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ID: 60097
Title: Regional-scale estimation of evapotranspiration for the North China plain using MODIS data and the triangle -approach.
Author: Mads Olander Rasmussen, Mikael Kamp Sorensen, Bingfang Wu, Nana Yan, Huanhuan Qin, Inge Sandholt.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 143-153 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Evapotranspiration, MODIS, Triangle method, Fengyun, Latent heat.
Abstract: A method for the estimation of daily evapotranspiration is tested for the North China Plain. The method is designed to be simple to implement and with very limited requirements for ground data (air temperature and humidity). The method uses MODIS NDVI and Land Surface Temperature (LST) data to derive evaporative fraction, using an adaption of the ?triangle method?. The energy available for evapotranspiration is estimated using a combination of satellite data from MODIS and the (geostationary) Fengyun 2-series of sensors and station-based air temperature data. A gapfilling routine is applied to the time series of evaporative fraction to create complete daily maps for the region, allowing for the use of the ET-estimates for applications requiring complete daily coverage (e.g. hydrological models). Results show that ET estimation on a daily scale is feasible with the proposed method, and that seasonal patterns are in accordance with other independent ET-estimates. There are some indications that our ET-estimates are somewhat overestimated when comparing to other RS-methods and model simulations. It is demonstrated that the proposed method provides a relatively simple way of obtaining spatially distributed daily estimates of ET, making the method suitable for applications in studies where ground data availability is limited.
Location: TE 15 New Biology Building
Literature cited 1: Anderson, M., Norman, J., Diak, G., Kustas, W., Mecikalski, J., 1997. A two- source time-integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sens. Environ. 60(2), 195-216. Bristow, K., Campbell, G., Papendick, R., Elliott, L., 1986. Simulation of heat and moisture transfer through a surface residue soil system. Agric. Forest Meteorol. 36 (3), 193-214.
Literature cited 2: Campbell, G., 1985. Soil Physics with BASIC: Transport Models for Soil-plant Systems, Elsevier, Amsterdam. Cao, G., Zheng, C., Scanlon, B.R., Liu, J., Li, W., 2013. Use of flow modeling to assess sustainability of groundwater resources in the North China Plain. Water Resour. Res. 49 (1), 159-175.

ID: 60096
Title: A monitoring protocol for vegetation changes on Irish peatland and heath.
Author: J.O Connell, J. Connolly, N.M.Holden
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 130-142 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Change detection, Cross calibration, Peatlands, EV12, Heaths.
Abstract: Amendments to Article 3.3 and 3.4 of the Kyoto Protocol have meant that detection of vegetation change may now from an interracial part of national soil carbon stocks. In this study multispectral multi-platform satellite data was processed to detect change to the surface vegetation of four peatland sites and one heath in Ireland. Spectral and spatial thresholds were used on difference images between master and slave data in the extraction of temporally invariant targets for multi-platform cross calibration. The Kolmogorov -Smirnov test was used to evaluate any difference in the cumulative probability distributions of the master, slave and calibrated slave data as expressed by the D statistic, with values reduced by an average of 89.7% due to the cross calibration procedure. A change detection model was created which incorporated a spatial threshold of 9 pixels and a standard deviation (SD) spectral threshold. Kappa accuracy values for the five sites ranged from 80 to 97%, showing that 1.5 SD was optimum spectral threshold for detecting vegetation change. Change detection results showed mean percentage change ranging from 2.11 to 3.28% of total area and cumulative change over the observed tome period of between 15.24 and 49.27% of total area.
Location: TE 15 New Biology Building
Literature cited 1: Achard, F., G., Herold, M., Mollicone, D., 2008. Use of satellite remote sensing in LULUCF sector. In: GOFLCD. (Ed) IPCC Guidance on Estimating Emissions and Removals of Greenhouse Gases from Land Uses such as Agriculture and Forestry. Land Cover Project Office, pp. 1-25. Bragg, O.M., Tallis, J.H., 2001. The sensitivity of peat-covered upland landscapes. Catena 423, 345-360.
Literature cited 2: Connolly, J., Holden, N.M., 2009. Mapping peat soils in Ireland; updating the derived Irish peat map. Irish Geogr. 3, 343-352. Connolly, J., Holden, N.M., 2011a. Classification of peatland disturbance. Land Degrad. Dev. 24, 548-555.

ID: 60095
Title: Sparse dimensionality reduction of hyperspectral image based on semi-supervised local Fisher discriminant analysis.
