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ID: 61020
Title: Evaluation of SPOT imagery for the estimation of grassland biomass.
Author: P.Dusseux, L.Hubert-Moy, T.Corpetti, F.Vertes.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 72-77 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Remote sensing, Satellite images, Meadows, LAI, Agriculture.
Abstract: In many regions, a decrease in grasslands and change in their management, which are associated with agricultural intensification, have been observed in the last half-century. Such changes in agricultural practices have caused negative environmental effects that include water pollution, soil degradation and biodiversity loss. Moreover, climate-driven changes in grassland productivity could have serious consequences for the profitability of agriculture. The aim of this study was to assess the ability of remotely sensed data with high spatial resolution to estimate grassland biomass in agricultural areas. A vegetation Index, namely the Normalized Difference Vegetation Index (NDVI), and two biophysical variables, the Leaf Area Index (LAI) and the fraction of Vegetation Cover (fCOVER) were computed using five SPOT images acquired during the growing season. In parallel, ground-based information on grassland growth was collected to calculate biomass values. The analysis of the relationship between the variables derived from the remotely sensed data and the biomass values. The analysis of the relationship between the variables derived from the remotely sensed data and the biomass (R2 values of 0.68 against 0.30 and 0.50, respectively). The squared Pearson correlation coefficient between observed and estimated biomass using LAI derived SPOT images reached 0.73.Biomass maps generated from remotely sensed data were then used to estimate grass reserves at the farm scale in the perspective of operational monitoring and forecasting.
Location: T E 15 New Biology Building.
Literature cited 1: Arvalis, 2011.Methode Herbo-LIS ?.Institut du Vegetal. Atzberger, C., Richter, K., 2012. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future sentinel-2 imagery. Remote Sens. Environ.120.208218.
Literature cited 2: Baret, F., Guyot, G., Mar 1991.Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens.Environ.35, 161-173. Batary, P., Baldi, A., Erdos, S., 2007.Grassland versus non-grassland bird a abundance and diversity in managed grasslands: local, landscape and regional scale effects.Biodivers.Conserv.16, 871-881.

ID: 61019
Title: Estimates of forest structure parameters from GLAS data and multi-angle imaging spectrometer data.
Author: Ying Yu, Xiguang Yang, Wenyi Fan.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 65-71 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Lidar, GLAS, Tree height, Biomass, MISR.
Abstract: Quantitative estimates of forest vertical and spatial distribution using remote sensing technology play an important role in better understanding forest ecosystem function, forest carbon storage and the global carbon cycle. Although most remote sensing systems can provide horizontal distribution of canopies, information concerning the vertical distribution of canopies cannot be detected. Fortunately, laser radars have become available, such as GLAS (Geoscience laser altimeter system).Because laser radar can penetrate foliage; it is superior to other remote sensing technologies for detecting vertical forest structure and has higher accuracy. GLAS waveform data were used in this study to retrieve average tree height and biomass in a GLAS footprint area in Heilongjiang Province. However, GLAS data are not spatially continuous. To fill the gaps, MISR (multi-angle imaging spectrometer) spectral radiance was chosen to predict the regional continuous tree height by developing a multivariate linear regression model. We compared tree height estimated by the regression model and GLAS data. The results confirmed that estimates of tree height and biomass based on GLAS data are considerably more accurate than estimates based on traditional methods. The accuracy is approximately 90 %.MISR can be used to estimate tree height in continuous areas with a robust regression model. The R2, precision and root mean square error of the regression model were 0.8, 83 % and 1 m, respectively. This study provides an important reference for mapping forest vertical parameters.
Location: T E 15 New Biology Building.
Literature cited 1: Abshire, J.B., Sun, X., Riris, H., Sirota, J.M., McGarry, J.F., Palm, S., Yi, D., Liiva, P., 2005.Geoscience laser altimeter system (GLAS) on the ICES at mission: on-orbit measurement performance.Geophys.Res.Lett, 32. Ballhorn, U., Jubanski, J.,Siegert,F.,2011.ICESat/GLAS data as a measurement tool for peatland topography and peat swamp forest biomass in Kalimantan, Indonesia. Remote Sens.3, 1957-1982.
Literature cited 2: Blair, J., Coyle, D., Bufton, J.L., Harding, D., 1994.Optimization of an airborne laser altimeter for remote sensing of vegetation and tree canopies, geosciences and remote sensing symposium,1994.IGARSS ' 94.Surface and atmospheric remote sensing:technologies,data analysis and interpretation,international.IEEE,939-941.

ID: 61018
Title: Applicability of Landsat 8 data for characterizing glacier facies and supraglacial debris.
Author: Anshuman Bhardwaj, PK Joshi, Snehmani, Lydia Sam, Mritunjay Kumar Singh, Shaktiman Singh, Rajesh Kumar.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 51-64 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Glacier facies, Supraglacial debris, Remote sensing, Landsat 8.
