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ID: 60585
Title: Evaluation of feature-based 3-d registration of probabilistic volumetric scenes.
Author: Maria I. Restrepo, Ali O. Ulusoy, Joseph L. Mundy.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 98 1-18 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Probabilistic 3-d modeling, Feature-based 3-d registration.
Abstract: Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the PVM to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of PVMs to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.
Location: T E 15 New Biology Building.
Literature cited 1: Arun, K.S., Huang, T.S., Blostein, S.D., 1987. Least-squares fitting of two 3-d point sets. IEEE Trans.PAMI Pattern Anal.Mach Intell. 9 (5), 698-700, http://ieeexplore.ieee.org/Ipdocs/epic03/wrapper.htm?arnumber=4767965. Besl.P.J., McKay, N.D., 1992. A method for registration of 3-D shapes.IEEE Trans. Pattern Anal. Mach. Intell. 14 (2), 239-256, <http://ieeexplore.ieee.org/xpl/article Details.jsp?tp=121791 & content Type=Journals+% 26 +Magazines &match Boolean%3Dtrue%26rows pewr Page %D30%26searchField%3DSearch_All %26queryText%3D%28_Title%3A%22A+method+for +registration of +3-D+shapes%22%29.
Literature cited 2: Biber, P., Strasser, W., 2003 .The normal distributions transform: a new approach to laser scan matching. In: IROS.IEEE, pp. 2743-2748, http://ieeexplore.ieee.org/Ipdocs/epic03/wrapper.htm?arnumber=1249285 Calaki, F., Ulusoy, A.O., Restrepo, M. Taubin, G., Mundy,J., 2012.High resolution surface reconstruction from multi-view aerial imagery. In: International Joint Conference on Pattern Recognition.pp.25-32.http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6374973&contentType=Conference+Publications&matchBoolean%3Dtrue%26rowsPerpage%3D30%26searchField%3dSearch_Alll%26queryText%3D%28p_Title%3A22High+Resolution+Surface+Reconstruction+from+Multi-view+Aerial+Imagery%22%29.

ID: 60584
Title: Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology.
Author: Jan U.H. Eitel, Troy S. Magney, Lee A. Vierling, Gunter Dittmar.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 229-240 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Foliar biochemistry, Leaf-level bidirectional reflection, distribution function (BRDFleaf) , Precision agriculture, Laser ratio index green, red, Normalized difference laser indexgreen, red, Light detection and ranging (LiDAR)
Abstract: Advanced technologies for improved nitrogen (N) fertilizer management are paramount for sustainably meeting future food demands. Green laser systems that measure pulse return int4ensity can provide more reliable information about foliar N than can traditional passive remote sensing devices during the critical early crop growth stages (e.g., before canopy closure when vegetation and soil signals are spectrally mixed ) when further decisions regarding N management can be made. However, current green laser systems are not designed for agricultural applications and only employ a single green laser wavelength, which may limit applications because many factors that require normalization techniques can affect pulse return intensity. Here, we describe the design of a tractor-mountable, green (532 nm)- and red (658 nm ) dual wavelength laser system and evaluate the potential of an additional red reference wave-length to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensity (RLRI). We hypothesized that such laser spectral indices aid in accounting for factors that confound laser based foliar N estimates including variations in leaf angle, measurement distance, soil returns, and mixed edge returns. Leaf level measurements in winter wheat (Triticum aestivum) revealed that the two laser spectral indices improved the relationship with foliar N (r2 > 0.71, RMSE < 0. 28 %) compared to the sole use of GLRI (r2 =0.47, RMSE = 0.38 %). Laboratory measurements also showed that laser spectral indices reduced the effect of measurement distance on laser readings and allowed leaf returns to be better separated from edge returns and soil returns. However, laboratory measurements showed that laser spectral indices did not account for variations in leaf angle, possibly explaining the weak relationships (r2 < 0.36, RMSE =0.49 % ) between foliar N and laser spectral indices observed when employing the laser system under field conditions. In fact, the strongest relationship at the field canopy level was shown for GLRI (r2 =0.65, RMSE = 0.37 %) alone. Laboratory measurements suggest that the better performance of GLRI compared to ratio-based laser spectral indices may result from pronounced differences in the leaf-level bidirectional reflectance distribution factor (BRDFleaf) between the green and red laser wavelengths, thus confounding leaf angle effects so that they are not cancelled when calculating laser spectral indices. This finding suggests that the small spot size of the laser pulses (? 5 mm diameter) interacts with BRDFleaf at very fine scales, therefore causing differential, wavelength-specific scattering effects. Additional study of BRDFleaf at the mm scale is therefore warranted, and should be carefully considered in future development and use of multi-wavelength laser systems for remot3ly sensing foliar biochemistry.
