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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.

ID: 60007
Title: A comparison of selected classification algorithms for mapping bamboo patches in lower Gangetic plains using very high resolution Worldview 2 imagery.
Author: Aniruddha Ghosh, P.K. Joshi.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 298-311 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Bamboo mapping, Feature selection, GLCM texture, Pixel and object based classification, Random forest, Support Vector Machine, Word view 2.
Abstract: Bamboo is used by different communities in India to develop indigenous products, maintain livelihood and sustain life. Indian National Bamboo Mission focuses on evaluation, monitoring and development of bamboo as an important plant resource. Knowledge of spatial distribution of bamboo therefore becomes necessary in this context. The present study attempts to map bamboo patches using very high resolution (VHR) Worldview 2 (WV2) imagery in parts of South 24 Parganas, West Bengal, India using both pixel and object-based approaches. A combined layer of pan-sharpened multi-spectral (MS) bands, first 3 principal components (PC) of these bands and seven second order texture measures based Gray Level Co-occurrence Matrices (GLCM) of first three PC were used as input variables. For pixel-based image analysis (PBIA), recursive feature elimination (RFE) based feature selection was carried out to identify the most important input variables. Results of the feature selection indicate that the 10 most important variables include PC 1, PC 2, and their GLCM mean along with 6 MS bands. Three different sets of predictor variables (5 and 10 most important variables and all 32 variables) were classified with Support Vector Machine 10 most important variables selected from RFE were classified with SVM (82%). However object-based image analysis (OBIA) achieved higher classification accuracy than PBIA using the same 32 variables, but with less number of training samples. Using object-based SVM classifier, the producer accuracy of bamboo reached 94 %. The significance of this study is that the present framework is capable of accurately identifying bamboo patches as well as detecting other tree species in a tropical region with heterogeneous land use land cover (LULC), which could further aid the mandate of National Bamboo Mission and related programs.
Location: TE 15 New Biology Building
Literature cited 1: Arenas-castro, S., Julien, Y., Jimenez-Munoz, J.C. Sobrino, J.A., Fernandez-Haeger, J., Jordano Barbudo, D., 2012. Mapping wild pear trees (Pyrus bourgaeana ) in Mediterranean forest using high-resolution QuickBird satellite imagery. International Journal of Remote Sensing 34 (9-10), 3376-3396. Bratista, M.H., Haertel, V., 2010. On the classification of remote sensing high spatial resolution image data. International Journal of Remote Sensing 31 (20), 5533-5548.
Literature cited 2: Belluco, E., Camuffo, M., Ferrari, S., Modenese, L., Silvestri, S., Marani, M., 2006. Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing. Remote Sensing of Environment 105 (1), 54-67. Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing.

ID: 60006
Title: Evaluating suitability of MODIS-Terra images for reproducing historic sediment concentrations in water bodies: Lake Tana, Ethiopia.
Author: Essayas Kaba, William Philpot, Tammo Steenhuis.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 286-297 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: MODIS, TSS, Lake Tana, Getis-Ord GI
Abstract: Government and NGO funded conservation programs are being implemented in developing countries with the potential benefit of reduced sediment inflow into fresh water lakes. However, these claims are difficult to verify due to limited historical sediment concentration data in lakes and rivers. Remote sensing can potentially aid in monitoring sediment concentration. With almost daily availability over the past ten years and consistent atmospheric correction. With almost daily availability over the past ten years and consistent atmospheric correction applied to the images, Moderate Resolution Imaging Spectroradiometer (MODIS) 250 meter images are potential resources capable of monitoring future concentrations and reconstructing historical sediment concentration records. In this paper, site-specific relationships are developed between reflectance in near -infrared (NIR) images and three factors: total suspended solids (TSS), turbidity and Secchi depth for Lake Tana near the mouth of the Gumara River. The first two sampling campaigns on November 27, 2010 and May 13, 2011 are used in calibration. Reflectance in the NIR varies linearly with turbidity (R2= 0.89) and TSS (R2=0.95). Secchi depth fit best to an exponential relation with R2 of 0.74. The relationships are validated using a third sample set collected on November 7, 2011 with RMSE of 11 Nephelometric Turbidity Units (NTU) for Turbidity, 16.5 mg1-1 for TSS and 0.12 meters for secchi depth. The MAE was 10% for TSS, 14 % for turbidity and 0.1% for Secchi depth. Using the relationship for TSS, a 10-year time series of sediment concentration in Lake Tana near the Gumara River was plotted. It was found that after the severe drought of 2002 and 2003 the concentration in the lake increased significantly. The results showed that MODIS images are potential cost effective tools to monitor suspended sediment concentration and obtain a past history of concentration for evaluating the effect of best management practices.
Location: TE 15 New Biology Building
Literature cited 1: Ayana, E.K., 2007. Validation Of Radar Altimetry Lake Level Data And It ' s Application In Water Resources Management. University of Twente, The Netherland, Master Thesis. Baban, S.M., 1993. Detecting water quality parameters in the Norfolk Broads, UK, using Landsat imagery. International Journal of Remote Sensing 14, 1247-1267.
Literature cited 2: Betru, N., Sonali, W., 2010. Disaster risk reduction: experience from the MERET project in Ethiopia. In: Steven Were Omamo, U.G.a.S.S. (Ed.) Revolution: From Food Aid to Food Assistance. WPF, Rome, pp.139-156. Bewket, W., Sterk, G., 2003. Assessment of soil erosion in cultivated fields using a survey methodology for rills in the Chemoga watershed, Ethiopia, Agriculture, Ecosystems & Environment 97, 81-93.