Abstract: The present work evaluates the applicability of operational land imager (OLI) and thermal infrared sensor (TIRS) on-board Landsat 8 satellite. We demonstrate an algorithm for automated mapping of glacier facies and supraglacial debris using data collected in blue, near infrared (NIR), shortwave infrared (SWIR) and thermal infrared (TIR) bands. The reflectance properties in visible and NIR regions of OLI for various glacier facies are in contrast with those in SWIR region. Based on the premise that different surface types (snow, ice and debris) a glacier should show distinct thermal regimes, the ' at-satellite brightness temperature ' obtained using TIRS was used as a base layer for developing the algorithm. This base layer was enhanced and modified using contrasting reflectance properties of OLI bands. In addition to facies and debris cover characterization, another interesting outcome of this algorithm was extraction of crevasses on the glacier surface which were distinctly visible in output and classified images. The validity of this algorithm was checked using field data along a transect of the glacier acquired during the satellite pass over the study area. With slight scene-dependent threshold adjustments, this work can be replicated for mapping glacier facies and supraglacial debris in any alpine valley glacier.
Location: T E 15 New Biology Building.
Literature cited 1: : Ackerman, T., Erickson, T., Williams, M.W., 2001. Combining GIS and GPS to improve our understanding of the spatial distribution of snow water equivalence (SWE).In: Proceedings of the 2001 ESRI User Conference, 10 July 2001, San Diego, CA, Available online at: http://snowbear.colorado.edu/Markw/Research/ESRI/ESRI.html (accessed 10.09.13). Ahlmann, H.W., 1935.Contribution to the physics of glaciers.Geog.J.86 (2), 97-113.
Literature cited 2: Benson, C.S., 1959. Physical investigations on the snow and firn of the northwest Greenland: 1952-1954.SIPRE Res.Rep, 26. Benn, D.I., Evans, D.J.A., 1998.Glaciers and Glaciation.Arnold, New York.

ID: 61017
Title: Agriculture pest and disease risk maps considering MSG satellite data and land surface temperature.
Author: J.R.Marques da silva, C.V.Damasio, A.M.O.Sousa, L.Bugalho, L.Pessanha, P. Quaresma.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 40-50 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Land surface temperature, LST, Satellite application facility, SAF, EUMESAT, MSG, Pest management, Pest risk maps.
Abstract: Pest risk maps for agricultural use are usually constructed from data obtained from in-situ meteorological weather stations, which are relatively sparsely distributed and are often quite expensive to install and difficult to maintain. This leads to the creation of maps with relatively low spatial resolutions, which are very much dependent on interpolation methodologies. Considering that agricultural applications typically require a more detailed scale analysis than has traditionally been available, remote sensing technology can offer better monitoring at increasing spatial and temporal resolutions, thereby, improving pest management results and reducing costs. This article uses ground temperature, or land surface temperature (LST), data distributed by EUMETSAT/LSASAF (with a spatial resolution of 3 x 3 km (nadir resolution) and a revisiting time of 15 min) to generate one of the most commonly used parameters in pest modeling and monitoring: ?thermal integral over air temperature (accumulated degree-days)?. The results show a clear association between the accumulated LST values over a threshold and the accumulated values computed from meteorological stations over the same threshold (specific to a particular tomato pest). The results are very promising and enable the production of risk maps for agricultural pests with a degree of spatial and temporal detail that is difficult to achieve using in-situ meteorological stations.
Location: T E 15 New Biology Building.
Literature cited 1: Ahn, J.J., Yang, C.Y., Jung, C., 2012. Model of grapholita molesta spring emergence in pear orchards based on statistical information criteria.J.Asia-Pac.Entomol.15, 589-593. Babu, A., Cook, D.R., Caprio, M.A., Allen, K.C., Musser, F.R., 2014. Prevalence of Helicoverpa zea (Lepidoptera: Noctuidae) on late season volunteer corn in Missisippi: implications on Bt resistance management. Crop Prot.64, 207-214.
Literature cited 2: Bao, Y., -W., Yu, M.-X, Wu, 2011. Design and implementation of database for a webGIS-based rice diseases and pests system. Procedia Environ.Sci.10, 535-540. Barrientos, Z.R., Apablaza, H.J., Norero, S.A., Estay, P.P., 1998. Threshold temperature and thermal constant for development of the South American tomato moth, Tuta absoluta (Lepidoptera, Gelechiidae).Ciencia e InvesCgacion Agraria 25, 133-137 (In spanish).

ID: 61016
Title: Very high spatial resolution optical and radar imagery in tracking water level fluctuations of a small inland reservoir.
Author: R.N.Simon, T.Tormos, P.-A.Danis.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 36-39 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Water level fluctuations, water bodies, Pleiades, COSMO-SkyMed, TerraSAR-X, Geographic object-based image analysis (GEOBIA), Spatial resolution.
