Enter records

ID: 60605
Title: A rigorous cylinder-based self-calibration approach for terrestrial laser scanners.
Author: Ting On Chan, Derek D. Lichti, David Belton
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 84-99 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Cylinder, Laser scanning, Geometric calibration, Close range, Accuracy, Correlation.
Abstract: Existing self-calibration methods for terrestrial laser scanners are predominantly point-based and plane-based. In this paper, we present a new cylinder-based self calibration method with its variants for several scanners having different architectures and scanning mechanisms. The method not only increases the flexibility of in situ self-calibration, but also its rigor because of reduced functional dependencies between adjustment parameters. Based on the analysis of linear dependencies between columns of the design matrices for both the cylindrical and planar models, it is shown that using the vertical cylindrical model is advantageous over using the planar model as some high linear dependencies can be avoided. The proposed method and its variants were first applied to two simulated datasets, to compare their effectiveness, and then to three real datasets captured by three different types of scanners are presented: a Faro focus 3D (a phase-based panoramic scanner); a Velodyne HDL-32E (a pulse-based multi spinning beam scanner); and a Leica ScanStation C10 ( a dual operating-mode scanner). The experimental results show that the proposed method can properly estimate the additional parameters with high precision. More importantly, no high correlations were found between the additional parameters and other parameters when the network configuration is strong. The overall results indicate that the proposed calibration method is rigorous and flexible.
Location: T E 15 New Biology Building.
Literature cited 1: Abbas, M.A., Lichti, D., Chong, A.K, Setan, H., Majid, Z., 2014. An on-site approach for the self-calibration of terrestrial laser scanner. Measurement 52, 111-123. Atanacio-Jimenez.G., Hurtado-Ramos, J.B., Gonzalez-Barbosa, R., 2011. LiDAR Velodyne HDL-64 E calibration using pattern planes. Int.J.Adv.Robotic Syst.8 (5), 70-82.
Literature cited 2: Cabo, C., Ordonez, C., Garcia-Cortes, S., Martinez, J., 2014. An algorithm for automation detection of pole-like street furniture objects from mobile laser scanner point clouds.ISPRS J.Photogram.Remote Sens. 87, 47-56. Chan, T.O., Lichti, D.D., 2012. Cylinder-based self-calibration of a panoramic terrestrial laser scanner. Int.Arch.Photogram.RTemote Sens.Spatial Info.Sci.39 (PartB5) 169-174.

ID: 60604
Title: Estimation and analysis of gross primary production of soybean under various management practices and drought conditions.
Author: Pradeep Wagle, Xiangming Xiao, Andrew E. Suyker.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 70-83 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Gross primary production, Light use efficiency, Remote sensing, Vapor pressure deficit, Vegetation indices, Vegetation photosynthesis model.
Abstract: Gross primary production (GPP) of croplands may be used to quantify crop productivity and evaluate a range of management practices. Eddy flux data from three soybean (Glycine max L) fields under different management practices (no-till vs till; rainfed vs.irrigated) and Moderate Resolution Imaging Spectroradiometer (MODIS) derived vegetation indices (VIs) were used to test the capabilities of remotely sensed VIs and soybean phenology to estimate the seasonal dynamics of carbon fluxes. The modeled GPP (GPPVPM) using vegetation photosynthesis model (VPM) was compared with GPP (GPPEC) estimated from eddy covariance measurements. The VIs tracked soybean phenology well and delineated the growing season length (GSL), which was closely related to carbon uptake period (CUP, R2=0.84), seasonal sums of net ecosystem CO2 exchange (NEE, R2=0.78), and GPPEC (R2=0.54).Land surface water index (LSWI) tracked drought-impacted vegetation well, as the LSWI values were positive during non-drought periods and negative during severe droughts within the soybean growing season. On seasonal scale, NEE of the soybean sites ranged from -37 to -264 g Cm-2. The result suggests that rainfed soybean fields needed about 450-500 mm of well-distributed seasonal rainfall to maximize the net carbon sink. During non-drought conditions, VPM accurately estimated seasonal dynamics and interannual variation of GPP of soybean under different management practices. However, some large discrepancies between GPPVPM and GPPEC were observed under drought conditions as the VI did not reflect the corresponding decrease in GPPEC. Diurnal GPPEC dynamics showed a bimodal distribution with a pronounced midday depression at the period of higher water vapor pressure deficit (>1.2 kPa). A modified Wscalar based on LSWI to account for the water stress in VPM helped quantify the reduction in GPP during severe drought and the model ' s performance improved substantially. In conclusion, this study demonstrates the potential of integrating vegetation activity through satellite remote sensing with ground-based flux and climate data for a better understanding and upscalling of carbon fluxes of soybean croplands.
Location: T E 15 New Biology Building.
Literature cited 1: Angers, D., Bolinder, M., Carter, M., Gregorich, E., Drury, C., B., Voroney, R., Simard, R., Donald, R., Beyaert, R., 1997. Impact of tillage practices on organic carbon and nitrogen storage in cool, humid soils of eastern Canada.Soil Till.Res. 41, 191-201. Baker, J., Griffs, T., 2005. Examining strategies to improve the carbon balance of corn/soybean agriculture using eddy covariance and mass balance techniques. Agric.Forest Meteorol.128, 163-177.
Literature cited 2: Baldocchi, D., Flage, E., GU, L., Olson, R., Hollinger, D., Running, S., Anthoni, P., Bernhofer, C., Davis, K., Evans, R., 2001. FLUXNET: a new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities.Bull.Am.Meteorol.Soc82, 2415-2434. Brown, D.M., 1960.Soybean ecology.I.Development-temperature relationships from controlled environment studies.Agron.J.52, 493-496.