Author: Zhenfeng Shao, Lei Zhang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 122-129 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Sparsity preserving projections (SPP) Dimensionality reduction , Semi-supervised local Fisher discriminant.
Abstract: This paper presents a novel sparse dimensionality reduction method of hyperspectral image based on semi-supervised local Fisher discriminant analysis (SELF). The proposed method is designed to be especially effective for dealing with the out-of -sample extrapolation to realize advantageous complementarities between SELF and Sparsity preserving projections (SPP). Compared to SELF and SPP, the method proposed herein offers highly discriminative ability and produces an explicit nonlinear feature mapping for the out-of sample extrapolation. This is due to the fact that the proposed method can get an explicit feature mapping for dimensionality reduction. Experimental analysis on the sparsity and efficacy of low dimensional outputs shows that, sparse dimensionality reduction based on SELF can yield good classification results and interpretability in the field of hyperspectral remote sensing.
Location: TE 15 New Biology Building
Literature cited 1: Belhumeur, P.N., Hespanha, J.P., Kreigman, D.J., 1997. Eigenfaces vs. fisherfaces: recognition using class specific linear projection. IEEE Trans.Pattern Anal.19 (7), 711-720. Belkin, M., Niyogi, P., 2003. Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput. 15 (6), 1373-1396.
Literature cited 2: Bellman, R., 1961. Adaptive Control Processes: A guided Tour. Princeton University Press, Princeton. Chakrabarti, A., Zickler, T., 2011. Statistics of Real-World Hyperspectral Images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

ID: 60094
Title: Object based change detection of Central Asian Tugai vegetation with very high spatial resolution satellite imagery.
Author: Philipp Gartner, Michael Forster, Alishir Kurban, Birgit Kleinschmit.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 110-121 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Tree detection, Tree crown delineation, QuickBird, WorldView 2, Riparian forest, Populus euphratica.
Abstract: Ecological restoration of degraded riparian Tugai forests in north-western China is a key driver to combat desertification in this region. Recent restoration efforts attempt to recover the forest along with its most dominant tree species, Populus euphratica. The present research observed the response of natural vegetation using an object based change detection method on QuickBird (2005) and WorldView2 (2011) data. We applied the region growing approach to derived Normalized Difference Vegetation Index (NDVI) values in order to identify single P.Euphrantica trees, delineate tree crown areas and quantify crown diameter changes. Results were compared to 59 reference trees. The findings confirmed a positive tree crown growth and suggest a crown diameter increase of 1.14 m, on average. On a single tree basis, tree crown diameters of larger crowns were generally underestimated. Small crowns were slightly underestimated in QuickBird and overestimated in WorldView2 images. The results of the automated tree crown delineation show a moderate relation to field reference data with R22005: 0.36 and R22011: 0.48. The object based image analysis (OBIA) method proved to be applicable in sparse riparian Tugai forests and showed great suitability to evaluate ecological restoration efforts in an endangered ecosystem.
Location: TE 15 New Biology Building
Literature cited 1: Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., 2012a. Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images. Int.J.Appl.Earth Observ.Geoinform.15, 57-69, http://dx.doi.org/10.1016/j.jag.2011.06.005. Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., Nov 2012b.Quantification of crown changes and change uncertainty of trees in an urban environment.ISPRS J. Photogramm.Remote Sens.74, 41-55, http://dx.doi.org/10.1016/j.isprsjprs.2012.08.007.
Literature cited 2: Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS J.Photogram.Remote Sens. 65, 2-16, htpp://d.doi.org/10.1016/j.isprsjprs.2009.06.004. Blaschke,T., Johansen,K., Tiede, D., 2011. Object-based image analysis for vegetation mapping and monitoring. In: Weng,Q.(Ed), Advances in Environmental Remote Sensing: Sensors, Algorithms, and Applications.CRC Press Taylor & Francis Group, Boca Raton, FL, United States, pp.241-271.

ID: 60093
Title: Lithological mapping from hyperspectral data by improved use of spectral angle mapper.
Author: Xiya Zhang, Peijun Li.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 95-109 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Lithological mapping, Hyperspectral data, Spectral variability, Spectral angle mapper, Matched filtering.
