to estimate the rates of potential subsidence due to elastic and inelastic deformations of the aquifer and overlying strata in response to the lowering of groundwater level.
Location: TE 12 New Biology Building
Literature cited 1: None
Literature cited 2: None