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ID: 60127
Title: Leaf and canopy water content estimation in cotton using hyperspectral indices and radiative transfer models.
Author: Qiuxiang Yi, Fumin Wang, Anming Bao, Guli Jiapaer.
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. 33. 67-75 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: EWT, EWT canopy, PROSPECT-5 model, PROSPECT-5 +SAILH model, Hyperspectral vegetation indices, Cotton.
Abstract: In present study some vegetation indices for estimating leaf EWTand EWT canopy were investigated using simulations and field measurements. Leaf and canopy spectral reflectance as well as leaf EWT and EWT canopy were measured in cotton during the growing seasons of 2010 and 2011. The PROSPECT-5 model was coupled with the SAILH model to explore the performance of water -related vegetation indices for leaf EWT and EWT canopy estimation. The vegetation indices evaluated were published formulations and new simple ratio vegetation indices formulated with wavebands at 1060 nm and 1640 nm. The sensitivities of these indices to leaf internal structural N and LAI effects were assessed. Simulation results indicated that all of the water-related vegetation indices were insensitive to leaf internal structural N, with the highest coefficient of determination R2 <0.15 and the proposed index SR1640 (R1060 / R1640 ) and published index SR2 (R1070 /R 1340 ) showed the lowest relationships (R2 < 0.35) with LAI of all the vegetation indices. Furthermore, coefficients of determination between simulated leaf EWT (R2 >0.9; P<0.001) and EWT canopy (R2>0.8; P<0.001). Results obtained with field measurements were in agreement with simulation results, with the coefficient of determination R2=0.5 (P<0.001) for leaf EWT and R2 =0.57 (P<0.001) for EWT canopy by the new simple ratio indices. This study provides a new candidate for leaf EWT and EWT canopy estimation using hyperspectral vegetation indices.
Location: TE 15 New Biology Building
Literature cited 1: Aldakheel, Y.Y., Danson, F.M., 1997. Spectral reflectance of dehydrating leaves: measurements and modeling. Int.J. Remote Sens. 18, 3683-3690. Bacour, C., Jaccquemoud, S., T ourbier, Y., Dechambre, M., Frangi, J.P., 2002. Design and analysis of numerical experiments to compare four canopy reflectance models. Remote Sens. Environ. 79, 72-83.
Literature cited 2: Bowyer, P., Danson, F.M., 2004. Sensitivity of remotely sensed spectral reflectance to variation in live fuel moisture content. Remote Sens. Environ. 92, 297-308. Carlson, J.D., Burgan, R.E., 2003. Review of user needs in operational fire danger estimation: the Oklahoma example. Int. J. Remote Sens. 24, 1601-1620.

ID: 60126
Title: Mapping the alteration footprint and structural control of Taknar IOCG deposit in east of Iran, using ASTER satellite data.
Author: Khosrow Maroufi Naghadehi, Ardeshir Hezarkhani, Saeid Asadzadeh.
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. 33. 57-66 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: ASTER, Alteration, Mineral map, Match filtering, IOCG, Taknar.
Abstract: Taknar Fe + Cu ? Zn ? Pb ?Au ? Ag deposit in northeast of Iran is studied by Advanced Spaceborne Thermal Emission and Reflectance Radiometer (ASTER) reflectance and emittance data. Structural and mineralogical evidence of IOCG mineralization is mapped by visual image interpretation and spectral processing techniques. The tectonic model is consistent with an extensional zone associated with a releasing bend of right-lateral regional faults, extending about 7 km2 and encompassing all the known orebodies of Taknar. A combination of band ratio logical operator and matched filtering were used for spectral mapping, which lead to a series of mineral content and crystallinity maps included ferric oxide, ferrous, white, mica, Chlorite, silica and opaque minerals. The channel way in which hydrothermal fluids were migrating is accurately defined by abundance of white mica and ferric iron oxide maps. Rhythmic sediments of Taknar formation which was characterized by chlorite mineral map is a ?reducing? environment that hosts the mineralization. This REDOX environment is also marked by a sudden change in white mica composition from acidic phases to neutral/alkaline. Subsequent field check and microscopic study indicated the accuracy of these remotely mapped minerals. Based on this finding, several new prospects for further exploration was proposed. These results indicate that ASTER data is capable of delineating alteration footprints of an IOCG mineral system in deposit scale exploration.
Location: TE 15 New Biology Building
Literature cited 1: Abrams, M., Hook, S., 2000. ASTER User Handbook, JetPropulsion Laboratory, ASTER User ' s guide. Part 1 General (ver. 3.0) 2001. Earth Remote Sensing Data Analysis Center, http://www.ersdac.org.jp/ Adler-Golden, S.M., Matthew, M.W., Bernstein, L.S., Levine, R.Y., Berk, A., Richtsmeier, S.C., Acharya, P.K., Anderson, G.P., Felde, G., Gardner, J., Hoke, M., Jeong, L.S., Pukall, B., Ratkowski, A., Burke, H.H., 1999. Atmospheric correction for short -wave spectral imagery based on MODTRAN4. IN: SPIE Proceedings on Imaging Spectrometry, v. 3753, pp. 61-69.
Literature cited 2: Barton, M.D., 2009. IOCG Deposits: A Cordilleran Perspective. University of Arizona, Tucson, AZ. Barton, M.D., Jhonson, D.A., 2004. Footprints of Fe-oxide (-Cu-Au) systems SEG 2004 Predictive Mineral Discovery Under Cover. Centre for Global Metallogeny, Spec. pub.33. The University of Western Australia, pp. 112-116.