Abstract: A Tracking Water level fluctuation in small lakes and reservoirs is important in order to better understand and manage these ecosystems. A geographic object-based image analysis (GEOBIA) method using very high spatial and temporal resolution optical (Pleiades) and radar (COSMO-SkyMed) and TerraSAR-X) remote sensing imagery is presented here which (1) tracks water level fluctuations via variations in water surface area and (2) avoids common difficulties found in using single-band radar images for water-land image classification. Results are robust, with over 98 % of image surface area correctly classified into land or water, R2= 0.963 and RMSE =0.42 m for a total water level fluctuation range of 5.94 m. Multispectral optical imagery is found to be more straightforward in producing results than single-band radar imagery, but the latter crucially increase temporal resolution to the point where fluctuations can be satisfactorily tracked in time. Moreover, an analysis suggest that high and medium spatial resolution imagery is sufficient, in at least some cases, in tracking the water level fluctuations of small inland reservoirs. Finally, limitations of the methodology presented here are briefly discussed along with potential solutions to overcome them.
Location: T E 15 New Biology Building.
Literature cited 1: Adams, K.D., Sada, D.W., 2014. Surface water hydrology and geomorphic characterization of a playa lake system: implications for monitoring the effects of climate Change.J.Hydrol.510, 92-102. Alsodorf, D.E., Rodriguez, E., Lettenmaier, D.P., 2007. Measuring surface water from space.Rev.Geophys.45, RG2002.
Literature cited 2: Astrium, 2012.Pleiades Imagery User Guide. Astrium Geo-Information Services, pp.118. Bates, B.C., Kundzewicz, Z.W., Wu, S., Palutikof, J.P. (Eds). 2008. Climate Change and Water. Technical Paper of the Intergovernmental Panel on Climate Change.

ID: 61015
Title: Semi-automated mapping of burned areas in semi-arid ecosystems using MODIS time-series imagery.
Author: Leonardo A.Hardtke, Paula D.Blanco, Hector.F.del Valle, Graciela I.Metternicht, Walter F.Sione.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 25-35 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Bushfires, Burned area, Time-series, Image segmentation, MODIS, Normalized burn ratio, Rangelands.
Abstract: Understanding spatial and temporal patterns of burned areas at regional scales, provides a long-term perspective of fire processes and its effects on ecosystems and vegetation recovery patterns, and it is a key factor to design prevention and post-fire restoration plans and strategies. Remote sensing has become the most widely used tool to detect fire affected areas over large tracts of land (e.g., ecosystem, regional and global levels) Standard satellite burned area and active fire products derived from the 500-m Moderate Resolution Imaging. Spectroradiometer (MODIS) and the Satellite Pour 1 ' observation de la Terre (SPOT) are available to this end. However, prior research caution on the use of these global-scale products for regional and sub-regional applications. Consequently, we propose a novel semi-automated algorithm for identification and mapping of burned areas at regional scale. The Semi-arid Monte shrublands, a biome covering 240, 000 km2 in the western part of Argentina, and exposed to seasonal bushfires was selected at the test area. The algorithm uses a set of the normalized burned ratio index products derived from MODIS time series; using a two phased cycle, it firstly detects potentially burned pixels while keeping a low commission error (false detection of burned areas), and subsequently labels them as seed patches in the second-phase, to define the perimeter of fire affected areas while decreasing omission errors (missing real burned areas). Independently-derived Landsat ETM+burned-area reference data was used for validation purposes. Additionally, the performance of the adaptive algorithm was assessed against standard global fire products derived from MODIS Aqua and Terra satellites, total burned area (MCD45A1), the active fire algorithm (MODI4); and the L3 JRC SPOT VEGETATION 1 km GLOBCARBON products. The correlation between the size of burned areas detected by the global fire products and independently-derived Landsat reference data a ranged from R2=0.01-0.28, while our algorithm performed showed a stronger correlation coefficient (R2=0.96). Our findings confirm prior research calling for caution when using the global fire products locally or regionally.
Location: T E 15 New Biology Building.
Literature cited 1: Archibald, S., Roy, D., van Wilgen, B., Scholes, R., 2008.What limits fire? An examination of drivers of burnt area in Southern Africa. Global Change Biol.15, 613-630. Ares, J., Beeskow, A., Bertiller, M.,Rostagno,M., Irisarri, M.,Anchorena, J.,Merino, C.,1990.Structural and dynamic characteristics of overgrazed lands of Northern Patagonia, Argentina Ecosystems of the World 17A, 149-175.
Literature cited 2: Barbosa, P., Cardoso Pereira, J., Gregoire, J.-M., 1998.Comositing criteria for burned area assessment using multitemporal low resolution satellite data.Remote Sens.44, 1765-1773. Boschetti, L.,Brivio,P.,Eva,H.,Gallego,J.,Baraldi,A.,Gregoire,J.,2006.A sampling method for the retrospective validation of global burned area products.Geosci.Remote Sens.44, 1765-1773.

