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ID: 60022
Title: Mineral mapping in the Meherabad area, eastern Iran, using the HyMap remote sensing data.
Author: Yusuf Eshqi Molan, Davood Refahi, Ali Hoseinmardi Tarashti.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 27 (B) 117-127 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: HyMap, Mineral mapping, Moving threshold.
Abstract: This study applies matched filtering on the HYMap airborne hyperspectral data to obtain the distribution map of alteration minerals in the Maherabad area and uses virtual verification to verify the results. This paper also introduces ?moving threshold? which tries to find an appropriate threshold value to convert gray scale images, produced by mapping methods, to target and background pixels. The Maherabad area, located in the eastern part of the Lut block, is a Cu-Au porphyry system in which quartz-sericite-pyrite, argillic and propylitic alteration are most common. Minimum noise fraction transform coupled with a pixel purity index was applied on the HyMap images to extract the endmembers of the alteration minerals, including kaolinite, montmorillonite, sericite (muscovite/illite), calcite, chlorite, epidote, and goethite. Since there was no access to any portable spectrometer and /or lab spectral measurements for the verification of the remote sensing imagery results, virtual verification achieved using the USGS spectral library and showed an agreement of 83.19%. The comparison between the results of the matched filtering and x-ray diffraction (XRD) analyses also showed an agreement of 56.13%.
Location: TE 15 New Biology Building
Literature cited 1: Berberian, M., King, G.C.P., 1981. Towards a paleogeography and tectonic evolution of Iran. Canadian Journal of Earth Sciences 18, 210-265. Berberian, M., Jackson, J.A., Qorashi, M., Khatib, M.M., Priestley, K., Talebian, M., Ghafuri-Ashtiani, M., 1999. The 1997 may of Zirkuh (Qaenat) earthquake (Mw7.2): faulting along the Sistan suture zone of eastern Iran. Geophysical Journal International 136, 671-694.
Literature cited 2: Berk, A., Ansderson, G.P., Acharya, P.K, Chetwynd, J.H., Bernstein, L.S., Shettle, E.P., Matthew, M.W., Adler-Golden, S.M., 2000. MODTRAN4 Users Manual. Air Force Research Laboratory, Space Vehicles Directorate, Air Force Material Command, Hanscom AFB, USA, pp.97. Bishop, J.L., Murad, E., 2005. The visible and infrared spectral properties of jarosite and alunite. American Mineralogist 90 (7), 1100-1107.

ID: 60021
Title: Beyond modern landscape features: New insights in the archaeological area of Tiwanaku in Bolivia from satellite data.
Author: Rosa Lasaponara, Nicola Masini.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 464-471 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Satellite, Archaeology, Tiwanaku, Aster, QuickBird, Spatial autocorrelation.
Abstract: The aim of this paper is to investigate the cultural landscape of the archaeological area of Tiwanaku (Bolivia) using multiscale, multispectral, and multitemporal, satellite data. Geospatial analysis techniques were applied to the satellite data sets in order to enhance and map traces of past human activities and perform a spatial characterization of environmental and cultural patterns. In particular, in the Tiwanaku area, the approach the approach based on local indicators of spatial autocorrelation (LISA) applied to ASTER data allowed us to identify traces of a possible ancient hydrographic network with a clear spatial relation with the well-known moat surrounding the core of the monumental area. The same approach applied to QuickBird data, allowed us to identify numerous traces of archaeological interest, in Mollo Kontu mound, less investigated than the monumental area. Some these traces were in perfect accordance with the results of independent studies, other were completely unknown. As a Whole, the detected features, composing a geometric pattern with roughly North-South orientation, closely match those of the other residential contexts at Tiwanaku. These new insights, captured from ASTER and QuickBird data processing, suggested new questions on the ancient landscape and provided important information for planning future field surveys and archaeogeophysical investigations.
Location: TE 15 New Biology Building
Literature cited 1: Aiazzi, B., Baronti, S., Selva, M., Improving component substitution pansharpening through multivariate regression of MS+ PAN data. IEEE Trans. Geosci. Remote Sens. 45 (10), 3230-3239. Anselin, L., 1995. Local indicators of spatial association LISA. Geogr. Anal. 27 (2), 93-115.