ID: 60603
Title: Estimating wide range Total Suspended Solids concentrations from MODIS 250-m imageries: An improved method.
Author: Shuisen Chen, Liusheng Han, Xiuzhi Chen, Dan Li, Lin Sun, Yong Li.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 58-69 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: MODIS-250 m, Remote Sensing, Total Suspended Solids (TSS) Wide range, Model.
Abstract: The objective of this study was to evaluate the performance of moderate resolution imaging spectroradiometer (MODIS) 250 m based TSS (Total Suspended Solids) retrieval model for developing the model of wide-range TSS concentrations. Using field spectral and TSS data (5.8-577.2 mg/l) collected from estuary and cost of China, we calibrated (N=40) and validated (N=20) the 6 TSS retrieval models in forms of single band (B1 of B2), difference of the two bands, sediment index, band ratio and log-ratio by the least squares technique. Results showed that the quadratic model of log-ratio is of the best accuracy (Calibration): R2 =0.752, N=40. Validation: TSS >31 mg/l, RMSE=37.9 mg/l, N=12; TSS? 31mg/l, RMSE =3.25 mg/l, N=8). We also found that the spectral log-ratio values increased with the increasing of TSS when TSS<31 mg/l, but decreased with increasing TSS when TSS.31 mg/l. The findings of quadratic curve vertex (log-ratio: ~1.58) in the proposed TSS model indicated that the spectral log-ratio may be sensitive to TSS of both low and high concentrations. We further applied the preferred model to retrieve TSS concentration from the MODIS 250-m images in turbid estuarial and clear coastal waters, and obtained a good mapping accuracy from the result (TSS)>31 mg/l:RMSE=38.6mg/l, MRE =24.7%, N=17; TSS ? 31mg/l :RMSE =2.1 mg/l, MRE=19.5 %, N=11). The vertex-based methodology of TSS model developed in the study is applicable in mapping TSS concentrations that are of a wide range variation in estuarine and coastal water bodies based on MODIS 250-m image, and as well to maximize its application potential due to high imaging frequency (two times during daytime) and appropriate space resolution of MODIS images. Therefore, the method can be used to detect the high temporal variability of TSS during tidal cycle. As such, the application of MODIS-water quality detection technology can be extended to coastal sediment movement.
Location: T E 15 New Biology Building.
Literature cited 1: Binding, C.E., Browers, D.G., Mitchelson-Jacob, E.G., 2005. Estimating suspended sediment concentrations from ocean colour measurements in moderately turbid waters; the impact of variable particle scattering properties. Remote Sens.Environ. 94, 373-383. Binding, C.E., Jerome, J.H., Bukata, R.P., Booty, W.G., 2010. Suspended particulate matter in Lake Erie derived from MODIS aquatic colour imagery.Int.J.Remote Sens. 31 (19), 5239-5255.
Literature cited 2: Binding, C.E., Greenberg, T.A., Bukata, R.P., 2012. An analysis of MODIS-derived algal and mineral turbidity in Lake Erie.J.Great Lakes Res. 38 (1), 107-116. Caroline, P., Guillem, C., Francis, G., David, D., Jean-Marie, FG. , Yolanda, S., 2010. Estimating turbidity and total suspended matter in the Adour River plume (South Bay of Biscay) using MODIS 250-m imagery. Cont.Shelf Res. 30, 379-392.