Location: T E 15 New Biology Building.
Literature cited 1: Adamsen, F., Pinter, P., Barnes, E., LaMorte, R., Wall, G., Leavitt, S., Kimball, B., 1999. Measuring wheat senescence with a digital camera. Crop Sci. 39, 719-724. Box, E., 1996. Plant functional types and climate at the global scale. J. Veg. Sci. 7, 309-320.
Literature cited 2: Bousquet, L., Lacherade, S., Jacquemoud, S., Moya, I., 2005. Leaf BRDF measurements and model for specular and diffuse components differentiation. Remote Sens. Environ. 98, 201-211. Breec3e, H.T., Holmes, R.A., 1971. Bidirectional scattering characteristics of healthy green soybean and corn leaves in vivo.Appl.Opt.10, 119-127.

ID: 60583
Title: A parametric model for classifying land cover and evaluating training data based on multi-temporal remote sensing data.
Author: Hunter Glanz, Luis Carvalho, Damien Sulla-Menashe, Mark A. Friedl.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 219-228 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Maximum likelihood estimation, Image classification.
Abstract: Time series of multispectral images are widely used to monitor and map land cover. However, high dimensionality and missing data present significant challenges for classification algorithms that use multi-temporal remotely sensed data. Further, generation and assessment of high quality training data, including detection of outliers and changed pixels in training data, is difficult. In this paper we present a new statistical framework that is based on a parametric model that enables a targeted principal component analysis (PCA) to reduce the dimensionality of multi-temporal remote sensing data. In doing so, the model provides a novel basis for land cover classification and evaluating the nature and quality of training data used for supervised classifications. The methodology we describe uses a Kronecker operator to reduce the spectral dimensionality of multi-temporal images. While preserving their temporal structure, thereby providing low-dimensional data is well-suited for classification and outlier detection problems. As part of our framework, we use an expectation-maximization method to impute missing data, and propose new metrics that characterize the representativeness and pixel-to-pixel homogeneity of training sites used for supervised classification. To evaluate our approach, we use data from NASA ' s Moderate Resolution Imaging Spectroradiometer (MODIS) and extracted more than 200 training sites where the land cover has been characterized from high spatial resolution imagery. The original input data was composed of 196 features (28 dates x 7 bands), and the PCA-based approach we describe captured 91 % of the variance, in these 7 bands, in 3 components. Results from maximum likelihood classification show that retained principal components successfully distinguish land cover classes from one another, with classification results that were comparable to supervised machine learning methods applied to the original MODIS data. Analysis of our site composition metrics show that they successfully characterize the homogeneity (or lack thereof) and representativeness of individual pixels and entire sites relative to other training sites in the same class.
Location: T E 15 New Biology Building.
Literature cited 1: Arino, O, Gross, D., Ranera, F., Bourg, L., Leroy, M., Bicheron, P., Latham, J., Di Gregorio, A., Brockman, C., Witt, R., Defourney, P., Vancutsem, C., Herold, M., Sambale, J., Archard, F., Durieux, L., Plummer, S., Weber, J. -L, 2007. GlobCover; Sensing Symposium, 2007. IGARSS 2007, IGARSS 2007. IEEE International. IEEE, pp 2412-2415 Barthoome, E., Belward, A., 2005. GLC2000: a new approach to global land cover mapping from Earth observation data. Int. J. Remote Sens 26 (9), 1959-1977.
Literature cited 2: Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320 (5882), 1444-1449. Bonan, G.B., Oleson, K.W., Vertenstein, M., Levis, S., Zeng, X., Dai, Y., Dickinson, R.E., Yang, Z., -L, 2002. The land surface climatology of the community land model coupled to the NCAR community climate model, J. Clim 15 (22), 3123-3149.

ID: 60582
Title: Semi-automatic verification of cropland and grassland using very high resolution mono-temporal satellite images.
Author: Petra Helmholz, Franz Rottensteiner, Christian Heipke.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 204-218 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Automation, GIS, Quality control, Verification, Mono-temporal, Satellite images.
Abstract: Many public and private decisions rely on geospatial information stored in a GIS database. For good decision making this information has to be complete, consistent, accurate and up-to-date. In this paper we introduce a new approach for the semi-automatic verification of a specific part of the, possibly outdated GIS database, namely cropland and grassland objects, using mono-temporal very high resolution (VHR) multispectral satellite images. The approach consists of two steps: first, a supervised pixel-based classification based on a Markov Random Field is employed to extract image regions which contain agricultural areas (without distinction between cropland and grassland), and these regions are intersected with boundaries of the agricultural objects from the GIS database. Subsequently, GIS objects labeled as cropland or grassland in the database and showing agricultural areas in the image are subdivided into different homogeneous regions by means of image segmentation, followed by a classification of these segments into either cropland or grassland using a Support Vector Machine. The classification result of all segments belonging to one GIS object are finally merged and compared with the GIS database label. The developed approach was tested on a number of images. The evaluation shows that errors in the GIS database can be significantly reduced while also speeding up the whole verification task when compared to a manual process.
