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ID: 60600
Title: Localization of mobile laser scanner using classical mechanics.
Author: Ville, V. Lehtola, Juho-Pekka Virtanen, Antero Kukko, Harri Kaartinen, Hannu Hyyppa.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 25-29 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Mobile, Scanner, Platforms, Design, LIDAR, IMU, Localization, Trajectory.
Abstract: We use a single 2D laser scanner to 3D indoor environments, without any inertial measurement units or reference coordinates. The localization is done directly from the point cloud in an intrinsic manner compared to other state-of-the-art mobile laser scanning methods where external inertial or odometry sensors are employed and synchronized with the laser scanner. Our approach is based on treating the scanner as a holonomic system. A novel type of scanner platform, called VILMA, is designed and built to demonstrate the functionality of the presented approach. Results from flat-floor and non-flat-floor environments are presented. They suggest that intrinsic localization may be generalized for broader use.
Location: T E 15 New Biology Building.
Literature cited 1: Barber, D., Mills, J., Smith-Voysey, S., 2008. Geometric validation of a ground-based mobile laser scanning system. ISPRS J. Photogr. Remote Sens. 63 (1), 128-141. Bloch, A.M., 2003. Nonholonomic Mechanics and Control, vol. 24. Springer.
Literature cited 2: Bosse, M., Zlot, R., 2009. Continuous 3d scan-matching with a spinning 2d laser. In IEEE International Conference on Robotics and Automation, 2009 (ICRA ' 09), pp. 4312-4319, iD: 1. Bosse, M., Zlot, R., 2013. Place recognition using keypoint voting in large 3d lidar datasets. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 2677-2684, iD: 1

ID: 60599
Title: Seeing through shadow: Modelling surface irradiance for topographic correction of Landsat ETM+ data.
Author: Tobias Schulmann, Marwan Katurji, Peyman Zawar-Reza.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 14-24 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Topographic correction, Topographic shadow, Shadow correction, Radiative transfer, Complex terrain.
Abstract: Despite advances in remote sensing, retrieving surface properties at high resolutions in complex terrain is a major challenge. Slope and aspect as well as the topography surrounding a target impact surface insolution and lead to variability in calculated surface reflectance even for homogeneous landcover. Retrieval of surface reflectance is particularly problematic in case of topographic shading, where the total irradiation at the surface is a combination of diffuse irradiation and terrain-reflected irradiation from nearby slopes. To facilitate the retrieval of surface reflectance from high-resolution optical remote sensing, we have explored the feasibility of using a three dimensional radiative transfer code to stimulate gridded surface irradiance for a ~37 km2 area in the New Zealand Southern Alps. We have tested the sensitivity of simulated irradiance and calculated surface reflectance both in-and outside shaded areas to atmospheric aerosol content, surface albedo, atmospheric boundary layer structure and different sola spectra. Retrieved surface reflectance has been shown to be highly sensitive to atmospheric aerosols and surface albedo, particularly for areas shaded by topography. Not considering atmospheric aerosols in topographic correction can contribute 40 % to surface in shaded areas, even for wider valleys. Both factors should therefore be considered in topographic correction of satellite imagery, even for relatively aerosol-free atmospheres and low surface albedo. Topographic correction for the whole scene was performed with the model settings resulting in the smallest RMSD between surface reflectivity in shaded and unshaded areas of similar land cover. Topographic correction based on 3D radiative transfer simulations has proven to effectively remove topographic effects and almost equalize derived mean reflectance in -and outside shaded areas. While the effective removal of shadows likely requires a higher dynamic range than Landsat ' s ETM+ can offer, we suggest further evaluation of this approach in future studies at other sites and with other sensors.
Location: T E 15 New Biology Building.
Literature cited 1: Adeline, K., Chen, M., Briotter, X., Pang, S., Paparoditis, N., 2013.Shadow detection in very high spatial resolution aerial images: a comparative study .ISPRS J. Photogramm. Rem. Sens. 80, 21-38. Anderson, G., Clough, S., Kneizys, F., Chetwynd, J., Shettle, E., 1986. AFGL Atmospheric Constituent Profiles (0-120 k). Tech. Rep., Air Force Geophysics Laboratory.
