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ID: 60075
Title: Hierarchical Segmentation of urban satellite imagery.
Author: Bardia Yousefi, Seyed Mostafa Mirhassani, Alireza AhmadiFard, MohammadMehdi Hosseini.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 158-166 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Very high resolution satellite imagery, Gabor wavelet, Bayesian classifier, Relaxation labeling.
Abstract: This paper proposes a method to combine contextual, structural, and spectral information for classification. This method is an integrated method for automatically classifying urban-area objects in very high-resolution satellite imagery. The approach addresses three aspects. First, the Gabor wavelet is applied to the image along with morphological operations, with the sparsity of the outcome considered. A Bayesian classifier then categorizes the different classes, such as buildings, roads, open areas, and shadows. There are some false positives (wrong classification), and false negatives (non-classification) in the initial results. These results can be corrected by the relaxation labeling categorization of the unknown regions. The novelty of the proposed approach lies in the extensive use of spatiotemporal features considering the sparsity of urban objects. The results indicate improvements in classification through relaxation labeling compared with existing methods.
Location: TE 15 New Biology Building
Literature cited 1: Ahmadi, F.F., Ebadi, H., 2009. An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images. Sensors 9 (4), 2320-2333. Al Khudairy, D.H., Caravaggi, I., Glada, S., 2005. Structural damage assessments from IKONOS data using change detection, object-oriented segmentation, and classification techniques. Photogr. Eng. Remote Sensing 71 (7), 825-837
Literature cited 2: Araya, Y.H., Cabral, P., 2010. Analysis and modeling of urban land cover change in Setbal and Sesimbra, Portugal. Remote Sensing 2, 1549-1563. Aubrecht, C., Steinnocher, K., Hollaus, M., Wagner, W., 2008. Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use. Comput. Environ. Urban Syst. 33 (1), 15-25.

ID: 60074
Title: Oil spill detection using synthetic aperture radar images and feature selection in shape space.
Author: Yue Guo, Heng Zhen Zhang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 146-157 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: : SAR, Oil-spill, Lookalikes, Feature selection, Shape space.
Abstract: The major goal of the present study is to describe a method by which synthetic aperture radar (SAR) images of oil spills can be discriminated from other phenomena of similar appearance. The optimal features of these dark formations are here identified. Because different materials have different physical properties, they form different shapes. In this case, oil films and lookalike materials have different fluid properties. In this paper, 9 shape features with a total of 95 eigenvalues were selected. Using differential evolution feature selection (DEFS), similar eigenvalues were extracted from total space of oil spills and lookalike phenomena. This process assumes that these similar eigenvalues impair classification. These similar eigenvalues are removed from the total space, and the important eigenvalues (IEs), those useful to the discrimination of the targets, are identified. At least 30 eigenvalues were found to be inappropriate for classification of our shapes spaces. The proposed method was found to be capable of facilitating the selection of the top 50 IEs. This allows more accurate classification. Here, accuracy reached 94%. The results of the experiments show that this novel method performs well. It could also be made available to teams across the world very easily.
Location: TE 15 New Biology Building
Literature cited 1: Ai-Bin, J., 2009. Research on Visual Feature Analysis and Classification of Network Education Graphics Resources. Shandong Normal University. Danisi, A., Di Martino, G., Iodice, A., Riccio, D., Ruello, G., Tello, M., Mallorqui, J.J., Lopez-Martinez, C., 2007, SAR simulation of ocean scenes covered by oils slicks with arbitrary shapes. IGARSS 2007, 1314-1317.
Literature cited 2: Brekke, C., Solberg, A., 2005a. Oil spill detection by satellite remote sensing. Remote Sensing of Environment 95 (1), 1-13. Brekke, C., Solberg, A., 2005b. Feature extraction for oil spill detection based on SAR images. Lecture Notes in Computer Science 3540, 75-84, http://dx.doi.org/10.1007/b 137285.

ID: 60073
Title: Temporal dynamics of spatial heterogeneity over cropland quantified by time-series NDVI, near infrared and red reflectance of Landsat 8 OLI imagery.
Author: Yanling Ding, Kai Zhao. Xingming Zheng, Tao Jiang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 139-145 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Spatial heterogeneity, Mean length variability, NDVI, Near infrared and red reflectance, Fractional vegetation cover.