Location: T E 15 New Biology Building.
Literature cited 1: Adv, Arbeitsgemeindshaft der Vermessungsverwaltungen der Lander der Blundersrepublik Deutschland, 2014: ATKIS- Amtlich Topographisch-Kartographisches Informationsystem, Gemany. http://www.adv-online.de (last visit 02.05.14) Amadasun, M., King, R., 1089. Textural features corresponding to textural properties. IEEE Trans. Syst. Man Cybern. 19 (5), 1264-1274.
Literature cited 2: Becker, C., Buschenfeld, T., Ostermann, 2009: Impacts of resolution pyramid on Gibbs random field classification. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 38 (Part 1-4-7/WS) (on CD-ROM). BKG (Bundesant fur Kartographie und Geodasie). 2009: Leistungsbeschreibung zum Vorhaben ?Aktualisierung des DLM-DE fur das Stichjahr 2009?, Version 1.0 from 12.02.2009, 27 pages.

ID: 60581
Title: Modeling spatiotemporal patterns of understory light intensity using airborne laser scanner (LiDAR)
Author: Shouzhang Peng, Chuanyan Zhao, Zhonglin Xu.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 195-203 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: LiDAR, 3D raytrace model, Forest-shaded area, Solar ray, Understory light, Qinghai spruce.
Abstract: This study described a spatiotemporally explicit 3D raytrace model to provide spatiotemporal patterns of understory light (light intensity in the forest floor and along the vertical gradient). The model was built based on voxels derived LiDAR and field investigation data, geographical information (elevation and location), and solar position (azimuth and altitude angles). We calculated the distance (L, in meters) traveled by solar ray in the crowns based on the model, and then calibrated and verified the light attenuation function using L based on Beer ' s law. L and the ratio of below canopy light intensity to above canopy light intensity showed obviously exponential relationship, with R2 = 0.94 and P < 0.05. Estimated and observed understory light intensities were obviously positively correlated, with R2 = 0.92 and P < 0.01, and the estimated values were slightly lower than the observed values. The spatiotemporal patterns of the light intensity in the forest floor were mapped with the respect to the solar position, and these patterns represented the variations in the forest-shaded area. The spatial patterns of the light intensity along vertical gradient were also mapped, and they showed strong variations. We concluded that L could account for the complex patterns of understory light environment with respect to the geographical and solar position variations. The 3D raytrace model can be integrated with ecological or hydrological models to resolve several issues, such as plant succession and competition, soil evaporation, plant transpiration, and snow-melt in the forest.
Location: T E 15 New Biology Building.
Literature cited 1: Alexander, C., Moeslund, J.E., Bocher, P.K., Arge, L., Svenning, J.C., 2013.Airborne laser scanner (LiDAR) proxies for understory light conditions. Rem. Sens. Environ. 134, 152-161. Ameztegui, A., Coll, L., Benavides, R., Valladares, F., Paquette, A., 2012. Understory light predictions in mixed conifer mountain forests: role of aspect-induced variation in crown geometry and openness. For. Ecol. Manage. 276, 52-61
Literature cited 2: Beland, M., Widlowski, J.L., Fournier, R.A., Cote, J.F., Verstraete, M.M., 2011. Estimating leaf area distribution in savanna trees from terrestrial LiDAR measurements.Agric.For.Meteorol. 151 (9), 1252-1266. Below, J.G., Nair, P.K.R., 2003. Comparing common methods for assessing understory light availability in shaded-perennial agroforestry systems. Agric. For. Meteorol. 114 (3-4), 197-211.

ID: 60580
Title: Method for orthorectification of terrestrial radar maps.
Author: Marion Jaud, Raphael Rouveure, Patrice Faure, Laure Moiroux-Arvis, Marie-Odile Monod.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 185-194 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: FMCW radar, Orthorectification, Relief effects, Radar cartography, Radar SLAM algorithm, DEM.
Abstract: The vehicle-based PELICAN radar system is used in the context of mobile mapping. The R-SLAM algorithm allows simultaneous retrieval of the vehicle trajectory and of the map of the environment. As the purpose of PELICAN is to provide a means for gathering spatial information, the impact of distortion caused by the topography is not negligible. This article proposes an orthorectification process to correct panoramic radar images and the consequent R-SLAM trajectory and radar map. The a priori knowledge of the area topography is provided by a digital elevation model. By applying the method to the data obtained from a path with large variations in altitude it is shown that the corrected panoramic radar images are contracted by the orthorectification process. The efficiency of the orthorectification process is assessed firstly by comparing R-SLAM trajectories to a GPS trajectory and secondly by comparing the position of Ground Control Points on the radar map with their GPS position. The RMS positioning errors moves from 5.56 m for the raw radar map to 0.75 m for the orthorectified radar map.