Literature cited 2: Astar, G., Myneni, R., Choudhary, B., 1992. Spatial heterogeneity in vegetation canopies and remote sensing of absorbed photosynthetically active radation: a modeling study.Rem.Sens.Environ. 41 (2-3), 85-103. Balthazar, V., Vanacker, V., Lambin, E., 2012. Evaluation and parameterization of ATCOR3 topographic correction method for forestcover mapping in mountain areas. In.J.Appl.Earth Obs.Geoinform. 18, 436-450.

ID: 60598
Title: Compression strategies for LiDAR waveform cube.
Author: Grzegorz Jozkow, Charles Toth, Mihaela Quirk, Dorota Grejner-Brzezinska.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 1-13 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: LiDAR, Full-waveform, JPEG-2000 Standard, Decorrelation, Image compression, Principal component transform, Performance analysis.
Abstract: Full-waveform LiDAR (FWD) provides a wealth of information about the shape and materials of the surveyed areas. Unlike discrete data that retains only a few strong returns, FWD will have an increasingly well-deserved role in mapping and beyond, in the much desired classification in the raw data format. Full-waveform systems currently perform only the recording of the waveform data at the acquisition stage; the return extraction is mostly deferred to post-processing. Although the full waveform preserves most of the details of the real data, it presents a serious practical challenge for a wide use: much larger datasets compared to those from the classical discrete return systems. A top the need for more storage space, the acquisition speed of the FWD may also limit the pulse rate on most systems that cannot store data fast enough, and thus, reduces the perceived system performance. This work introduces a waveform cube model to compress waveforms in selected subsets of the cube, aimed at achieving decreased storage while maintaining the maximum pulse rate of FWD systems. In our experiments, the waveform cube is compressed using classical methods for 2D imagery that are further tested to assess the feasibility of the proposed solution. The spatial distribution of airborne waveform data is irregular; however, the manner of the FWD acquisition allows the organization of the waveforms in a regular 3D volumetric tomography scans. This study presents the performance analysis of several lossy compression methods applied to the LiDAR waveform cube, including JPEG-2000, and PCA-based techniques .Wide ranges of tests performed on real airborne datasets have demonstrated the benefits of the JEG-2000 Standard where high compression rates incur fairly small data degradation. In addition, theJPEG-2000 standard-complaint compression implementation can be fast and, thus used in real-time systems, as compressed data sequences can be formed progressively during the waveform data collection. We conclude from our experiments that 2D image compression strategies are feasible and efficient approaches, thus they might be applied during the acquisition of the FWD sensors.
Location: T E 15 New Biology Building.
Literature cited 1: Akkarakaran, S., Vaidyanathan, P.P., 2001. Filterbank optimization with convex objectives and the optimality of principal component forms. IEEE Trans.Signal Process. 49 (1), 100-114. Beraldin, J.-A, Blais, F., Lohr, U., 2010. Laser Scanning Technology. In: Vosselman, G., Mass, H.-G. (Eds). Airborne and Terrestrial Laser Scanning. Whiteeles Publishing, Dunbeath, pp. 1-42.
Literature cited 2: Biasizzo, A., Novak, F., 2013. Hardware accelerated compression of LiDAR data using FPGA devices. Sensors 13 (5), 6405-6422. Brillinger, D.R., 1975. Time Series: Data Analysis and Theory. Holt, Rinehart and Winston Inc, New York.

ID: 60597
Title: Remotely sensed surface temperature variation of an inland saline lake over the central Qinghai-Tibet Plateau.
Author: Ke Linghong, Song Chunqiao.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 157-167 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Qinghai-Tibet Plateau, Climate change, Surface water temperature, Lake, Siling Co, MODIS.