ID: 60125
Title: Modeling soil parameters using hyperspectral image reflectance in subtropical coastal wetlands.
Author: Naveen J.P., Anne, Amr H.Abd-Elrahman, David B.Lewis, Nicole A. Hewitt.
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. 33. 47-56 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperspectral remote sensing, Coastal wetlands, Soil properties, Particulate organic matter, Labile carbon, Labile nitrogen.
Abstract: Developing-spectral models of soils properties is an important frontier in remote sensing and soil science. Several studies have focused on modeling soil properties such as total pools of soil organic matter and carbon in bare soils. We extended this effort to model soil parameters in areas densely covered with coastal vegetation. Moreover, we investigated soil properties indicative of soil functions such as nutrient and organic matter turnover and storage. These properties include the portioning of mineral and organic soil between particulate (>53?m) and fine size classes, and the portioning of soil carbon and nitrogen pools between stable and labile fractions. Soil samples were obtained from Avicennia germinans mangrove forest and Juncus roemerianus salt marsh plots on the west coast of Central Florida. Spectra corresponding to field plot locations from Hyperion hyperspectral image were extracted and analyzed. The spectral information was regressed against the soil variables to determine the best single bands and optimal band combinations for the simple ratio (SR) and normalized difference index (NDI) indices. The regression analysis yielded levels of correlation for soil variables with R2 values ranging from 0.21 to 0.47 for best individual bands, 0.28 to 0.81 for two-band indices, and 0.53 to 0.96 for partial least-squares (PLS) regressions for the Hyperion image data. Spectral models using Hyperion data adequately (RPD> 1.4) predicted particulate organic matter (POM), silt +clay, labile carbon ?, and labile nitrogen (N) (where RPD= ratio of standard deviation to root mean square error of cross -validation [RMSECV].) The SR (0.53 ? m, 2.11 ? m) model of labile N with R2 =0.81, RMSECV=0.28, and RPD=1.94 produced the best results in this study. Our results provide optimism that remote-sensing spectral models can successfully predict soil properties indicative of ecosystem nutrient and organic matter turnover and storage, and do so in areas with dense canopy cover.
Location: TE 15 New Biology Building
Literature cited 1: Alongi, D., Trott, L., Wattayakorn, G., Clough, B., 2002. Below-ground nitrogen cycling in relation to net canopy production in mangrove forests of southern Thailand. Mar.Biol. 140 (4), 855-864. Anderson, I.C., Tobias, C.R., Neikirk, B.B., Wetzel, R.L., 1997. Development of a process-based nitrogen mass balance model for a Virginia (USA) Spartina alterniflora salt marsh: implications for net DIN flux. Mar. Ecol.Prog.Ser. 159, 13-27.
Literature cited 2: Baret, F., Guyot, G., 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens.Environ. 35 (2-3), 161-173. Bartholomeus, H., Kooistra, L., Stevens, A., van Leeuwen, M., van Wesemael, B., Ben-Dor, E., Tychon, B., 2011. Soil organic carbon mapping of partially vegetated agricultural fields with imaging spectroscopy. Int. J. Appl. Earth Obs. Geoinf. 13 (1), 81-88.

ID: 60124
Title: Predicting maize yield in Zimbabwe using dry dekads derived from remotely sensed vegetation Condition Index.
Author: Farai Kuri, Amon Murwira, Karin S. Murwira, Mhosisi Masocha
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. 33. 39-46 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Vegetation Condition Index, Dry dekads, Maize yield, SPOT Normalized Difference Vegetation, Index.
Abstract: Maize is a key crop contributing to food security in Southern Africa yet accurate estimates of maize yield prior to harvesting are scarce. Timely and accurate estimates of maize production are essential for ensuring food security by enabling actionable mitigation strategies and policies for prevention of food shortages. In this study, we regressed the number of dry dekads derived from VCI against official ground-based maize yield estimates to generate simple linear regression models for predicting maize yield throughout Zimbabwe over four seasons (2009-10, 2010-11, 2011-12 and 2012-2013). The VCI was computed using Normalized Difference Vegetation Index (NDVI) time series data set from the SPOT VEGETATION sensor for the period 1998-2013. A significant negative linear relationship between number of dry dekads and maize yield was observed in each season. The variation in yield explained by the models ranged from 75 % to 90%. The models were evaluated with official ground-based yield data that was not used to generate the models. There is a close match between the predicted yield and the official yield statistics with an error of 33 %. The observed consistency in the negative relationship between number of dry dekads and ground-based estimates of maize yield as well as the high explanatory power of the regression models suggest that VCI-derived dry dekads could be used to predict maize yield before the end of the season thereby making it possible to plan strategies for dealing with food deficits or surpluses on time.
Location: TE 15 New Biology Building
Literature cited 1: Arawal, R., Meht, S.C., 2007. Weather based forecasting of crop yields, pests and diseases-IASRI Models J.Indian Soc. Agric.Stat. 61 (2), 255-263. Casley, D.J., Kumar, K., 1988. The collection, Analysis and Use of Monitoring and Evaluation Data. Johns Hopkins University Press for the World Bank, Baltimore, MD.