Location: T E 15 New Biology Building.
Literature cited 1: Curlander, J.C., McDonough, R., 1991. Synthetic aperture radar: Systems and signal processing. Wiley Series in Remote Sensing and Image Processing, vol.5. Wiley, New York. Domik, G., Raggam, J., Leberl, F., 1984. Rectification of radar images using stereo derived height models and simulations. Int.Arch.Photogram.Remote Sens.Spatial Information Sci. 25 (Part A3), 109-116.
Literature cited 2: Jaud, M., Rouveure, R., Faure, P., Monod, M.O., 2013. Methods for FMCW radar map georeferencing, ISPRS J. Photogram.Remote Sens. 84, 33-42. http://dx.doi.org/10.1016/j.isprs.2013.07.002. Liu, H., Zhao, Z., Jezek, K.C., 2004. Correction of positional errors and geometric distortions in topographic maps and DEMs using rigorous SAR simulation technique. Photogram. Eng. Remote Sens. 70 (9), 1031-1042.

ID: 60579
Title: On temporal consistency of chlorophyll products derived from three ocean- colour sensors.
Author: Robert J.W. Brewin, Frederic Melin, Shubha Sathyendranath, Francois Steinmetz, Andrei Chuprin, Mike Grant
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 171-184 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Phytoplankton, Ocean colour, Merging, Remote sensing, Chlorophyll-a
Abstract: Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002-2010 time period. By subsampling the monthly Chl-a among these three sensors over consistently, we found that the Chl-a time- series and Chl-a anomalies among sensors were significantly correlated for < 90% of the global ocean. These correlations were also relatively insensitive to the choice of tree Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for > 92 % of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.
Location: T E 15 New Biology Building.
Literature cited 1: Antoine, D., Morel, A., Gordon, H.R., Banzon, V.F., Evans, R.H., 2005. Bridging ocean color observations of the 1980s and 2000s in search of long-term trends. J. Geophys.Res. 110, C060009.http://dx.doi.org/10.1029/2004jC002620 AVISO, 2014a, MSLA-Maps of Sea Level Anomalies & Geostrophic Velocity Anomalies. http://www.aviso.oceanobs.com/en/data/products/sea-surface-height-products/global/msla.html.
Literature cited 2: AVISO, 2014b. Processing Steps and Data Levels.http://www.aviso.altimetry.fr/en/data/product-information/information-about-mono-and-multi-mission-procesing/processing-steps-and-data-levels.html Bealieu, C., Henson, S.A., Sarmiento, J.L., Dunne, J.P., S.C., Rykaczewski, R.R, Bopp, L., 2013. Factors challenging our ability to detect long-term trends in ocean chlorophyll. Biogeosciences 10, 2711-2724. http://dx.doi.org/10.5194/bg-10-2711-2013.

ID: 60578
Title: Sequential digital elevation models of active lava flows from ground-based stereo time-lapse imagery.
Author: M.R. James, S.Robson.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 160-170 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Photogrammetry, Volcanoes, Sequences, Terrestrial, Stereoscopic, DEM/DTM.
Abstract: We describe a framework for deriving sequences of digital elevation models (DEMs) for the analysis of active lava flows using oblique stereo-pair time-lapse imagery. A photo-based technique was favoured over laser-based alternatives due to low equipment cost, high portability and capability for network expansion, with images of advancing flows captured by digital SLR cameras over durations up to several hours. However, under typical field scale scenarios, relative camera orientations cannot be rigidly maintained (e.g. through the use of a stereo bar), preventing the use of standard stereo time-lapse processing software. Thus, we trial semi-automated DEM-sequence workflows capable of handling the small camera motions, variable image quality and restricted photogrammetric control that result from the practicalities of data collection at remote and hazardous sites. The image processing workflows implemented either link separate close-range photogrammetry and traditional stereo-matching software, or are integrated in a single software package based on structure-from motion (SfM). We apply these techniques in contrasting case studies from Kilauea volcano, Hawaii and Mount Etna, Sicily, which differ in scale, duration and image texture. On, Kilauea, the advance direction of thin fluid lava lobes was difficult to forecast, preventing good distribution of control. Consequently, volume changes calculated through the different workflows differed by ~10 % for DEMs (over ~30 m2 ) that were captured once a minute for 37 min. On Mt. Etna, more predictable advance (~3 m h-1 for ~ 3 h) of a thicker, more viscous lava allowed robust control to be deployed and volumetric change results were generally within 5% (over ~ 500 m2 ). Overall, the integrated SfM software was more straightforward to use and, under favourable conditions, produced results comparable to those from the close-range photogrammetric pipeline. However, under conditions with limited options for photogrammetric control, error in SfM-based surfaces may be difficult to detect.