ID: 61014
Title: Flood detection from multi-temporal SAR data using harmonic analysis and change detection.
Author: Stefan Schlaffer, Patrick Matgen, Markus Hollaus, Wolfgang Wagner.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 15-24 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: ENVISAT, Sentinel-1, Time series analysis, Otsu, Flood hazard, Hand index.
Abstract: Flood mapping from Synthetic Aperture Radar (SAR) data has attracted considerable attention in recent Years. Most available algorithms typically focus on single-image techniques which do not take into account the backscatter signature of a land surface under non-flooded conditions. In this study, harmonic analysis of a multi-temporal time series of >500ENVISAT Advanced SAR (ASAR) scenes with a spatial resolution of 150 m was used to characterize the seasonality in backscatter under non-flooded conditions. Pixels which were inundated during a large -scale flood event during the summer 2007 floods of the River Severn (United Kingdom) showed strong deviations from normal seasonal behaviour as inferred from the harmonic model. The residuals were classified by means of an automatic threshold optimization algorithm after masking out areas which are unlikely to be flooded using a topography-derived index. The results were validated against a reference dataset derived from high-resolution airborne imagery. For the water class, accuracies >80 % were found for non-urban land uses. A slight underestimation of the reference flood extent can be seen, mostly due to the lower spatial resolution of the ASAR imagery. Finally, an outlook for the proposed algorithm is given in the light of the Sentinel-1 mission.
Location: T E 15 New Biology Building.
Literature cited 1: Bartsch, A. Pathe,C.,Wagner,W., Scipal, K., 2008.Detection of permanent open water surfaces in central Siberia with ENVISAT ASAR wide swath data with special emphasis on the estimation of methane fluxes from tundra wetlands.Hydrol.Res.39 (2), 89-100 http://www.iwaponline.com/nh/0390089.htm. Bales, X.Holecz, F., Van Leeuwen, H.J.C., Defourny, P., 2007.Regional crop monitoring and discrimination based on simulated ENVISAT ASAR wide swath mode images.Int.J.Remote Sens.28 (2), 371-393 http://www.scopus.com/inward/record.url?eid=2-s2.0-34250899958&partnerID=40&md5=92a20120d88a833da47dcfdc24d3cb.
Literature cited 2: Buttner, G., Kosztra, B., Maucha, G., Pataki, R., 2010.Implementation and Achievements of CLC2006.Tech.Rep.European Environment Agency.http://www.eea.europa.eu/data-and-maps/data/corine-land-cover-2006-raster-2. Cumming, I.G., Wong, F.H., 2005.Digital Processing of Synthetic Aperture Radar Data: Algorithms and Implementation. Artech House.

ID: 61013
Title: Linking land cover dynamics with driving forces in mountain landscape of the Northwestern Iberian Peninsula.
Author: Adrian Regos, Miquel Ninyerola, Gerard More, Xavier Pons.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 1-14 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Landcover changes, Landabondonment, Supervised classification, Landsat time-series, Wildfires, Change drivers.
Abstract: The mountainous areas of the northwestern Iberian Peninsula have undergone intense land abandonment. In this work, we wanted to determine if the abandonment of the rural areas was the main driver of landscape dynamics in Geres-Xures Transboundary Biosphere Reserve (NW Iberian Peninsula), or if other factors, such as wildfires and the land management were also directly affecting these spatio-temporal dynamics. For this purpose, we use earth observation data acquired from Landsat TM and ETM+satellite sensors, complemented by ancillary data and prior field knowledge, to evaluate the land use/land cover changes in our study region over a 10 year period (2000-2010). The images were radiometrically calibrated using a digital elevation model to avoid cast-and self-shadows and different illumination effects caused by intense topographic variations in the study area. We applied a maximum likelihood classifier, as well as other five approaches that provided insights into the comparison of thematic maps. To describe the land cover changes we addressed the analysis from a multilevel approach in three areas with different regimes of environmental protection. The possible impact of wildfires was assessed from statistical and spatially explicit fire data. Our findings suggest that land abandonment and forestry activities are the main factors causing the changes in landscape patterns. Specifically, we found a strong decrease of the ' meadows and crops ' and ' sparse vegetation areas ' in favor of woodlands and scrublands. In addition, the huge impact of wildfires on the Portuguese side have generated new ' rocky area ' , while on the Spanish side its impact does not seem to have been a decisive factor on the landscape dynamics in recent years. We conclude rural exodus of the last century, differences in land management and fire suppression policies between the two countries and the different protection schemes could partly explain the different patterns of changes recorded in these covers.
Location: T E 15 New Biology Building.
Literature cited 1: Alvarez-Martinez, J., Stoorvogel, J., Suarez-Seoane, S., de Luis calabuig, E., 2010.Uncertainty analysis as a tool for refining land dynamics modeling on changing landscapes: a case study in Spanish natural park. Landscape Ecology 25, 1385-1404. Alvarez-Martinez, J.M., Suarez-Seoane, S., De Luis Calabuig, E., 2011.Modelling the risk of land cover change from environmental and socio-economic drivers in heterogenous and changing landscapes: the role of uncertainty. Landscape urban plan.101, 108-119.