Abstract: The spectral angle mapper (SAM), as a spectral matching method, has been widely used in lithological type identification and mapping using hyperspectral data. The SAM quantifies the spectral similarity between an image pixel spectrum and a reference spectrum with known components. In most existing studies a mean reflectance spectrum has been used as the reference spectrum for a specific lithological class. However, this conventional use of SAM does not take into account the spectral variability, which is an inherent property of many rocks and is further magnified in remote sensing data acquisition process. In this study, two methods of determining reference spectra used in SAM are proposed for the improved lithological mapping. In first method the mean of spectral derivative was combined with the mean of original spectra, i.e., the mean spectrum and the mean spectral derivative were jointly used in SAM classification, to improve the class separability. The second method is the use of multiple reference spectra in SAM to accommodate the spectral variability. The proposed methods were evaluated in lithological mapping using EO-1 Hyperion hyperspectral data of two arid areas. The spectral variability and separability of the rock types under investigation were also examined and compared using spectral data alone and using both spectral data and first derivatives. The experimental results indicated that spectral variability significantly affected the identification of lithological classes with the conventional SAM method using a mean reference spectrum. The proposed methods achieved significant improvement in the accuracy of lithological mapping, outperforming the conventional use of SAM with a mean spectrum as the reference spectrum, and the matching filtering, a widely used spectral mapping method.
Location: TE 15 New Biology Building
Literature cited 1: Angelopoulou, E., Lee, S.W., Bajcsy, R., 1999. Spectral gradient: a material descriptor invariant to geometry and incident illumination. In: The Proceedings of the Seventh IEEE International Conference on Computer Vision, pp. 861-867. Barry, P., 2001, EO-1/Hyperion science data user ' s guide, Level 1_B. TRW Space, Defense & Information Systems, Redondo Beach, CA, Rep.HYP.TO 1.
Literature cited 2: Bateson, C.A., Asner, G.P., Wessman, C.A., 2000. Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis. IEEE Trans.Geosci.Remote Sens.38, 1083-1094. Bowers, T.L., Rowan, L.C., 1996. Remote minerologic and lithologic mapping of the ice river alkaline complex, British Columbia, Canada, using AVIRIS data. Photogramm.Eng.Remote Sens.62, 1379-1386.

ID: 60092
Title: Estimating ecological indicators of karst rocky desertification by linear spectral unmixing method.
Author: Xia Zhang, Kun Shang, Yi Cen, Tong Shuai, Yanli Sun.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 86-94 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperspectral remote sensing, Linear spectral unmixing, Spectral index, Karst rocky desertification.
Abstract: Coverage rates of vegetation and exposed bedrock are two key indicators of karst rocky desertification. In this study, the abundance of vegetation and exposed rock were retrieved from a hyperspectral Hyperion image using linear spectral unmixing method. The results were verified using the spectral indices of karst rocky desertification (KRDSI) and an integrated LAI spectral index: modified chlorophyll absorption ratio index (MCAR12). The abundances showed significant linear correlations with KRDSI and MCAR12. The coefficients of determination (R2) were 0.93, 0.66, and 0.84 for vegetation, soil, and rock, respectively, indicating that the abundances of vegetation and bedrock can characterize their coverage rates to a certain extent. Finally, the abundances of vegetation and bedrock were graded and integrated to evaluate rocky desertification in a typical karst region. This study suggests that spectral unmixing algorithm and hyperspectral remote sensing imagery can be used to monitor and evaluate karst rocky desertification.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J.B., Sabol, D.E., Kapos, V., et al., 1995. Classification of multispectral images based on fractions of endmembers: application to land -cover change in the Brazilian Amazon. Remote Sens. Environ. 52, 137-154. Baret, F., Jacquemoud, S., Guyot, G., Leprieur, C., 1992. Modelled analysis of the biophysical nature of spectral shifts and comparison with information content of broad bands. Remote Sens. Environ. 41, 133-142.
Literature cited 2: Boardman, J.W., Kruse, F.A., 1994. Automated spectral analysis: a geological example using AVIRIS data, north Grapevine Mountains. In: Proceedings of ERIM Tenth Thematic Conference on Geologic Remote Sensing, pp. 1-407-1-418. Broge, N.H., Leblanc, E., 2000. Comparing prediction power and stability of broad-band and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density. Remote Sens. Environ. 76, 156-172.

ID: 60091
Title: Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion.
Author: Feng Zhao, Yiqing Guo, Yanbo Huang, Krishna N. Reddy, Matthew A. Lee, Reginald S. Fletcher, Steven J.Thomson.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 78-85 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Crop injury, Glyphosate, Foliar biochemistry, Sensitive analysis, Model inversion, Hyperspectrtal.