Location: T E 15 New Biology Building.
Literature cited 1: Baldi, P., Bonvalot, S., Briole, P., Marsella, M., 2000. Digital photogrammetry and kinematic GPS applied to the monitoring of Vulcano Island, Aeolian Arc, Italy. Geophys. J. Int. 142 (3), 801-811. Brecher, H.H., Thompson, L.G., 1993. Measurements of the retreat of Qori Kalis glacier in the tropical Andes of Peru by terrestrial photogrammety. Photogramm.Eng.Remot.Sens. 59 (6), 1017-1022.
Literature cited 2: Brown, M., Lowe, D.G., 2005. Unsupervised 3D object recognition and reconstruction in unordered datasets. In: Fifth International Conference on 3-D Digital Imaging and Modeling, Proceedings, pp. 56-63. Cecchi, E., van Wyk de Vries, B, Lavest, J.M., Harris, A., Davies, M., 2003. N-view reconstruction: a new method for morphological modeling and deformation measurement in volcanology.J. Volcanol. Geoth.Res. 123 (1-2), 181-201.

ID: 60577
Title: Automatic building detection based on Purposive FastICA (PFICA) algorithm using monocular high resolution Google Earth images.
Author: Saman Ghaffarian, Salar Ghaffarian.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 152-159 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Building detection, Google Earth images, ICA, LUV color space, Monocular images, Purposive FastICA.
Abstract: This paper proposes an improved FastICA model named as Purposive FastICA (PFICA) with initializing by a simple color space transformation and novel masking approach to automatically detect buildings from high resolution Google-Earth imagery. ICA and FastICA algorithms are defined as Blind Source Separation (BSS) techniques for unmixing source signals using the reference data sets. In order to overcome the limitations of the ICA and FastICA algorithms and make them purposeful, we developed a novel method involving three main steps: 1-Improving the FastICA algorithm using Moore-Penrose pseudo inverse matrix model, 2-Automated seeding of the PFICA algorithm based on LUV color space and proposed simple rules to split image into three regions; shadow + vegetation, baresoil + roads and buildings, respectively, 3-Masking out the final building detection results from PFICA outputs utilizing the K-means clustering algorithm with two number of clusters and conducting simple morphological operations to remove noises. Evaluation of the results illustrates that buildings detected from dense and suburban districts with divers characteristics and color combinations using our proposed method have 88.6% and 85.5 % overall pixel-based precision performances, respectively.
Location: T E 15 New Biology Building.
Literature cited 1: Ahmadi, S., Zoej, M.J.V., Ebadi, H., Moghddam, H.A., Mohammadzadeh, A., 2010. Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours. Int. J. Appl. Earth Obs. Gooinf. 12 (3), 150-157 Aksoy, S., Yalniz, I.Z., Tasdemir, K., 2012. Automatic detection and segmentation of orchards using very high resolution imagery. IEEE Trans. Geosci. Remote Sens. 50 (8), 3117-3131.
Literature cited 2: Baltsavias, E.P., 2004. Object extraction and revision by image analysis using existing geodata and knowledge: current status and steps towards operational systems. ISPRS J. Photogr. Remote Sens. 58 (3-4), 129-151. Bayliss, J., Gualtieri, J.A., Cromp, R.F., 1998. Analyzing hyperspectral data with Independent Component Analysis. Proc. SPIE 3240, 133-143.

ID: 60576
Title: Tracking seasonal changes of leaf and canopy light use efficiency in a Phlomis fruticosa Mediterranean ecosystem using field measurements and multi-angular satellite hyperspectral imagery.
Author: Stavros Stagakis, Nikos Markos, Olga Sykioti, Aris Kyparissis.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 138-151 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Light use efficiency, PRI, Hyperspectral, CHRIS/PROBA, Viewing angle, Phlomis fruticosa.