Literature cited 2: Alvarez-Martinez, J.M., Squarez-Seasone, S., Stoorvogel, J.J., de Luis Calabuig, E., 2014.Influence of land use and climate on recent forest expansion: a case study in Eurosiberian-Mediterranean limit of north-west Spain.J.Ecol.102, 905-919. Brotons, L.,Aquilue,N.,De Caceres,M.,Fortin,M.J.,Fall,A.,2013.How fire history, fire suppression practices and climate change affect wildfire regimes in Mediterranean landscapes. PloS ONE 8 (5), e62392.

ID: 61012
Title: Mapping forest biomass from space-Fusion of hyperspectral EO1-hyperion data and Tandem-X and WorldView-2 canopy height models.
Author: Teja Kattenborn, Joachim Maack, Fabian Fa?nacht, Fabian En?le, Jorg Ermert, Barbara Koch.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 359-367 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Biomass modeling, Hyperspectral, Tandem-X, Worldview-2, Canopy height models, Machine-learning-algorithms.
Abstract: Spaceborne sensors allow for wide-scale assessments of forest ecosystems. Combining the products of multiple sensors is hypothesized to improve the estimation of forest biomass. We applied interferometric (Tandem-X) and photogrammetric (WorldView-2) based predictors, e.g. canopy height models, in combination with hyperspectral predictors (EO1-Hyperion) by using 4 different machine learning algorithms for biomass estimation in temperate forest stands near Karlruhe, Germany. An iterative model selection procedure was used to identify the optimal combination of predictors. The most accurate model (Random Forest) reached a r2 of 0.73 with a RMSE of 14. 9 % (29.4 t/ha). Further results revealed that the predictive accuracy depended highly on the statistical model and the area size of the field samples. We conclude that a fusion of canopy height and spectral information allows for accurate estimations of forest biomass from space.
Location: T E 15 New Biology Building.
Literature cited 1: Anderson, J.E., Plourde, L.C., Martin, M.E., Braswell, B.H., Smith, M.L., Dubayah, R.O., Hofton, M.A., Blair, J.B., 2008. Integrating waveform LiDAR with hyperspectral imagery for inventory of a northern temperate forest. Remote Sens.Environ. 112, 1856-1870. Annighofer, P., Molder, I., Zerbe, S., Kawaletz, H., Terwei, A., Ammer, C., 2012. Biomass functions for the two alien tree species Prunus serotina Ehrh. And Robinia pseudoacacia L in floodplain forests of Northern Italy.Eur.J.Forest.Res. 131 (5), 1619-1635.
Literature cited 2: Bauer, E., Kohavi, R., 1999. An empirical comparison of voting classification algorithms: bagging, boosting, and variants.Mach.Learn. 36 (1-2), 105-139. Breiman, L., 2001. Random forests.Mach.Learn. 45 (1), 5-32.

ID: 61011
Title: Brown and green LAI mapping through spectral indices.
Author: Jesus Deegido, Jochem Verrelst, Juan P.Rivera, Antonio Ruiz-Verdu, Jose Moreno.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 350-358 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Brown LAI, Vegetation indices, Hyperspectral, Agroecosystem, Senescent vegetation, Sentinel-2
Abstract: When crops senescence, leaves remain until they fall off or are harvested. Hence, leaf area index (LAI) stays high even when chlorophyll content degrades to zero. Current LAI approaches from remote sensing techniques are not optimized for estimating LAI of senescent vegetation. In this paper a two-step approach has been proposed to realize simultaneous LAI mapping over green and senescent croplands. The first step separates green from brown LAI by means of a newly proposed index, ' Green Brown Vegetation Index (GBVI) ' . This index exploits two shortwave infrared (SWIR) spectral bands centered at 2100 and 2000 nm, which fall right in the dry matter absorption regions, thereby providing positive values for senescent vegetation and negative for green vegetation. The second step involves applying linear regression functions based on optimized vegetation indices to estimate green and brown LAI estimation respectively. While the green LAI index uses a band in the red and a band in the red-edge, the brown LAI index uses bands located in the same spectral region as GBVI, i.e. an absorption band located in the region of maximum absorption of cellulose and lignin at 2154 nm, and a reference band at 1635 nm where the absorption of both water and dry matter is low. The two-step approach was applied to a HyMap image acquired over an agroecosystem at the agricultural site Barrax, Spain.
Location: T E 15 New Biology Building.
Literature cited 1: Baret, F., Hagolle, O., Geiger, B., Bicheron, P., Miras, B., Huc, M., Berthelot, B., Nino, F., Weiss, M., Samain, O., Roujean, J.L., Leroy, M., 2007. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Part 1: Principles of the algorithm. Remote Sens.Environ. 110, 275-286. Broge, N.H., Leblanc, E., 2000. Comparing prediction power and stability of broad-band and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sens. Environ. 76, 156-172.