Literature cited 2: Argollo, J., Leocadio, T., Kolata, Al. L., Rivera, O., 1996. Geology, geomorphology, and soils of the Tiwanaku and Catari river basinbs. In: Kolata, A. (Ed.), Tiwanaku and its Hinterland: Archaeology and Paleoecology of an Andean Civilization, vol. I. Smithsonian Institution Press, Washington, DC, pp. 57-88. Blom, D.E., Janusek, J.W., Buikstra, J.E., 2003. A re-evaluation of human remains from Tiwanaku. In: Kolata, A.L., (Ed), Tiwanaku and Its Hinterland: Archaelogy and Paleoecology of an Andean Civilization, vol. 2. Smithsonian Institution Press, Washington, DC, pp. 435-448.

ID: 60020
Title: Semi-automatic detection of linear archaeological traces from orthorectified aerial images.
Author: Benedetto Figorito, Eufemia Tarantino
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 458-463 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Trace extraction, Multiphase ACM, Geospatial image processing
Abstract: This paper presents a semi-automatic approach for archaeological traces detection from aerial images. The method developed was based on the multiphase active contour model (ACM). The image was segmented into three competing regions to improve the visibility of buried remains showing in the image as crop marks (i.e. centuriations, agricultural allocations, ancient roads, etc). An initial determination of relevant traces can be quickly carried out by the operator by sketching straight lines close to the traces. Subsequently, tuning parameters (i.e. eccentricity, orientation, minimum area and distance from input line) are used to remove non-target objects and parameterize the detected traces. The algorithm and graphical user interface for this method were developed in a MATLAB environment and tested on high resolution orthorectified aerial images. A qualitative analysis of the method was lastly performed by comparing the traces extracted with ancient traces verified by archaeologists.
Location: TE 15 New Biology Building
Literature cited 1: Agapiou, A., Alexakis, D.D, Hadjimitsis, D.G., 2012. Spectral sensitivity of ALOS, ASTER, IKONOS, LANDSAT and SPOT satellite imagery intended for the detection of archaeological crop marks. International Journal of Digital Earth, 1-22. Ahmadi, S., Zoej, M., Ebadi, H., Moghaddam, H.A., Mohammadzadeh, A., 2010. Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours. International Journal of Applied Earth Observation and Geoinformation 12 (3) 150-157.
Literature cited 2: Alexakis, D., Sarris, A., Astaras, T., Albanakis, K., 2009. Detection of Neolithic settlements in Thessaly (Greece) through multispectral and hyperspectral satellite imagery. Sensors 9 (2), 1167-1187. Aqdus, S.A., Hanson, W.S, Drummond, J., 2012. The potential of hyperspectral and multi-spectral imagery to enhance archaeological cropmark detection: a comparative study. Journal of Archaeological Science. 39 (7), 1915-1924.

ID: 60019
Title: Urban metabolism and climate change: A planning support system.
Author: Ivan Blecic, Arnaldo Cecchini, Matthias Falk, Serena Marras, Dacvid R.Pyles, Donatella Spano, Giuseppe A.Trunfio
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 447-457 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Urban metabolism, Climate change, Urban sustainability, Cellular automata, CO2, Urban planning.
Abstract: Patterns of urban development influence flows of material and energy within urban settlements and exchanges with its surrounding. In recent years the quantitative estimation of the components of the so-called urban metabolism has increasingly attracted the attention of researchers from different fields. To contribute to this effort we developed a modeling framework for estimating the carbon exchanges together with sensible and latent heat fluxes and air temperature in relation to alternative land-use scenarios. The framework bundles three components: (1) a Cellular Automata model for the simulation of the urban land-use dynamics; (ii) a transportation model for estimating the variation of the transportation network load and (iii) the Advanced Canopy-Atmosphere-Soil Algorithm (ACASA) model tightly coupled with the mesoscale weather forecasting WRF. We present and discuss the results of an example application on the city of Florence.
Location: TE 15 New Biology Building
Literature cited 1: Batty, M., Xie, Y., 1994. From cells to cities. Environment and planning B, 31-48. Blecic, I., Cecchini, A., Trunfio, G.A., 2008. A software infrastructure for multiagent geosimulation applications. Lecture Notes in Computer Science 5072, 375-388.
Literature cited 2: Blecic, I., Cecchini, A., Trunfio, G.A., 2009. A general-purpose geosimulation infrastructure for spatial decision support. Transactions on computational Science 6, 200-218. Blecic, I., Cecchini, A., Trunfio, G.A., 2010. A Comparison of evolutionary algorithms for automatic calibration of constrained cellular automata. Lecture Notes in Computer Science 6016, 166-181.