Abstract: Spatial heterogeneity is an important characteristic of the land surface. Because multi-spectral bands are used to describe the land surface, an approach has to be established to characterize the surface spatial heterogeneity from multi-spectral remote-sensing observations. This work aims at quantifying the spatial heterogeneity of cropland using variograms for multi-temporal NDVI, near infrared (NIR) and red reflectance. A concept of mean length variability is proposed to compare the difference in spatial heterogeneity detected by variables with different magnitudes. The important temporal changes in spatial heterogeneity observed by NDVI, NIR and red bands over cropland are a result of changes in the fraction of vegetation cover. The results indicate the following: (1) the NIR and red variables detect a similar spatial heterogeneity of the cropland with similar values of the mean length variability before the sowing crops; (2) the NDVI, NIR and red values capture different degrees of spatial heterogeneity when vegetation is low; (3) over medium vegetation cover, the NDVI and NIR values capture similar spatial heterogeneity, which is low compared to the red band due to the homogeneity of soil; and (4) the spatial heterogeneity quantified by the NIR values is more heterogeneous than those of the NDVI and red values when vegetation cover is high. The red reflectance is sensitive to soil properties while the NIR reflectance responds to vegetation. The spatial heterogeneity of red reflectance decreases and that of the NIR reflectance increases with the growth of vegetation. The NDVI value shows the greatest heterogeneity in the early stage of crop growth. With an increase in the image pixel size, the spatial heterogeneity quantified by the mean length variability of the NDVI, NIR and red variables tends to be the same.
Location: TE 15 New Biology Building
Literature cited 1: Allen, W.A., Richardson, A.J., 1968. Interaction of light with plant canopy. Journal of the optical Society of America 58 (8), 1023-1028. Burgheimer, J., Wilske, B., Maseyk, K., Karnieli, A., Zaddy, E., Yakir, D., Kesselmeier, J., 2006. Relationships between Normalized Difference Vegetation Index (NDVI) and carbon fluxes of biologic soil crusts assessed by ground measurements. Journal of Arid Environment 64, 651-669.
Literature cited 2: Chen, P.Y., Chen, C.H., Hsu, N.S., Wu, C.M., Wen, J.C., 2012. Influence of heterogeneity on unsaturated hydraulic properties: 1. Local heterogeneity and scale effect. Hydrological processes 22 (1), 61-78. Currah, P.J., Atkinson, P.M., 1998. Geostatistics and remote sensing. Progress in Physical Geography. 22 (1), 61-78.

ID: 60072
Title: Bayesian area-to -point Kriging using expert knowledge as informative priors.
Author: Phuong N. Truong, Gerard B.M. Heuvelink, Edzer Pebesma.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 128-138 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Spatial disaggregation, Area-to-point kriging, Informative Bayesian area-to-point, estimator, Statistical expert elicitation, Expert knowledge, Area-to-point conditional simulation.
Abstract: Area-to-point (ATP) kriging is a common geostatistical framework to address the problem of spatial disaggregation or downscaling from block support observations (BSO) to point support (poS) predictions for continuous variables. This approach requires that the poS variogram is known. Without poS observations, the parameters of the poS variogram cannot be deterministically estimated from BSO, and as a result, the poS variogram parameters are uncertain. In this research, we used Bayesian ATP conditional simulation to estimate the poS variogram parameters from expert knowledge and BSO, and quantify uncertainty of the poS variogram parameters and disaggregation outcomes. We first clarified that the nugget parameter of the poS variogram cannot be estimated from only BSO. Next, we used statistical expert elicitation techniques to elicit the poS variogram parameters from expert knowledge. These were used as informative priors in a Bayesian inference of the poS variogram from BSO and implemented using a Markov chain Monte Carlo algorithm. ATP conditional simulation was done to obtain stochastic simulations at point support. MODIS (Moderate Resolution Imaging Spectroradiometer) atmospheric temperature profile data were used in an illustrative example. The outcomes from the Bayesian ATP inference for the Matern variogram model parameters confirmed at the posterior distribution of the nugget parameter was effectively the same as its prior distribution; for the other parameters, the uncertainty was substantially decreased when BSO were introduced the Bayesian ATP estimator. This confirmed that expert knowledge brought new information to infer the nugget effect at poS while BSO only brought new information to infer the other parameters. Bayesian ATP conditional simulations provided a satisfactory way to quantify parameters and model uncertainty propagation through spatial disaggregation.
Location: TE 15 New Biology Building
Literature cited 1: Albert, J., 2009. Bayesian Computation with R. Springer, New York. Atkinson, P.M., 2013. Downscaling in remote sensing. Int. J. Appl. Earth Obs. Geoinf. 22, 106-114.