Literature cited 2: Brown, L., Chen, J., Leblanc, S., Cihlar, J., 2000. A shortwave infrared modification to the simple ratio for LAI retrieval n boreal forests: an image and model analysis. Remote Sens. Environ. 76, 156-172. Bsibes, A., Courault, D., Baret, F., Weiss, M., Olioso, A., Jacob, F., Hagolle, O., Marloie, O., Bertrand, N., Desfond, V., Kzemipour, F., 2009. Albedo and LAI estimates from FORMOSTART-2 data for crop monitoring. Remote Sens.Environ.113 (4), 716-729.

ID: 61010
Title: SAR interferometry and optical remote sensing for analysis of co-seismic deformation, source characteristics and mass wasting pattern of Lushan (China, April 2013) earthquake
Author: John Mathew, Ritwik Majumdar, K. Vinod Kumar.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 338-349 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Differential SAR interferometry, Longmenshan fault zone, C0-seismic, Inversion modeling, Earthquake induced landslide.
Abstract: Co-seismic deformation associated with the Lushan (China) earthquake that occurred along the south-western segment of the Longmenshan Fault Zone (LFZ) on the 20th April 2013 has been estimated by differential interferometric SAR (DinSAR) technique using Radarsat-2 data. The Lushan earthquake resulted in the deformation of the Sichuan basin and the Longmenshan ranges in proximity to the LFZ. The line of sight (LOS) displacement values obtained from DInSAR techniques mainly range between -4.0 cm to +3.0 cm. The western Sichuan basin shows oblique westward movement with predominant downward movement in areas closer to the source fault. Inversion modeling has been used to derive the seismic source characteristics from DInSAR derived deformation values using elastic dislocation source type. The linear inversion model converged at a double-fault source solution consisting of a deeper, steep, NW dipping fault plane-1 of 60 km x 16 km dimension and a shallower, gentle, NW dipping fault plane 2 of 60 km x15 km dimension, with distributed slip values varying between 0 to 2.26 m. These fault planes (fault planes-1 and -2) coincide with the Dachuan-Shuangshi fault and the buried Range Front Fault respectively. The inversion model gives a moment magnitude of 6.81 and geodetic moment of 2.07x1019 Nm, comparable to those given in literature, derived using teleseismic body wave data. Thus DInSAR technique helped to quantify the co-seismic deformation and to retrieve the source characteristics from the estimated deformation values. The study also evaluated the distribution pattern of earthquake and found that they show spatial association with the seismic source zone and also with various pre-conditioning factors of slope instability.
Location: T E 15 New Biology Building.
Literature cited 1: Askne, J., Nordius, H., 1987. Estimation of tropospheric delay for microwaves from surface weather data. Radio Sci. 22 (3), 379-386. Atzori, S., Hunstad, I., Chini, M., Salvi, S., Tolomei, C., Bignami, C., Stramondo, S., Trasatti, E., Antonioli, A., Boschi, E., 2009. Finite fault inversion of DInSAR coseismic displacement of the 2009 L ' Aquila earthquake (central Italy). Geophys.Res.Lett. 36, L15305/1-6.
Literature cited 2: Buck, A.L., 1981. New equations for computing vapor pressure and enhancement factor. J. Appl.Meteorol. 20 (12), 1527-1532. Chen, G., Ji, F., Zhou, R., Jie, X., Ben-gang, Z., Xiao-gang, L, You-qing, Y., 2007. Primary research of active segmentation of Longmenshan fault zone.Chin.Sci.Bull.58 (28-29), 3475-3482.

ID: 61009
Title: An assessment of a collaborative mapping approach for exploring land use patterns for several European metropolises.
Author: Jamal Jokar Arsanjani, Eric Vaz.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 305-319 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Landuse mapping, Comparative assessment, GMESUA, OpenStreetMap, Collaborative mapping, Citizen Science.
Abstract: Until recently, land surveys and digital interpretation of remotely sensed imagery have been used to generate land use inventories. These techniques however, are often cumbersome and costly, allocating large amounts of technical and temporal costs. The technological achievements, stimulating the participatory role in collaborative and crowd sourced mapping products. This has been forested by GPS-enabled devices, and accessible tools that enable visual interpretation of high resolution satellite images/air photos provided in collaborative mapping projects. Such technologies offer an integrative approach to geography by means of promoting public participation and allowing accurate assessment and classification of land use as well as geographical features. OpenStreetMap (OSM) has supported the evolution of such techniques, contributing to the existence of a large inventory of spatial land use information. This paper explores the introduction of this novel participatory phenomenon for land use classification in Europe ' s metropolitan regions. We adopt a positivistic approach to assess comparatively the accuracy of these contributions of OSM for land use classifications in seven large European metropolitan regions. Thematic accuracy and degree of completeness of OSM data was compared to available Global Monitoring for Environment and Security Urban Atlas (GMESUA) datasets for the chosen metropolises. We further extend our findings of land use within a novel framework for geography, justifying that volunteered geographic information (VFGI) sources are of great benefit for land use mapping depending on location and degree of VGI dynamism and offer a great alternative to traditional mapping techniques for metropolitan regions throughout Europe. Evaluation of several land use types at the local level suggests that a number of OSM classes (such as anthropogenic land use, agricultural and some natural environment classes) are viable alternatives for land use classification. These are highly accurate and can be integrated into planning decisions for stakeholders and policymakers.