Abstract: Numerous normalized difference spectral indices (NDSIs) derived from leaf measurements and CHRIS/PROBA hyperspectral and multi-angular satellite images were examined for their capacity to track seasonal variations of leaf (?leaf) and canopy (?can) light use efficiency of a Mediterranean phryganic ecosystem. A series of seasonal field ecophysiological measurements, i.e. leaf area index (LAI), leaf photosynthesis and leaf reflectance, were conducted on the Phlomis fruticosa shrubs at the days of CHRIS acquisitions over the study site. Leaf scale analysis confirmed background theory on the relationship of the photochemical reflectance index (PRI) with ?leaf and provided a detailed view of the wavelengths that can be used in PRI formulation for the specific species. In canopy scale analysis, PRI and some alternative formulations of this index based on CHRIS bands, presented the most significant relationships with ?can. Taking into account the functional relationship between ?can and chlorophyll content, a combination of the xanthophyll de-epoxidation band (531 nm) with 701 nm CHRIS band in a NDSI is suggested as an alternative to the original PRI formulation that could improve seasonal ?can estimations. The satellite observation geometry effects on the determination of ?can were not very intense for the studied ecosystem. However, the most effective viewing direction was proved to be the backward scattering, while zenith observations were the least efficient for the specific ecosystem, most probably due to increased background effects. Even though the sensitivity of the original PRI formulation to ?can was reduced in forward scattering viewing directions, when 531 nm xanthophyll de-epoxidation band was replaced with higher wavelength bands (540-550 nm), a strong PRI-?can relationship reappeared. These findings indicate possible shift of xanthophylls de-epoxidation signal according to viewing direction.
Location: T E 15 New Biology Building.
Literature cited 1: Adams, W.W., Demming-Adams, B., 1994. Carotenoid composition and down regulation of photosystem II in three conifer species during the winter. Physiol.Plant.92, 451-458. Asner, G.P., 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens. Environ. 64, 234-253.
Literature cited 2: Barton, C.V.M., North, P.R.J., 2001. Remote sensing of canopy light use efficiency using the photochemical reflectance index-model and sensitivity analysis. Remote Sens. Environ. 78, 264-273. BEAM Project, 2014. BEAM Earth Observation Toolbox and Development Platform, European Space Agency (ESA), Brockmann Consult. http://www.brockmann-consult.de/beam (accessed 17.01.14).

ID: 60575
Title: Semi-supervised classification for hyperspectral imagery based on spatial-spectral Label Propagation.
Author: Liguo Wang, Siyuan Hao, Qunming Wang, Ying Wang.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 123-137 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Hyperspectral imagery, Semi-supervised classification, Spatial-spectral graph, Label Propagation, Adaptive method, Gabor filter
Abstract: Graph-based classification algorithms have gained increasing attention in semi-supervised classification. Nevertheless, the graph cannot fully represent the inherent spatial-spectral Label Propagation is proposed for semi-supervised classification of hyperspectral imagery. The spatial information was used in two aspects: on the one hand, the spatial features extracted by a 2-D Gabor filter were stacked with spectral features; on the other hand, the width of the Guassian function, which was used to construct graph, was determined with an adaptive method. Subsequently, the unlabeled samples from the spatial neighbors of the labeled samples were selected and the spatial graph was constructed based on spatial smoothness. Finally, labels were propagated from labeled samples to unlabeled samples with spatial-spectral graph to update the training set for a basic classifier (e.g., support Vector Machine, SVM). Experiments on four hypespectral datasets show that the proposed Spatial-Spectral Label Propagation based on the SVM (SS-LPSVM) can effectively represent the spatial information in the framework of semi-supervised learning and consistently produces greater classification accuracy than the standard SVM, the Laplacian Support Vector Machine (LapSVM), Transductive Support Vector Machine (TSVM) and Spatial-Contextual Semi-Supervised Support Vector Machine (SCS3VM).
Location: T E 15 New Biology Building.
Literature cited 1: Bau, T.C., S., Healey, G., 2010. Hyperspectral region classification using a three-dimensional Gabor filer bank. IEEE Trans. Geosci. Remote Sens. 48 (9), 3457-3464. Belkin, M., Niyogi, P., 2005. Semi-supervised learning on manifolds.Machine Learning J. 56, 209-239.
Literature cited 2: Belkin, M., Niyogi, P., Sindhwani, V., 2006. Manifold regularization: a geometric framework for learning from labeled and unlabeled examples.J Machine Learn. Res 7, 2399-2434 Benediktsson, J.A., Palmason, J.A., Sveinsson, J., 2005. Classification of hyperspectral data from urban areas based on extended morphological profiles. IEEE Trans. Geosci. Remote Sens. 43 (3), 480-491.

ID: 60574
Title: Spectroscopic remote sensing of plant stress at leaf and canopy levels using the chlorophyll 680 nm absorption feature with continuum.
Author: Ieda Del ' Arco Sanches, Carlos Roberto Souza Filho, Raymond Floyd Kokaly.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 111-122 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Hyperspectral, Airborne sensor, Chlorophyll absorption feature, Continuum removal, Spectral feature analysis, Vegetation index.