Literature cited 2: Chib, S., Greenberg, E., 1995. Understanding the Metropolis-Hastings algorithm.Am.Stat.49, 327-335. Chiles, J.P., Delfiner, P., 1999. Geostatistics: Modeling Spatial Uncertainty. Wiley Series in probability and Statistics. Wiley, New York.

ID: 60071
Title: Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation.
Author: Paolo Villa, Alijafar Mousivand, Mariano Bresciani.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 113-127 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Vegetation indices, Remote sensing, Sensitivity analysis, Radiative transfer models, NDAVI, WAVI.
Abstract: Although spectral vegetation indices (Vis) have been widely used for remote sensing of vegetation in general, such indices have been traditionally targeted at terrestrial, more than aquatic, vegetation. This study introduces two new VIs specifically targeted at aquatic vegetation: NDAVI and WAVI and assesses their performance in capturing information about aquatic vegetation features by comparison with preexisting performance in capturing information about aquatic vegetation features by comparison with preexisting indices: NDVI, SAVI and EVI. The assessment methodology is based on: (i) theoretical radiative transfer modeling of vegetation canopy-backgrounds coupling, and (ii) spectral linear mixture simulation based on real-case endmembers. Two study areas, Lake Garda and Lakes of Mantua, in Northern Italy, and a multisensory dataset have been exploited for our study. Our results demonstrate the advantages of the new indices. In particular, NDAVI and WAVI sensitivity scores to LAI and LIDF parameters were generally higher than pr-existing indices ' ones. Radiative transfer modeling and real-case based linear mixture simulation showed a general positive, non-linear correlation of vegetation indices with increasing LAI and vegetation fractional cover (FC), more marked for NDVI and NDAVI. Moreover, NDAVI and WAVI show enhanced capabilities in separating terrestrial from aquatic vegetation response, compared to pre-existing indices, especially of NDVI. The new indices provide good performance in distinguishing aquatic from terrestrial vegetation: NDAVI over low density vegetation (LAI< 0.7-1.0, FC<40-50%), and WAVI over medium-high density vegetation (LAI>1.0, FC> 50%). Specific vegetation indices can therefore improve remote sensing applications for aquatic vegetation monitoring.
Location: TE 15 New Biology Building
Literature cited 1: Asrar, G., Myneni, R.B., Li, Y., Kanemasu, E.T., 1989. Measuring and modeling spectral characteristics of a tallgrass prairie. Remote Sensing of Environment 27 (2), 143-155. Bacour, C., Jacquemoud, S., Tourbier, Y., Dechambre, M., Frangi, J.P., 2002. Design and analysis of numerical experiments to compare four canopy reflectance models. Remote Sensing of Environment 79, 72-83.
Literature cited 2: Borja, A., Elliott, M., Henriksen, P., Marba, N., 2013. Transitional and Coastal waters ecological status assessment: advances and challenges resulting from implementing the European Water Framework Directive. Hydrobiologia 704, 213-229. Bresciani, M., Stroppiana, D., Fila, G.L., Montagna, M., Giardino, C., 2009. Monitoring reed vegetation in environmentally sensitive areas in Italy.European Journal of Remote Sensing 41 (2, 125-137.

ID: 60070
Title: High Nature value farmland identification from satellite imagery, a comparison of two methodological approaches.
Author: Gerard Hazeu, Pavel Milenov, Bas Pedroli, Vessela Samoungi, Michiel Van Eupen, Vassil Vassilev.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 98-112 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: HNV farmland, Monitoring, Mapping, Remote sensing, Netherlands, Bulgaria.
Abstract: While the identification of High Nature Value (HNV) farmland is possible using the difference types of spatial information categories available at European scale, most data used is still too coarse and therefore only provides an approximate estimate of the presence of HNV farmland. This paper describes two promising methods using remote sensing-one for HNV farmland identification and one for change detection within HNV farmland. The performance of the two methods is demonstrated by detailed results for two case studies-the Netherlands for the HNV farmland identification, and Bulgaria for change detection within HNV farmland. An estimation of the presence of HNV farmland or of HNV farmland change can well be based on high -resolution satellite imagery, but the classification method must be adapted to regional characteristics such as field size and type of landscape. The temporal variability and bio-climatological characteristics across Europe do not allow for a simple European classification of HNV farmland. Also comparison between years is complicated because of the large impact of seasonal variation in the land cover expression and the complexity of the HNV farmland definitions. Although HNV farmland detection methods are promising, remote sensing alone does not yet provide the appropriate tools for adequate monitoring.