Literature cited 2: Chen, J., Jonsson, P., Tamura, M., Gu, Z., Matsushita, B., Eklundh, L., 2004. A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter. Remote Sens Environ. 91 (3-4), 332-344. Chenje, M., Sola, L., Paleczny, D., 1998. The State of Zimbabwe ' s Environment 1998. Government of the Republic of Zimbabwe, Ministry of Mines, Environment and Tourism, Harare, Zimbabwe.

ID: 60123
Title: Forest cover classification using Landsat ETM+ data and time series MODIS NDVI data.
Author: Kun Jia, Shunlin Liang, Lei Zhang, Xiangqin Wei, Yunjun Yao, Xianhong Xie.
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. 33. 32-38 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Forest cover, Classification, Time series NDVI data, Remote sensing, Fusion.
Abstract: Forest cover plays a key role in climate change by influencing the carbon stocks, the hydrological cycle and the energy balance. Forest cover information can be determined from fine-resolution data, such as Landsat Enhanced Thematic Mapper Plus (ETM+). However, forest cover classification with fine-resolution data usually uses only one temporal data because successive data acquirement is difficult. It may achieve mis-classification result without involving vegetation growth information, because different vegetation types may have the similar spectral features in the fine-resolution data. To overcome these issues, a forest cover classification method using Landsat ETM+ data appending with time series Moderate -resolution Imaging-Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data was proposed. The objective was to investigate the potential of temporal features extracted from coarse-resolution time series vegetation index data on improving the forest cover classification accuracy using fine-resolution remote sensing data. This method firstly fused Landsat ETM+ NDVI and MODIS NDVI data to obtain time series fine-resolution NDVI data, and then the temporal features were extracted from the fused NDVI data. Finally, temporal features combined with Landsat ETM+ spectral data was used to improve forest cover classification accuracy using supervised classifier. The study in North China region confirmed that time series NDVI features had significant effects on improving forest cover classification accuracy of fine resolution remote sensing data. The NDVI features extracted from time series fused NDVI data could improve the overall classification accuracy approximately 5 % from 88.99 % to 93.88 % compared to only using single Landsat ETM+ data.
Location: TE 15 New Biology Building
Literature cited 1: Barthlome, E., Belward, A.S., 2005. GLC2000: a new approach to global land cover mapping from Earth observation data. Int. J. Remote Sens. 26, 1959-1977. Bonan, G.B., 2008.Forests and climate change: forcings, feedbacks, and the climate benefits of forests. Science 320, 1444-1449.
Literature cited 2: Brown, J.C., Kastens, J.H., Coutinho, A.C., Victoria, D.D., Bishop, C.R., 2013. Classifying multiyear agricultural land use data from Mato Grosso Using time-series MODIS vegetation index data. Remote Sens. Environ. 130, 39-50. Caplow, S., Jagger, P., Lawlor, K., Sills, E., 2011. Evaluating land use and livelihood impacts of early forest carbon projects: lessons for learning about REDD.Environ. Sci.Policy 14, 152-167.

ID: 60122
Title: Coupling potential of ICES at/GLAS and STRM for the discrimination of forest landscape types in French Guiana.
Author: I.Fayad, N.Baghdadi, V.Gond, J.S. Bailly, N.Barbier, M.El Hajj, F. Fabre.
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. 33. 21-31 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: SRTM DEM, ICESat/GLAS, Tropical forest, French Guiana.
Abstract: The Shuttle Radar Topography Mission (SRTM) has produced the most accurate nearly global elevation dataset to date. Over vegetated areas, the measured SRTM elevations are the result of a complex interaction between radar waves and tree crowns. In this study, waveforms acquired by the Geoscience Laser Altimeter System (GLAS) were combined with SRTM elevations to discriminate the five forest landscape types (LTs) in French Guiana. Two differences were calculated: (1) penetration depth, defined as the GLAS highest elevations minus the SRTM elevations and (2) the GLAS centroid elevations minus the SRTM elevations. The results show that these differences were similar for the five LTs, and they increased as a function of the GLAS canopy height and of the SRTM roughness index. Next, a Random Forest (RF) classification was used to analyze the coupling potential of GLAS and SRTM in the discrimination of forest landscape types in French Guiana. The parameters used in the RF classification were the GLAS canopy height, the SRTM roughness index, the difference between the GLAS centroid elevations and the SRTM elevations. Discrimination of the five forest landscape types in French Guiana was possible, with an overall classification accuracy of 81.3 % and a kappa coefficient of 0.75. All forest LTs were well classified with an accuracy varying from 78.4 % to 97.5%. Finally, differences of near coincident GLAS waveforms, one from the wet season and one from the dry season, were analyzed. The results showed that the open forest (LT (LT12), in some locations, contains trees that loose leaves during the dry season. These trees allow LT12 to be easily discriminated from the other LTs that retain their leaves using the following three criteria: (1) difference between the GLAS centroid elevations and the SRTM elevations, (2) ratio of top energy in the wet season to top energy in the dry season, or (3) ratio of ground energy in the wet season to ground energy in the dry season.
Location: TE 15 New Biology Building
Literature cited 1: Addo-Fordjour, P., Rahmad, Z.B., 2013. Mixed species allometric models for estimating above-ground liana biomass in tropical primary and secondary forests, Ghana.ISRN Forestry Vol. 2013, Article ID 153587. Ali, S.S., Dare, P., Jones, S.D., 2008. Fusion of remotely sensed multispectral imagery and Lidar data for forest structure assessment at the tree level. ISPRS Proceedings, Beijing XXXVII, B7.