Abstract: This paper explores the use of spectral feature analysis to detect plant stress in visible/near infrared wavelengths. A time series of close range leaf and canopy reflectance data of two plant species grown in hydrocarbon-contaminated soil was acquired with a portable spectrometer. The ProSpecTIR-VS air-borne imaging spectrometer was used to obtain far range hyperspectral remote sensing data over the field experiment. Parameters describing the chlorophyll 680 nm absorption feature (depth, width, and area) were derived using continuum removal applied to the spectra. A new index, the Plant Stress Detection Index (PSDI), was calculated using continuum -removed values near the chlorophyll feature centre (680 nm) and on the green-edge (560 and 575 nm). Chlorophyll feature ' s depth, width and area, the PSDI and a narrow-band normalized difference vegetation index were evaluated for their ability to detect stressed plants. The objective was to analyse how the parameters/indices were affected by increasing degrees of plant stress and to examine their utility as plant stress indicators at the remote sensing level (e.g. airborne sensor). For leaf data, PSDI and the chlorophyll feature area revealed the highest percentage (67-70%) of stressed plants. The PSDI also proved to be the best constraint for detecting the stress in hydrocarbon-impacted plants with field canopy spectra and airborne imaging spectroscopy data. This was particularly true using thresholds based on the ASD canopy data and considering the combination of higher percentage of stressed plants detected (across the thresholds) and fewer false-positives.
Location: T E 15 New Biology Building.
Literature cited 1: Analytical Spectral Devices (ASD), 2011a. FieldSpec Hi-Res portable spectroradiometer. http://www.asdi.com/products/fieldspec-3-hi-res-portable-spectroradiomerter (accessed 04.02.11). Analytical Spectral Devices (ASD), 2011b. Plant probe. http://www.asdi.com/acessories/plant-probe (accessed 08.02.11).
Literature cited 2: Carter, G.A., 1993. Responses of leaf spectral reflectance to plant stress. Am. J. Bot. 80 (3), 239-243. Carter, G.A., 1994. Ratios of leaf reflectance in narrow wavebands as indicators of plant stress. Int. J. Remote Sens. 15 (3), 697-703.

ID: 60573
Title: Applying object-based segmentation in the temporal domain to characterise snow seasonality.
Author: Jeffery A. Thompson, Brian G. Lees.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 98-110 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: MODIS, Object-based image analysis, Time-series, Alpine, Australia, Snow cover, Seasonality.
Abstract: In the context of a changing climate it is important to be able to monitor and map descriptors of snow seasonality. Because of its relatively low elevation range. Australia ' s alpine bioregion is a marginal area for seasonal snow-cover with high inter-annual variability. It has been predicted that snow-cover will become increasingly ephemeral within the alpine bioregion as warming continues. To assist the monitoring of snow seasonality and ephemeral snow-cover, a remote sensing method is proposed. The method adapted principles of object-based image analysis that have traditionally be used in the spatial domain and applied them in the temporal domain. The method allows for a more comprehensive characterisation of snow seasonality relative to other methods. Using high-temporal resolution (daily) MODIS image time-series, remotely sensed descriptors were derived and validated using in situ observations. Overall, moderate to strong relationships were observed between the remotely sensed descriptors of the persistent snow-covered period (start r = 0.70, p < 0.001; end r =0.88, p < 0.001 and duration r=0.88, p <0.001) and their in situ counterparts. Although only weak correspondence (r = 0.39, p < 0.05) was observed for the number of ephemeral events detected using remote sensing, this was thought to be related to differences in the sampling frequency of the in situ observations relative to the remotely sense observations. For 2009, the mapped results for the number of snow-cover events suggested that snow-cover between 1400 and 1799 m was characterized by a high numbers of ephemeral events.
Location: T E 15 New Biology Building.
Literature cited 1: Aitchison, C.W., 2001. The effect of snow cover on small animals. In: Jones, H.G., Pomeory, J.W., Walker, D.A., Hoham, R.W. (Eds), Snow Ecology: An Interdisciplinary Examination of Snow-covered Ecosystems. Cambridge University Press, Cambridge, pp. 229-265. Aplin, P., Smith, G.M., 2011.Introduction to object-based landscape analysis.Int.J.Geogr.Inf.Sci.25, 869-875.
Literature cited 2: Ault, T.W., Czajkowski, K.P., Benko, T., Coss, J., Struble, J., Spongberg, A., Templin, M., Gross, C., 2006. Validation of the MODIS snow product and cloud mask using student and NWS cooperative station observations in the Lower Great Lakes Region. Remote Sens. Environ. 105, 341-353. Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I., Heynen, M., 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for Gis-ready information. ISPRS J. Photogr. Remote Sens. 58, 239-258.

ID: 60572
Title: Accuracy in estimation of timber assortments and stem distribution-A comparison of airborne and terrestrial laser scanning techniques.
Author: Ville Kankare, Jari Vauhkonen, Topi Tanhuanpaa, Markus Holopainen, Mikko Vastaranta, Mariana, Joensuu, Anssi Krooks, Juha Hyyppa, Hannu Hyyppa, Ptteri Alho, Risto Viitala.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 89-97 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Stem distribution, Timber assortments, Timber quality, TLS, ALS, Individual tree.