Abstract: Early detection of crop injury from herbicide glyphosate is of significant importance in crop management. In this paper, we attempt to detect glyphosate-induced crop injury by PROSPECT (leaf optical PROperty SPECTra model) inversion through leaf hyperspectral reflectance measurements for non-Glyphosate-Resistant (non-GR) soybean and non-GR cotton leaves. The PROSPECT model was inverted to retrieve chlorophyll content (Ca+b), equivalent water thickness (Cw), and leaf mass per area (Cm) from leaf hyper-spectral reflectance spectra. The leaf stress conditions were then evaluated by examining the temporal variations of these biochemical constituents after glyphosate treatment. The approach was validated with green-house-measured datasets. Results indicated that the leaf injury caused by glyphosate treatments could be detected shortly after the spraying for both soybean and cotton by PROSPECT inversion, with Ca+b of the leaves treated with high dose solution decreasing more rapidly compared with leaves left untreated, whereas the Cw and Cm showed no obvious difference between treated and untreated leaves. For both non-GR soybean and non-GR cotton, the retrieved Ca+b values of the glyphosate treated plants from leaf hyperspectral data could be distinguished from that of the untreated plants within 48 h after the treatment, which could be employed as a useful indicator for glyphosate injury detection. These findings demonstrate the feasibility of applying the PROSPECT inversion technique for the early detection of leaf injury from glyphosate and its potential for agricultural plant status monitoring.
Location: TE 15 New Biology Building
Literature cited 1: ASD Inc, 2008. ASD Document 60060 Rev. B., Integrating Sphere User Manual. Barnes, J.D., Balaguer, L., Manrique, E., Elvira, S., Davison, A.W., 1992. A reappraisal of the use of DMSO for the extraction and determination of chlorophylls a and b in lichens and higher plants. Environ.Exp.Bot. 32, 85-100.
Literature cited 2: Carter, G.A., 1994. Ratios of leaf reflectances in narrow wavebands as indicators of plant stress. Int. J. Remote Sens. 15, 697-703. Ding, W., Reddy, K.N., Krutz, L.J., Thomson, S.J., Huang, Y., Zablotowicz, R.M., 2011. Biological response of soybean and cotton to aerial glyphosate drift. J. Crop Improv. 25, 291-302.

ID: 60090
Title: Remote sensing of CO2 leakage from geologic sequestration projects.
Author: Joshua L. Verkerke, David J. Williams, Eben Thoma.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 67-77 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Carbon capture and sequestration (CCS) geological sequestration, Climate change, Remote sensing.
Abstract: Monitoring for leak hazards is an important consideration in the deployment of carbon dioxide geologic sequestration. Failure to detect and correct leaks may invalidate any potential emissions benefits intended by such projects. Presented is a review of remote sensing methods primed to serve a central role in any monitoring program due to their minimally invasive nature and potential for large area coverage in a limited timeframe or in real-time as a continuous monitoring program. Methods investigated were divided into those capable of indirect detection of carbon dioxide leakage, such as monitoring for vegetative stress and ground surface deformation, and those that directly detect gaseous and atmospheric compounds, by means of such tools as Open-path Fourier Transform Infrared or Tunable Diode Lasers. Both direct and indirect methods present viable means of detecting a leak event, though ultimately, a robust approach will multiple monitoring tools that may include both direct and indirect remote sensing methods.
Location: TE 15 New Biology Building
Literature cited 1: Abshire , J.B., Riris, H., Allan, G.R., Weaver, C.J., Mao,J., Sun, X., Hassel-brack, W.E., Kawa, S.R., Biraud, S., 2010a. Pulsed airborne lidar measurements of atmospheric CO2 column absorption. Tellus B 62 (5), 770-783, htpp://dx.doi.org/10.1111/j.1600-0889.2010.00502.x Abshire, J.B., Riris,H., Allan, G.R., Weaver, C.J., Mao, J., Sun, X., Hasselbrack, W.E., Yu, A., Amediek, A., Choi, Y., Browell, E.V., 2010b.A lidar approach to measure CO2 concentrations from space for the ASCENDS Mission. Lidar Technologies, Techniques, and Measurements for Atmospheric Remote Sensing VI, 7832, Toulouse, France, http://dx.doi.org/10.1117/12.868567.
Literature cited 2: Amthor, J.S., 1995. Terrestrial higher-plant response to increasing atmospheric [CO2] in relation to the global carbon cycle. Global Change Biol. 1 (4), 243-274, http://dx.doi.org/10.1111/j.1365-2486.1995.tb00025.x. Aschbacher, J., Milagro-perez, M.P., 2012. The European Earth monitoring (GMES) programme: statusandperspectives.RemoteSens.Environ.120 (0), 3-8, http.//dx.doi.org./10.1016/j.rse.2011.08.028.