Location: TE 15 New Biology Building
Literature cited 1: Andersen, E., Baldock, D., Bennett, H., Beaufoy, G., Bignal, E., Brouwer, F., Elbersen, B., Eiden, G., Godeschalk, F., Jones, G., McCracken, D., Nieuwenhuizen, W., van, Eupen, M., Hennekens, S., Zervas, G., 2003. Developing a High Nature Value Farming area indicator. Report to the European Environment Agency, Copenhagen. Beaufoy, G., Jones, G., De Rijck, K., Kazakova, Y., 2008. High Nature Value farmlands: recognizing the importance of South East European landscapes (Bulagaria & Romania). In: WWF Danube-Carpathian Programme and European Forum on Nature Conservation and Pastoralism.
Literature cited 2: Cooper, T., Arblaster, K., Baldock, D., Farmer, M., Beaufoy, G., Jones, G., Poux, X., McCracken, D., Bignal, E., Elbersen, B., Wascher, D., Angelstam, P., Roberge, J-M., Pointerau, P., Seffer, J., Galvanek, D., 2007. Final report for the study on HNV indicators for evaluation. Report for the European Commission, DG Agriculture, contract notice 2006-G4-04. Institute for European Environmental Policy (IEEP), London, pp.190. Definiens, 2005. Definiens eCognition Version 5 Object Oriented Image Analysis User 5 Guide. Definiens AG, Munich.

ID: 60069
Title: Variation analysis of lake extension in space and time from MODIS images using random sets.
Author: Xi Zhao, Alfred Stein, Xiang Zhang, Lian Feng, Xiaoling Chen.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 86-97 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Water extent, Spatial- temporal pattern, Variation, Random spread process, Random set, Multitemporal images.
Abstract: Understanding inundation in wetlands may benefit from a joint variation analysis in changes of size, shape, position and extent of water bodies. In this study, we modeled wetland inundation as a random spread process and used random sets to characterize stochastic properties of water body extents. Periodicity, trend and random components were captured by monthly and yearly random sets that were derived from multitemporal images. The covering-Distance matrix and related operators summarized and visualized the spatial pattern and quantified the similarity of different inundation stages. The study was carried out on the Poyang Lake wetland area in China, and MODIS images for a period of eleven years were used. Results revealed that substantial seasonal dynamic pattern of the inundation and a subtle interannual change in its extension from 2000 to 2010. Various spatial properties including the size, shape, position and extent are visible: areas of high flooding risk are very elongated and locate along the water channel; few of the inundation areas tend to be more circular and spread extensively; the majority of the inundation areas have various extent and size in different month and year. Large differences in the spatial distribution of inundation extents were shown to exist between months from different seasons. A unique spatial pattern occurred during those months that a dramatic flooding or recession happened. Yearly random sets gave detailed information on the spatial distributions of inundation frequency and showed a shrinking trend from 2000 to 2009. 2003 is the partition year in the declining trend and 2010 breaking the trend as an abnormal year. Besides, probability bounds were derived from the model for a region that was attacked by flooding. This ability of supporting decision making is shown in a simple management scenario. We conclude that a random sets analysis is a valuable addition to a frequency analysis that quantifies inundation variation in space and time.
Location: TE 15 New Biology Building
Literature cited 1: Barndorff-Nielsen, O., Kendall, W., Lieshout, M., (Eds), 1999. Stochastic Geometry: Likelihood and Computation. Chapman & Hall/ CRC, Boca Raton, Fla., London. Benke, A., Chaubey, I., Milton, G., Dunn, E., 2000. Flood pulse dynamics of an unregulated river floodplain in the southeastern us coastal plain. Ecology 81, 2730-2741.
Literature cited 2: Bryant, R.G., Rainey, M.P., 2002. Investigation of flood inundation on playas within the zone of Chotts, using a time-series of AVHRR. Remote Sensing of Environment 82, 360-375. Cressie, N., 1993. Statistics for Spatial Data. Wiley-Interscience, New York, pp. 725-803.

ID: 60068
Title: Detecting pruning of individual stems using Airborne Laser Scanning data captured from an Unmanned Aerial Vehicle.
Author: Luke Wallace, Christopher Watson, Arko Lucieer.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 76-85 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Laser Scanning, Unmanned Aerial Vehicle, Forest management, Pruning, Change detection.