Abstract: Research on surface war temperature (SWT) variations in large lakes over the Qinghai-Tibet Plateau (QTP) has been limited by lack of in situ measurements. By taking advantage of the increased availability of remotely sensed observations, this study investigated SWT variation of Siling Co in central QTP by processing complete MODIS Land surface temperature (LST) images over the lake covering from 2001 to 2013. The temporal (diurnal, intra-annual and inter-annual) variations of Siling Co SWT as well as the spatial patterns were analyzed. The results show that on average from late December to mid-April the lake is in a mixing state of water analyzed. The results show that on average from late December to mid-April the lake is in a mixing state of water and ice and drastic diurnal temperature differences occur, especially along the shallow shoreline areas. The extent of spatial variations in monthly SWT ranges from1.25 ? C to 3.5 ?C, and particularly large at nighttime and in winter months. The spatial patterns of annual average of SWT were likely impacted by the cooling effect of river inflow from the west and eastside of the lake. The annual cycle o f spatial pattern of SWT is characterized by seasonal reversions between the shallow littoral regions and deep parts due to different heat capacity. Compared to the deep regions, the littoral shallow shoreline areas warms up quickly in spring and summer, and cool down drastically in autumn and winter, showing large diurnal, and seasonal variation amplitudes of SWT. Two cold belt zones in the western and eastern side of the lake and warm patches along the southwestern and northeastern shorelines are shaped by the combined effects of the lakebed topography and river runoff. Overall, the lake-averaged SWT increased by the combined effects of the lakebed topography and river runoff. Overall, the lake-averaged SWT increased at a rate of 0.26 ? C/decade during 2001-2013. Faster increase of temperature was found at nighttime (0.34? C/decade) and in winter and spring, consistent with the asymmetric warming pattern over land areas reported in prior studies. The rate of temperature increase over Siling Co is remarkably lower than that over Bangoin station, which is probably attributable to the large heat capacity of water and partly reflects the sensitive of alpine saltwater lake to climate change.
Location: T E 15 New Biology Building.
Literature cited 1: Adams, W.P., Prowse, T.D., 1981. Evolution and magnitude of spatial patterns in the winter cover of temperate lakes. Fennia-Int.J.Geogr. 159 (2), 343-359. Austin, J.A., Colman, S.M., 2007. Lake Superior summer water temperatures are increasing more rapidly than regional air temperatures: a positive ice-albedo feedback.Geophys.Res.Lett. 34 (6).
Literature cited 2: Balsamo, G., Dutra, E., Stepanenko, V.M., Viterbo, P., Miranda, P., Mironov, D., 2010. Deriving an effective lake depth from satellite lake surface temperature data: a feasibility study with MODIS data. Boreal Environ.Res. 15 (2). Bian, D., Yang, Z., Li, L., Chu., D., Zhu, G., Bianba, C., et al., 2006. The response of lake area change to climate variations in north Tibetan Plateau during last 30 years. Acta Geor.Sin.5, 007.

ID: 60596
Title: Evaluating the performance of new classifier-the GP-OAD: A comparison with existing methods for classifying rock type and mineralogy from hyperspectral imagery.
Author: Sven Schneider, Richard J. Murphy, Arman Melkumyan
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 145-156 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Hyperspectral, Absorption feature, Iron minerals, Vertical geology, Illumination conditions, Machine learning, Classification, Remote sensing.
Abstract: In this study, we compare three commonly used methods for hyperspectral image classification, namely Support Vector Machines (SVMs), Guassian Processes (GPs) and the Spectral Angle Mapper (SAM). We assess their performance in combination with different kernels (i.e. which use distance-based and angle-based metrics0. The assessment is done in two experiments, under ideal conditions in the laboratory and, separately, in the field (an operational open pit mine) using natural light. For both experiments independent training and test sets are used. Results show that GPs generally outperform the SVMs, irrespective of the kernel used. Furthermore, angle-based methods, including the Spectral Angle Mapper, outperform GPs and SVMs when using distance-based (i.e. a stationary) kernels in the field experiment. A new GP method using an angle-based (i.e. a non-stationary) kernel- the Observation Angle Dependent (OAD) covariance function-outperforms SAM and SVMs in both experiments using only a small number of training spectra. These findings show that distance-based kernels are more affected by changes in illumination between the training and test set than are angular-based methods/kernels. Taken together, this study shows that independent training data can be used for classification of hyperspectral data in the field such as in open pit mines, by using Bayesian machine-learning methods and non-stationary kernels such as GPs and OAD kernel. This provides a necessary component for automated classifications, such as autonomous mining where many images have to be classified without user interaction.
Location: T E 15 New Biology Building.
Literature cited 1: Alajlan, N., Bazi, Y., Alhichri, H., Othman, E., 2012. Robust classification of hyperspectral images based on the combination of supervised and unsupervised learning paradigms. In: Geoscience and Remote Sensing Symposium (IGARSS). 2012. IEEE International, pp. 1417-1420. Bazi, Y., Melgani, F., 2006.Toward an optimal SVM classification system for hyperspectral remote sensing images. Geosci.Remote Sens., IEEE Trans. 44 (11), 3374-3385.
Literature cited 2: Bazi, Y., Melgani,F., 2008. Classification o hyperspectral remote sensing images using guassian processes. In: Geoscience and Remote Sensing Symposium, 2008.IGARSS 2008. IEEE International, pp. II-1013-II-1016. Bazi, Y., Melgani, F., 2010. Guassian process approach to remote sensing image classification.Geosci.Remote Sens., IEEE Trans.48 (1), 186-197.