Location: T E 15 New Biology Building.
Literature cited 1: Bakillah, M., Lauer, J., Liang, S., Zipf, A., Jokar Arsanjani, J., Loos, L., Mobasheri, A., 2014. Exploiting big VGI to improve routing and navigation services. In: Big Data Techniques and Technologies in Geoinformatics., pp.177-192. Bontemps, S., Defourny, P., Van Bogaert, E., Arino, O., Kalogirou, V., Ramos, P., Jose, J., 2011. GLOBCOVER 2009. Products Description and Validation Report.In: Universite catholique de Louvain (UCL) & European Space Agency (esa), vers.2.2., pp 53.
Literature cited 2: Buettner, G., Feranec, J., Jaffrain, G., 2002. December.Corine land cover update 2000.EEA.Technical Report, vol.89 (Copenhagen). Cao, L., Luo, J., Gallagher, A., Jin, X., Han, J., Huang, T.S., 2010. A worldwide tourism recommendation system based on geotagged web photos. In: IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010., pp. 2274-2277.

ID: 61008
Title: The effect of atmospheric and topographic correction on pixel-based image composites: Improved forest cover detection in mountain environments.
Author: Steven Vanonckelen, Stef Lhermitte, Anton Van Rompaey.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 305-319 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Forest cover mapping, Classification accuracy assessment, Topographic correction, Landsat, Pixel-based composting, Mountain areas.
Abstract: Quantification of forest cover is essential as a tool to stimulate forest management and conservation. Image compositing techniques that sample the most suited pixel from multi-temporal image acquisitions provide an important tool for forest cover detection as they provide alternatives for missing data due to cloud cover and data discontinuities. At present, however, it is not clear to which extent forest cover detection based on compositing can be improved if the source imagery is firstly corrected for topographic distortions on a pixel-basis. In this study, the results of a pixel compositing algorithm with and without preprocessing topographic correction are compared for a study area covering 9 Landsat footprints in the Romanian Carpathians based on two different classifiers: Maximum Likelihood (ML) and support Vector Machine (SVM). Results show that classifier selection has a stronger impact on classification accuracy than topographic correction. Finally, application of the optimal method (SVM classifier with topographic correction) on the Romanian Carpathian Ecoregion between 1985, 1995 and 2010 shows a steady greening due to more afforestation than deforestation.
Location: T E 15 New Biology Building.
Literature cited 1: Alcantara, C., Radeloff, V.C., Prishchepov, A.V., Kuemmerle, T., 2012. Mapping abandoned agriculture with multi-temporal MODIS satellite data. Remote Sens.Environ. 124, 334-347. Arvidson, T., Gasch, J., Goward, S.N., 2001. Landsat 7 ' s long term acquisition plan-an innovative approach to building a global archive, Special Issue on Landsat 7. Remote Sens.Environ.78, 13-26.
Literature cited 2: Arvidson, T., Goward, S., Gasch, J., Williams, D., 2006. Landsat-7 long-term acquisition plan: development and validation.Photogram.Eng.Remote Sens. 72, 1137-1146. Balthazar, V., Vanacker, V., Lambin, E., 2012. Evaluation and parameterization of ATCOR3 topographic correction method for forest cover mapping in mountain areas.Int.J.Appl.Earth Obs.Geoinform. 18, 436-450.

ID: 61007
Title: Active extreme learning machines for quad-polarimetric SAR imagery classification.
Author: Alim Samat, Paolo Gamba, Peijun Du, Jieqiong Luo.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 305-319 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: PolSAR, Extreme learning machine, Ensemble learning, Active learning, Active extreme learning machines.
Abstract: Supervised classification of quad-polarimetric SAR images is often constrained by the availability of reliable training samples. Active learning (AL) provides a unique capability at selecting samples with high representation quality and low redundancy. The most important part of AL is the criterion for selecting the most informative candidates (pixels) by ranking. In this paper, class supports based on the posterior probability function are approximated by ensemble learning and majority voting. This approximation is statistically meaningful when a large enough classifier ensemble is exploited. In this work, we propose to use extreme learning machines and apply AL to quad-polarimetric SAR image classification. Extreme learning machines are ideal because of their fast operation, straightforward solution and strong generalization. As inputs to the so-called active extreme learning machines, both polarimetric and spatial features (morphological profiles) are considered. In order to validate the proposed method, results and performance are compared with random sampling and state-of-the-art AL methods, such as margin sampling, normalized entropy query-by-bagging and multiclass level uncertainty. Experimental results for four quad-polarimetric SAR images collected by RADARSAT-2, AirSAR and EMISAR indicate that the proposed method achieves promising results in different scenarios. Moreover, the proposed method is faster than existing techniques in both the learning and the classification phases.