Literature cited 2: Baghdadi, N., le Maire, G., Fayad, I., Bailly, J.S., Nouvellon, Y., Lemos, C., Hakamada, R., 2014. Testing different methods of forest height and aboveground biomass estimations from ICESat/GLAS data in Eucalyptus plantations in Brazil. IEEE-JSTARS 7, 290-299. Bartholome, E., Belward, A., Beuchle, R., Eva, H., Fritz, S., Hartley, A., Mayaux, P., Stibig, H.J., 2004. Global land cover for the year 2000, landcover classification produced with data acquired in 2000 from the VEGETATION instrument, onboard the SPOT-4 satellite, 1/25.500.000 scale map. In: European Commission, LB-55-03-099-ENC.

ID: 60121
Title: Atmospheric effects on the performance and threshold extrapolation of multi-temporal Landsat derived dNBR for burn severity assessment.
Author: Lei Fang, Jian Yang.
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. 33. 10-20 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Burn severity, Landsat, dNBR, Optimality, Atmospheric correction, Chinese boreal forest.
Abstract: The Landsat derived differenced Normalized Burn Ratio (dNBR) is widely used for burn severity assessments. Studies of regional wildfire trends in response to climate change require consistency in dNBR mapping across multiple image dates, which may vary in atmospheric condition. Conversion of continuous dNBR images into categorical burn severity maps often requires extrapolation of dNBR thresholds from present fires for which field severity measurements such as Composite Burn Index (CBI) data are available, to historical fires for which CBI data are typically unavailable. Although differential atmospheric effects between image collection dates could be lead to biased estimates of historical burn severity patterns, little is known concerning the influence of atmospheric effects on dNBR performance and threshold extrapolation. In this study, we compared the performance of dNBR calculated from six atmospheric correction methods using an optimality approach. The six correction methods included one partial (Top of atmosphere reflectance, TOA), two absolute, and three relative methods. We assessed how the correction methods affected the CBI-dNBR correlation and burn severity mapping in a Chinese boreal forest fire which occurred in 2010. The dNBR thresholds of the 2010 fire for each of the correction methods were then extrapolated to classify a historical fire from 2000. Classification accuracies of threshold extrapolations were assessed based on Cohen ' s Kappa analysis with 73 field-based validation plots. Our study found most correction methods improved mean dNBR optimality of the two fires. The relative correction methods generated 32 % higher optimality than both TOA and absolute correction methods. All the correction methods yielded high CBIdNBR correlations (mean R2 =0.847) but distinctly different dNBR thresholds for severity classification of 2010 fire. Absolute correction methods could substantially increase optimality score, but were insufficient to provide a consistent scale of radiometric condition between multi-temporal Landsat images, which resulted in lower severity classification accuracies (Kappa=0.53) than those relative correction methods (Kappa =0.72) for the 2000 fire. Consistent radiometric response in remote sensing datasets proved essential for accuracy in regional burn severity trends monitoring Extrapolation of empirical dNBR thresholds to historical conditions without relative normalization will likely lead to biased burn severity classifications.
Location: TE 15 New Biology Building
Literature cited 1: Allen, J.L., Sorbel, B., 2008. Assessing the differenced Normalized Burn Ratio ' s ability to map burn severity in the boreal forest and tundra ecosystems of Alaska ' s national parks. IJWF 17, 463-475. Bobbe, T., Finco, M.V., Quayle, B., Lannom, K., Sohlberg, R., Parsons, A., 2001. Field measurements for the training and validation of burn severity maps from space-borne, remotely sensed imagery. USDI Joint Fire Science Program Final Project Report JFSP RFP.
Literature cited 2: Boby, L.A., Schuur, E.A.G., Mack, M.C., Verbyla, D., Jhonstone, J.F., 2010. Quantifying fire severity, carbon, and nitrogen emissions in Alaska ' s boreal forest. Ecol.Appl.20, 1633-1647. Cai, W., Yang, J., Liu, Z., Hu, Y., Weisberg, P.J., 2013. Post-fire tree recruitment of a boreal larch forest in Northeast China.For.E col.Manage. 307, 20-29.

ID: 60120
Title: Alerts of forest disturbance from MODIS imagery.
Author: Dan Hammer, Robin Kraft, David Wheeler.
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. 33. 1-9 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Deforestation, MODIS, Time series, Parallel processing, Cloud computing.
Abstract: This paper reports the methodology and computational strategy for a forest cover disturbance alerting system. Analytical techniques from time series econometrics are applied to imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to detect temporal instability in vegetation indices. The characteristics from each MODIS pixel ' s spectral history are extracted and compared against historical data on forest cover loss to develop a geographically localized classification rule that can be applied cross the humid tropical biome. The final output is a probability of forest disturbance for each 500m pixel that is updated every 16 days. The primary objective is to provide high-confidence alerts of forest disturbance, while minimizing false positives. We find that the alerts serve this purpose exceedingly well in Para, Brazil, with high probability alerts garnering a user accuracy of 98 percent over the training period and 93 percent after the training period (2000-2005) when compared against the PRODES deforestation data set, which is used to assess spatial accuracy. Implemented in Clojure and Java on the Hadoop distributed data processing platform, the algorithm is a fast, automated, and open source system for detecting forest disturbance. It is intended to be used in conjunction with higher-resolution imagery and data products that cannot be updated as quickly as MODIS-based data products. By highlighting hotspots of change, the algorithm and associated output can focus high-resolution data acquisition and aid in efforts to enforce local forest conservation efforts.
