Enter records

ID: 61825
Title: Inter-and intra-annual variations of clumping index derived from the MODIS BRDF product.
Author: Liming He, Jane Liu, Jing M.Chen, Holly Croft, Rong Wang, Michael Sprintsin, Ting Zheng, Youngryel Ryu, Jan Pisek, Alemu Gonsamo, Feng Deng, Yongqin Zhang.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 53-60 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Clumping index, MODIS, Seasonality, Variation, BRDF.
Abstract: Clumping index quantities the level of foliage aggregation, relative to a random distribution, and is a key structural parameter of plant canopies and is widely used in ecological and meteorological models. In this study, the inter-and intra-annual variations in clumping index values, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) BRDF product, are investigated at six forest sites, including conifer forests, a mixed deciduous forest and an oak-savanna system. We find that the clumping index displays large seasonal variation, particularly for the deciduous sites, with the magnitude in clumping index values at each site comparable on an intra-annual basis, and the seasonality of clumping index well captured after noise removal. For broadleaved and mixed forest sites, minimum clumping index values are usually found during the season when leaf area index is at its maximum. The magnitude of MODIS clumping index is validated by ground data collected from 17 sites.Validation shows that the MODIS clumping index can explain 75 % of variance in measured values (bias=0.03 and rmse =0.08), although with a narrower amplitude in variation. This study suggests that the MODIS BRDF product has the potential to produce good seasonal trajectories of clumping index values, but with an improved estimation of background reflectance.
Location: T E 15 New Biology Building
Literature cited 1: Baldocchi, D.D., Harley, P.C., 1995.Scaling carbon dioxide and water vapour exchange from leaf to canopy in a deciduous forest.II. Model testing application. Plant Cell Environ.18, 1157-1173. Baldocchi, D.D., Xu, L.K., Kiang, N., 2004.How plant functional-type, weather, seasonal drought, and soil physical properties alter water and energy fluxes of an oak-grass savanna and an annual grassland. Agric. Forest Meteorol.123.13-39.
Literature cited 2: Baldocchi, D., 1997.Measuring and modeling carbon dioxide and water vapour exchange over a temperate broad-leaved forest during the 1995 summer drought. Plant Cell Environ.20, 1108-1122. Barr, A.G., Black, T.A., Hogg, E.H., Kljun, N., Morgenstern, K., Nesic, Z., 2004.Inte-annual variability in the leaf area index of a boreal aspen-hazelnut forest in relation to net ecosystem production.Agri.Frest Meteorol.126, 237-255.

ID: 61824
Title: Monitoring forest disturbances in Southeast Oklahoma using Landsat and MODIS images.
Author: Trung V.Tran, Kirsten M.de Beurs, Jason P.Julian
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 42-52 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Landsat, MODIS, STAARCH, Forest disturbance, Synthetic imagery, Disturbance index.
Abstract: Monitoring forest disturbances using remote sensing data with high spatial and temporal resolution can reveal relationships between forest disturbances and forest ecological patterns and processes. In this study, we fused Landsat data at high spatial resolution (30 m) with 8-day MODIS data to produce high spatial and temporal resolution image time-series. The Spatial Temporal Adaptive Algorithm for mapping Reflectance Change (STAARCH) is a simple but effective fusion method. We adapted the STAARCH fusion method to successfully produce a time-series of disturbances with high overall accuracy (89-92 %) in mixed forests in southeast Oklahoma. The results demonstrated that in southeast Oklahoma, forest area disturbed in 2011 was higher than it was in 2000.However, two remarkable drops were identified in 2001 and 2006.We speculated that the drops were related to the economic recessions causing reduction in the demand of woody products. The detected fluctuation of area disturbed calls for continuing monitoring of spatial and temporal changes in this and other forest landscapes using high spatial and temporal resolution imagery datasets to better recognize the economic and environmental factors, as well as the consequences of those changes.
Location: T E 15 New Biology Building
Literature cited 1: Amiro, B.D., Chen, J.M., 2003.Forest-fire-scar aging using SPOT-VEGETATION for Canadian ecoregions.Can.J.Forest Res.33, 1116-1125. Asner, G.P., Keller, M., Silva, J.N.M., 2004.Spatial and temporal dynamics of forest canopy gaps following selective logging in the eastern Amazon. Global Change Biol.10, 765-783.
Literature cited 2: Bradford, J.B., Birdsey, R.A., Joyce, L.A., Ryan, M.G., 2008.Tree age, disturbance history, and carbon stocks and fluxes in subalpine Rocky Mountain Forests. Global Change Biol.14, 2882-2897. Chen, J., Jonsson, P., Tamura, M., Gu, Z., Matsushita, B., Eklundh, L., 2004.A simple method for reconstructing a high-quality NDVI time-series dataset based on the Savitzky-Golay filter. Remote Sens.Environ.91, 332-344.

