Enter records

ID: 61820
Title: Landscape pattern and transition under natural and anthropogenic disturbance in an arid region of northwestern China.
Author: Yu Zhang, Tianwei Wang, Chongfa Cai, Chongguang Li, Yaojun Liu, Yuze Bao, Wuhong Guan.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 1-10 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Landscape transition, Driving force, Anthropogenic disturbance, Redundancy analysis (RDA), Variation portioning
Abstract: There is a pressing need to determine the relationships between driving variables and landscape transformations. Human activities shape landscapes and turn them into complex assemblages of highly diverse structures. Other factors, including climate and topography, also play significant roles in landscape transitions, and identifying the interactions among the variables is critical to environmental management. This study analyzed the configurations and spatial-temporal process of landscape changes from 1998 to 2011 under different anthropogenic disturbances, identified the main variables that determine the landscape patterns and transitions, and quantified the relationships between pairs of driver sets. Landsat images of Baicheng and Tekes from 1998, 2006and 2011 were used to classify landscapes by supervised classification. Redundancy analysis (RDA) and variation portioning were performed to identify the main driving forces and to quantify the unique, shared, and total explained variation of the sets of variables. The results indicate that the proportions of otherwise identical landscapes in Baicheng and Tekes were very different. The area of the grassland in Tekes was much larger than that of the cropland; however, the differences between the grassland and cropland in Baicheng were not as pronounced. Much of the grassland in Tekes was located in an area that was near residents, whereas most of the grassland in Baicheng was far from residents. The slope, elevation, annual precipitation, annual temperature, and distance to the nearest resident were strong driving forces influencing the patterns and transitions of the landscapes. The results of the variation portioning indicated complex interrelationships among all of the pairs of driver sets. All of the variables sets had significant explanatory roles, most of which had both unique and shared variations with the others. The results of this study can assist policy makers and planners in implementing sustainable landscape management and effective protection strategies.
Location: T E 15 New Biology Building
Literature cited 1: Beyer, H.L., 2007.Hawth ' s analysis tools for ArcGIS.Available at http://www.spatialecology.com/htools. Bicik, I.Jeleck, L., Stepanek, V., 2001.Land-use changes and their social driving forces in Czechia in the 19th and 20th centuries. Land Use Policy 18, 65-73.
Literature cited 2: Borcard, D., Legendre, P., Drepeau, P., 1992.Partialling out the spatial component of ecological variation. Ecology 73, 1045-1055. Brinkmann, K.,Schumacher, J.,Dittrich, A.,Kadaore, I., Buerkert, A., 2012.Analysis of landscape transformation processes in and around four West African cities over the last 50 years.Landsc.Urban Plann.105, 94-105.

ID: 61819
Title: Forest inventories by LiDAR data: A comparison of single tree segmentation and metric-based methods for inventories of a heterogeneous temperate forest.
Author: Hooman Latifi, Fabian E.Fassnacht, Jorg Muller, Agalya Tharani, Stefan Dech, Marco Heurich.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 162-174 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: LiDAR, Forest structure inventory, Single tree segment-based method, Area-based method, Spatial model, Landscape level management.
Abstract: Inventories of temperate forests of Central Europe mainly rely on terrestrial measurements. Rapid alterations of forests by disturbances and multilayer silvicultural systems increasingly challenge the use of conventional plot based inventories, particularly in protected areas. Airborne LiDAR offers an alternative or supplement to conventional inventories, but despite the possibility of obtaining such remote sensing data, its operational use for broader areas in Central Europe remains Experimental. We evaluated two methods of forest inventory that use LiDAR data at the landscape level: the single tree segment-based method and an area-based method. We compared a set of structural forest attributes modeled by these methods with a conventional forest inventory of the highly heterogeneous forest of the Bavarian Forest National Park (Germany), which partially includes stands affected by severe natural disturbances. Area-based models were accurate for all structural attributes, with cross-validated average root mean squared error ranging from ~3.4 to ~13.4 in the best modeling case. The coefficients of variation for the mapped area-based estimations were mostly minor. The area-based estimations were varied but highly correlated (Pearson ' s correlations between ~0.56 and 0.85) with single tree segmentation estimations; undetected trees in the single tree-segment-based method were the main sources of inconsistency. The single tree segment-based method was highly correlated (~0.54 to 0.90) with data from ground-based forest inventories. The single tree-based algorithm delivered highly reliable estimates for a set of forest structural attributes that are of interest in forest inventories at the landscape scale. We recommended LiDAR forest inventories at the landscape scale in both heterogeneous commercial forests and large protected areas in the central European temperate sites.
Location: T E 15 New Biology Building
Literature cited 1: Boncina, A., 2011.Conceptual approaches to integrate nature conservation into forest management: a Central European perspective.Int.Forest.Rev.13, 13-22. Buehlmann, P., 2006.Boosting for high-dimensional linear models.Ann.Stat.34 (2), 559-583.
Literature cited 2: Drake, J.B.,Dubayah,R.O.,Knox,R.G.,Clark,D.B.,Blair,J.B., 2002.Sensitivity of large-footprint LiDAR to canopy structure and biomass in a neotropical rainforest. Remote Sens.Environ.81 (2-3), 378-392. Eerikainen, K., Valkonen, S., Saska, T., 2014.Ingrowth, survival and height growth of small trees in uneven-aged Picea abies stands in southern Finland.For.Ecosyst.1, 5, http://dx.doi.org/10.1186/2197-5620-1-5.