Location: TE 15 New Biology Building
Literature cited 1: Anderson, L., Shimabukuro, Y., DeFries, R., Morton, D., 2005. Assessment of deforestation in near real time over the Brazilian Amazon using multitemporal fraction images derived from terra MODIS. IEEE Geosci. Remote Sens.Lett. 2, 315-318. Asner, G.P., Powell, G.V.N., Mascaro, J., Knapp, D.E., Clark, J.J., Jacobson, J., Kennedy-Bowdoin, T., Balaji, A., Paez-Acosta, G., Victoria, E., Secada, L., Valqui, M., Hughes, R.F., 2010. High-resolution forest carbon stocks and emissions in the Amazon.Proc. Natl.Acad.Sci. 107, 16738-16742.
Literature cited 2: Bonifaz-Alfonzo, R., 2011. Assessing Seasonal Features of Tropical Forests Using Remote Sensing. Technical Report. University of Nebraska-Lincoln. Broich, M., Hansen, M.C., Potapov, P.V., Adusei, B., Lindquist, E., Stehman, S.V., 2011. Time-series analysis of multi-resolution optical imagery for quantifying forest cover loss in Sumatra and Kalimantan, Indonesia.Int.J.Appl.Earth Observ. Geoinform. 13, 277-291.

ID: 60119
Title: Yield estimation using SPOT-VEGETATION products: A case study of wheat in European countries.
Author: Wanda Kowalik, Katarzyna Dabrowska-Zielinska, Michele Meroni, Teresa Urszula Raczka, Allard de Wit.
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. 32. 228-239 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Yield forecasting, Wheat, Remote sensing, Crop simulations models: European scale.
Abstract: In the Period 1999-2009 ten day SPOT-VEGETATION products of the Normalized Difference Vegetation Index (NDVI) and Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) at 1 km spatial resolution were used in order to estimate and forecast the wheat yield over Europe. The products were used together with official wheat yield statistics to fine-tune a statistical model for each NUTS2 region, based on the Partial Least Squares Regression (PLSR) method. This method has been chosen to construct the model in the presence of many correlated predictor variables (10-day values of remote sensing indicators) and a limited number of wheat yield observations. The model was run in two different modalities: the ?monitoring mode?, which allows for an overall yield assessment at the end of the growing season, and the ?forecasting mode?, which provides early and timely yield estimates when the growing season is on-going. Performances of yield estimation at the regional and national level were compared with those of a reference crop growth model. Models based on either NDVI or FAPAR normalized indicators achieved similar results with a minimal advantage of the model based on the FAPAR product. Best modeling results were obtained for the countries in Central Europe (Poland, North-Eastern Germany) and also Great Britain. By contrast, poor model performances characterize countries as follows: Sweden, Finland, Ireland, Portugal, Romania and Hungary. Country level yield estimates using the PLSR model in the monitoring mode, and those of a reference crop growth model that do not make use of remote sensing information showed comparable accuracies. The largest estimation errors were observed n Portugal, Spain and Finland for both approaches. This convergence may indicate poor reliability of the official yield statistics in these countries.
Location: TE 15 New Biology Building
Literature cited 1: Atzberger, C., 2013. Advances in remote sensing of agriculture: context description, existing operational monitoring systems and major information needs. Remote Sens. 5 (2), 949-981, http://dx.doi.org/10.3390/rs5020949. Atzberger, C., Rembold, F., 2013. Mapping the spatial distribution of winter crops at sub-pixel level using AVHRR NDVI time series and neural nets. Remote Sens. (Basel) 5 (3), 1335-1354.
Literature cited 2: Balaghi, R., Tychon, B., Eerens, H., Jlibene, M., 2008. Empirical regression models using NDVI, rainfall and temperature data for the early prediction of wheat grain yied in Morocco.Int.J.Appl.Earth Obs.Geoing.10, 438-452. Baret, F., Morisette, J., Fernandes, R.A., Champeaux, J.L., Myneni, R.B., Chen, J., Plumer, S., Weiss, M., Bacour, C ., Garrigues, S., Nickeson, J.E., 2006. Evaluation of the representativeness of networks of sites for the global validation and intercomparison of land biophysical products: proposition of the CEOS-BELMANIP. IEEE Trans.Geosci.Remote Sens. 44 (7), 1794-1803.

ID: 60118
Title: Monitoring of the risk of farmland abandonment as an efficient tool to assess the environmental and socio-economic impact of the common Agriculture policy.
Author: Pavel Milenov, Vassil Vassilev, Anna Vassileva, Radko Radkov, Vessela Samoungi, Zlatomir Dimitrov, Nikola Vichev.
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. 32. 218-227 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: CAP, CIS, Farmland abondment, LPIS, OBIA, Biophysical parameters.