ID: 60595
Title: Domain adaptation for land use classification: A spatio-temporal knowledge reusing method.
Author: Yilun Liu, Xia Li.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 133-144 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Domain adaptation, Transfer learning, Land use classification, k-Nearest neighbours, TrAdaBoost, TrCbrBoost.
Abstract: Land use classification requires a significant amount of labeled data, which may be difficult and time consuming to obtain. On the other hand, without a sufficient number of training samples, conventional calssifiers are unable to produce satisfactory classification results. This paper aims to overcome this issue by proposing a new model, TrCrBoost, which uses old domain data to successfully train a classifier for mapping the land use types of target domain when new labeled data are unavailable. TrCrBoost adopts a fuzzy CBR (Case Based Reasoning) model to estimate the land use probabilities for the target (new) domain, which are subsequently used to estimate the classifier performance. Source (old) domain samples are used to train the classifier of a revised TrAdaBoost algorithm in which the weight o each sample is adjusted according to the classifier ' s performance. This method is tested using time-series SPOT images for land use classification. Our experimental results indicate that TrCbrBoost is more effective than traditional classification models, provided that sufficient amount of old domain data is available. Under these conditions, the proposed method is 9.19 % more accurate.
Location: T E 15 New Biology Building.
Literature cited 1: Aamodt, A., Plazza, E., 1994. Case-based reasoning: foundational issues, methodological variations, and system approaches. Al Commun, 7, 39-59. Awrangjeb, M., Ravanbakhsh, M., Fraser, C.S., 2010. Automatic detection of residential buildings using LIDAR data and multispectral imagery. ISPRS J. Photogram. Remote Sens.65, 457-467.
Literature cited 2: Awrangjeb, M., Zhang, C., Fraser, C.S., 2012. Building in complex scenes through effective separation of buildings from trees.Photogram.Eng.Rem.Sens.78, 729-745. Bennett, K.P., Demiriz, A., 1999. Semi-superised support vector machines.Adv.Neural Inf.Process.Syst., 368-374.

ID: 60594
Title: Multi-class geospatial object detection and geographic image classification based on collection of part detectors.
Author: Gong Cheng, Junwei Han, Peicheng Zhou, Lei Guo.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 119-132 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Geospatial object detection, Geographic image classification, Very-high-resolution (VHR), Remote sensing images, Part-based model, Collection of part detectors (COPD).
Abstract: The rapid development of remote sensing technology has facilitated us the acquisition of remote sensing images with higher and higher spatial resolution, but how to automatically understand the image contents is still a big challenge. In this paper, we develop a practical and rotation-invariant framework for multi-class geospatial object detection and geographic image classification based on collection of part detectors (COPD). The COPD is composed of set of representative and discriminative part detectors, where each part detector is a linear support vector machine (SVM) classifier used for the detection of objects or recurring spatial patterns within a certain range of orientation. Specifically, when performing multi-class geospatial object detection, we learnt a set of seed-based part detectors where each part detector corresponds to a particular viewpoint of an object class, so the collection of them provides a solution for rotation-invariant detection of multi-class objects. When performing geographic image classification, we utilize a large number of pre-trained part detectors to discovery distinctive visual parts from images and use them as attributes to represent the images. Comprehensive evaluations on two remote sensing image databases and comparisons with some state-of-the-art approaches demonstrate the effectiveness and superiority of the developed framework.
Location: T E 15 New Biology Building.
Literature cited 1: Aksoy, S., Koperski, K.Tusk, C., Marchisio, G., Tilton, J.C., 2005. Learning Bayesian classifiers for scene classification with a visual grammar.IEEE Trans.Geosci. Remote Sens. 43, 581-589. Aytekin, O., Erener, A., Ulusoy, I., Duzgun, S., 2012.Unsupervised building detection in complex urban environments from multispectral satellite imagery.Int.J.Remote Sens.43, 581-589.
Literature cited 2: Aytekin, O., Zongur, U. Halici, U., 2013. Texture-based airport runway detection. IEEE Geosci.Remote Sens.Lett. 10, 471-475. Bhagavathy, S., Manjunath, B.S., 2006. Modeling and detection of geospatial objects using texture motifs.IEEE Trans.Geosci.Remote Sens.44, 3706-3715.