Abstract: Modern forest management involves implementing optimal pruning regimes. These regimes aim to achieve the highest quality timber in the shortest possible rotation period. Although a valuable addition to forest management activities, tracking the application of these treatments in the field to ensure best practice management is not economically viable. This paper describes the use of Airborne Laser Scanner (ALS) data to track the rate of pruning in a Eucalyptus globules stand. Data is obtained from an Unmanned Aerial Vehicle (UAV) and we describe automated processing routines that provide a cost-effective alternative to field sampling. We manually prune a 500 m2 plot to 2.5 m above the ground at rates between 160 and 660 stems/ha. Utilising the high density ALS data, we first derived crown base height (CBH) with an RMSE of 0.60 m at each stage of pruning. Variability in the measurement of CBH resulted in both false positive (mean rate of 11%) and false negative detection (3.5%), however, detected rates of pruning of between 96% and 125 % of the actual rate of pruning were achieved. The successful automated detection of pruning within this study highlights the suitability of UAV laser scanning as a cost-effective tool for monitoring forest management activities.
Location: TE 15 New Biology Building
Literature cited 1: Alcorn, P.J., Bauhas, J., Thomas, D.S., James, R.N., Smith, R.G.B., Nicotra, A.B., 2008. Photosynthetic response to green crown pruning in young plantation-grown Eucalyptus pilularis and E. cloeziana. Forest Ecology and Management 255 (11), 3827-3838. Axelsson, P., 1999. Processing of laser scanner data algorithms and applications. ISPRS Journal of Photogrammetry and Remote Sensing 54 (2-3), 138-147.
Literature cited 2: Ben-Arie, J.R., Hay, G.J., Powers, R.P., Castilla, G., St-onge, B., 2009. Development of a pit filling algorithm for lidar canopy height models. Computers and Geosciences 35 (9), 1940-1949. Bollandsas, O., 2013. Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data. Statistical Methods and Applications 22 (1), 113-129.

ID: 60067
Title: Development of an invasive species distribution model with fine-resolution remote sensing.
Author: Chunyuan Diao, Le Wang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 65-75 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Saltcedar, Species distribution model, Fine scale, Harmonic analysis, Spatial autocorrelation, Remote sensing.
Abstract: Saltcedar (Tamarix spp) is recognized as one of the most aggressively invasive species throughout the Western United States. Mapping its suitable habitat is of paramount importance to effective management, and thus, becomes a high priority for conservation practitioners. In previous studies, species distribution models (SDMs) have been applied to predicting the suitable habitats of saltcedar at national scale, but at coarser spatial resolution (1 km). Although such studies achieved some success, they are lacking of capability to accommodate fine-scale resolution environmental variables, and therefore, fail to uncover detailed spatial pattern of habitats. The objective of this study was to develop a remote sensing driven SDM so as to characterize suitable habitats of saltcedar at very fine spatial scale (30 m). We exploited several fine-scale environmental predictors through remote sensing images, and utilized the logistic regression model to analyze the species-habitat relationship by identifying influential factors with subset selection criteria. We also incorporated the spatial autocorrelation achieved a higher accuracy than that of regression only model. Among 10 environmental variables, the distance to the river and the phonological attributes summarized by the harmonic analysis were regarded as the most significant in predicting the invasive potential of saltcedar. We conclude that remote sensing driven SDM has potential to identify the suitable habitat of saltcedar at a fine scale and locate appropriate areas at high risk of saltcedar infestation, which could benefit the early control and proactive management strategies to a large extent.
Location: TE 15 New Biology Building
Literature cited 1: Andrew, M.E., Ustin, S.L., 2009. Habitat suitability modeling of an invasive plant with advanced remote sensing data. Diversity and Distributions 15, 627-640. Arieira, J., Karssenberg, D., Jong, S.d., Addink, E., Nunes da Cunha, C., Skoien, J., 2011. Integrating field sampling, geostatistics and remote sensing to map wetland vegetation in the Pantanal, Brazil, Biogeosciences 8, 667-686.
Literature cited 2: Borcard, D., Legendre, P., 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbor matrices. Ecological Modelling 153, 51-68. Briggs, W., Henson, V., 1995. The DFT: An Owner ' s Manual for the Discrete Fourier Transform. Society for Industrial and Applied Mathematics, Philadelphia.

ID: 60066
Title: Extraction of multilayer vegetation coverage using airborne LiDAR discrete points with intensity information in urban areas: A case study in Nanjing City, China.