ID: 61818
Title: Analysis of current validation practices in Europe for space-based climate data records of essential climate variables
Author: Y.Zeng, Z.Su, J.-C.Calvet, T.Manninen, E.Swinnen, J.Schulz, R.Roebeling, P.Poli, D.Tan, A.Riihela, C.-M.Tanis, A.-N.Arslan,A.Obregon,A.Kaiser-Weiss, V.O.John,W.Timmermans,J.Timmermans,F.Kaspar,H.Gregow,A.-L.Barbu, D.Fairbairn,E.Gelati,C.Meurey.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 150-161 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: None
Abstract: The climate Data Records (CDRs) of Essential Climate Variables (ECVs) that are based on satellite observations need to be precisely described. In particular, when these products are delivered to end-users, the error characteristics information and how this information is obtained (e.g., through a validation process) need to be documented. Such validation information is intended to help end-users understanding to what extent the product is suitable for their specific applications. Based on how different European initiative approached the validation of CDR and ECV products, we reviewed several aspects of the current validation practices. Based on the analysis of current practices, essentials of validation are discussed. A generic validation process is subsequently proposed, together with a quality indicator.
Location: T E 15 New Biology Building
Literature cited 1: Barbu, A.L., Calvet, J.C., Mahfouf, J.F., Lafont, S., 2014.Integrating ASCAT surface soil moisture and GEOV1 leaf area index into the SURFEX modeling platform: a land data assimilation application over france.Hydrol.Earth Syst.Sci. 18 (1), 173-192. Baret, F.,Hagolle, O., Geiger, B.,Bicheron, P., Miras, B., Huc,M., Berthelot, B., Nino, F., Weiss,M.,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 (3), 275-286.
Literature cited 2: Baret, F., H.Makhmara, R.Lacaze, B.Smets (2013).BioPar Product User Manual: LAI, FAPAR, FCover, NDVI version 1 from SPOT/BEGETATION data: FAPAR.GIO Global Land Component-Lot 1 Operation of the Global Land Component (Issue 11.00): pp39. Beggs, H., Verein, G., Kippo, H., Underwood, M., 2012.Enhancing ship of opportunity sea surface temperature observations in the Australia region.J.Oper.Oceanogr. 5 (1) 59-73.

ID: 61817
Title: Detecting settlement expansion in South Africa using a hyper-temporal SAR change detection approach.
Author: W.Kleyhans, B.P.Salmon, J.C.Olivier.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 142-149 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Change detection, SAR, Time-series, Hyper-temporal, Settlements
Abstract: Recent times have seen a significant increase in the amount of readily available SAR data, with many current and historic SAR data holdings now adopting an open distribution policy. As more regular SAR observations are becoming available, the use of a hyper-temporal SAR change detection framework (utilizing a stack of potentially hundreds of SAR images) is now becoming significantly more feasible. A relevant use case is the detection of new informal settlements in South Africa. Here, hyper-temporal change detection has been shown to be very effective but has been limited to coarse resolution optical satellite imagery only. In particular, it has been found that for optical data the Temporal Autocorrelation Change Detection (TACD) method is able to effectively detect the formation of new informal settlements using hyper-temporal MODIS time-series data. In this paper, the TACD is modified for the use of coarse resolution hyper-temporal SAR data for the detection of new informal settlements, a higher overall accuracy was achievable when compared to standard bi-temporal change detection. A dataset of ENVISAT Advanced Synthetic Aperture Radar images over the study area was used to create a hyper-temporal time-series of backscatter values for each of the pixels in the study area. It was found that the proposed method achieved change detection accuracies of 87 % at a false alarm rate of less than 1 % with bi-temporal SAR change detection achieving a change detection accuracy of 70 % at an approximate 1 % false alarm rate.
Location: T E 15 New Biology Building
Literature cited 1: Bazi, L.B.Y., Melgani, F., 2005.An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images. IEEE Trans.Geosci.Remote Sens. 43 (4), 874-887. Corincotte, C., Derrode, S., Bourennane, S., 2006.Unsuprvised change detection on SAR images using fuzzy hidden Markovchains.IEEE Trans.Geosci.Remote Sens. 44 (2), 432-441.
Literature cited 2: de Beurs, K., Henerby, G., 2005.A statistical framework for the analysis of long image time series.Int.J.Remote Sens.26 (8), 1551-1573. Gamba, P., Lisni,G., 2013.Fast and efficient urban extent extraction using ASAR wide swath mode data.IEEE J.Sel.Topics Appl.Earth Observ.Remote Sens. 6 (5), 2184-2195, http://dx.doi.org/10.1109/JSTARS.2012.2235410.