ID: 60593
Title: An effective approach for gap-filling continental scale remotely sensed time-series.
Author: DanielJ.Weiss, PeterM. Atkinson, Samir Bhatt, Bonnie Mappin, Simon I. Hay, Perter W. Gething,
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 106-118 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Gap-filling, MODIS, EVI, LST, Africa.
Abstract: The archives of imagery and modeled data products derived from remote sensing programs with high temporal resolution provide powerful resources for characterizing inter-and intra-annul environmental dynamics. The impressive depth of available time-series from such missions (e.g., MODIS and AVHRR) affords new opportunities for improving data usability by leveraging spatial and temporal information inherent to longitudinal geospatial datasets. In this research we develop an approach for filling gaps in imagery time-series that result primarily from cloud cover, which is particularly problematic in forested equatorial regions. Our approach consists of two, complementary gap-filling algorithms and a variety of run-time options that allow users to balance competing demands of model accuracy and processing time. We applied the gap-filling methodology to MODIS Enhanced Vegetation Index (EVI) and daytime and nighttime Land Surface Temperature (LST) datasets for the African continent for 2000-2012, with a 1 km spatial resolution, and an 8-day temporal resolution .We validated the method by introducing and filling artificial gaps, and then comparing the original data with model predictions. Our approach achieved R2 values above 0.87 even for pixels within 500 km wide introduced gaps. Furthermore, the structure of our approach allows estimation of the error associated with each gap-filled pixel based on the distance to the non-gap pixels used to model its fill value, thus providing a mechanism for including uncertainty associated with the gap-filling process in downstream applications of the resulting datasets.
Location: T E 15 New Biology Building.
Literature cited 1: Addink, E.A., 1999. A comparison of conventional and geostatistical methods to replace clouded pixels in NOAA-AVHRR images. Int.J.Remote Sens. 20, 961-977. Bedard, F., Reichert, G., Dobbins, R., Trepanier, I., 2008. Evaluation of segment-based gap-filled Landsat ETM+ SLC-off satellite data for land cover classification in southern Saskatchewan, Canada.Int.J.Remote Sens.29, 2041-2054.
Literature cited 2: Borak, J.S., Jasinski, M.F., 2009. Effective interpolation of incomplete satellite derived leaf-area index time series for the continental United States.Agric.For. Meteorol. 149, 320-332. Chen, J., Zhu, X., Volgelmann, J.E., Gao, F., Jin, S, 2011. A simple and effective method for filling gaps in Landsat ETM+SLC-off images. Remote Sens.Environ, 115, 1053-1064.

ID: 60592
Title: On quantifying post-classification subpixel landcover changes.
Author: Jose L., Silvan-Cardenas, Le Wang.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 94-105 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Subpixel classification, Fractional landcover, Change matrix, Constrained least squares.
Abstract: The post- classification change matrix is well defined for hard classifications. However, for soft classifications, where partial membership of pixels to landcover classes is allowed, there is no single definition for such a matrix. In this paper, we argue that a natural definition of the post-classification change matrix for subpixel classifications can be done in terms of a constrained optimization problem, according to which the change matrix should allow an optimal prediction of the subpixel landcover fractions at the latest date from those of the earliest date. We first show that the traditional change matrix for crisp classification corresponds to the optimal solution of the unconstrained problem. Then, the formulation is generalized for subpixel classifications by incorporating certain constraints pertaining to desirable properties of a change matrix, thus resulting in a constrained least square (CLS) change matrix. In addition, based on intuitive criteria, a generalized product (GPROD) was parameterized in terms of an exponent parameter of the GPROD operator tends to infinity, one of the most commonly used methods for map comparison from subpixel fractions, namely the MINPROD composite operator, results. The three matrices (CLS, GPROD and MINPROD) were tested on both simulated and real subpixel changes derived from QuickBird and Landsat. TM images. Results indicated that, for small exponent values (0-0.5), the GPROD matrix yielded the lowest errors of estimated landcover changes, whereas the MINPROD generally yielded the highest errors for the same estimations.
Location: T E 15 New Biology Building.
Literature cited 1: Binaghi, E., Brivio, P.A., Ghezzi, P., Rampini, A., 1999. A fuzzy set-based assessment of soft classification. Pattern Recogn.Lett.20, 935-948. Canty.J.M., Nielsen, A.A., 2008. Automatic radiometric normalization of multitemporal satellite imagery with the iterativelly re-weighted MAD transformation. Remote Sens.Environ.112, 1025-1036.