Author: Wenquan Han, Shuhe Zhao, Xuezhi Feng, Lei Chen.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 56-64 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Airborne LiDAR, Urban vegetation, Laser point intensity, Multilayer vegetation coverage, Median filter.
Abstract: Urban vegetation is of a strategic importance for the life quality in the increasing urbanized societies. However, it is still difficult to extract accurately urban vegetation vertical distribution with remote sensing images. This paper presented an effective method to extract multilayer vegetation coverage in urban areas using airborne Light Detection and Ranging (LiDAR) discrete points with intensity information. It was applied in Nanjing City, one of the ecological cities in China. Firstly, a median filtering algorithm based on discrete points was used to restrain high-frequency noise. The airborne LiDAR data intensities of different urban objects were analyzed and obtained three rules, which can distinguish between vegetation and non-vegetation in urban areas, after removing the influence of topography. According to the footprint size and principles of distribution of the point cloud, multilayer vegetation coverage, including trees, shrubs and grass, was achieved by the inverse distance weighting (IDW) interpolation method. The results show that the overall accuracy of the vegetation point classification is 94.57%, which is much accurate than that of the methods in TerraSolid software, through comparing with the investigation in the field and Digital Orthophoto Maps (DOM). This method proposed in our work can be applied to in the extraction of multilayer vegetation coverage in urban area.
Location: TE 15 New Biology Building
Literature cited 1: Chen, L., Zhao, S., Han, W., Li, Y., 2012. Building detection in an urban area using LiDAR data and Quickbird imagery. International Journal of Remote Sensing 16, 5135-5148. Chiesura, A., 2004. The role of urban parks for the sustainable city. Landscape and Urban Planning 68, 129-138.
Literature cited 2: Felix, M., Caroline, N., Timothy, M., Ian, H.W., 2009. Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modeling. Remote Sensing of Environment 113, 2152-2163. Hartfield, K.A., Landau, KI., Leeuwen, W.J.D., 2011. Fusion of high resolution aerial multispectral and LiDAR data: land cover in the context of urban mosquito habitat. Remote Sensing 3, 2364-2383.

ID: 60065
Title: Urban growth and environmental impacts in Jing-Jin-Ji, the Yangtze, River Delta and Pearl River Delta.
Author: Jan Haas, Yifang Ban.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 42-55 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Urban growth, Land use/land cover (LULC), Ecosystem services, Landscape metrics, Environmental impact, Random forest.
Abstract: This study investigates land cover changes, magnitude and speed of urbanization and evaluates possible impacts on the environment by the concepts of land scape metrics and ecosystem services in China ' s three largest and most urban agglomerations: Jing-Jin-Ji, the Yangtze River Delta and the Pearl River Delta. Based on the classification of six Landsat TM and HJ-1A/B remotely sensed space-borne optical satellite image mosaics with a superior random forest decision tree ensemble classifier, a total increase in urban land about 28,000 km2 could be detected alongside a simultaneous decrease in natural land cover classes and cropland. Two urbanization indices describing both speed and magnitude of urbanization were derived and ecosystem services were calculated with a valuation scheme adapted to the Chinese market based on the classification results from 1990 and 2010 for the predominant land cover classes affected by urbanization: forest, cropland, wetlands, water and aquaculture. The speed and relative urban growth in Jing-Jin-Ji was highest, followed by the Yangtze River Delta and Pearl River Delta, resulting in a continuously fragmented landscape and substantial decreases in ecosystem service values of approximately 18.5 billion CNY with coastal wetlands and agriculture being the largest contributors. The results indicate both similarities and differences in urban-regional development trends implicating adverse effects on the natural and rural landscape, not only in the rural-urban fringe, but also in the cities ' important hinterlands as a result of rapid urbanization in China.
Location: TE 15 New Biology Building
Literature cited 1: Aguilera, F., Valenzuela, L.M., Botequilha-Leitao, A., 2011. Landscape metrics in the analysis of urban land use patterns: a case study in a Spanish metropolitan area. Landsc. Urban Plan. 99 (3-4), 226-238. Ban, Y., Jacob, A., 2013. Object-based fusion of multitemporal multi-angle ENVISAT ASAR and HJ-1 multispectral data for urban land-cover mapping. IEEE Trans. Geosci. Rem. Sens. 51 (4), 1998-2006.
Literature cited 2: Ban, Y., Yousif, O.A., 2012. Multitemporal spaceborne SAR data for urban change detection in China. IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens. 5 (4), 1087-1094. Breiman, L., 2001. Random Forests. Mach. Learn 45 (1), 5-32.