ID: 60089
Title: Tree species mapping in tropical forests using multi-temporal imaging spectroscopy: wavelength adaptive spectral mixture analysis.
Author: B.Somers, G.P. Asner
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 57-66 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperion, Hyperspectral, MESMA, Morella faya, Phenology, Psidium cattleianum.
Abstract: The use of imaging spectroscopy for florisic mapping of forests is complicated by the spectral similarity among co-existing species. Here we evaluated an alternative spectral unmixing strategy combining a time series of EO-1 Hyperion images and an automated feature selection in Multiple Endmember Spectral Mixture Analysis (MESMA). The temporal analysis provided a way to incorporate species phenology while feature selection indicated the best phonological time and best spectral feature set to optimize the separability between tree species. Instead of using the same set of spectral bands throughout the image which is the standard approach allowed the spectral subsets to vary on a per pixel basis. As such we were able to optimize the spectral separability between the tree species present in each pixel. The potential of the new approach for floristic mapping of tree species in Hawaiian rainforests was quantitatively assessed using both simulated and actual hyperspectral image time-series. With a cohen ' s Kappa coefficient of 0.65, WASMA provided a more accurate tree species map compared to conventional MESMA(Kappa = 0.54; p -value < 0.05. T he flexible or adaptive use of band sets in WASMA provides an interesting avenue to address spectral similarities in complex vegetation canopies.
Location: TE 15 New Biology Building
Literature cited 1: Armstrong, R.W., 1983. Atlas of Hawaii, 2nd Ed. University of Hawaii Press. State of Hawaii, Honolulu. Asner, G.P., Heidebrecht, K.B., 2003. Imaging spectroscopy for desertification studies: comparing AVIRIS and EO-1 Hyperion in Argentina drylands. IEEE Trans. Geosci. Remote Sens, 41, 1283-1296.
Literature cited 2: Asner, G.P., Lobell, D.B., 2000. A biogeophysical approach for automated SWIR unmixing of soils and vegetation. Remote Sens. Environ. 74, 99-112. Asner, G.P., Vitousek, P.M., 2005. Remotely analysis of biological invasion and biogeo-chemical change. Proc. Natl. Acad.Sci.U.S.A. 102, 4383-4386.

ID: 60088
Title: Estimation of aboveground biomass in Mediterranean forests by statistical modeling of ASTER fraction images.
Author: O. Fernandez-Manso, A. Fernandez-Manso, C.Quintano.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 45-56 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: ASTER, Biomass estimation, Spectral mixture analysis, Multiple linear regression, Forest inventory, Mediterranean pine.
Abstract: Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression models of original or synthetic bands. To overcome the poor relation between AGB and spectral bands due to mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGB estimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is managed Mediterranean pine woodland (Pinus pinaster Ait) in central Spain. A total of 1033 circular field plots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression to identify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Difference Vegetation Index and Tasselled Cap Components. Four linear models and one nonlinear model were tested. A linear combination of ASTER band 2 (red, 0.630-0.690 ? m), band 8 (short wave infrared 5, 2.295-2.365 ?m) and green vegetation fraction (from LSMA) was the best AGB predictor (R2adj = 0.632, the root-mean-squared error of estimated AGB was 13.3 Mg ha-1 (or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests. The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be used as baseline information for forest managers in future studies, such as quantifying the regional carbon budget, fuel accumulation or monitoring of management practices.
Location: TE 15 New Biology Building
Literature cited 1: Aldred, A.H., Alemdag, I.S., 1988. Guidelines for Forest Biomass Inventory.Inf.Report. PI-X-77. Canadian Forest Service, Petawawa National Forest Institute. Ardo, J., 1992. Volume quantification of coniferous forest compartments using spectral radiance recorded by Landsat Thematic Mapper. Int. J., Remote Sens. 3 (9), 1779-1786.
Literature cited 2: Asner, G.P. 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens. Environ. 64 (3), 234-253. Barbosa, J.M., Melendez-Pastor, I., Navarro-Pedreno, J., Bitencourt, M.D., 2014. Remotely sensed biomass over steep slopes: an evaluation among successional stands of the Atlantic forest, Brazil.ISPRS J., Photogramm. Remote Sens. 88, 91-100.

ID: 60087
Title: Accuracy of vegetation height and terrain elevation derived from ICESat/ GLAS in forested areas.