ID: 61816
Title: Early-season mapping of crops and cultural operations using very high-spatial resolution Pleiades images.
Author: E.Vaudour, P.E.Noirot-Cosson, O.Membrive
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 128-141 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Pleiades, VHSR, Cultural operations, Crop mapping, Phenological stages, SVM.
Abstract: The aim of this study was to assess the contribution of very high spatial resolution (VHSR) Pleiades images to both early season crop identification and the mapping of bare soil surface characteristics due to cultural operations. The study region covering 21 km2 is located west of the peri-urban territory of the Versailles plain and the Alluets plateau (Yvelines, France).About 100 cropped fields were observed on the ground synchronously with two Pleiades images of 3 and 24 April 2013 and one SPOT4 image of 2 April 2013.The GIS structuring of these field data along with vector information about field boundaries was used for delimitating both training and test zones for the support vector machine classifier with polynomial function kernel (pSVM).The pSVM was computed on the spectral bands and NDVI for both single-date Pleiades and the bi-temporal Pleiades pair. For the single-date classifications of crops, the overall-per-pixel accuracy reached 87 % for the SPOT4 image of 2 April (6 classes), 79 % for the Pleiades image of 3 April (6 classes) and 82 % for that 24 April (7 classes).At the earlier date (2-3 April), the Pleiades image very well discriminated cultural operations (>77%, user ' s or producer ' s accuracies) as well as fallows and grasslands, while winter cereals and rapeseed were better discriminated buy the SPOT4 image winter cereals (>70 %, user ' s or producer ' s accuracies).As Pleiades images revealed within field spatial variations of early phonological stages of winter cereals that could be critical for adjusting management of zones with delayed development during the growing season, they brought information complementary to multispectral images with high spatial resolution. For the bi-temporal Pleiades image, the overall per-pixel accuracy was about 80 %(7 classes), winter crops, grasslands and fallows being very well detected while confusion occurred between spring barley at initial stages (2-3 leaves) and bare soils prepared for other spring crops. Using an additional validation field set covering ~1/3 of the study area croplands, the crop map resulting from the bi-temporal Pleiades pair achieved correct crop prediction for about 89.7 % of the validation fields when considering composite classes for winter cereals and for spring crops. Early-season Pleiades images therefore show a considerable potential for anticipating regional crop patterns and detecting soil tillage operations in spring.
Location: T E 15 New Biology Building
Literature cited 1: Alganci, U., Sertel, E., Ozdogan, M., Ormeci, C., 2013.Parcel-level identification of crop types using different classification algorithms and multi-resolution imagery in Southeastern Turkey. Photogramm. Eng. Remote Sen.79 (11), 1053-1065. Amoros-Lopez, J., Gomez-Chova, L., Alonso, L., Guanter, L., Zurita-Milla, R., Moreno, J., Camps-Valls, G., 2013.Multitemporal fusion of Landsat/TM and ENVISAT/MERIS for crop monitoring.Int.J.Appl.Earth.Observ.Geoinf.23, 132-141.
Literature cited 2: Astritum Geoinformation Services, 2012.Pleiades Imagery User Guide. Astrium Geo-Information Services, Toulouse, France, pp.106 http://www.satimagingcorp.com/media/pdf/User_Guide_Pleiades.pdf Atzberger, C., 2013.Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sens.5, 949-981.

