Enter records

ID: 61027
Title: Satellite monitoring of urbanization and environmental impacts-A comparison of Stockholm and Shanghai.
Author: Jan Hass, Dorothy Furberg, Yifang Ban.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 138-149 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Urbanization, Landuse/land cover (LULC), Ecosystem services, Landscape metrics, Environmental impact, SVM.
Abstract: This study investigates urbanization and its potential environmental consequences in Shanghai and Stockholm metropolitan areas over two decades. Changes in land use/land cover are estimated from support vector machine classifications of Landsat mosaics with grey-level co-occurrence matrix features. Landscape metrics are used to investigate changes in landscape composition and configuration and to draw preliminary conclusions about environmental impacts. Speed and magnitude of urbanization is calculated by urbanization indices and the resulting impacts on the environment are quantified by ecosystem services. Growth of urban areas and urban green spaces occurred at the expense of cropland in both regions. Alongside a decrease in natural land cover, urban areas increased by approximately 120% in Shanghai, nearly ten times as much as in Stockholm, where the most significant land cover change was a 12 % urban expansion that mostly replaced agricultural areas. From the landscape metrics results, it appears that fragmentation in both study regions occurred mainly due to the growth of high density built-up areas in previously more natural/agricultural environments, while the expansion of low density built-up areas was for the most part in conjunction with pre-existing patches. Urban growth resulted in ecosystem service value losses of approximately 445 million US dollars in Shanghai, mostly due to the decrease in natural coastal wetlands while in Stockholm the value of ecosystem services changed very little. Total urban growth in Shanghai was 1768 km2 and 100km2 in Stockholm. The developed methodology is considered a straight-forward low-cost globally applicable approach to quantitatively and qualitatively evaluate urban growth patterns that could help to address spatial, economic and ecological questions in urban and regional planning.
Location: T E 15 New Biology Building.
Literature cited 1: Alberti, M., 2005.The effects of urban patterns on ecosystemfunction.Int.Reg.Sci.Rev.28 (2), 168-192. Anderson, E., Ahrne, K., Pyykonen, M., Elmqvist, T., 2009.Patterns and scale relations among urbanization measures in Stockholm, Sweden.Lan.Ecol.24 (10), 1331-1339.
Literature cited 2: Ban,Y., Jacob,A.,2013.Object-based fusion of multitemporal multi-angle ENVISAT ASAR and HJ1-B multispectral data for urban land-cover mapping.IEEE Trans.Geosci.Remote Sens.51 (4), 1998-2006. Ban,Y.,Jacob,A.,Gamba,P.,2014a.Spaceborne SAR data for global urban mapping at 30 m resolution using a robust urban extractor.ISPRS J.Photogramm.Remote Sens., In press.

ID: 61026
Title: Land cover changed object detection in remote sensing data with medium spatial resolution.
Author: Xiao tong Yang, Huiping Liu, Xiaofeng Gao.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 129-137 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Multi-temporal segmentation, Landcover changed object, Change indicators, Segmentation scale, Chi-square transformation.
Abstract: Landcover change information is crucial to analyse the process and the change patterns of environments and ecological systems. Recent studies have incorporated object-based image analysis for its ability to generate meaningful geographical objects into studies of change detection. In this research, we developed a systematic methodology to realize multi-type land cover changed object detection with medium spatial resolution remote sensing images in Beijing, China. Optimum index factor (OIF) was applied to determine the best change indicators and the chi-square transformation was carried out to determine the change threshold of the 4 classes of changed object. The clustering change vectors in the feature space were proposed to discriminate the change types. According to the accuracy assessment, the overall accuracy of changed/unchanged object detection was approximately 93.9 % with an overall kappa of 0.824, and the change type discrimination also achieved an overall accuracy of 81.67 %, indicating the effectiveness of the proposed method.
Location: T E 15 New Biology Building.
Literature cited 1: An, K., Zhang, J., Xiao, Y., 2007.Object-oriented urban dynamic monitoring-A case study of Haldian District of Beijing.Chin.Geog.Sci.17, 236-242. Benz, U.C., Hoffmann, P., Willhauck, G., Lingenfelder, I., Heynen, M., 2004.Multi-resoution: object-oriented fuzzy analysis of remote sensing data for GIS-ready information.ISPRS J.Photogramm.Remote Sens.58, 239-258.
Literature cited 2: Bontemps, S., Bogaert, P., Titeux, N., Defourny, P., 2008. An object-based change detection method accounting for temporal dependences in time series with medium to coarse spatial resolution. Remote Sens.Environ.112, 3181-3191. Bryant, R.G., Gilvear, D.J., 1999.Quntifying geomorphic and riparian land cover changes either side of a large flood event using airborne remote sensing: River Tay Scotland. Geomorphology 29, 307-321.