ID: 60018
Title: Fisher- Shannon information plane analysis of SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) time series to characterize vegetation recovery after fire disturbance.
Author: Antonio Lanorte, Rosa Lasaponara, Michele Lovallo, Luciano Telesca.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 441-446 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Satellite time series, Fisher information measure, Shannon entropy, Fires, SPOT.
Abstract: The time dynamics of SPOT-VEGETATION Normalized Difference Vegetation Index (NDVI) time series are analyzed by using the statistical approach of the Fisher- Shannon (FS) information plane to assess and monitor vegetation recovery after fire disturbance. Fisher-Shannon information plane analysis allows us to gain insight in to the complex structure of a time series to quantify its degree of organization and order. The analysis was carried out using 10-day Maximum Value Composites of NDVI (MVC-NDVI) with a 1 km x 1 km spatial resolution. The investigation was performed on two test sites located in Galizia (North Spain) and Peloponnese (South Greece), selected for the vast fires which occurred during the summer of 2006 and 2007 and for their different vegetation covers made up mainly of low shrubland in Galizia test site and evergreen forest in Peloponnese. Time series of MVC-NDVI have been analyzed before and after the occurrence of the fire events. Results obtained for both the investigated areas clearly pointed out that the dynamics of the pixel time series before the occurrence of the fire is characterized by a larger degree of disorder and uncertainty; while the pixel time series after the occurrence of the fire are featured by a higher degree of organization and order. In particular, regarding the Peloponneso fire, such discrimination is more evident than in the Galizia fire. This suggests a clear possibility to discriminate the different post-fire behaviors and dynamics exhibited by the different vegetation covers.
Location: TE 15 New Biology Building
Literature cited 1: Allen, C.D., Savage, M., Falk, D.A., Suckling, K.F., Swetnam, T.W., Schulke, T., Stacey, P.B., Morgan, P., Hoffman, M., Klingel, J.T., 2002. Ecological restoration of Southwestern ponderosa pine ecosystems: a broad perspective. Ecological Applications 12, 1418-1433. Angulo, J.C., Anatolia, J., Sen, K.D., 2008. Fisher-Shannon plane and statistical complexity of atoms. Physics Letters A 372, 670-674.
Literature cited 2: Devroye, L., 1987. A course on Density Estimation. Birkhauser, Boston. Diaz-Delgado, R., Lloret, F., Pons, X., 2002. Satellite evidence of decreasing resilience in Mediterranean plant communities after recurrent wildfires. Ecology 83, 2293-2303.

ID: 60017
Title: Spatial data discretization methods for geocomputation.
Author: Feng Cao, Yong Ge, Jinfeng Wang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 432-440 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Geocomputation, Spatial data, Discretization, Spatial autocorrelation, Spatial heterogeneity.
Abstract: Geocomputation provides solutions to complex geographic problems. Continuous and discrete spatial data are involved in the geocomputational process; however, geocomputational methods for discrete spatial data cannot be directly applied to continuous or mixed spatial data. Therefore, discretization methods for continuous or mixed spatial data are involved in the process. Since spatial data has spatial features, such as association, heterogeneity and spatial structure, these features cannot be handled by traditional discretization methods. Therefore, this work develops feature-based spatial data discretization methods that achieve optimal discretization results for spatial data using spatial information implicit in those features. Two discretization methods considering autocorrelation of spatial data and the other is a supervised method considering spatial heterogeneity. Discretization processes of the two methods are exemplified using neural tube defects (NTD) for Heshun County in Shanxi Province, China. Effectiveness is also assessed.
Location: TE 15 New Biology Building
Literature cited 1: Ahlqvist, O., Keukelaar, J., Oukbir, K., 2000. Rough classification and accuracy assessment. International Journal of Geographical Information Science 14, 475-496. Ahlqvist, O., Keukelaar, J., Oukbir, K., 2003. Rough and fuzzy geographical data integration. International Journal of Geographical Information Science 17, 223-234.
Literature cited 2: Anselin, L., 1995. Local indicators of spatial association-LISA. Geographical Analysis 27, 93-115. Armstrong, M.P., Xiao, N.C., David, A., Bennett, D.A., 2003. Using genetic algorithms to create multicriteria class intervals for chropleth maps. Annals of the Association of American Geographers 93, 595-623.