Literature cited 2: Civco, D.L., 1989. Topographic normalization of landsat thematic mapper digital imagery. Photogramm.Eng.Remote Sens.55, 1303-1309. Cohen, J., 1960.Acoefficient aggrement for nominal scales.Educ.Psychol.Measur.20, 37-46.

ID: 60591
Title: Abrupt spatiotemporal land and water changes and their potential drivers in Poyang Lake, 2000-2012.
Author: Lifan Chen, Ryo Michishita, Bing Xu.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 85-93 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: MODIS, Time-series analysis, vegetation index, Signal decomposition, Trend breaks, Driving forces.
Abstract: Driven by various natural and anthropogenic factors, Poyang Lake, the largest freshwater lake in China has experienced significant land use/cover changes in the past few decades. The aim of this study is to investigate the spatial-temporal patterns of abrupt changes and detect their potential drivers in Poyang Lake, using time-series Moderate Resolution Imaging Spectroradiometer (MODIS 16-day maximum value composite vegetation indices between 2000 and 2012. The breaks for additive seasonal and trend (BFAST) method was applied to the smoothed time-series normalized difference vegetation index (NDVI), to detect the timing and magnitude of abrupt changes in the past 13 years, and the change patterns, including the distributions in timing and magnitudes of major abrupt trend changes between water bodies and land areas were clearly differentiated. Most water bodies had abrupt increasing NDVI changes between 2010 and 2011, caused by the sequential severe flooding and drought in the two years. In contrast, large parts of the surrounding land areas had abrupt decreasing NDVI changes. Large decreasing changes occurred around 2003 at the city of Nanchang, which were driven by urbanization. These results revealed spatial-temporal land cover changing patterns and potential drivers in the wetland ecosystem of Poyang Lake.
Location: T E 15 New Biology Building.
Literature cited 1: Chan, K.K.Y., Xu, B. 2013. Perspective on remote sensing change detection of Poyang Lake wetland. Ann.Gis 19, 231-243. Chen, J., Jonsson, P., Tamura, M., GU, Z., Matsushita, B., Eklundh, L., 2004. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter, Remote Sens.Environ. 91, 332-344.
Literature cited 2: Chu, C., -S.J., Hornik, K., Kaun, C.-M., 1995. MOSUM tests for parameter constancy. Biometrika 82, 603-617. Cleveland, R.B. Cleveland, W.S., McRae, J.E., Terpenning, I., 1990.STL: a seasonal-trend decomposition procedure based on loess.J.Off.Statist.6, 3-73.

ID: 60590
Title: Assessing integration of intensity, polarimetric scattering, interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification.
Author: Huiran Jin, Giorgos Mountrakis, Stwephen V. Stehman.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 70-84 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: ALOS/PALSAR, Dual polarization, Feature synergy, Land cover classification, Stratified sampling, Accuracy assessment.
Abstract: Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7 % Producer ' s and user ' s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.
Location: T E 15 New Biology Building.
Literature cited 1: Almeida-Filho, R., Shimabukuro, Y.E., Rosenqvist, A, Sanchez, G.A., 2009. Using dual-polarized ALOS PALSAR data for detecting new fronts of deforestation in the Brazilian Amazonia.Int.J.Remote Sens. 30, 3735-3743. Askne, J., Santoro, M., Smith, G., Fransson, J.E.S., 2003. Multitemporal repeat-pass SAR interferometry of boreal forests.IEEE Trans.Geosci.Remote Sens.41, 1540-1550.
Literature cited 2: Baghdadi, N., Boyer, N., Todoroff, P., Hajj, M.E., Begue, A., 2009. Potential of SAR sensors Terra SAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on reunion island. Remote Sens.Environ.113, 1724-1738. Bamler, R., Hartl, P. 1998. Synthetic aperture radar interferometry. Inverse Prob.14, 1-54.

ID: 60589
Title: Accuracy assessment of airborne photogrammetrically derived high-resolution digital elevation models in a high mountain environment.
Author: Johann Muller, Isabelle Gartner-Roer, Patrick Thee, Christian Ginzler.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 58-69 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Photogrammetry, Accuracy assessment of DEM, High resolution airborne photogrammetry, High resolution DEM, High mountain environment.