ID: 61025
Title: Methods for improving accuracy and extending results beyond periods covered by traditional ground-truth in remote sensing classification of a complex landscape.
Author: George W.Mueller-Warrant, Gerald W.Whittaker, Gary M.Banowetz, Stephen M.Griffith, Bradley L.Barnhart.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 115-128 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Agriculture, Ground-truth data, Landuse, Landcover, Object-based, Pixel-based, Majority-rule.
Abstract: Successful development of approaches to quantify impacts of diverse landuse and associated agricultural management practices on ecosystem services is frequently limited by lack of historical and contemporary landuse data. We hypothesized that ground truth data from one year could be used to extrapolate previous or future landuse in a complex landscape where cropping systems do not generally change greatly from year to year because the majority of crops are established perennials or the same annual crops grown on the same fields over multiple years. Prior to testing this hypothesis, it was first necessary to classify 57 major landuses in the Willamette Valley of western Oregon from 2005 to 2011 using normal same year ground-truth, elaborating on previously published work and traditional sources such as Cropland Data Layers (CDL) to more fully include minor crops grown in the region .Available remote sensing data included Landsat, MODIS 16-day composites, and National Aerial Imagery Program (NAIP) imagery, all of which were resampled to a common 30 m resolution. The frequent presence of clouds and Landsat7 scan line gaps forced us to conduct of series of separate classifications in each year, which were then merged by choosing whichever classification used the highest number of cloud-and gap-free bands at any given pixel. Procedures adopted to improve accuracy beyond that achieved by maximum likelihood pixel classification included majority-rule reclassification of pixels within 91,442 Common Land Unit (CLU) polygons, smoothing and aggregation of areas outside the CLU polygons, and majority-rule reclassification over time of forest and urban development areas. Find classifications in all seven years separated annually disturbed agriculture, established perennial crops, forest, and urban development from each other at 90 to 95 % overall 4-class validation accuracy. In the most successful use of subsequent year ground-truth data to classify prior year landuse, an overall 57-class accuracy of 75 % was achieved despite the omission of 10 entire classes, most of which were annually disturbed or perennial crops grown on very few fields. Synthetic ground-truth data for the 2004 harvest year based on the most common landuse classes over the following 7 years classified 49 of 57 categories at an overall accuracy of 96 % in a final version that included CLU polygon majority rule, default smoothing and aggregation, and forcing of urban development and forest from multi-year majority-rule.
Location: T E 15 New Biology Building.
Literature cited 1: Anonymous, 2007, USDA, National Agricultural Statistics Service, 2007 Oregon Cropland Data Layer. Available online at: http://www.nass.usda.gov/research/Cropland/metadata/metadata.or07 htm (accessed 19.05.2009) Anonymous, 2009, USDA, Natural Resources Conservation Service, Conservation Effects Assessment Project (CEAP).Available online at: http://www.nrsc.usda.gov/technical/NRI/ceap/index.html (accessed 14.10.2009).
Literature cited 2: Aplin, P.,Atkinson,P.M.,Curran,P.J.,1999.Per-field Classification of Land Use Using the Forthcoming Very Fine Spatial Resolution Satellite Sensors: Problems and Potential Solutions.In:Atkinson, Tate (Eds), In Advances in Remote Sensing and GIS Analysis. John Wiley and Sons, West Sussex, UK, pp.219-239. Gitau, M.W.,Chaubey, I., Gbur,E.,Pennington,J.H.,Gorham,B., 2010.Impacts of land-use change and best management practice implementation in a conservation effects assessment project watershed:northwest Arkansas.J.Soil Water Conserv.65 (6), 353-368.