ID: 60016
Title: Hyperion image analysis and linear spectral unmixing to evaluate the grades of iron ores in parts of Noamundi, Eastern India.
Author: T. Magendran, S. Sanjeevi.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 413-426 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Linear spectral unmixing, Hyperion, Spectral curves, Geochemistry, Iron ore grades, Noamundi.
Abstract: This paper reports the results of a study to differentiate iron ores in terms of their grades, using the hyperspectral (EO-1 Hyperion) image data, covering a mineralized belt in the Noamundi area, eastern India. The study involves hyperspectral data collection, pre-processing (reduction of atmospheric and solar flux effects), generation of spectral curves from the image for the iron ore deposits, extraction of key spectral parameters and linear spectral unmixing for mapping iron ore abundance. Spectral curves for iron ore deposits extracted from the Hyperion image pixels exhibit strong absorption at 850-900 nm and 2150-2250 nm wavelengths, which is typical of iron ores. The strength of the absorption features in the continuum removed spectra varies spatially in the image around the mining areas, indicating differences in composition/grade of the iron ores. Spectral parameters such as depth, width, area and wavelength position of the absorption features, derived from image spectra in the 850-900 nm and 2150-2250 nm regions, correlate well with the concentration of iron-oxide and alumina (gangue) in the ore samples obtained from the mine face. Well defined correlations are evident between the concentration of iron oxide and (i) the depth of NIR absorption feature (R2=0.883); (ii) the width of NIR absorption feature (R2=0.912); and (iii) the area of the NIR absorption feature and (R2=0.882). Further, the linear spectral unmixing resulted in an iron ore abundance map which, in conjunction with the image-and laboratory-spectra, helped in assessing the grades of iron ores in the study area. Thus, this study demonstrates the feasibility of discriminating grades of iron ores based on spectral information derived from spaceborne hyperspectral imagery.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J.B., Smith, M.O., Jhonson, P.E., 1986. Spectral mixture modeling: a new analysis of rock and soil types at the Viking Lander 1 site. Journal of geophysical Research 91, 8098-8112. Belanger, M.J., Miller, J.R., Boyer, M.G., 1995.Comparative relationships between some red edge parameters and seasonal leaf chlorophyll concentrations. Canadian Journal of Remote Sensing 21 (1), 16-21.
Literature cited 2: Boardman, J.W., Kruse, F.A., Green, R.O., 1995. Mapping target signatures via partial unmixing of AVIRIS data. In: Summaries, Fifth JPL Airborne Earth Science Workshop, vol. 95(1). JPL Publication, pp. 23-26. Chang, S.H., Collins, W., 1983. Confirmation of airborne biophysical mineral exploration techniques using laboratory methods. Economic Geology and Bulletin of the Society of Economic Geologists 78, 723-736.

ID: 60015
Title: An evaluation of SVM using polygon-based random sampling in landslide susceptibility mapping: The Candir catchment area (Western Antalya, Turkey)
Author: B.Taner San.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 399-412 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: SVM, Polygon based random sampling (PBRS) Antalya, Landslide susceptibility mapping, ASTER.
Abstract: The main purpose of this study was to present an approach that uses all of the input parameters from remotely sensed data to map landslide susceptibility. Furthermore, a novel sampling strategy, namely polygon-based random sampling (PBRS), which maintains the complete independence of sampled data sets for training and testing, was proposed to generate more realistic landslide susceptibility maps. An ASTER image of the Candir catchment area which is located in western Antalya (Turkey) was selected for implementing the proposed approach using a support vector machine classification (SVM) algorithm. The proposed methodology contains three sections: a polygon based sampling algorithm, an SVM classification, and an accuracy assessment. Two data sets (A and B) were generated and compared. Topographical parameters, proximity parameters and Normalized Difference Vegetation Index (NDVI) were used in the two data sets. In addition to these common parameters, data set (A) included lithological unit data produced from conventional geology maps and data set (B) had decorrelation stretched ASTER bands with four mineral (alunite, kaolinite, calcite, and quartz) indices. To construct and evaluate the models, training and testing data sets were generated using the proposed sampling strategy with three random sets for each data set (A and B). Next, the spatial performance of the obtained landslide susceptibility maps was evaluated using the area under the receiver-operating characteristics curves (AUC). The AUC values of the three random sets from set (A) were 0.913, 0.912, and 0.906. The AUC values of the three random sets from data set (B) were 0.923, 0.912, and 0.907. After comparison of the obtained AUC values, data set (B) presented considerably acceptable spatial performances in landslide susceptibility map production.