Abstract: Farmland abandonment (FLA) could be defined as the cessation of agricultural activities on a given surface of land (Pointereau et al, 2008). FLA, often associated with social and economic problems in rural areas, has significant environmental consequences. During the 1990s, millions of hectares of farmland in the new EU Member States, from Central and Eastern Europe, were abandoned as a result of the transition process from centralized and planned to market economy. The policy tools adopted gradually within the Common Agricultural Policy of the European Union (EUCAP), as well as the EU environmental and structural policies, aimed to prevent further expansion of this phenomenon and to facilitate the revival of the agriculture land, being abandoned (ComReg 1122/2009). The Agri-Environment (AGRI-ENV) component of the Core Information Service (CIS), developed within the scope of the FP7-funded project ?geoland 2? were designed to support the agricultural user community at pan-European and national levels by contributing to the improvement of more accurate and timely monitoring of the status of agricultural land in use in Europe and its change. The purpose of the product ?Farmland abandonment: as part of the AGRI-ENV packages, is to detect potentially abandoned agriculture land, based on multi-annual SPOT data with several Acquisitions per year. It provides essential independent information on the status of the agriculture land as recorded in the LandParcel Identification System (LPIS), which is one of the core instruments of the implementation of CAP. The production line is based on object-based image analysis and benefits from the extensive availability of Biophysical parameters derived from the satellite data (geoland 2). The method detects/ tracks those land (or so-called reference) parcels in the LPIS, holding significant amount of land agriculture found as potentially abandoned. Reference parcels with such change are flagged and reported, enabling the National Administration to further analyze the spatial distribution and magnitude of this phenomena at regional and national levels. Test results have been successfully generated for one test area (the Bulgarian part of the Strymunas -Strauma River Basin).
Location: TE 15 New Biology Building
Literature cited 1: Bicheron, P., Panagos, P., Pedroli, B., Hazeu, G., Wascher, D., Karyda, C., Gitas, I., Pros-peri, P., Erdogan, E.H., Vassilev, V., 2012. Towards an Operational GMES Land Monitoring Core Service- AgriEnv Service Summary, geoland 2. Commission Regulation (EC) No1122/2009 0f 30 November 2009 laying down detailed rules for the implementation of Council Regulation (EC) No. 73/2009.
Literature cited 2: Council Regulation (EC) No. 73/2009 as regards cross-compliance, modulation and the integrated administration and control system, under direct support schemes for farmers, amending Regulations (EC No. 1290/2005, (EC) No. 247/2006, (EC) No. 378/2007 and repealing Regulation (EC) No. 1782/2003. Development of agri-environmental indicators for monitoring the integration of environmental concerns in to the common agricultural policy, {SEC (2006) 1136}, COM (2006) 508 final, Brussels.

ID: 60117
Title: Application and evaluation of topographic correction methods to improve land cover mapping using object-based classification.
Author: Eder Paulo Moreira, Marcio Morisson Valeriano.
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. 32. 208-217 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Topographic effect, Landsat, SRTM, Classification accuracy, Landcover classification, Radiometric correction.
Abstract: This study applies and evaluates topographic correction methods to reduce radiometric variation due to topography characteristics in rugged terrain. The aim of this study was to improve the capability of satellite images to generate more reliable land cover mapping using object-based classification. Several semi-empirical correction methods, which require the estimation of empirically defined parameters, were selected for this study. Usually, these parameters are estimated relying on a previous land cover map. However, in this work the correction methods were applied considering the unavailability of a previous land cover map and the ease for implementation, so the main land cover type was used to estimate correction parameters to be applied to correct all land cover type. Landsat 5 TM image and topographic data derived from SRTM (Shuttle Radar Topography Mission) over an area located in an agricultural region of southeastern Brazil were used. Land cover classification was carried out using an object-based approach, which includes image segmentation and decision tree classification. The evaluation of topo-graphic correction methods was based on: spectral characteristics expressed by standard deviation and mean values of spectral data within land cover classes; relationship between spectral data and solar illumination angle on the slope (cosi); object (segment) mean size; decision tree structure; visual analysis; and classification accuracy. Results show that the standard deviation of spectral data and correlation between spectral values and cosi decreased after data correction, but not for all methods for some of the tested TMbands. The methods herein referred as Cosine, S1, Ad2S and SCS methods showed to increase the standard deviation and the correlation compared to the uncorrected data, mainly for bands 1, 2 and 3. Object mean size, in general, decreased after correction, except for C method. The effect on the object size showed to be related to a calculated standard deviation of adjacent pixels values. The decision tree structure given by the number of leaves also decreased after correction. The C, SCS+C and Minnaert methods showed the highest performance, followed by S2 and E-Stat, with a general accuracy increase around 10 %. Land cover classification from uncorrected and corrected data differed in a large portion of the total studied area, with values around 29% for all correction methods.
Location: TE 15 New Biology Building
Literature cited 1: ASTER GDEM Validation Team, 2009. ASTER Global DEM Validation. Baatz, M., Schape, A., 2000. Multiresolution segmentation: an optimization approach for high quality multi-scale image segmentation. In: Proceedings of the 12th Angewandte geographische Informationverarbeitung, Heidelberg, Germany, pp. 2-23.
Literature cited 2: Balthazar, V., Vanacker, V., Lambin, E.F., 2012. Evaluation and parameterization of ACTOR 3 topographic correction method for forest cover mapping in mountain areas. Int. J. Appl. Earth Observ. Geoinform. 18, 436-450, http://dx.doi.org/10.1016/j.isprsjprs.2003.10.002. Bishop, M.P., Colby, J.D., 2002. Anisotropic reflectance correction of SPOT-3 HRV imagery. Int. J. Remote Sens.23 (10) , 2125-2131, http://dx.doi.org/10.1080/01431160110097231.

ID: 60116
Title: Lithology-controlled subsidence and seasonal aquifer response in the Bandung basin, Indonesia, observed by synthetic aperture radar interferometry.
Author: Mokhamad Yusup Nur Khakim, Takeshi Tsuji, Toshifumi Matsuoka.