ID: 61815
Title: Mapping degraded grassland on the Eastern Tibetan Plateau with multi-temporal Landsat 8 data-where do the severely degraded areas occur?
Author: Fabian EwaldFassnacht, Li Li, Andreas Fritz.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 115-127 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Landsat 8, Grassland degradation, Tibetan Plateau, Multiple cloud-cover, SVM.
Abstract: The Tibetan Plateau in Western China is the world ' s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research. We argue that remote sensing data can help t o better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of he identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three countries Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phonological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phonological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were ?high-cover grassland?, grassland (including several stages of grassland vitality)?. ?(Severely) degraded grassland?, ?green shrubland?, ?grey shrubland?, ?urban areas? and ?water bodies?. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to kappa accuracy of 0.76.Mean producer ' s and user ' s accuracies for all classes were higher than 80 %, and confusion mainly occurred between the two shrub land classes and between the three grassland classes. Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300-4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5-7 %severely degraded land cover. Derlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas severe degradation (14%). Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures.
Location: T E 15 New Biology Building
Literature cited 1: Aba Prefecture Government Office (2008).Overview of Aba ' s Counties. Retrieved from http://www.abazhou.gov.cn/abgk/gxzc in Chinese. Agrawal, A., Sharma, A.R., Tayal, S., 2014.Assessment of regional climatic changes in the Eastern Himalayan region: a study using multi-satellite remote sensing data sets.Environ.Monit.Assess.186, 6521-6536.
Literature cited 2: Boval, M., Dixon, R.M., 2012.The importance of grasslands for animal production and other functions: a review on management and methodological progress in the tropics-Animal 6 (5), 748-762. Burges, C.J.C., 1998.A tutorial on support vector machines for pattern recognition. Data Min.Knowl. Discovery 2, 121-167.

ID: 61814
Title: Spatial application of Random Forest for fine-scale coastal vegetation classification using object based analysis of aerial orthophoto and DEM data.
Author: Anders Juel, Geoffrey Brian Groom, Jens-Christian Svenning, Rasmus Ejrnaes.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 106-114 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Habitat structure, Object-based image analysis, Machine learning, Aerial orthophoto imagery, Model transferability.
Abstract: High spatial resolution mapping of natural resources is much needed for monitoring and management of species, habitats and landscapes. Generally, detailed surveillance has been conducted as fieldwork, numerical analysis of satellite images or manual interpretation of aerial images, but methods of object-based image analysis (OBIA) and machine learning have recently produced promising examples of automated classifications of aerial imagery. The spatial application potential of such models is however still questionable since the transferability has rarely been evaluated We investigated the potential of mosaic aerial orthophoto red, green, and blue (RGB) near infrared (NIR) imagery and digital elevation model (DEM) data for mapping very fine-scale vegetation structure in semi-natural terrestrial coastal areas in Denmark. The random Forest (RF) algorithm, with wide range of object-derived image and DEM variables, was applied for classification of vegetation structure types using two hierarchical levels of complexity. Models were constructed and validated by cross-validation. Using three scenarios: (1) training and validation data without spatial separation, (2) training and validation data spatially separated within sites, and (3) training and validation data spatially separated between different sites. Without spatial separation of training and validation data, high classification accuracies of coastal structures of 92.1 % and 91.8 % were achieved on coarse and fine thematic levels, respectively. When models were applied to spatially separated observations within sites classification accuracies dropped to 85.8%accuracy at the coarse thematic level, an 81.9 % at the fine thematic level. When the models were applied to observations from other sites than those trained upon the ability to discriminate vegetation structures was low, with 69.0 % and 54.2 % accuracy at the coarse and fine thematic levels, respectively. Evaluating classification models with different prediction accuracies, thereby highlighting model transferability and application potential, Aerial image and DEM-based RF models had low transferability to new areas due to lack of representation of aerial image, landscape and vegetation variation in training data. They do, however, show promise at local scale for supporting conservation and management with vegetation mapping of high spatial and thematic detail based on low-cost image data.
Location: T E 15 New Biology Building
Literature cited 1: Bahn, V., McGill, B.J.2013., Testing the predictive performance of distribution models.Oikos 122, 321-331. Baily, B., Nowell, D., 1996.Techniques for monitoring coastal change: a review and case study. Ocean Coastal Manage.32, 85-95.
Literature cited 2: Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, I., Heynene, M., 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information.Isprs J.Photogramm.RemoteSens.58, 239-258. Bradter, U., Thom, T.J., Alttringham,J.D., Kunin, W.E., W.E., Benton, T.G.,2011.Prediction of National Vegetation Classification communities in the British uplands using environmental data at multiple spatial scales. Aerial images and the classifier random forest.J.Appl.Ecol.48, 1057-1065.