Location: TE 15 New Biology Building
Literature cited 1: Abrams, M., 2000. The advanced spaceborne thermal emission and reflection radiometer (ASTER): data products for the high spatial resolution imager on NASA ' s Terra platform. International Journal of Remote Sensing 21, 847-859. Akgun, A., Sezer, E.A., Nefeslioglu, H.A., Gokceoglu, C., Pradhan, B., 2012. An easy-to-use MATLAB program (MamLand) for the assessment of landslide susceptibility using a Mamdani fuzzy algorithm. Computers & Geosciences 38, 23-34.
Literature cited 2: Ayalew, L., Yamagishi, H., 2005. The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan, Geomorphology 65, 15-31. Baeza, C., Corominas, J., 2001. Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surface Processes and Landforms 26, 1251-1263.

ID: 60014
Title: A Spatial-spectral approach for deriving high signal quality eigenvectors for remote sensing image transformations.
Author: Derek Rogge, Martin Bachmann, Benoit Rivard, Allan Aasbjerg Nielsen, Jilu Feng.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 387-398 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Hyperspectral imaging, Spatial and spectral processing, Eigenvector transformations.
Abstract: Spectral decorrelation (transformations) methods have long been used in remote sensing. Transformation of the image data onto eigenvectors that comprise physically meaningful spectra properties (signal) can be used to reduce dimensionality of hyperspectral images as the number of spectrally distinct signal sources composing a given hyprspectral scene is generally much less than the number of spectral bands. Determining eigenvectors dominated by signal variance as opposed to noise is a difficult task. Problems also arise in using these transformations on large images, multi flight-line surveys, or temporal data as computational burden becomes significant. In this paper we present a spatial -spectral approach to deriving high signal quality eigenvectors for image transformations which possess an inherently ability to reduce the effects of noise. The approach applies a spatial and spectral subsampling to the data, which is accomplished by deriving a limited set of eigenvectors for spatially contiguous subsets. These subset eigenvectors are compiled together to form a new noise reduced data set, which is subsequently used to derive a set of global orthogonal eigenvectors. Data from two hyperspectral surveys are used to demonstrate that the approach can significantly speed up eigenvector derivation, successfully be applied to multiple flight-line surveys or multi-temporal data sets, derive a representative eigenvector set for the full image data set, and lastly, improve the separation of those eigenvectors representing signal as opposed to noise.
Location: TE 15 New Biology Building
Literature cited 1: Akaike, H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control AC-19, 716-723. Andreou, C., Karathanassi, V., 2013. Estimation of the number of endmembers using robust outlier detection method. IEEE Journal of Selected Topics in Applied Earth Observation and Remote Sensing (in press).
Literature cited 2: Boardman, J.W., Kruse, F.A., Green, R.O., 1995. Mapping target signatures via partial unmixing of AVIRIS data. In: Summaries, Fifth JPL Airborne Earth ScienceWorkshop, vol. 1. JPL Publications 95-1, pp. 23-26. Buckingham, R., Staenz, K., 2008. Review of current and planned civilian space hyperspectral sensors for EO. Canadian Journal for Remote Sensing 34, S187-S-197.

ID: 60013
Title: Combination of optical and LiDAR satellite imagery with forest inventory data to improve wall-to-wall assessment of growing stock in Italy.
Author: F.Maselli, M. Chiesi, M.Mura, M.Marchetti, P. Corona, G. Chirici.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 377-386 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Forest inventory, Locally weighted regression, CORINE land cover, GLAS, MODIS.
Abstract: The acquisition of information about growing stock is a fundamental step in the framework of forest management planning and scenario modeling, besides being essential for assessing the amount of carbon stored within forest ecosystems. Galluan et al. (2010) produced a pan-European map of forest growing stock by the combination of ground and remotely sensed data. The first objective of the current paper is to assess the accuracy of this map versus the ground data collected during the latest Italian National Forest Inventory (INFC). Next, a new wall-to-wall estimation of growing stock is obtained by combining ground measurements of four regional forest inventories with the CORINE land cover map of Italy and the global canopy height map derived from Geoscience Laser Altimeter System (GLAS) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. More particularly, the growing stock measurements of the four inventories are stratified by ecosystem type and extended over all Italian forest areas through the application of locally weighted regressions to the GLAS/MODIS canopy height map. When compared to the INFC measurements, the new map shows higher accuracy than that by Gallaun et al., particularly for high growing stock values. The coefficient of determination between estimated and INFC growing stocks is improved by about 0.5, whilst the mean square error is reduced from 90 to 48 m3 ha-1.