Abstract: Detailed information about timber assortments and diameter distributions is required in forest management. Forest owners can make better decisions concerning the timing of timber sales and forest companies can utilize more detailed information to optimize their wood supply chain from forest to factory. The objective here was to compare the accuracies of high-density laser scanning techniques for the estimation of tree-level diameter distribution and timber assortments. We also introduce a method that utilizes a combination of airborne and terrestrial laser scanning in timber assortment estimation. The study was conducted in Evo, Finland. Harvester measurements were used as reference for 144 trees within a single clear-cut stand. The results showed that accurate tree-level timber assortments and diameter distributions can be obtained, using terrestrial laser scanning (TLS) or a combination of TLS and airborne laser scanning (ALS). Saw log volumes were estimate with higher accuracy than pulpwood volumes. The saw log volumes were estimated with relative root-mean -squared errors of 17.5 % and 16.8% with TLS and a combination of TLS and ALS, respectively. The respective accuracies for pulpwood were 60.1% and 59.3%. The differences in the bucking method used also caused some large errors. In addition, tree quality factors highly affected the bucking accuracy, especially with pulpwood volume.
Location: T E 15 New Biology Building.
Literature cited 1: Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. Int. Arch. Photogram .Remote Sens. 33 (B4/1: Part 4), 111-118. Brandtberg, T., Warner, T., Landenberger, R., McGraw, J., 2003. Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America. Remote Sens. Environ. 85, 290-303.
Literature cited 2: Breidenbach, J., Naesset, E., Lien, V., Gobakken, T., Solberg, S., 2010. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data. Remote Sens. Environ. 114, 911-924. Chandra, S., Sivaswamy, J., 2006. An analysis of curvature based ridge and valley detection. In: Proc. IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006. Toulouse, France, 14-19 May, 2006, pp. 737-740.

ID: 60571
Title: Modeling diurnal land temperature cycles over Los Angeles using downscaled GOES imagery.
Author: Qihao Weng, Peng Fu.
Editor: Derek Lichti
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: PHOTOGRAMMETRY AND REMOTE SENSING Vol 97 78-88 (2014)
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Land surface temperature, Urban heat island, Diurnal temperature cycle, Thermal downscaling, Data fusion, Temporal resolution.
Abstract: Land surface temperature is a key parameter for monitoring urban heat islands, assessing heat related risks, and estimating building energy consumption. These environmental issues are characterized by high temporal variability. A possible solution from the remote sensing perspective is to utilize geostationary satellites images, for instance, images from Geostationary Operational Environmental System (GOES) and Meteosat Second Generation (MSG). These satellite systems, however with coarse spatial but high temporal resolution (sub-hourly imagery at 3-10 km resolution), often limit their usage to meteorological forecasting and global climate modeling. Therefore, how to develop efficient and effective methods to disaggregate these coarse resolution images to a proper scale suitable for regional and local studies need be explored. In this study, we propose a least square support vector machine (LSSVM) method to achieve the goal of downscaling of GOES image data to half-hourly 1-km LSTs by fusing it with MODIS data products and shuttle Radar topography Mission (SRTM) digital elevation data. The result of downscaling suggests that the proposed method successfully disaggregated GOES images to half-hourly 1-km LSTs with accuracy of approximately 2.5 k when when validated against with MODIS LSTs at the same over-passing time. The synthetic LST datasets were further explored for monitoring of surface urban heat island (UHI) in the Los Angeles region by extracting key diurnal temperature cycle (DTC) parameters. It is found that the datasets and DTC derived parameters were more suitable for monitoring of daytime- other than nighttime-UHI. With the downscaled GOES 1-km LSTs, the diurnal temperature variations can be well be characterized. An accuracy of about 2.5 k was achieved in terms of the fitted results at both 1 km and 5 km resolutions.
Location: T E 15 New Biology Building.
Literature cited 1: Anderson, M.C., Allen, R.G., Morse, A., Kustas, W.P., 2012. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sens. Environ.122, 50-65. Buscail, C., Upegui, E., Viel, J.F., 2012. Mapping heatwave health risk at the community level for public health action. Int. J. Health Geographics 11, 38. http://dx.doi.org/10.1186/1476-072X-11-38
Literature cited 2: Carlson, T., 2007. An overview of the ?triangle method? for estimating surface evapotranspiration and soil moisture from satellite imagery. Sensors 7 (8), 1612-1629 Dominguez, A., Kleissl, J., Luvall, J.C., Rickman, D.L., 2011. High-resolution urban thermal sharpener (HUTS). Remote Sens. Environ. 115 (7), 1772-1780.