ID: 60602
Title: Hierarchical extraction of urban objects from mobile laser scanning data.
Author: Bisheng Yang, Zhen Dong, Gang Zhao, Wenxia Dai.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 45-57 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Mobile laser scanning, Multi-scale supervoxel, Segmentation, Object extraction, Classification, Filtering.
Abstract: Point clouds collected in urban scenes contain a huge number of points (e.g., billions), numerous objects with significant size variability, complex and incomplete structures, and variable point densities, raising great challenges for the automated extraction of urban objects in the field of photogrammetry, computer vision, and robotics. This paper addresses these challenges by proposing an automated method to extract urban objects robustly and efficiently. The proposed method generates multi-scale supervoxels from 3D point clouds using the point attributes (e.g., principal direction, colors) of the supervoxels .The proposed method defines a set of rules for merging segments into meaningful units according to types of urban objects and forms the semantic knowledge of urban objects for the classification of objects .Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by the saliency of the segments. Finally, the proposed method extracts and classifies urban objects in a hierarchical order ranked by saliency of segments. Experiments show that the proposed method is efficient and robust for extracting buildings, streetlamps, trees, telegraph poles, traffic signs, cars and enclosures from mobile laser scanning (MLS) point clouds, with an overall accuracy of 92. 3 %.
Location: T E 15 New Biology Building.
Literature cited 1: Achanta, R., Shaji, A., Smith, K., Lucchi, A., Fua, P., Susstrunk, S. 2012. SLIC superpixels comopared to state-of -the -art superpixel methods .IEEE Trans. Pattern Anasl.Mach.Intell. 34, 2274-2282. Aijazi, A.K., Checchin, P., Trassoudaine, L., 2013. Segmentation based classification of 3D urban point clouds: a super-voxel based approach with evaluation. Remote Sens. 5, 1624-1650.
Literature cited 2: Barnea, S., Filin, S., 2013 .Segmentation of terrestrial laser scanning data using geometry and image information. ISPRS J. Photogramm.Remote Sens.76, 33-48. Boyko, A., Funkhouser, T., 2011. Extracting roads from dense point clouds in large scale urban environment. ISPRS J. Photogramm.Remote Sens. 66, S2-S12.

ID: 60601
Title: A generic discriminative part-based model for geospatial object detection in optical remote sensing images.
Author: Wanceng Zhang, Xian Sun, Hongqi Wang, Kun Fu.
Editor: Derek Lichti
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 99 30-44 (2015)
Subject: Photogrammetry and Remote Sensing
Keywords: Geospatial object detection, Part-based model, Rotation invariance, Deformation feature.
Abstract: Detecting geospatial objects with complex structure has been explored for years and it is still a challenging task in high resolution optical remote sensing images (RSI) interpretation. In this paper, we mainly focus on the problem of rotation variance in detecting geospatial objects and propose a generic discriminative part-based model (GDPBM) to build a practical object detection framework. In our model, a geospatial object with arbitrary orientation is divided into several parts and represented via three terms: the appearance features, the spatial deformation and the rotation deformation features. The appearance features characterize the local patch appearance of the object and parts, and we propose a new kind of rotation invariant feature to represent the appearance using the local intensity gradients. The spatial deformation features capture the geometric deformation of parts by representing the relative displacements among parts. The rotation deformation features define the pose variances of the parts relative to the objects based on their dominant orientations. In generating the two deformation features, we introduce the statistic methods to encode the features in the category level. Concatenating the three terms of the features, a classifier based on the support vector machine is learned to detect geospatial objects. In the experiments, two datasets in optical RSI are used to evaluate the performance of our model and the results demonstrate its robustness and effectiveness.
Location: T E 15 New Biology Building.
Literature cited 1: Akcay, H.G., Aksoy, S., 2008. Automatic detection of geospatial objects using multiple hierarchical segmentations. IEEE Trans.Geosci.Remote Sens. 46 (7), 2097-2111. Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I., Heymen, M., 2004. Muliresolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information.ISPRS J. Photogramm.Remote Sens. 58 (3-4), 239-258.
Literature cited 2: Bhagavathy, S., Manjunath, B., 2006. Modeling and detection of geospatial objects using texture motifs.IEEE Trans.Geosci.Remote Sens.44 (12), 3706-3715. Bi, F., Zhu, B., Gao, L., Bian, M., 2012. A visual search inspired computational model for ship detection in optical satellite images. IEEE Geosci.Remote Sens.Lett. 9 (4), 749-753.

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.