ID: 60064
Title: Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland.
Author: Edward M. Olexa, Rick L. Lawrence.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 30-41 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Landsat, MODIS, Rangeland, Remote sensing, STARFM.
Abstract: Federal land management agencies provide stewardship over much of the rangelands in the arid and semi-arid western United States, but they often lack data of the proper spatiotemporal resolution and extent needed to assess range conditions and monitor trends. Recent advances in the blending of complementary, remotely sensed data could provide public lands managers with the needed information. We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TM and concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses to evaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Predicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlation with observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended to decline as the lag between base and prediction dates increased: however, mean absolute errors (MAE) were typically ? 10%. The quality of area-wide NDVI estimates was less consistent than either spectral band, although the MAE of estimates predicted using early season base pairs were ? 10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1 regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions, based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM ' s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.
Location: TE 15 New Biology Building
Literature cited 1: Andelman, S., Gillem, K., Groves, C., Hansen, C., Humke, J., Klahr, T., Kramme, L., Moseley, B., Reid, M., Vander Schaaf, D., Coad, M., Deforest, C., Macdonald, C., Baumgarther, J., Hak, J., Hobbs, S., Lunte, L., Smith, L., Soper, C., 1999. The Columbia Plateau Ecoregional Assessment: A Pilot Effort in Ecoregional Conservation. The Nature Conservancy, Seattle, Washington. Bailey, R.G., 1995. Description of the Ecoregions of the United States, second ed. U.S. Department of Agriculture, Forest Service, Washington, Dc.
Literature cited 2: Blanco, L.J., Ferrando, C.A., Biurrun, F.N., 2009. Remote sensing of spatial and temporal vegetation patterns in two grazing systems. Rangeland Ecology and Management 62, 445-451. Booth, D.T., Tueller, P.T., 2003. Rangeland monitoring using remote sensing. Arid Land Research and Management. 17, 455-451.

ID: 60063
Title: Detection of windthrown trees using airborne laser scanning.
Author: Mattias Nystrom, Johan Holmgren, Johan E.S. Fransson, Hakan Olsson
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 21-29 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Storm damage, Downed logs, Template matching, Active surface, ALS, LiDAR.
Abstract: In this study, a method has been developed for the detection of windthrown trees under a forest canopy, using the difference between two elevation models created from the same high density (65 points/m2) airborne laser scanning data. The difference image showing objects near the ground was created by subtracting a standard digital elevation model (DEM) from a more detailed DEM created using an active surface algorithm. Template matching was used to automatically detect windthrown trees in the difference image. The 54 ha study area is located in hemi-boreal forest in southern Sweden (Lat. 58? 29`N, Long. 13? 38` E) and is dominated by Norway spruce (Picea abies) with 3.5 % deciduous species (mostly birch) and 1.7 % Scots pine (Pinus sylvestris). The result was evaluated using 651 field measured windthrown trees. At individual tree level, the detection rate was 38 % with a commison error of 36%, Much higher detection rates were obtained for taller trees; 89% of the trees taller than 27 m were detected . For pine the individual tree detection rate was 82%, most likely due to the more easily visible stem and lack of branches. When aggregating the results to 40 m square grid cells, at least one tree was detected in 77% of the grid cells which according to the field measurements contained one or more windthrown trees.
Location: TE 15 New Biology Building
Literature cited 1: Axelson, P., 1999.Processing of laser scanner data-algorithms and applications. ISPRS Journal of Photogrammetry & and Remote Sensing 54, 138-147. Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. International Archives of Photogrammetry & Remote Sensing 33, 110-117.
Literature cited 2: Ballard, D., Brown, C.M., 1982. Computer Vision, 1st ed. Prentice Hall, Engelwood Cliffs, New Jersey. Bebber, D., Thomas, S., 2003. Prism sweeps for coarse woody debris. Canadian Journal of Forest Research 33, 1737-1743.

ID: 60062
Title: Mapping long -term temporal change in imperviousness using topographic maps.
Author: James D. Miller, Stephen Grebby.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 9-20 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Imperviousness, Urban, Remote sensing, Hydrology, Land use change.