ID: 61813
Title: Detecting subpixel deciduous components to complement traditional land cover classifications in Southwest Finland.
Author: Timo P.Pitkanene, Helle Skanes, Niina Kayhko
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 97-105 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Subpixel fractions, k-NN modeling, Remote sensing, Landscape heterogeneity, Ecotones, Key habitat mapping.
Abstract: To ensure successful conservation of ecological and cultural landscape values, detailed and up-to-date spatial information of existing habitat patterns is essential. However, traditional satellite-based and raster classifications rely on pixels that are assigned to a single category and often generalized. For many fragmented key habitats, such as strategy is too coarse and complementary data is needed. In this paper, we aim a detecting pixel-wise fractional coverage of broadleaved woodland and grassland components in a hemiboreal landscape. This approach targets ecologically relevant deciduous fractions and complements traditional crisp land cover classifications. We modeled fractional components using a k-NN approach, which was based on multispectral satellite data, assisted by a digital elevation model and a contemporary map database. The modeled components were then analyzed based on landscape structure indicators, and evaluated in conjunction with CORINE classification. The results indicate that both broadleaved forest and grassland components are widely distributed in the study area, principally organized as transition zones and small patches. Landscape structure indicators show a substantial variation based on fractional threshold, pinpointing their dependency on the classification scheme and grain. The modeled components, on the other hand, suggest high internal variation for most CORINE classes, indicating their heterogeneous appearance and showing that the presence of deciduous components in the landscape are not properly captured in a coarse land cover classification. To gain a realistic perception of the landscape, and use this information for the needs of spatial planning, both fractional results and existing land cover classifications are needed. This is because they mutually contribute to an improved understanding of habitat patterns and structures, and should be used to complement each other.
Location: T E 15 New Biology Building
Literature cited 1: Ahti, T., Hamet-Ahti, L., Jalas, J., 1968.Vegetation zones and their sections in northwestern Europe.Ann.Bot.Fenn.5, 169-211. Alanen, A., Osara, M., 1986.Tammen suojelu (conservation of oak).Sorbifolia 17, 65-76.
Literature cited 2: Arnot, C., Fisher, P., 2007.Mapping the ecotone with fuzzy sets. In: Morris, A, Svitlana, K. (Eds), Geographic Uncertainty in Environmental Security. Springer, Dordrecth, pp.19-32. Auestad, I., Rydren, K., ?kland, R.H., 2008.Scale-dependence of vegetation-environment relationships in semi-natural grasslands.J.Veg.Sci19, 139-148, http:dx.doi.org/10.3170/2007-8-18344.

ID: 61812
Title: Characterizing bi-temporal patterns of land surface temperature using landscape metrics based on sub-pixel classifications from Landsat TM/ETM+.
Author: Youshui Zhang, Heiko Balzter, Chuncheng Zou, Hanqiu Xu, Fei Tang.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 87-96 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Urban, Linear spectral unmixing, Percent impervious surface area, Threshold continuum, Land surface temperature, Landscape metrics.
Abstract: Landscape patterns in a region have different sizes, shapes and spatial arrangements, which contribute to the spatial heterogeneity of the landscape and are linked to the distinct behavior of thermal environments. There is a lack of research generating landscape metrics from discretized impervious surface area data (ISA), which can be used as an indicator of urban spatial structure and level of development, and quantitatively characterizing the spatial patterns of landscapes and land surface temperatures (LST).In this study, linear spectral mixture analysis (LSMA) is used to derive sub-pixel ISA. Continuous fractional cover thresholds are used to discretize percent ISA into different categories related to urban land cover patterns. Landscape metrics are calculated based on different ISA categories and used to quantify urban landscape patterns metrics such as indices of patch density, aggregation, connectedness, shape and shape complexity. The urban thermal intensity to the variation of pixel values of fractional ISA, and the integration of LST, LSMA. Landscape metrics provide a quantitative method for describing the spatial distribution and seasonal variation in urban thermal patterns in response to associated urban land cover patterns.
Location: T E 15 New Biology Building
Literature cited 1: Adams, J.B., Sabol, D.E., Kapos, V., Filho, R.A., Roberts, D.A., Smith, M.O., et al., 1995.Classification of multispectral images based on fractions of endmemebers: application to land cover change in the Brazilian Amazon. Remote Sens.Environ.52, 137-154. Amiri, R., Weng, Q., Alimohammadi, A., Alavipanah, S.K., 2009.The spatial-temporal dynamics of land surface temperatures in relation to fractional vegetation cover and landuse/cover in the Tabriz urban area, Iran. Remote Sens.Environ.113, 2606-2617.
Literature cited 2: Arnold Jr., C.L., Gibbons, C.J., 1996. Impervious surface coverage the emergence of a key environmental indicator.J.Am.Plann.Assoc.62, 243-258. Barsi, J.A., Schott, J.R., Palluconi, F.D., Hook, S.J., 2005.Validation of web-based atmospheric correction tool for single thermal band instruments. In: Proceedings, SPIE, Bellingham, W.A.