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. 32. 199-207 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Groundwater extraction, Subsidence characterization, DInSAR, IPTA, Seasonal variation.
Abstract: Land subsidence in the Bandung basin, West Java, Indonesia, is characterized based on differential interferometric synthetic aperture radar (DInSAR) and interferometric point target analysis (IPTA). We generated interferograms from 21 ascending SAR images over the period 1 January 2007 to 3 March 2011. The estimated subsidence history shows that subsidence continuously increased reaching a cumulative 45 cm during this period, and the linear subsidence rate reached ~12 cm/yr. This significant subsidence occurred in the industrial and densely populated residential regions of the Banding basin where large amounts of groundwater are consumed. However, in several areas the subsidence patterns do not correlate wih the distribution of groundwater production wells and mapped aquifer degradation. We conclude that groundwater production controls subsidence, but lithology is a counteracting factor for subsidence in the Bandung basin. Moreover, seasonal trends of nonlinear surface deformations are highly relate with the variation of rainfall. They indicate that there is elastic expansion (rebound) of aquifer system response to seasonal-natural recharge during rainy season.
Location: TE 15 New Biology Building
Literature cited 1: Abidini, H.Z., Andreas, H., Gamal, M., Wirakusumah, A.D., Darmawan, D., Deguchi, T., Maruyama, Y., 2008. Land subsidence characteristics of the Bandung basin, Indonesia, as estimated from GPS and InSAR.J.Appl.Geodesy 2(3), 167-177, http://dx.doi.org/10.1515.JAG.2008.019 Amelung, F., Galloway, D.L., Bell, J.W., Zebker, H.A., Laczniak, R.J., 1999. Sensing the ups and downs of LAS Vegas: InSAR reveals structural control of land subsidence and aquifer-system deformation. Geology 27, 483-486.
Literature cited 2: Bell, J.W., Amelung, F., Ferretti, A., Bianchi, M., Novali, F., 2008. Permanent scatterer InSAR reveal seasonal and long-term aquifer-system response to groundwater pumping and artificial recharge. Water Resour. Res. 44 (WO2407), 1-18, http://dx.doi.org/10.1029/2007WR006152. Bitelli, G., Bonsignore, F., Unguendoli, M., Novali, F., 2008. Permanent scatterer InSAR reveal seasonal and long-term aquifer-system response to groundwater pumping and artificial recharge. Water Resour. Res. 44 (W02407), 1-18, http://dx.doi.org/10.1029/2007WR006152.

ID: 60115
Title: Retrieval of Wheat leaf area index from AWiFS multispectral data using canopy radiative transfer simulation.
Author: Rahul Nigam, Bimal K. Bhattacharya, Swapnil Vyas, Markand P.Oza.
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. 32. 173-185 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: LAI retrieval, Canopy radiative transfer, Satellite, Crop.
Abstract: Accurate representation of leaf area index (LAI) from high resolution satellite observations is obligatory for various modelling exercises and predicting the precise farm productivity. Present study compared the retrieval transfer (CRT) method and using four vegetation indices (VI) (e.g. NDVI, NDWI, RVI and GNDVI) to estimate the wheat LAI. Reflectance observations available at very high (56 m) spatial resolution from Advanced Wide-Field Sensor (AwiFS) sensor onboard Indian Remote Sensing (IRS), P6, Resources-1 satellite was used in this study. This study was performed over two different wheat growing regions, situated in different agro-climatic settings/environments: Trans-Gangetic Plain Region, (TGPR) and Central Plateau and Hill Region (CPHR). Forward simulation canopy reflectances in four AWiFS bands viz. green (0.52-0.59 ?m), red (0.62.0.68 ?m), NIR (0.77-0.86 ?m) and SWIR (1.55-1.70 ?m) were carried out to generate the look up table (LUT) using CRT model PROSAIL from all combinations of canopy intrinsic variables. An inversion technique based on minimization of cost function was used to retrieve LAI from LUT and observed AWiFS surface reflectances. Two consecutive wheat growing seasons (November 2005-March 2006 and November 2006-March 2007) datasets were used in this study. The empirical models were developed from first season data and second growing season data used for validation. Among all the models, Lai-NDVI empirical model showed the least RMSE (root mean square error) of 0.54 and 0.51 in both agro-climatic regions respectively. The comparison of PROSAIL.retrieved LAI with in situ measurements of 2006-2007 over the two agro-climatic regions produced substantially less RMSE of 0.34 and 0.41 having more R? of 0.91 and 0.95 for TGPR and CPHR respectively in comparison to empirical models. Moreover, CRT retrieved LAI had less value of errors in all the LAI classes contrary to empirical estimates. The PROSAIL based retrieval has potential for operational implementation to determine the regional crop LAI and can be extendible to other regions after rigorous validation exercise.
Location: TE 15 New Biology Building
Literature cited 1: Allen, W.A., Gausman, H.W., Richardson, A.J., Thomas, J.R., 1969. Interaction of isotropic light with a compact plant leaf. J.Opt.Soc.Am. 59, 1376-1379. Asner, G.P., 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens.Environ. 64, 234-253.
Literature cited 2: Barker, D.M., Huang, W., Guo, Y.R., Bourgeois, A.J., Xiao, Q.N., 2004. A three dimensional variational data assimilation system for MM5: implementation and initial results. Mon. Weather Rev. 132, 897-914. Baret, F., Guyot, G., 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environment, 35, 161-173.