Abstract: High-resolution digital elevation models (DEMs) generated by airborne remote sensing are frequently used to analyze landform structures (monotemporal) and geomorphological processes (multitemporal) in remote areas or areas of extreme terrain. In order to assess the quantify such structures and processes it is necessary to know the absolute accuracy of the available DEMs. This study assesses the absolute vertical accuracy of DEMs generated by the High Resolution Stereo Camera-Airborne (HRSC-A), the Leica Air-borne Digital Sensors 40/80 (ADS40 and ADS80) and the analogue camera system RC30. The study area is located in the Turtmann valley. Valais, Switzerland, a glacially and periglacially formed hanging valley stretching from 2400 m to 3300 m a.s.I. The photogrammetrically deirved DEMs are evaluated against geodetic field measurements and an airborne laser scan (ALS). Traditional and robust global and local accuracy measurements are used to describe the vertical quality of the DEMs, which show a non Guassian distribution of errors. The results show that all four sensor systems produce DEMs with similar accuracy despite their different setups and generations. The ads40 and ads80 (both with a ground sampling distance of 0.50 m) generate the most accurate DEMs in complex high mountain areas with a RMSE of 0.8 m and NMAD of 0.6 m. They also show the highest accuracy relating to flying height (0.14 %). The pushbroom scanning system HRSC-A produces a RMSE and 1.03 m and a NMAD of 0.83 m (0.21 %) accuracy of the flying height and 10 times of the ground sampling distance). It is also shown that performance of the DEMs strongly depends on the inclination of the terrain. The RMSE of areas up to an inclination <40 ? is better than 1 m. In more inclined areas the error and outlier occurrence increase fo all DEMs. This study shows the level of detail to which airborne stereoscopically derived DEMs can reliably be used in high mountain environments. All four sensor systems perform similarly in flat terrain.
Location: T E 15 New Biology Building.
Literature cited 1: Abermann, J., Fischer, A., Laqmbrecht, A., Geist, T., 2010. On the potential of very high-resolution repeat DEMs in glacial and periglacial environments. The Cryosphere 4 (1), 53-65. http://dx.doi.org/10.5194/tc-4-53-2010. Aguilar, F.J., Aguilar, M.A., 2007. Accuracy assessment of digital elevation models using a non-parametric approach.IntJ. Geograph.Inf. Sci 21 (6), 667-686.http://dx.doi.org/10.1080/13658810601079783.
Literature cited 2: Albertz, J., Scholten, FG. Ebner, H., Heipke, C., Neukum, G., 1992. The camera experiments HRSC and WAOSS on the Mars 94 mission.Int.Arch.Photogrammetry Remote Sens.29 (Part B1), 130-137. Artuso, R., Bovet, S., Streilein, A., 2003. Practical Methods for the Verification of a countrywide terrain and surface modes, In: Mass, H., Vosselman, G., Streilein, A. (Eds). Proceedings of the ISPRS working group III/3 workshop 3-D reconstruction from airborne laser scanner and InSAR data, Dresden, Germany, 8-10 October.

ID: 60588
Title: A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada.
Author: Junjie Zhang, Gunho Sohn, Mathieu Bredif.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 44-57 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: LiDAR, Forestry, Single tree detection, Local maxima filtering, Marker-controlled watershed segmentation, Stochasrtic model, Energy minimization, MCMC.
Abstract: This study presents a hybrid framework for single tree detection from airborne laser scanning (ALS) data by integrating low-level image processing techniques into a high-level probabilistic framework. The proposed approach modeled tree crowns in a tree plot as a configuration of circular objects. We took advantage of low-level image processing techniques to generate candidate configurations from the canopy height model (CHM): the treetop positions were sampled within the over-extracted local maxima via local maxima filtering, and the crown sizes were derived from marker-controlled watershed segmentation using corresponding treetops as markers. The configuration containing the best possible set of detected tree objects was estimated by a goal optimization solver. To achieve this, we introduced a Gibbs energy, which contains a data term that judges the fitness of the objects with respect to the data, energy was then embedded into a Markov Chain Monte Carlo (MCMC) dynamics coupled with a simulated annealing to find its global minimum. In this research, we also proposed a Monte Carlo-based sampling method for parameter estimation. We tested the method on a temperate mature coniferous forest in Ontario, Canada and also on simulated coniferous forest plots with different degrees of crown overlap. The experimental results showed the effectiveness of our proposed method, which was capable of reducing the commission errors produced by local maxima filtering, thus increasing the overall detection accuracy by approximately 10 % on all of the datasets.