ID: 61823
Title: Spectral mapping of morphological features on the moon with MGM and SAM.
Author: Gayantha R.L.Kodikara, P.K.Champati ray, Prakash Chauhan, R.S.Chatterjee.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 31-41 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Spectral mapping, Modified Guassian method, Spectral angle mapper, Moon mineralogy mapper, Spectral deconvolution.
Abstract: Three types of morphological features observed in different lunar crustal terrains were studied and mapped using hyperspectral Moon mineralogy mapper (M3) data onboard Chandrayaan 1 mission in order to assess the utility of cascaded MGM-SAM spectral mixture modeling approach to characteristize the surface materials, which may occur as mineral mixtures, at different topography of the lunar surface. Selected morphological features include: the impact melts in Orientale basin, sinuous rilles in Procellarum KREEP Terrane 9PKT) and a rayed crater in Feldspathic Highland Terrane (FHT).Methodology involves extraction of spectrally pure pixels (endmembers) of the area using Pixel Purity Index (PPI), identification of mineralogy of the selected end member spectrum using the Spectral Angle Mapper (SAM) method. Mapping results demonstrate both the capabilities and the limitations of the MGM method of spectral deconvolution and the SAM method spectral matching as effective tools for compositional characterizations of morphological features on the lunar surface. As a method of spectral deconvolution, MGM was able to identify and characterize both high-and low-Ca pyroxenes along with plagioclase feldspar. The Spectral Angle Mapper (SAM) was able to map identified mineral mixtures from MGM.
Location: T E 15 New Biology Building
Literature cited 1: Adams, J.B., 1974.Visible and near-infrared diffuse reflectance spectra of pyroxenes as applied to remote sensing of solid objects in the solar system.J.Geophys.Res.79 (32), 4829-4836. Adams, J.B, Gillespie, A.R., 2006.Remote sensing of Landscapes with Spectral Images: A physical Modeling Approach. Cambridge University Press, 362 pp.
Literature cited 2: Adams, J.B, Goullaud, L.H., 1978.Plagioclase feldspars: Visible and near infrared diffuse reflectance spectra as applied to remote sensing.proc.Lunar Planet.Sci.Conf.9th: p.2901-2909.http://adsabs.harvard.edu/full/1978LPSC.9.2901 A Bateson, A., Curtiss, B.A., 1996.Method for manual endmember selection and spectral unmixing.Remote Sens.Environ.55, 229-243.