ID: 60114
Title: The use of motor-glider in topoclimatic studies.
Author: Marta Kubiak, Alfred Stach.
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. 32. 186-198 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Motor-glider, Thermal remote sensing, Thermovision camera, Land surface temperature (LST).
Abstract: This paper reports on the advantages and disadvantages of motor-glider use in studying topoclimates. Despite the widespread use of images taken from low-altitude flying platforms (planes, helicopters, UAVs), the use of a motor-glider for imagery collection has not been reported in environmental studies. In presented study, the low-altitude remote sensing techniques were used to increase the spatial resolution of thermal maps derived from Landsat ETM+ thermal bands. Thermal images from motor glider were taken by a thermovision camera. At the local scale, landsurface temperature (LST) is one of the factors influencing topoclimatic diversity hence, by analysing LST distribution one can determine topoclimatic variability. Topoclimate has been the subject of previous studies, however, they have not used thermal remote sensing in the research process but instead relied on ground measurement network. The presented research contributes to better understanding of the thermal environment of the Earth by employing an innovative data collection method suitable for relatively large areas under specific weather conditions. The data collection with motor glider offers good spatial resolution of less 1m and facilitates the compilation of good quality LST maps. The paper discusses the influence of spatial resolution on LST variability and demonstrates again information granularity resulting from sub-meter resolution of collected data.
Location: TE 15 New Biology Building
Literature cited 1: Amarsaikhan, D., Ganzori, M., Tae-heon, Moo., 2005. Investigation of urban temperature changes using multitemporal thermal infrared images. In: 26th Asian Conference on Remote Sensing and 2nd Asian Space Conference ACRS2005, Hanoi, Vietnam. Bakker, W.H., 2004. Principles of Remote Sensing. The International Institute for Geo-Information Science and Earth Observation (ITC), The Netherlands.
Literature cited 2: Bendell, L.I., Wan, P.C.Y., 2011. Application of aerial photography in combination with GIS for coastal management at small spatial scales: a case study of shellfish aquaculture. J. Coast. Conservat. 15, 417-431. Berni, J., Zarco-Tejada, P.J., Suarez, L., Fereres, E., 2009. Thermal and narrowband multispectral remote sensing for vegetation from an unmanned aerial vehicle, Geoscience and Remote sensing for vegetation from an unmanned aerial vehicle, Geoscience and Remote Sensing. IEEE Trans. 47 (3), 722-738.

ID: 60113
Title: Retrieval of Wheat leaf area index from AWiFS multispectral data using canopy radiative transfer simulation.
Author: Rahul Nigam, Bimal K. Bhattacharya, Swapnil Vyas, Markand P.Oza.
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. 32. 173-185 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: LAI retrieval, Canopy radiative transfer, Satellite, Crop.
Abstract: Accurate representation of leaf area index (LAI) from high resolution satellite observations is obligatory for various modelling exercises and predicting the precise farm productivity. Present study compared the retrieval transfer (CRT) method and using four vegetation indices (VI) (e.g. NDVI, NDWI, RVI and GNDVI) to estimate the wheat LAI. Reflectance observations available at very high (56 m) spatial resolution from Advanced Wide-Field Sensor (AwiFS) sensor onboard Indian Remote Sensing (IRS), P6, Resources-1 satellite was used in this study. This study was performed over two different wheat growing regions, situated in different agro-climatic settings/environments: Trans-Gangetic Plain Region, (TGPR) and Central Plateau and Hill Region (CPHR). Forward simulation canopy reflectances in four AWiFS bands viz. green (0.52-0.59 ?m), red (0.62.0.68 ?m), NIR (0.77-0.86 ?m) and SWIR (1.55-1.70 ?m) were carried out to generate the look up table (LUT) using CRT model PROSAIL from all combinations of canopy intrinsic variables. An inversion technique based on minimization of cost function was used to retrieve LAI from LUT and observed AWiFS surface reflectances. Two consecutive wheat growing seasons (November 2005-March 2006 and November 2006-March 2007) datasets were used in this study. The empirical models were developed from first season data and second growing season data used for validation. Among all the models, Lai-NDVI empirical model showed the least RMSE (root mean square error) of 0.54 and 0.51 in both agro-climatic regions respectively. The comparison of PROSAIL.retrieved LAI with in situ measurements of 2006-2007 over the two agro-climatic regions produced substantially less RMSE of 0.34 and 0.41 having more R? of 0.91 and 0.95 for TGPR and CPHR respectively in comparison to empirical models. Moreover, CRT retrieved LAI had less value of errors in all the LAI classes contrary to empirical estimates. The PROSAIL based retrieval has potential for operational implementation to determine the regional crop LAI and can be extendible to other regions after rigorous validation exercise.
Location: TE 15 New Biology Building
Literature cited 1: Allen, W.A., Gausman, H.W., Richardson, A.J., Thomas, J.R., 1969. Interaction of isotropic light with a compact plant leaf. J.Opt.Soc.Am. 59, 1376-1379. Asner, G.P., 1998. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sens.Environ. 64, 234-253.
Literature cited 2: Barker, D.M., Huang, W., Guo, Y.R., Bourgeois, A.J., Xiao, Q.N., 2004. A three dimensional variational data assimilation system for MM5: implementation and initial results. Mon. Weather Rev. 132, 897-914. Baret, F., Guyot, G., 1991. Potentials and limits of vegetation indices for LAI and APAR assessment. Remote Sens. Environment, 35, 161-173.