ID: 61024
Title: A spatiotemporal mining framework for abnormal association patterns in marine envoironments with a time series of remote sensing images.
Author: Cunjin Xue, Wanjiao Song, Lijuan Qin, Qing Dong, Xiaoyang Wen.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 38 105-114 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Marine association pattern, Spatiotemporal mining framework, Global change, Remote sensing, Pacific Ocean.
Abstract: A spatiotemporal mining framework is a novel tool for the analysis of marine association patterns using multiple remote sensing images. From data pretreatment, to algorithm design, to association rule mining and pattern visualization, this paper outlines a spatiotemporal mining framework for abnormal association patterns in marine environments, including pixel-based and object-based mining models. Within this framework, some key issues are also addressed. In the data pretreatment phase, we propose an algorithm for extracting abnormal objects or pixels over marine surfaces, and construct a mining transaction table with object-based and pixel-based and object-based mining models. Within this framework, some key issues are also addressed In this data pretreatment phase, we propose an algorithm for extracting abnormal objects or pixels over marine surfaces, and construct a mining transaction table with object-based and pixel-based strategies. In the mining algorithm phase, a recursion method to construct a direct association pattern tree is addressed with an asymmetric mutual information table, and a recursive mining algorithm to find frequent items. In the knowledge visualization phase, a ?Dimension-Attributes? visualization framework is used to display spatiotemporal association patterns. Finally, spatiotemporal association patterns for marine environmental parameters in the Pacific Ocean are identified, and the results prove the effectiveness and the efficiency of the proposed mining framework.
Location: T E 15 New Biology Building.
Literature cited 1: Agrawal, R., Srikant, R.1994.Fast algorithm for mining association rules. September 12-15, 1994, Santiago, Chile, Morgan Kaufmann In: Bocca, J.B., Jerke, M., Zaniolo, C. (Eds), Proceeding of the 20th International Conference on Very Large Databases, VLDB, 1215, pp.407-419, ISBN 1-55860-153-8. Bertolotto, M., DiMartino, S., Ferrucci, F., Kechadi, T., 2007.Towards a framework for mining and analysis spatio-temporal datasets.Int.J.Geog.Inf.Sci. 21 (8), 895-906.
Literature cited 2: Blanchard, J., Pinaud, B., Kuntz, P., Guilet, F., 2007.A 2D-3D visualization support for human-centered rule mining.Comput. Graphics 31, 350-360. Casey, K.S., Adamec, D., 2002.Sea surface temperature and sea surface height variability in the North Pacific Ocean from 1993 to 1999.J.Geophys.Res.107 (C8), 3099, http://dx.doi.org/10.1029/2001JC001060.

ID: 61023
Title: Fusion of TerraSAR-x and Landsat ETM+data for protected area mapping in Uganda.
Author: John Ricard Otukei, Thomas Blaschke, Michael Collins.
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 99-104 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: TerraSAR-X, Landsat ETM+, Decision trees, Image fusion.
Abstract: TerraSAR-X satellite acquires very high spatial resolution data with potential for detailed land cover mapping.A known problem with synthetic aperture radar (SAR) data is the lack of spectral information. Fusion of SAR and multispectral data provides opportunities for better image interpretation and information extraction. The aim of this study was to investigate the fusion between TerraSAR-X and Landsat ETM+ for protected area mapping using high pass filtering (HPF), principal component analysis with band substitution (PCA) and principal component with wavelet transform (WPCA). A total of thirteen land cover classes were identified for classification using a non-parametric C 4.5 decision tree classifier. Overall classification accuracies of 74.99 %, 83.12 % and 85.38 % and kappa indices of 0.7220, 0.8100 and 0.8369 were obtained for HPF, PCA and WPCA fusion approaches respectively. These results indicate a high potential for a combined use of TerraSAR-X and Landsat ETM+ data for
Location: T E 15 New Biology Building.
Literature cited 1: Abd-Elrahman, A., Shaker, I.F., Abdel-Gawad, A.K., Abdel-Wahab, A., 2008.Enhancement of cloud-associated shadow areas in satellite images using wavelet image fusion. World Appl.Sci.J.4, 363-370. Al-Wasai, F.A., Kalyankar, N.V., Al-Zuky, A.A., 2011.The HIS transformations based image fusion.J.Global Res.Comput.Sci.2, 70-77.
Literature cited 2: Amolins, K., Zhang, Y., Dare, P., 2007.Wavelet based image fusion techniques-an introduction, review and comparison.ISPRS J.Photogramm.RTemote Sens.62, 249-263. Aplin, P., 2003.Remote sensing: base mapping.Prog.Phys.Geog.27, 275-283.