ID: 61822
Title: Testing the discrimination and detection limits of WorldView-2 imagery on a challenging invasive plant target.
Author: T.P.Robinson, G.W.Wardell-Johnson, G.Pracilio, C.Brown, R.Corner, R.D.van Klinken
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 23-30 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Invasive plants, Remote sensing, Woody weeds, Mesquite, Prosopis, WorldView-2.
Abstract: Invasive plants pose significant threats to biodiversity an ecosystem function globally, leading to costly monitoring and management effort. While remote sensing promises cost-effective, robust and repeatable monitoring tools to support intervention, it has been largely restricted to airborne platforms that have higher spatial and spectral resolutions, but which lack the coverage and versatility of satellite-based platforms. This study tests the ability of the WorldView-2 (WV2) eight-band satellite sensor for detecting the invasive shrub mesquite (Prosopis spp.) in the north-west Pilbara region of Australia. Detectability was challenged by the target taxa being largely defoliated by a leaf-tying biological control agent (Gelechiidae: Evippe sp. #1) and the presence of other shrubs and trees. Variable importance in the projection (VIP) scores identified bands offering greatest capacity for discrimination were those covering the near-infrared, red, and red-edge wavelengths. Wavelengths between 400 nm and 630 nm (coastal blue, blue, green, yellow) were not useful for species level discrimination in this case. Classification accuracy was tested on three band sets (simulated standard multispectral, all bands and bands with VIP scores ?).Overall accuracies were comparable amongst all band-sets (Kappa=0.71-0.77). However, mesquite omission rates were unacceptably high (21.3%) when using all eight bands relative to the simulated standard multispectral band-set (9.5%) and the band-set informed by VIP scores (11.9 %).An incremental cover evaluation on the latter identified most omissions to be for objects <16 m2 allows application for mapping mesquite shrubs and coalesced stands, the former not previously possible, even with 3 m resolution hyperspectral imagery.WV2 imagery offers excellent portability potential for detecting other species where spectral/spatial resolution or coverage has been an impediment. New generation satellite sensors are removing barriers previously preventing widespread adoption of remote sensing technologies in natural resource management.
Location: T E 15 New Biology Building
Literature cited 1: Anderson, G., Everitt, J.H., Rcharson, A.J., Escobar, D.E., 1993.Using satellite data to map false broomweed (Ericameria austrotexana) infestations on south Texas rangelands. Weed Technol.7, 865-871. Ansley, R.J., Wu, X.B., Kramp, B.A., 2001.Observation: long-term increases in mesquite canopy cover in a north Texas savannah.J.Range Manag.54.171-176.
Literature cited 2: Archer, S.1995.Tree-grass dynamics in a Prosopis-thornscrub savanna parkland: reconstructing the past and predicting the future.Ecoscience 2, 83-99. Arianoutsou, M., Delipetrou, P., Vila, M., Dimitrakopoulos, P.G., Celesti-Grapow, L., Wardell-Johnson, G., Henderson, L., Fuentes, N., Ugarte-Mendes, E., Rundel, P.W., 2013.Comparative patterns of plant invasions in the Mediterranean Biome.PLoS One 8, e79174.

ID: 61821
Title: Classification of forest land attributes using multi-source remotely sensed data.
Author: Inka Pippuri, Aki Suvanto, Matti Maltamo, Kari T.Korhonen, Juho Pitkanen, Petteri Packalen.
Editor: F.D.van der Meer
Year: 2016
Publisher: Elsevier B.V.
Source: EWRG, CES
Reference: Applied Earth Observation and Geoinformation. Vol. 44 11-22 (2016).
Subject: Applied Earth Observation and Geoinformation
Keywords: Classification, Forest land, Landsat, LiDAR, Site type, Surface model.
Abstract: The aim of the study was to (1) examine the classification of forest land using airborne laser scanning (ALS) data, satellite images and sample plots of the Finnish National Forest Inventory (NFI) as training data and to (2) identify best performing metrics for classifying forest land attributes. Six different schemes of forest land classification were studied: land use/land cover (LU/LC) classification using both national classes and FAO (Food and Agricultural Organization of the United Nations) classes, main type, site type, peat land type and drainage status. Special interest was to test different ALS-based surface metrics in classification of forest land and remotely sensed data was from summer 2010.Multinominal logistic regression was used as the classification method. Classifications of LU/LC classes were highly accurate (kappa-values 0.90 and 0.91) but also the classification method. Classification of site type, peat land type and drainage status succeeded moderately well (kappa-values 0.51, 0.69 and 0.52).ALS-based surface metrics were found to be the most important predictor variables in classification of LU/LC class, main type and drainage status. In best classification models of forest sites types both spectral metrics from satellite data and point cloud metrics from ALS were used. In turn, in the classification of peat land types ALS point cloud metrics played the most important role. Results indicated that the prediction of site type and forest land category could be incorporated into stand level forest management inventory system in Finland.
Location: T E 15 New Biology Building
Literature cited 1: Antonarakis, A.S., Richard, K.S., Brasington, J.2008.Object-based land cover classification using airborne LiDAR.Remote Sens.Environ.112 (6), 2988-2998. Axelsson, P., 2000.DEM generation from laser scanning data using adaptive TIN models.Int.Arch.Photogramm.Remote Sens.33 (Part B4), 110-117.
Literature cited 2: Brennan, R., Webster, T.L., 2006.Object-oriented land cover classification of Lidar-derived surfaces.Can.J.Remote Sens.32 (2), 162-172. Cajander, A.K., 1926.The theory of forests types. Acta For.Fenn.29 (3), 1-108.

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.