Author: F.Enble, J. Heinzel, B. Koch
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 37-44 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: ICESat, GLAS, LiDAR, ALS, Canopy height, Elevation
Abstract: This paper focuses on accuracy assessment of canopy top elevation, ground elevation and vegetation height (VH) derived from space borne full -waveform LiDAR (Light Detection And Ranging) data across forested areas. Computed height metrics from LiDAR data which were acquired by the GLAS sensor aboard the ICESat (Ice Cloud and land Elevation Satellite) are compared against airborne laser scanning (ALS) based digital elevation models. Due to the dynamic topography of the sites under investigation, a wide range of slope angles could be investigated. ICESat ' s raw waveform data (GLA01) and the land surface altimetry data (GLA 14) products are used to determine height metrics with different methods. GLA14 based elevation and vegetation heights are computed from range offset information. Values are provided for signal begin, signal end, land range and up to six Guassian peaks for each received waveform. GLA01based terrain heights are computed by locally weighted polynomial regression and peak detection on the received waveform itself. A range of different smoothing spans and noise threshold values on the original waveform, which is represented by 544 single values (bins), were tested. A new method based on the unsmoothed waveform was developed for the detection of the signal begin. By detecting the location above the noise threshold, where the signal rises at least for 5 bins (75 cm), achieved more precise results, than the given signal begin in the GLA 14 product. For ground peak detection by smoothing of the waveform it was found that noise thresholds of 4 and 4.5 times the standard deviation plus the mean noise level give the best performance. For VH computation in areas up to 10? terrain slope, a smoothing span of 10 bins achieved r2= 0.58, where as the GLA14 based method achieved r2 of 0.75 in flat terrain (0-5?) .For these flat areas, best results in VH computation (r2= 0.91) were achieved by using the new method for canopy top detection and the GLA14 based ground elevations. Determination of terrain elevations was observed to be best by computation with GLA14 based parameters. The stronger of second last two peaks was found to be closest to the ground level elevation.
Location: TE 15 New Biology Building
Literature cited 1: Abshire, J.B., Sun, X., Riris, H., Sirota, J.M., M McGarry, J.F., Palm, S., Yi, D., Liva, P., 2005. Geoscience Laser Altimeter System (GLAS) on the ICESat mission: on-orbit measurement performance. Geophysical Research Letters 32. Abshire, J., Ketchum, E., Afzal, R., Millar, P., Sun, X., 2000. The Geoscience Laser Altimeter System (GLAS) for the ICESat mission. In: Conference on Lasers and Electro-Optics (CLEO 2000). Technical Digest. Postconference Edition. TOPS Vol. 39 (IEEE Cat. No. 00CH37088). Opt. Soc. America.pp.602-603.
Literature cited 2: Ballhorn, U., Jubanski, J., Siegert, F., 2011. ICESat/GLAS data as measurement tool for peatland topography and Peat Swamp Forest biomass in Kalimantan, Indonesia. Remote Sensing 3, 1957-1982. Boudreau, J., Nelson, R., Magrolis, H., Beaudoin, A., Guidon, L., Kimes, D.S., 2008. Regional aboveground forest biomass using airborne and spaceborne LiDARin Quebec. Remote Sensing of Environment 112, 3876-3890.

ID: 60086
Title: Using Landsat Thematic Mapper records to map land cover change and the impacts of reforestation programmes in the borderlands of southeast Yunnan, China: 1990-2010.
Author: Jialong Zhang, Thi-Thanh-Hien Pham, Margaret Kalacska, Sarah Turner.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 25-36 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Land cover monitoring, Landsat TM, Support vector machines, Reforestation, Yunnan, China.
Abstract: At the beginning of the new millennium, after a severe drought and destructive floods along the Yangtze River, the Chinese government implemented two large ecological rehabilitation and reforestation projects: the Natural Forest Protection Programme and the Sloping Land Conversion Programme. Using Landsat data from a decade before, during and after the inception of these programmes, we analyze their impacts along with other policies on land use, land cover change (LULCC) in south west China. Our goal is to quantify the predominant land cover changes in four borderline counties, home to tens of thousands of ethnic minority individuals. We do this in three time stages (1990, 2000and 2010). We use support vector machines as well as transition matrix to monitor and land cover changes. The land cover classifications resulted in an overall accuracy and Kappa coefficient for forested area and cropland respectively 91% (2% confidence interval) and 0.87. Our results suggest that the total forested area observed increased 3% over this 20-year period, while cropland decreased between 1990 and 2000 and then increased between 2000 and 2010. In contrast, cropland increased and then decreased. These results suggest the important impacts of reforestation programmes that have accelerated a land cover transition in this region. We also found large changes in LULC occurring around fast growing urban areas, with changes in these peri-urban zones occurring faster to the east than west. This suggests that differences in socioeconomic conditions and specific local and regional policies have influenced the rates of forest, cropland and urban net changes, disturbances and net transitions. While it appears that a combination of economic growth and forest protection in this region over the past 20 years has been fairly successful, threats like drought, other extreme weather events and land degradation remain.