Location: TE 15 New Biology Building
Literature cited 1: Brunsdon, C., Fotheringham, A.S., Charlton, M.E., 1996. Geographically weighted regression: a method for exploring spatial nonstationarity. Geographical Analysis. 28, 281-298. Chiesi, M., Maselli, F., Moriondo, M., Fibbi, L., Bindi, M., Running, S.W., 2007. Application of BIOME-BGC to simulate Mediterranean forest processes. Ecological Modelling 206, 179-190.
Literature cited 2: Chirci, G., Giuliarlli, D., Biscontini, D., Tonti., D., Mattioli, W., Marchetti, M., Corona, P., 2008. Large-scale monitoring of coppice forest clearcuts by multitemporal very high resolution satellite imagery. A case study from central Italy. Remote Sensing of Environment 115, 1025-1033. Cleveland, W.S., Devlin, S.J, 1988. Locally weighted regression: an approach to regression analysis by local fitting. Journal of the American Statistical Association 83, 596-610.

ID: 60012
Title: Modeling and forecasting MODIS-based Fire Potential Index on a pixel basis using time series models.
Author: Margarita Huesca, Javier Litago, Silvia Merino-de-Miguel, VictorCicuendez-Lopez-Ocana, Alicia Palacios-Orueta.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 363-376 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Time series analysis, MODIS, Autoregressive models.
Abstract: The aim of this research was to model and forecast MODIS-based Fire Potential Index (FPI), implemented with Normalized Difference Water Index (NDWI), as a proxy of forest fire risk, in Navarre (Spain) on a pixel basis using time series models with a forecasting horizon of one year. We forecast FPI NDWI for 2009 based on time series from 2001to 2008. In the modeling process, the Box and Jenkins methodology was applied in two consecutive stages. First, several generic models based on average FPI NDWI time series from different ?fuel type-ecoregion? combinations were developed. In a second stage, the generic models were implemented at the pixel level for the entire study region. The usefulness of the proposed autoregressive (AR) model, using the original data and introducing significant seasonal AR parameters, was demonstrated. Results show that 93.18 % of the estimated models (Ems) are highly accurate and present good forecasting ability, precisely reproducing the original FPI NDWI dynamics. Best results were found in the Mediterranean areas dominated by grasslands; slightly lower accuracies were found in the temperate and alpine regions, and especially in the transition areas between them and the Mediterranean region.
Location: TE 15 New Biology Building
Literature cited 1: Alhamad, M.N., Stuth, J., Vannucci, M., 2007. Biophysical modeling and NDVI time series to project near- term forage supply: spectral analysis aided by wavelet denoising and ARIMA modeling. Int. J. Remote Sens. 11, 2513-2548. Barret, E.C., Curtis, L.F., 1999. Introduction to Environmental Remote Sensing. Stanley Thornes (Publishers) Ltd.
Literature cited 2: Barsky, R.B., Miron, J.A., 1989. The seasonal cycle and the business cycle. J. Polit. Econ. 97, 503-534. Beaulieu, J., Miron, J., 1993. Seasonal unit roots in aggregate US data. J. Econometrics 55, 305-328.

ID: 60011
Title: Mapping spatio-temporal flood inundation dynamics at large river basin scale using time-series flow data and MODIS imagery.
Author: Chang Huang, Yun Chen, Jianping Wu.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 350-362 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Observed flow, Annual flood series, MODIS, OWL, Inundation frequency, Inundation probability
Abstract: Flood inundation is crucial to the survival and prosperity of flora and fauna communities in floodplain and wetland ecosystems. This study tried to map flood inundation characteristics in the Murray-Darling, Basin, Australia, utilizing hydrological and remotely sensed data. It integrated river flow time series and Moderate Resolution Imaging Spectroradiometer (MODIS) images to map inundation dynamics over the study area on both temporal and spatial dimensions. Flow data were analyzed to derive flow peaks and Annual Exceedance Probabilities (AEPs) using the annual flood series method. The peaks were linked with MODIS images for inundation detection. Ten annual maximum inundation maps were generated for water years 2001-2010, which were then overlaid to derive an inundation frequency map. AEPs were also combined with the annual maximum inundation maps to derive an inundation probability map. The resultant maps revealed spatial and temporal patterns of flood inundation in the basin, which will benefit ecological and environmental studies when considering response of floodplain and wetland ecosystems to flood inundation.