Abstract: Change in urban land use and impervious surface cover are valuable sources of information for determining the environmental impacts of urban development. However, our understanding of these impacts is limited due to the general lack of historical data beyond the last few decades. This study presents two methodologies for mapping and revealing long-term change in urban land use and imperviousness from topographic maps. Method 1 involves the generation of maps of fractional impervious surface for direct computation of catchment -level imperviousness based on an urban extent index. Both methods are applied to estimate change in catchment imperviousness in a town in the South of England, at decadal intervals for the period 1960-2010. The performance of each method is assessed using contemporary reference data obtained from aerial photographs, with the results indicating that both methods are capable of providing good estimates of catchment imperviousness. Both methods reveal that peri-urban developments within the study area have undergone a significant expansion of impervious cover over the period 1960-2010, which is likely to have resulted in changes to the hydrological response of the previously rural areas. Overall, results of this study suggest that topographic maps provide a useful source of determining long-term change in imperviousness in the absence of suitable data, such as remotely sensed imagery. Potential applications of the two methods presented here include hydrological modeling, environmental investigations and urban planning.
Location: TE 15 New Biology Building
Literature cited 1: Amirsalari, F., Li, Li, J., Guan, X., Booty, W.G., 2013. Investigation of correlation between remotely sensed impervious surfaces and chloride concentrations. International Journal of Remote Sensing 34, 1507-1525. Arnold, C.L., Gibbons, C.J., 1996. Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American Planning Association 62, 243-258.
Literature cited 2: Bauer, M.E., Heinert, N.J., Doyle, J.K., Yuan, F., 2004. Impervious surface mapping and change monitoring using Landsat remote sensing. In: ASPRS Annual Conference Proceedings, Denver, Colorado, May 2004. Bayliss, A.C., Black, K.B., Fava-Verde, A., Kjeldsen, T.R., 2006. URBEXT2000 - a new FEH catchment descriptor: calculation, dissemination and application. In: Joint Defra/EA Flood and Coastal Erosion Risk management R & D Programme. R & D Technical Report FD 1919/TR., pp. 49.

ID: 60061
Title: Validation of the ASCAT Soil Water Index using in situ data from the international Soil Moisture Network.
Author: Christoph Paulik, Wouter Dorigo, Wolgang Wagner, Richard Kidd.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 1-8 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Soil moisture, Remote sensing, Validation, Soil Water Index.
Abstract: Soil moisture is an essential climate variable and a key parameter in hydrology, meteorology and agriculture. Surface Soil Moisture (SSM) can be estimated from measurements taken by ASCAT onboard Metop-A and have been successfully validated by several studies. Profile soil moisture, while equally important, cannot be directly measured by remote sensing but must be modeled. The Soil Water Index (SWI) product developed for near real time applications within the frame work of the GMES project geoland 2 aims to provide such a modeled profile estimate using satellite data as input. It is produced from ASCAT SSM estimates using a two-layer water balance model which describes the relationship between surface and profile soil moisture as a function of time. It provides daily global data about moisture conditions for eight characteristic time lengths representing different depths. The objective of this work was to assess the overall quality of the SWI data. Furthermore We tested the assumptions of the used water balance model and checked if ancillary information about topography, water fraction and noise information are useful for identifying observations of questionable quality. SWI data from January 1st 2007 until the end of 2011 was compared to in situ soil moisture data from 664 stations belonging to 23 observation networks which are available through the International Soil Moisture Network (ISMN). These stations delivered 2081 time series at different depths which were compared to the SWI values. The average of the significant Pearson correlation coefficients was 0.54 while being greater than 0.5 for 64.4% of all time series. It was found that the characteristic time length showing the highest correlation increases with in situ observation depth, thus confirming the SWI model assumptions. Relationship of the correlation coefficients with topographic complexity, water fraction, in situ observation depth, and soil moisture noise were found.
Location: TE 15 New Biology Building
Literature cited 1: Albergel, C., de Rosnay, P., Gruhier, C., Munoz Sabater, J., Hasenauer, S., Isaksen, L, Kerr, Y., Wagner, W., 2012. Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment 118, 215-226. Albergel, C., Dorigo, W., Balsamo, G., Munoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu, R., Wagner, W., 2013a. Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses. Remote Sensing of Environment 138, 77-89.
Literature cited 2: Albergel, C., Dorigo, W., Reichle, R.H., Balsamo, G., de Rosnay, P., Munoz Sabater, J., Isaksen, L., de Jeu, R., Wagner, W., 2013 b. Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing. Journal of Hydrome- teorology 14 (4), 1259-1277. Albergel, C., Rudiger, C., Carrer, D., Calvet, J. -c., Fritz, N., Naeimi, V., Bartalis, Z., Hasenauer, S., 2009. An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France. Hydrology and Earth System Sciences 13 (February (2), 115-124.