Location: TE 15 New Biology Building
Literature cited 1: Baumann, M., Ozdogan, M., Kuemmerle, T., Wendland, K.J., Esipova, E., Radeloff, V.C., 2012. Using the Landsat record to detect forest-cover changes during and after the collapse of the Soviet Union in the temperate zone of European Russia. Remote Sensing of Environment 124, 174-184. Berk, A., Bernstein, L.S., Anderson, G.P., Acharya, P.K., Robertson, D.C., Chetwynd, J.H., Adler-Golden , S.M., 1998. MODTRAN cloud and multiple scattering upgrades with application to AVIRIS. Remote Sensing of Environment 65, 367-375.
Literature cited 2: Bonan, G.B., 2008. Forests and climate change: forcings, feedbacks, and the climate benefits of forests, Science 320, 1444-1449. Brandt, J.S., Kuemmerle, T., Li, H.M., Ren, G.P., Zhu, J.G., Radeloff, V.C., 2012. Using Landsat imagery to map forest change in southwest Ch9ina in response to the national logging ban and ecotourism development. Remote Sensing of Environment 121, 358-369.

ID: 60085
Title: Fusion of pan-tropical biomass maps using weighted averaging and regional calibration data.
Author: Yong Ge, Valerio Avitabile, Gerard B.M. Heuvelink, Jianghao Wang, Mrtin Herold.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 13-24 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Biomass maps, Accuracy, Fusion model, Spatial variability.
Abstract: Biomass is a key environmental variable that influences many biosphere -atmosphere interactions. Recently, a number of biomass maps at national, regional and global scales have been produced using different approaches with a variety of input data, such as from field observation, remotely sensed imagery and other spatial datasets. However, the accuracy of these maps varies regionally and is largely unknown. This research proposes a fusion method to increase the accuracy of regional biomass estimates by using higher-quality calibrtiona data. In this fusion method, the biases in the source maps were first adjusted to correct for over-and underestimation but comparison with the calibration data. Next, the biomasss maps were combined linearly using weights derived from the variance -covariance matrix associated with the accuracies of the source maps. Because each map may have different biases and accuracies for different land use types, the biases and fusion weights were computed for each of the main land cover types separately. The conceptual arguments are sustained by a case study conducted in East Africa. Evaluation analysis shows that fusing multiple source biomass maps may produce a more accurate map than when only one biomass map or unweighted averaging is used.
Location: TE 15 New Biology Building
Literature cited 1: Avitable., V., Baccini, A., Fried, M.A., Schmullius, C., 2012. Capabilities and limitations of landsat land cover data for aboveground woody biomass estimation of Uganda. Remote Sens. Environ. 117, 366-380 Avitabile, V., Herold, M., Henry, M., Schmulius, C., 2011. Mapping biomass with remote sensing: a comparison of methods for the case study of Uganda. Carbon Balance Manag. 6 (7), 1-14.
Literature cited 2: Baccini, A., Goetz, S.J., Walker, W.S., Laporte, N.T., Sun, M., Sull-Menashe, D., Hackler, J., Beck, P.S.A., Dubayah, R., Friedl, M.A., Samanta, S., Houghton, R.A., 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-d3ensity maps. Nat.Clim.Change 2, 182-185 Baccini, A., Laporte, N., Goetz, S.J., Sun, M., Don, H., 2008. A first map of tropical Africa ' s above -ground biomass derived from satellite imagery. Environ.Res.Lett. 3, 1-9.

ID: 60084
Title: IRSeL- An approach to enhance continuity and accuracy of remotely sensed land cover data.
Author: H. Rathjens, K., Dornhofer, N. Oppelt.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 31. 1-12 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Land use change, Crop rotations, Space-time interpolation, Remote sensing, Landsat.