ID: 60005
Title: First results of the earth observation Water Cycle Multi-mission Observation Strategy (WACMOS)
Author: Z. Su, D. Fernandez-Prieto, J. Timmermans, X. Chen, K.Hungershoefer, R. Roebeling, M.Schroder, J.Schulz, P.Stammes, P.Wang, E. Woltrs.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 270-285 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Earth observation, Evapotranspiration, Solar irradiance, Precipitation, Water vapour.
Abstract: Observing and monitoring the different components of the global water cycle and their dynamics are essential steps to understand the climate of the Earth, forecast the weather, predict natural disasters like floods and droughts, and improve water resources management. Earth observation technology is a unique tool to provide a global understanding of many of the essential variables governing the water cycle and monitor their evolution from global to basin scales. In the coming years, an increasing number of Earth observation missions will provide an unprecedented capacity to quantify several of these variables on a routine basis. However, this growing observational capacity is also increasing the need for dedicated research efforts aimed at exploring the potential offered by the synergies among different and complementary EO data records. In this context, the European Space Agency (ESA) launched the Water Cycle Multi-mission Observation Strategy (WACMOS) in 2009 aiming at enhancing, developing and validating a novel set of multi-mission based methods and algorithms to retrieve a number of key variables relevant to the water cycle. In particular the project addressed four major scientific challenges associated to a number of key variables governing the water cycle: evapotranspiration, soil moisture, cloud properties related to surface solar irradiance and precipitation, and water vapour. This paper provides an overview of the scientific results and findings with the ultimate goal of demonstrating the potential of strategies based on utilizing multi-mission observations in maximizing the synergistic use of the different types of information provided by the currently available observation systems and establish the basis for further work.
Location: TE 15 New Biology Building
Literature cited 1: Adler, R.F., Negri, A.J., 1988. A satellite IR technique to estimate tropical connective and statiform rainfall. J.Appl.Meteorol, 27, 30-51. Adler, R.F., Huffman, G.J., Chang, A., Ferraro, R., Xie, P., Janowiak, J., Rudolf, Schneider, U., Curtis, S.,Bolvin, D., Gruber, A., Susskind, J., Arkin,P., Nelkin, E., 2003.The version 2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979-present). J. Hydrometer.4, 1147-1167.
Literature cited 2: Aires, F., Prigent, C., 2006. Toward a new generation of satellite surface products? J.Geophys. Res. 111, D22S10, http://dx.doi.org/10.1029/2006JD007362. Anderson, A., Fenning, K., Klepp, C., Bakan, S., Gra?, H., Schulz, J., 2010. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data-HOAPS-3.Earth.Syst.Sci.Data 2, 215-234, http://dx.doi.org/10.5194/essd-2-215-2010.