ID: 61811
Title: Open-pit mining geomorphic feature characterization.
Author: Jianping Chen, Ke Li, Kuo-Jen Chang, Giulia Sofia, Paolo Tarolli.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 76-86 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Open-pit mine, UAV, SfM, DSM, SLIAC.
Abstract: Among the anthropogenic topographic signatures on Earth, open-pit mines are of great importance. Mining is of interest to geomorphologists and environmental researchers because of its implication in geomorphic hazards and processes. In addition, open-pit mines and quarries are considered the most dangerous industrial sector, with injuries and accidents occurring in numerous countries. Their fast, accurate and low-cost investigation, therefore, represents a challenge for the Earth science community. The purpose of this work is to characterize the open-pit mining features using high-resolution topography and a recently published landscape metric, the Slope Local Length of Auto-Correlation (SLLAC) (Sofia et al., 2014).As novel steps, aside from the correlation length, the terrace ' s orientation is also calculated, and a simple empirical model to derive the percentage of artificial surfaces is tested. The research focuses on two main case studies of iron mines, both located in the Beijing district (P.R.China).The main topographic information (Digital Surface Models, DSMs) was derived using an Unmanned Aerial Vehicle (UAV) and the Structure from Motion (SfM) photogrammetric technique. The r3esults underline the effectiveness of the adopted methodologies and survey techniques in the characterisation of h main mine ' s geomorphic features. Thanks to the SLLAC, the terraced area given by open-cast/open-pit mining for iron extraction is automatically depicted, thus allowing researchers to quickly estimate the surface covered by the open-pit. This information could be used as a starting point of future research (i) given the availability of multi-temporal surveys to track the changes in the extent of the mine; (ii) to relate the extent of the mines to the amount of processes in the area (e.g. pollution, erosion, etc.), and to (iii) combine the two points, and analyse the effects of the change related to changes in erosion. The analysis of the correlation length orientation also allows researchers to identify the terrace ' s orientation and to understand the shape of the open-pit area. The tectonic environment and history, or inheritance, of a given slope can determine if and geologic features, is of major significance. Therefore, the proposed approach can provide a basis for a large-scale and low-cost topographic survey for sustainable environmental planning and, for example, for the mitigation of environmental anthropogenic impacts due to mining.
Location: T E 15 New Biology Building
Literature cited 1: Abo Akel, N., Filin, S., Doytsher, Y., 2007.Orthogona polynomials supported by region growing segmentation for the extraction of terrain from LiDAR data.Photogramm.Eng.Remote Sens. 73 (11), 1253-1266. Badri, A., Nadeau, S., Gbodossou, A., 2011.Integration of OHS into risk management in an open-pit mining project in Quebec (Canada).Minerals 1, 3-29.
Literature cited 2: Colomina, I., Molina, P., 2014.Unmanned aerial systems for photogrammetry and remote sensing: A review.ISPRS J.Photogramm.Remote Sens.92, 79-97. Ellis, E.C., 2004.Long-term ecological changes in the densely populated rural landscapes of China. In: DeFries, R.S., Asner, G.P., Houghton, R.A. (Eds.), Ecosystems and Land Use Change. American Geophysical Union, Washington, DC, pp.303-320.

ID: 61810
Title: Development of a snow wetness inversion algorithm using polarimetric scattering power decomposition model.
Author: M.Surendar, A.Bhttacharya, G.Singh, Y.Yamaguchi, G.Venkataraman.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 65-75 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: SAR, Polarimetry, Decomposition, Dielectric, Snow wetness.
Abstract: In this paper, a new snow wetness estimation model is proposed for full-polarimetric Synthetic Aperture Radar (SAR) data. Surface and volume are the dominant scattering componenets in wet-snow conditions. The generalized four component polarimetric decomposition with unitary transformation (G4U) based generalized surface and volume parameters are utilized to invert snow surface and volume dielectric constants using the Bragg coefficients and Fresnel transmission coefficients respectively. The snow surface and volume wetness are then estimated using an empirical relationship. The effective snow wetness is derived from the weighted averaged surface and volume snow wetness. The weights are derived from the normalized surface and volume scattering powers obtained from the generalized full-polarimetric SAR decomposition method.Six-Radarsat-2 fine resolution full-polarimetric datasets acquired over Himachal Pradesh, India along with the near-real time measurements were used to validate the proposed model. The snow wetness derived from the SAR data by the proposed model with in situ measurements indicated that the absolute error at 95 % confidence interval is 1.3% by volume.
Location: T E 15 New Biology Building
Literature cited 1: An, W., Cui, Y., Yang, J., 2010.Three-component model-based decomposition for polarimetric SAR data.IEEE Trans.Geosci.Remote Sens.48 (June (6)), 2732-2739. Arii, M., van zyl, J., Kim, Y., 2011.Adaptive model-based decomposition of polarimetric SAR covariance matrices.IEEE Trans.Geosci.Remote Sens.49 (March (3)), 1104-1113.
Literature cited 2: Bernier, P., et al., 1987.Microwave remote sensing of snowpack properties: potential and limitations. Nordic Hydrol.18 (1), 1-20. Chen, S.-W., song Wang, X., ping Xiao, S., Sato, M., 2014.General polarimetric model-based decomposition for coherency matrix.IEEE Trans.Geosci.Remote Sens.52 (March (3), 1843-1855.