Abstract: Land cover data gives the opportunity to study interactions between land cover status and environmental issues such as hydrologic processes, soil properties, or biodiversity. Land cover data often are based on classification of remote sensing data that seldom provides the requisite accuracy, spatial availability and temporal observational frequency for environmental studies. Thus, there is a high demand for accurate and spatio-temporal complete time series off land cover. In the past considerable research was undertaken to increase land cover dat. The approach leverages special properties known for agricultural areas such as crop rotations or temporally static land cover classes. The newly developed IRSeL-tool (Interpolation and improvement of Remotely Sensed Land cover) corrects classification errors and interpolates missing land cover pixels. The easy -to -use tool solely requires an initial land cover data set. The IRSeL specific interpolation and revision technique, the data input requirements and data output structure are described in detail. A case study in an area around the city of Neumunster in Northern Germany from 2006 to 2012 was performed for IRSeL validation with initial land cover data sets (Landsat TM image classifications) for the years 2006, 2007, 2009, 2010 and 2011. The results of the case study showed that IRSeL performs well; including years with no classification data overall accuracy of the land cover data; overall accuracy values rise 0.08 in average resulting in overall accuracy values of at least 0.86. Considering estimated reliabilities, the IRSeL tool provides a temporally and spatially completed and revised land cover data set that allows drawing conclusions for land cover related studies.
Location: TE 15 New Biology Building
Literature cited 1: Agresti, A., 2007. An introduction to Categorical Data Analysis. Wiley Series in Probability and Statistics, Wiley-Interscience, Hoboken, New Jersey. Allan, J., Erickson, D., Fay, J., 1997. The influence of catchment land use on stream integrity across multiple spatial scales. Freshw. Biol. 37, 149-161.
Literature cited 2: Boucher, A., Seto, K., Journel, A., 2006. A novel method for mapping land cover changes: incorporating time and space with geostatistics. IEEE Trans. Geosci. Remote Sens 44, 3427-3435. Burkhard, B., Kroll, F., Nedkov, S., Muller, F., 2012. Mapping ecosystem service supply, demand and budgets. Ecol. Indic. 21, 17-29.

ID: 60083
Title: Retrieving water surface temperature from archive LANDSAT thermal infrared data: Application of the mono-channel atmospheric correction algorithm over two freshwater reservoirs.
Author: R.N. Simon, T.Tormos, P.-A.Danis.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 247-250 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Waterbodies, Remote sensing, Thermal infrared, Water surface temperature, LANDSAT 7 ETM+, Atmospheric correction, Mono-channel algorithm.
Abstract: Water surface temperature is a key element in characterizing the thermodynamics of waterbodies ,and for irregularly-shaped inland reservoirs, LANDSAT thermal infrared images are the best alternative yet for the retrieval of this parameter. However, images must be corrected mainly for atmospheric effects in order to be fully exploitable. The objective of this study is to validate the mono-channel correction algorithm for single-band thermal infrared LANDSAT data as put forward by Jimenez-Munoz et al. (2009). Two freshwater reservoirs in continental France were selected as study sites, and best use was made of all accessible image and field data. Results obtained are satisfactory and in accordance with the literature: r2 values are above 0.90 and root-mean-square error values are comprised between 1 and 2 ? C. Moreover, paired Wilcoxon signed rank tests showed a highly significant difference between field and uncorrected image data, a very highly significant difference between uncorrected and corrected image data, and no significant difference field and corrected image data. The mono-channel algorithm is hence recommended for correcting archive LANDSAT single-band thermal infrared data for inland waterbody monitoring and study.
Location: TE 15 New Biology Building
Literature cited 1: Alcantara, E.H., Stech, J.L., Lorenzzetti, J.A., Bonnet, M.P., Casamitjana, X., Assireu, A.T., Novo, E.M.L.D.M., 2010. Remote sensing of water surface temperature and heat flux over a tropical hydroelectric reservoir. Remote Sensing of Environment 114, 2651-2665. Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P. Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer,A.J., Haimberger, L., Healy, S.B., Hersbach, H., Holm, E.V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.J., Park, B.K., Peubey, C., De Rosnay, P., Tovolato, C., Thepaut.J.N., Vitatrt, F., 2011. The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Quaterly Journal of the Royal Meteorological Society 137, 533-597.
Literature cited 2: Dekker, A.G., Peters, S.W.M., 1993. The use of the Thematic Mapper for the analysis of eutrophic lakes: a case study in the Netherlands. International Journal of Remote Sensing 14, 799-821. Giardino, C., Pepe, M., Brivio, P.A., Ghezzi, P., Zilioli, E., 2001. Detecting chlorophyll, Secchi disk depth and surface temperature in a sub-alpine lake using Landsat imgery. Science of the Total Environment 268, 19-29.