Location: TE 15 New Biology Building
Literature cited 1: Alsdorf, D.E., Lettenmaier, D.P., 2003. Tracking fresh water from space. Science 301, 1491-1494. Alsdorf, D.E., Rodriguez, E., Lettenmaier, D.P., 2007. Measuring surface water from space.Rev. Geophys.45, 1-24.
Literature cited 2: APFM, 2006. Environmental aspects of integrated flood management. Associated Programme on Flood Management, Geneva, Switzerland. Bates, P.D., Horritt, M.S., Fewtrell, T.J., 2010. A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modeling. J. Hydrol. 387, 33-45.

ID: 60010
Title: Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data.
Author: Igor Klein, Andreas J. Dietz, Ursula Gessner, Anastassiya Galayeva, Akhan Myrzakhmetov, Claudia Kuenzer.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 335-349 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Water bodies, Central Asia, Medium resolution satellite data, Time-series.
Abstract: In this study medium resolution remote sensing data of the AVHRR and MODIS sensors were used for derivation of inland water bodies extents over a period from 1986 till 2012 for the region of Central Asia. Daily near-infrared (NIR) spectra from the AVHRR sensor with 1.1 km spatial resolution and 8-day NIR composites from the MODIS sensor with 250 m spatial resolution for the months April, July and September were used as input data. The methodological approach uses temporal dynamic thresholds for individual data sets, which allows detection of water pixel independent from differing conditions or sensor differences. The individual results are summed up and combined to monthly composites of areal extent of water bodies. The presented water masks for the months April, July and September were chosen to detect seasonal patterns as well as inter-annual dynamics and show diverse behavior of static, decreasing, or dynamic water bodies in the study region. The size of the southern Aral Sea, as the most popular example for an ecologic catastrophe, is decreasing significantly throughout all seasons (R2 0.96 for April; 0.97 for July; 0.96 for September). Same is true for shallow natural lakes in the northern Kazakhstan, exemplary the Tengiz-Korgalzhyn lake system, which have been shrinking in the last two decades due to drier conditions (R2 0.91 for July; 0.90 for September). On the contrary, water reservoirs show high seasonality and are very dynamic within one year in their areal extent with maximum before growing season and minimum after growing season. Furthermore, there are water bodies such as Alakol-Saykol lake system and natural mountainous lakes which have been stable in their areal extent throughout the entire time period. Validation was performed based on several Lindsay images with 30 m resolution and reveals an overall accuracy of 83% for AVHRR and 91 % for MODIS monthly water masks. The results should assist for climatological and ecological studies, land and water management, and as input data for different modeling applications.
Location: TE 15 New Biology Building
Literature cited 1: Ackerman, S., Strabala, K., Menzel, P., Frey, R., Moeller, C., Gumley, L., Baum, B., 2006. Discriminating Clear-Sky from Cloud with MODIS Algorithm Theoretical Basis Document (MOD 35)., PP. 124. Aizen, V.B., Aizen, E.M., Melack, J.M., Dozier, J., 1997. Climatic and hydrologic changes in Tien Shan, Central Asia, Journal of Climate 10 (6), 1393-1404.
Literature cited 2: Aizen, V.B., Aizen, E.M., Kuzmichenok, V.A. 2007. Geo-informational simulation of possible changes in Central Asia water resources. Global and Planetary Change 56, 341-358. Aizen, V.B., Mayewski, P.A., Aizen, E.M., Joswaik, D.R., Surazakov, A.B., Kespari, S., Grigholm, B., Krachler, M., Handley, M., Finaev, A., 2009. Stable-isotope and trace element time series from Fedchenko glacier (Pamirs) snow/firn cores. Journal of Glaciology 55 (190) 275-291.

ID: 60009
Title: Investing rural poverty and marginality in Burkina Faso using remote sensing-based products.