ID: 60004
Title: MODIS-derived albedo changes of Vatnajokull (Iceland) due to tephra deposition from the 2004 Grimsvotn eruption.
Author: Rebbeca Moller, Marco Moller, Helgi Bjorrnsson, Sverrir Guomundsson, Finnur Palsson, Bjorn Oddsson, Peter A. Kukla, Christoph Schneider.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 256-269 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Ice-volcano interactions, Glacier-surface albedo, Iceland, Subglacial eruption, Tephra fallout, Remote sensing.
Abstract: Occasionally, the surface albedo of glaciers may be abruptly altered by deposition of light-absorbing aerosols, which consequently has a sustained impact on their energy-and mass balance. Volcanic eruptions may spread tephra deposits over regional-scale glacierized areas. In November 2004, an explosive, phreatomagmatic eruption of the subglacial Grimsvotn volcano, located in the centre of the Icelandic ice cap Vatnajokull, produced ash fall covering an area of ~ 1280 km2 in the northwestern part of the ice cap. This event affected the surface albedo of the glacier over several years after the eruption. We use MODIS surface-albedo data and an ash-dispersal dataset obtained from in situ measurements on the ice cap to develop a novel, empirically based modelling approach to describe the albedo decrease across the glacier surface caused by deposited tephra. We present analyses of the temporal and spatial variability of the albedo pattern over the post-eruption period from November 2004 to December 2008. The tephra-induced albedo changes were largest and most widely distributed over the glacier surface during the summer season 2005. The observed albedo decrease reached 0.35 when compared to modeled, undisturbed conditions. In the low-lying ablation area, where strong surface melting takes place, the tephra influence on albedo diminished with time and completely faded out within four years after the eruption. In contrast, at the rim of the Grimsvotn caldera surrounding the eruption site the tephra influences on albedo considerably increased with time. Throughout the rest of the high-lying accumulation area, the influences were scattered in both space and time
Location: TE 15 New Biology Building
Literature cited 1: Adhikary, S., Nakawo, M., Seko, Shakya, B., 2000. Dust influence on the melting process of glacier ice: experimental results from Lirung Glacier, Nepal Himalayas. In: IAHS Redbooks, vol. 264, pp. 43-52. Albino, F., Pinel, V., Sigmundsson, F., 2010. Influence of surface load variations on eruption likelihood: application to two Icelandic subglacial volcanoes, Grimsvotn and Katla, Geophys. J. Intern. 181, 1510-1524.
Literature cited 2: Benson, C., Motyka, R., McNutt, S., Luthi, M., Truffer, M., 2007. Glacier-volcano interactions in the North Crater of Mt Wrangell, Alaska.Ann.Glaciol.45, 48-57. Berthier, E., Bjornsson, H., Palsson, F., Feigl, K.L., Llubes, M., Remy, F., 2006. The level of the Grimsvotn subglacial lake, Vatnajokull, Iceland, monitored with SPOT5 images. Earth Planet.Sci.Lett. 243, 193-302.

ID: 60003
Title: Monitoring water stress in Mediterranean semi-natural vegetation with satellite and meteorological data.
Author: A. Moreno, F. Maselli, M. Chiesi, L.genesio, F. Vaccari, G.Seufert, M.A.Gilabert.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 246-255 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Light use efficiency, water stress, Satellite data, Semi-natural vegetation.
Abstract: In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ? due to water stress still relies mostly on meteorological data. Thus the GTP estimation based on procedures exclusively driven by remote sensing data has not found yet widespread use. In this work, the potential to characterize the water stress in semi-natural vegetation of three spectral indices (NDWI, SIWSI and NDI7) -from MODIS broad spectral bands-has been analyzed in comparison to a meteorological factor (Cws). The study comprises 70 sites (belonging to 7 different ecosystems ) uniformly distributed over Tuscany, and three eddy covariance tower sites. An operational methodology, which combines meteorological and MODIS data, to characterize the inter-annual variations of ? due to summer water stress is proposed. Its main advantage is that it relies on existing series of meteorological data characterizing each site and allows calculating a typical Cws profile that can be ?updated? (Cws) for the actual conditions using MODIS spectral indices. The results confirm that the modified Cws can be used as a proxy of water stress that does not require concurrent information on meteorological data.
Location: TE 15 New Biology Building
Literature cited 1: Allard, V., Ourcival, J.M., Rambal, S., Joffre, R., Rocheteau, A., 2008. Seasonal and annual variation of carbon exchange in an evergreen Mediterranean forest in southern France. Global Change Biol.14, 714-725, http://dx.doi.org/10.1111/j.1365-2486.2008.01539.x Arrigoni, P.V. Raffaeli, M., Rizzotto, M., Selvi, F., Vicini, D., Lombardi, L., Foggi, B., Melillo,C., Benesperi, R., Ferretti, G., Benucci, S., Turrini, S., di Tommaso, P.L., Signorini, M., Bargelli, E., Miniati,U., Farioli, C., de Dominicis, V., Casini,S., Chiarucci, A., Tomei, P.E., Ansaldi, M., Maccioni, S., Guazzi, E., Zocco Pisana, L., Cenerini, A., Dell ' olmo, L., Menacagli, E., 1998. La vegetazione forestale. Serie Boschi Macchie di Toscana, Regione Toscana, Giunta regionale.
Literature cited 2: Bolle, H.J., Eckardt, M., Koslowsky, D., Maselli, F., Melia Miralles, J., Menenti, M., Olesen, F.S, Petkov, L., Rasool, I., Van de Griend, A., 2006. Mediterranean land surface processes assessed from space. In: Regional Climate Studies, vol. XXVIII. Springer Series. Carter, G.A., 1991. Primary and secondary effects of water content on the spectral reflectance of leaves. Am. J. Bot. 78, 916-924.