Location: T E 15 New Biology Building.
Literature cited 1: Andersen, H.-E, Reutebuch, S.E., Schreuder, G.F., 2002. Bayesian object recognition for the analysis of complex forest scenes in airborne laser scanner data. Int. Arch.Photogrammetry Remote Sens., 35-41. Bortolot, Z.J., Wyne, R.H., 2005. Estimating forest biomass using small footprint LiDAR data: an individual tree-based approach that incorporates training data. ISPRS J. Photogrammetry Remote Sens 59, 342-360.
Literature cited 2: Brandtberg, T., 2007 .Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar.ISPRS J. Photogrammetry Remote Sens. 61, 325-340. Brandtberg, T., Walter, F., 1998. Automated delineatin of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis. Mach. Vis. Appl. 11, 64-73.

ID: 60587
Title: A hybrid method for optimization of the adaptive Goldstein filter.
Author: Mi Jiang, Xiaoli Ding, Xin Tian, Rakesh Malhotra, Weixue Kong.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 29-43 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Interferometric synthetic aperture radar, (InSAR), Phase standard deviation (STD), Iteration, Adaptive Goldstein filter.
Abstract: The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under-or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal non-linear model to determine alpha. In addition, an iteration is also merged in to the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.
Location: T E 15 New Biology Building.
Literature cited 1: Baran, I., Stewart, M.P., Kampes, B.M., Perski, Z., Lilly, P., 2003. A modification to the Goldstein radar interferogram filter. Geoscience and Remote Sensing, IEEE Transactions on 41, 2114-2118. Baumgartner, W., Wei?, P. Schindler, H., 1998. A nonparametric test for the general two-sample problem. Biometrics, 1129-1135.
Literature cited 2: Chen, C.W., 2001. Statistical-cost network-flow approaches to two-dimensional phase unwrapping for radar interferometry, ph.D, thesis, Stanford University. Deledalle, C.-A, Denis, L., Tupin, F., 2011. NL-InSAR: Nonlocal interferogram estimation. Geoscience a remote Sensing, IEEE Transactions on 49, 1441-1452.

ID: 60586
Title: Hybrid region merging method for segmentation of high-resolution remote sensing images.
Author: Xueliang Zhang, Pengfeng Xiao, Xuezhi Feng, Jiangeng Wang, Zuo Wang.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 19-28 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: High-resolution remote sensing, Image segmentation, Region merging, Graph model, Object-based image analysis.
Abstract: Image segmentation remains a challenging problem for object-based image analysis. In this paper, a hybrid region merging (HRM) method is proposed to segment high-resolution remote sensing images.HRM integrates the advantages of global-oriented a local-oriented region merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region, which provides an elegant way to avoid the problem of starting point assignment and to enhance the optimization ability for local-oriented region merging. During the region growing procedure, the merging iterations are constrained within the local vicinity, so that the segmentation is accelerated and can reflect local context, as compared with the global-oriented method. A set of high-resolution remote sensing image is used to test the effectiveness of the HRM method, and three region-based remote sensing images is used t o test the effectiveness of the HRM method, and three region-based remote sensing image segmentation methods are adopted for comparison, including the hierarchical stepwise optimization (HSWO) method, the local-mutual best region merging (LMM) method, and the multiresolution segmentation (MRS) method embedded in eCognition Developer software. Both the supervised evaluation and visual assessment show that HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM performs better than HSWO and LMM by combining both their advantages. The segmentation results of HRM and MRS are visually comparable, but HRM can describe objects as single better than MRS and the supervised and unsupervised evaluation results further prove the superiority of HRM.
Location: T E 15 New Biology Building.
Literature cited 1: Adams, R., NBischof, L., 1994. Seeded region growing. IEEE Trans.Pattern Anal. Mach. Intell. 16 (6), 641-647. Akcay, H.G., Aksoy, S., 2008. Automatic detection of geospatial objects using multiple hierarchical segmentations. IEEE Trans.Geosci.Remote Sens .46 (7), 2097-2111.
Literature cited 2: Albrtecht, F., 2008. Assessing the spatial accuracy of object-based image classifications. In: Geospatial Crossroads @Gl_Forum 08.Proceedings of the Geoinformatics Forum Salzburg Wichmann Verlag. Heidelberg, pp. 11-20. Arbelaz, P., Maire, M., Fowlkes, C., Malik, J., 2011. Contour detection and hierarchical image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 33 (5), 898-916.