Location: T E 15 New Biology Building.
Literature cited 1: Ainsworth, T.L., Kelly, J.P., Lee, J.S., 2009. Classification comparisons between dual-pool, compact polarimeric and quad-pol SAR imagery. ISPRS J.Photogr.Remote Sens. 64 (5), 464-471. Benediktsson, J.A, Palmason, J.A., Sveinsson, J.R., 2005. Classification of hyperspectral data from urban areas based on extended morphological profiles.IEEE Trans.Geosci.Remot Sens. 43 (3), 480-491.
Literature cited 2: Breiman, L., 1996.Bagging predictors.Mach.Learn. 24 (2), 123-140. Cloude, S.R., Pottier, E., 1996. A review of target decomposition theorems in radar polarimetry.IEEE Trans.Geosci.Remote Sens. 41 (1), 4-19.

ID: 61006
Title: Spectral anisotropy of subtropical forest using MISR and MODIS data acquired under large seasonal variation in solar zenith angle.
Author: Fabio Marcelo Breunig, Lenio Soares Galvao, Joao dos Santos, Anatoly A. Gitelson, Yhasmin Mendes de Moura, Thiago Sousa Teles, William Gaida.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 35 (B) 294-304 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: MISR, MODIS, View-illumination geometry, NDVI, EVI, PROSAIL.
Abstract: Recent studies in Amazonian tropical evergreen forests using the Multi-angle Imaging SpectroRadiometer (MISR) and Moderate Resolution Imaging Spectroradiometer (MODIS) have highlighted the importance of considering the view-illumination geometry in satellite data analysis. However, contrary to the observed for evergreen forests, bidirectional effects have not been evaluated in Brazilian subtropical deciduous forests. In this study, we used MISR data to characterize the reflectance and vegetation index anisotropies in subtropical deciduous forest from south Brazil under large seasonal solar zenith angle (SZA) variation and decreasing leaf area index (LAI) from summer to winter. MODIS data were used to observe seasonal changes in the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI). Topographic effects on their determination were inspected by dividing data from the summer to winter and projecting results over a digital elevation model (DEM). By using the PROSAIL, we investigated the relative contribution of LAI and SZA to vegetation indices (VI) of deciduous forest. We also simulated and compared the MISR NDVI and EVI response of subtropical deciduous and tropical evergreen forests as a function of the large seasonal SZA amplitude of 33?. Results showed that the MODIS-MISR NDVI and EVI presented higher values in the summer and lower ones in the winter with decreasing LAI and increasing SZA or greater amounts of canopy shadows viewed by the sensors. In the winter, NDVI reduced local topographic effects due to the red-near infrared (NIR) band normalization. However, the contrary was observed for the three-band EVI that enhanced local variations in shaded and sunlit surfaces due to its strong dependence on the NIR band response. The reflectance anisotropy of the MISR bands increased from the summer to winter and was stronger in the backscattering direction at large view zenith angles (VZA), EVI was much more anisotropic than NDVI and the anisotropy increased from the summer to winter. It also increased from the forward scatter to the backscattering direction with the predominance of sunlit canopy components viewed by MISR, especially at large VZA. Modeling PROSAIL results confirmed the stronger anisotropy of EVI than NDVI for the subtropical deciduous and tropical evergreen forests. PROSAIL showed that LAI and SZA are coupled factors to decrease seasonally the VIs of deciduous forest with the first one having greater importance than the latter. However, PROSAIL seasonal variations in VIs were much smaller than those observed with MODIS data probably because the effects of shadows in heterogeneous canopy structures or/and cast by emergent trees and from local topography were not modeled.
Location: T E 15 New Biology Building.
Literature cited 1: Anderson, L.O., Aragao, L., Shimabukuro, Y.E., Almeida, S., Huete, A., 2011. Fraction images for monitoring intra-annual phenology of different vegetation physiognomies in Amazonia.Int.J.Remote Sens.32, 387-408. Asner, G.P., Alencar, A., 2010. Drought impacts on the Amazon forest: the remote sensing perspective. New Phytol.187, 569-578.
Literature cited 2: Atkinson, P.M., Dash, J., Jeganathan, C., 2011. Amazon vegetation greenness as measured by satellite sensors over the last decade.Geophys.Res.Lett.38, Lett.38, L19105. Baptista V.A., Leal-Zancher, A.M., 2010. Land flatworm community structure in a subtropical deciduous forest in Southern Brazil.Belg.J.Zool.140, 83-90.