ID: 61022
Title: Fully constrained linear spectral unmixing based global shadow compensation for high resolution satellite imagery of urban areas.
Author: Jian Yang, Yuhong He, John Caspersen.
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 88-98 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Global shadow compensation, object-based shadow detection, Linear spectral unmixing, Spectral mixing space, Spectral scatter plot, WorldView-2.
Abstract: Shadows commonly exist in high resolution satellite imagery, particularly in urban areas, which is a combined effect of low sun elevation, off-nadir viewing angle, and high-rise buildings. The presence of shadows can negatively affect image processing, including land cover classification, mapping and object recognition due to the reduction or even total loss of spectral information in shadows. The compensation of spectral information in shadows is thus one of the most important preprocessing steps for the interpretation and exploitation of high resolution satellite imagery in urban areas. In this study, we propose a new approach for global shadow compensation through the utilization of fully constrained linear spectral unmixing. The basic assumption of the proposed method is that the construction of the spectral mixing space. In order to ensure the continuity of land covers, a smooth operator is further used to refine the restored shadow pixels on the edge of non-shadow and shadow areas. The proposed method is validated using the WorldView -2 multisopectral imagery collected from downtown Toronto, Ontario, Canada. In comparison with the existing linear-correlation method, the proposed method produced the compensated shadows with higher quality.
Location: T E 15 New Biology Building.
Literature cited 1: Arbel, E., Hel-Or, H., 2011. Shadow removal using intensity surfaces and texture anchor points.IEEE Trans.Pattern Anal.Mach.Intell. 33, 1202-1216. Benz, U.C., Hoffmann, P., Willhuck, G., Lingenfelder, I., Heynen, M., 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRSJ.Photogramm.Remote Sens.58, 239-258.
Literature cited 2: Chen, Y., Wen, D., Jing, L., Shi, P., 2007. Shadow information recovery in urban areas from very high resolution satellite imagery.Int.J.Remote Sens.28, 3249-3254. Dare, P.M., 2005.Shadow analysis in high-resolution satellite imagery of urban areas from very high resolution satellite imagery.Int.J.Remote Sens.28, 3249-3254.

ID: 61021
Title: An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data.
Author: Yang Sao, James B.Campbell, Gregory N.Taff, Baojuan Zheng.
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 78-87 (2015).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Cropland masks, MODIS, Ancillary data, Random forest, Corn yield forecasting.
Abstract: The Midwestern United States is one of the World ' s most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/yearly prediction. Our corn yield estimates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model ' s predictive error distribution .The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.
Location: T E 15 New Biology Building.
Literature cited 1: Becker-Reshef, I., Vermote, E., Linderman, M., Justice, C., 2010.A generalized regression-based model for forecasting winter wheat yields in Kansas and Ukraine using MODIS data. Remote Sens.Environ.114 (6), 1312-1323. Boryan, C., Yang, Z., Mueller, R., Craig, M., 2011.Monitoring US agriculture: the US department of agriculture, national agricultural statistics service, cropland data layer program.Geocarto Int.26 (5), 341-358.
Literature cited 2: Breiman, L., 2001. Random forests.Mach.learn, 45 (1), 5-32. Chen, J., Jonsson, P., Tamura, M., GU, Z., Matsushita, B., Eklundh, L., 2004. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sensor Environ.91 (3), 332-344.

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.