Author: M.Imran, A. Stein, R. Zurita-Milla.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 322-334 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Food security, Composite asset index, SPOT NDVI, TAMSAT rainfall, Geographical weighted regression.
Abstract: Poverty at the national and sub-national level is commonly mapped on the basis of household surveys. Typical poverty metrics like the head count index are not able to identify its underlaying factors, particularly in rural economies based on subsistence agriculture. This paper relates agro-ecological marginality identified from regional and global datasets including remote sensing products like the normalized difference vegetation index (NDVI) and rainfall to rural agricultural production and food consumption in Burkina Faso. The objective is to analyze poverty patterns and to generate a fine resolution poverty map at the national scale. We compose a new indicator from a range of welfare indicators quantified from Georeferenced household surveys, indicating a spatially varying set of welfare and poverty states of rural communities. Next, a local spatial regression is used to relate each welfare and poverty state to the agro-ecological marginality. Our results show strong spatial dependency of welfare and poverty states over agro-ecological marginality in heterogeneous regions, indicating that environmental factors affect living conditions in rural communities. The agro-ecological stress and related marginality vary locally between rural communities within each region. About 58% variance in the welfare indicator is explained by the factors of rural agricultural production and 42% is explained by the factor of food consumption. We found that the spatially explicit approach based multi-temporal remote sensing products effectively summarizes information on poverty and facilitates further interpretation of the newly developed welfare indicator. The proposed method was validated with poverty incidence obtained from national surveys.
Location: TE 15 New Biology Building
Literature cited 1: AGRISTAT, 2010.Reultats d?finitives champagne (2008-2009). Burkina Faso. Technical report. Statistiques sur I ' Agriculture et I ' Alimentation du Burkina Faso (AGRISTAT), Ouagadougou, Burkina Faso. Alasia, A., Bollman, R.D., Parkins, J., Reimer, B., 2008. An Index of Community Vulnerability: Conceptual Framework and Application to Population and Employment Changes (1981 to 2001. Statistics Canada, Agriculture Division.
Literature cited 2: Anselin, L., 1995. Local Indicators of Spatial Association-LISA, Geogr Anal 27, 93-115. Benson, T., Chamberlin, J., Rhinehart, I., 2005. An investigation of the spatial determinants of the local prevalence of poverty in rural Malawi. Food policy 30 (5-6), 532-550.

ID: 60008
Title: Implementation and performance of a general purpose graphics processing unit in hyperspectral image analysis.
Author: H.M.A. van der Werff, W.H. Bakker.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 312-321 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Hyperspectral, Classification, Graphicshardware, GPGPU, IDL
Abstract: A graphics processing Unit (GPU) can perform massively parallel computations at relatively low cost. Software interfaces like NVIDIA CUDA allow for General Purpose Computing on a GPU (GPGPU). Wrappers of the CUDA libraries for higher-level programming languages such as MATLAB and LDL allow its use in image processing. In this paper, we implement GPGPU in IDL with two distance measures frequently used in image classification, Euclidean distance and spectral angle, and apply these to hyperspectral imagery. First we vary the data volume of a synthetic dataset by changing the number of image pixels, spectral bands and classification endmembers to determine speed-up and to find the smallest data volume that would still benefit from using graphics hardware. Then we process real datasets that are too large to fit in the GPUmemory, and study the effect of resulting extra data transfers on computing performance. We show that our GPU algorithms outperform the same algorithms for a central processor unit (CPU), that a significant speed-up can already be obtained on relatively small datasets, and that data transfers in large datasets do not significantly influence performance. Given that no specific knowledge on parallel computing is required for this implementation, remote sensing scientists should now be able to implement and use GPGPU for their data analysis.
Location: TE 15 New Biology Building
Literature cited 1: Bakker, W., Schmidt, K., 2002. Hyperspectral edge filtering for measuring homogeneity of surface cover types. ISPRS Journal of Photogrammetry & Remote Sensing 56, 246-256. Berger, M., Aschbacher, J., 2012. The sentinel missions -new opportunities for science. Remote Sensing of Environment 120, 1-276.
Literature cited 2: Biehl, L., 2013. Multispec. https://engineering.purdue.edu/biehl/MultiSpec/ hyperspectral.html (accessed 17.05.13). Block, B., Virnau, P., Preis, T., 2010. Multi-GPU accelerated multi-spin Monte Carlo simulations of the 2D Ising model. Computer Physics Communications 181 (9), 1549-1556.