ID: 60002
Title: Objected-oriented mapping of urban trees Random Forest classifiers.
Author: Anne Puissant, Simon Rougier, Andre Stumpf.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 235-245 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Urban trees, VHR satellite images, Object based image analysis, Feature selection, Random Forest classifier.
Abstract: Since vegetation in urban areas delivers crucial ecological services as a support to human well-being and to the urban population in general, its monitoring is a major issue for urban planners. Mapping and monitoring the changes in urban green spaces are important tasks because of their functions such as the management of air, climate and water quality, the reduction of noise, the protection of species and the development of recreational activities. In this context, the objective of this work is to propose a methodology to inventory and map the urban tree spaces from a mono-temporal very high resolution (VHR) optical image using a Random Forest classifier in combination with object-oriented approaches. The methodology is developed and its performance is evaluated on a data set of the city of Strasbourg (France) for different categories of built-up areas. The results indicate a good accuracy and a high robustness for the classification of the green elements in terms of user and producer accuracies.
Location: TE 15 New Biology Building
Literature cited 1: Amro, I., Mateos, J., Vega, M., Molina, R., Katsaggelos, A., 2011. A survey of classical methods and new trends in panshgarpening of multispectral images. EURASIP Journal on Advances in Signal Processing 79, 1-22. Ardila, J.P., Tolpekin, V.A., Bijker, W., Stein, A., 2011. Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images. ISPRS Journal of Photogrammetry and Remote Sensing 66, 762-775.
Literature cited 2: Ardila, J.P. Bijker, W., Tolpekin, V.A., Stein, A., 2012. Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images. International Journal of Applied Earth Observation and Geoinformation 15, 57-69. Benz, U.C., Hofman, P., Willhauck, G., Lingenfelder, I., Heynen, M., 2004. Multiresolution object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing 58, 239-258.

ID: 60001
Title: Uncertainty of soil reflectance retrieval from SPOT and RapidEye multispectral satellite images usinga per-pixel bootstrapped empirical line atmospheric correction over an agricultural region.
Author: E. Vaudour, J.M. Gilliot, L.Bel, L. Brechet, J. Hamiache, D. Hadjar, Y. Lemonnier.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 26 217-234 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Soil reflectance, Per-pixel empirical line, Atmospheric correction accuracy, SPOT, RapidEye, ATCOR2.
Abstract: Many authors have reported the use of empirical line regression between field target sites and image pixels in order to perform atmospheric correction of multispectral images. However few studies were dedicated to the specific reflectance retrieval for cultivated bare soils from multispectral satellite images, from a large number (>=15)
Location: TE 15 New Biology Building
Literature cited 1: Anderson, K., Milton, E.J., 2006. On the temporal stability of ground calibration targets: implications for the reproducibility of remote sensing methodologies. International Journal of Remote Sensing 27 (15-16), 3365-3374. Atkinson, P.M. Sargent, I.M., Foody, G.M., Williams, J., 2007. Exploring the geostatistical method for estimating the signal-to-noise ratio of images. Photogrammetric Engineering & Remote Sensing 73 (7), 841-850.
Literature cited 2: Baugh, W.M., Groeneveld, D.P., 2008. Empirical proof of the empirical line. International Journal of Remote Sensing 29 (3), 665 -672. Bellon-Maurel, V., McBratney, A., 2011. Near-infrared (NIR) and mid-infrared (MIR) spectroscopic techniques for assessing the amount of carbon stock in soils. Critical review and research perspectives. Soil Biology & Biochemistry 43, 1348-1420.