ID: 61809
Title: Fire danger assessment in Iran based on geospatial information.
Author: Saeedeh Eskandari, Emilio Chuvieco.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 57-64 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Fire ignition probability, fire propagation probability, Geographic information system, Iran.
Abstract: Fire danger assessment is a vital issue alleviates the impacts of wildland fires. In this study, a fire danger assessment system is proposed, which extensively uses geographical databases to characterize the spatial variations of fire danger conditions in Iran. This assessment requires three steps: (i) generation of the required input variables, (ii) methods to integrate those variables for creating synthetic indices and (iii) validation of those indices versus fire occurrence data. This fire danger model is based on previous works but adapted to Iranian conditions. It includes an estimation of the fire ignition potential (both considering human and climatic factors) and fire propagation potential. The former was generated from a logistic regression approach based on wide range of input variables. The fire propagation probability was estimated from Flammap fire behavior model. A first stage for validation of our fire danger system was based on comparing the estimated danger values to actual fore occurrence, based on satellite detected active fires and burned areas. The logistic regression model for fire ignition probability estimated 72.7% of true ignitions. Detected hotpots occurred more frequently in areas with higher fire ignition probability (average value: 0.65) than non hotspots (average value: 0.4). Propagation probability showed higher values for areas with higher proportion of burned area (r=0.68, p<0.001.)
Location: T E 15 New Biology Building
Literature cited 1: Adab, H., Kannaih, K.D., Solaimani, K., 2013.Modeling forest fire risk in the northeast of Iran using remote sensing and gis techniques. Natural Hazards 65, 1723-1743. Adeli, E., Yakhkashi, A., 1975.Forest protection. Tehran University Press, Tehran, pp.279.
Literature cited 2: Andrews, P.L., Lofsgaarden, D.O., Bradshaw, L.S., 2003.Evaluation of fire danger rating indexes using logistic regression and percentile analysis.Int.J.Wildland Fire 12, 213-226. Biranvand, A., Babaei Kafaki, S., Kiadaliri, H., 2011.Investigation the ecological factors affecting fire spread in forest ecosystems (case study: kakareza-lorestan).J.Renew.Nat.Resour.Res. 2 (2), 1-13.

ID: 61808
Title: Free software: A review, in the context of disaster management.
Author: Mathias Leidig, Richard Teeuw.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 49-56 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: FOSS, Remote sensing, GIS, Geoinformatics, Disaster preparedness, Disaster management.
Abstract: This article examines the nature of freely available geospatial software systems in the context of disaster management. The use of geospatial data is crucial to effective disaster management, from preparedness to response and recovery. However, to make efficient use of available data and information-before, during and after disaster-reliable software is required. The software applications examined in this paper range from Geographical Information Systems, to the processing of remotely sensed images, crowd-source mapping, web applications and content management systems. Trends and challenges are considered, and guidelines are given, to foster and encourage the provision of information by freewater and Open Source Software. Free geoinformatics can help to optimize the limited financial, technological and manpower resources that many organizations face, providing a sustainable input to analytical activities.
Location: T E 15 New Biology Building
Literature cited 1: ACAPS website:http://acaps.org/en/news/other-situations-of-violence-in-the-northern-triangle-of-central-america/a, (accessed 17.06.14). Ames D.P., Michaelis C., Dunsford T., (2007).Introducing the MapWindow GIS project.OSGeo Journal, 2, osgeo.org/journal.
Literature cited 2: Anguix, A., Diaz, L., 2008.GvSIG: a desktop solution for an open SDI.J.Geogr.Reg.Plann.1 (3), 41-48. Bird, D., Ling., M., Haynes, K., 2012.Flooding facebook-the use of social media during the Queensland and Victorian floods.Aust.J.Emerg.Manage.27 (1), 27.

ID: 61807
Title: Resolution vs. image quality in pre-tsunami imagery used for tsunami impact models in Aceh, Indonesia.
Author: J.C.Laso Bayas, A.Ekadinata, A.Widayati, C.Marohn, G.Cadisch.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 38-48 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: Tsunami, West Aceh, GLIMMIX, Land cover roughness, Model selection, Landsat, SPOT.
Abstract: Land cover roughness coefficients (LCRs) have been used in multivariate spatial models to test the mitigation potential of coastal vegetation to reduce impacts of the 2004 tsunami in Ach, Indonesia. Previously, Landsat 2002 satellite imagery was employed to derive land cover maps, which were then combined with vegetation characteristics, i.e., stand height, stem diameter and planting density to obtain LCRs. The present study tested LCRs extracted from 2003 and 2004 Landsat (30m) images as well as combination of2003 and 2004 higher spatial resolution SPOT (10m) imagery, while keeping the previous vegetation characteristics. Transects along the coast were used to extract land cover, whenever availability and visibility allowed. These new LCRs applied in previously developed tsunami impact models on wave outreach, casualities and damages confirmed previous findings regarding distance to the shoreline as a main factor reducing tsunami impacts. Nevertheless, the models using 2002 LCRs performed better (?AIC >2) than the more recent Landsat and SPOT counterparts.Cloud cover at image acquisition for Landsat and low area coverage for SPOT images decreased statistical predictive power (fewer observations).Due to the large spatial heterogeneity of tsunami characteristics as well as topographic and land-use features, it was more important to cover a larger area. Nevertheless, if more land cover classes would be referenced and high resolution imagery with low cloud cover would be available, the full benefits of higher spatial resolution imagery used to extract more precise land use roughness coefficients could be exploited.
Location: T E 15 New Biology Building
Literature cited 1: Akaike, H., 1974.A new look at the statistical model identification.IEEE Trans.Autom.Control 19, 716-723. Atkinson, P.M., 1997.selecting the spatial resolution of airborne MSS imagery for small-scale agricultural mapping int.J.Remote Sens.18, 1903-1917.
Literature cited 2: Borrero, J.C., Sieh, K., Chlieh, M., Synolakis, C.E., 2006.Tsunami inundation modeling for western Sumatra.Proc.Natl.Acad.Sci.U.S.A.103, 19673-19677. BRR, 2005.Aceh and Nias One year after the tsunami: The Recovery Effort and Way Forward. Reconstruction and Rehabilitation Agency (BRR), Jakarta, Indonesia, 205 pp.

ID: 61806
Title: Use of WorldView -2 time series to establish a wetland monitoring program for potential offsite impacts of mine sit rehabilitation.
Author: Timothy G.Whiteside, Renee E.Bartolo.
Editor: F.D.van der Meer
Year: 2015
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 42 24-37 (2015).
Subject: Applied Earth Observation and Geoinformation
Keywords: WorldView-2, Time-series analysis, Vegetation change, Wetlands, Monitoring.
Abstract: The Ramsar-listed wetlands of the Magela Creek floodplain, situated in the World Heritage Kakadu National Park, in northern Australia are recognized for their biodiversity and cultural values. The flood-plain is also a downstream receiving environment for Ranger uranium mine, which is entering closure and rehabilitation phases. Vegetation on the floodplain is spatially and temporally variable which is related to the hydrology of the region, primarily the extent and level of inundation and available soil moisture. Time-series mapping of the floodplain vegetation will provide a contemporary baseline of annual vegetation dynamics to assist with determining whether change is natural or a result of the potential impacts of mine closure activities such as increased suspended sediment moving downstream. The research described here used geographic object-based image analysis (GEOBIA) to classify the upper Magela Creek floodplain vegetation from WorldView-2 imagery captured over four years (2010-2013) and ancillary data including a canopy height model. A step-wise rule set was used to implement a decision tree classification. The resulting maps showed the 12 major vegetation communities that exist on the Magela Creek floodplain and their distribution for May 2010, May 2011, June 2012 and June 2013with overall accuracies of over 80 % for each map. Most of the error appears to be associated with confusion between vegetation classes that are spectrally similar such as the classes dominated by grasses. Object-based change detection was then applied to the maps to analyse change between dates. Results indicate that change between dates was detected for large areas of the floodplain. Most of the change is associated with the amount of surface water present, indicating that although imagery was captured at the same time of year, the imagery represents different stages of the seasonal cycle of the floodplain.
Location: T E 15 New Biology Building
Literature cited 1: Adam, E., Mutanga, O., Rugege, D., 2010.Multispectral hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wetlands Ecol.Manage.1, 281-296. Baatz, M., Schape, A., 2000.Multiresolution segmentation-an optimization approach for high quality multi-scale image segmentation.In: Strobl, J., Blaschke, T., Griesebner, G., (Eds.), Angewandte Geographische Informationsverarbeitung XII.Wichmann-Verlag, Heidelberg, PP.12-23.
Literature cited 2: Baker, C., Lawrence, R., Montagne, C., Patten, D., 2006.Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision-tree based models. Wetlands 26, 465-474. Bartolo, R., Paulka, S., Van Dam, R.A.Iles, M., Harford, A., 2013.Rehabilitation and closure ecological risk assessment for Range r uranium mine: Ranger uranium mine: documentation of initial problem formulation activities. Internal Report 624.Supervising Scientist; Darwin.