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.
ID: 60112
Title: Using airborne hyperspectral data to characterize the surface pH and mineralogy of pyrite mine tailings.
Author: N. Zabcic, B. Rivard, C. Ong, A. Mueller.
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. 152-162 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Mine tailings, Hyperspectral, Mineral maps, pH, Sulfates, Oxides.
Abstract: Acid mine drainage (AMD) is a key concern of the mining industry due to its impact on the quality of water and soils surrounding mine waste deposits. Acid mine drainage derives from the oxidation of metal sulphides, e.g. pyrite (FeS2), exposed to oxygen and water. The leachate acidity is capable of releasing heavy metals contained in the mining waste rock, which can affect water quality and lead to metal enrichment in sediments and potentially resulting in ecosystem degradation. Predicting tailings leachate pH is key to the management of sulfide-bearing mine wastes and is an emerging remote sensing application with limited studies having been realized. Such a capability would supplement traditional methods (i.e. ground surveys) that are challenging to implement due to the extent and large volume of mine waste.
This study reports regional scale tailings mineral maps generated from airborne hyperspectral information of the Sotiel-Migollas complex in Spain and pinpoints sources of AMD. The extraction of spectral endmembers from imagery revealed twenty six endmembers for tailings material that represent mostly mineral mixtures. From these, eleven spectral groups were defined, each encompassing minor variations in mineral mixtures. The mineral maps resulting from the use of these endmembers for the detailed investigation of four tailings serve as indicators of the metal, sulphate, and ph levels of the AMD solution at the time of mineral precipitation. Predicted mineralogy was assessed using spectra from samples collected in the field and associated X-ray diffraction measurements.
We also discuss the relative merits of the minerals maps of this study and soil leachate pH maps that predictions consistent with the mineralogy predicted from the mineral maps and field and laboratory evidence. The pH maps offer information on the pH conditions of the tailings thus giving an insight on the different types of oxidation reactions that may occur.
Location: TE 15 New Biology Building
Literature cited 1: Bachmann, M., (PhD dissertation thesis) 2007. Automated MESMA Unmixing for Fractional Cover Estimates. University of Wurzburg, Wurzburg, Germany.
Bigham, J.M., 1994. Mineralogy of ochre deposits formed by sulfide oxidation. In: Blowes, J.L., J.A.D.W. (Ed), Environmental Geochemistry of Sulfide Mine-Wastes, Short Course Handbook. Mineral Association of Canada, pp. 103-132.
Literature cited 2: Briard, J., 1976. L ' age de bronze en Europe Barbare. Hesperides Publications, Paris, pp. 81-86.
Cloutis, E.A., Hawthrone, F., Mertzman, S., Krenn, K. Craig, M., Marcino, D., Methot, M., Strong, J., Mustard, J., Blaney, D., Bell III, J., Vilas, F., 2006. Detection and discrimination of sulfate minerals using reflectance spectroscopy. Icarus 184 (1), 121-157.
ID: 60111
Title: Jeffries Matusita based mixed-measure for improved spectral matching in hyperspectral image analysis.
Author: S.Padma, S.Sanjeevi.
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. 138-151 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Spectral matching, Hyperspectral image, Jeffries-Matusita, Spectral Angle Mapper, Classification.
Abstract: This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9 % and 91.47% accuracy compared to 73.13 %, 79.41 %, and 85.69 % of minimum-distance, SAM and JM measures.
It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands).
Location: TE 15 New Biology Building
Literature cited 1: Andreoli, G., Bulgarelli, B., Hosgood, B., Tarchi, D., 2007. Hyperspectral Analysis of Oil and Oil-impacted Soils for Remote Sensing Purposes. EUR 22739 EN-DF Joint Research Centre. Office for Official Publications of the European Communities, Scientific and Technical Research series, Luxembourg, 34 pp.
Ajithkumar, T.T., Thangaradjou, T., Kannan, L., 2008. Spectral reflectance properties of mangrove species of the Muthupettai mangrove environment, Tamil Nadu. J. Environ. Biol. 29, 785-788.
Literature cited 2: Bruzzone, L., Roli, F., Serpico, S.B., 1995. An extension of the jeffreys-Matusita distance to multiclass cases for feature selection. IEEE Trans. Geosci. Remote Sens. 33, 1318-1321.
Cantero, M.C., Perez, R., Martinez, P., Aguilar, P.L., Plaza, J., Plaza, A., 2004. Analysis of the behavior of a neural network model in the identification and quantification of hyperspectral signatures applied to the determination of water quality. In: SPIE Optics East Conference, Chemical and Biological Standoff Detection, Philadelphia, PA.
ID: 60110
Title: Automated road markings extraction from mobile laser scanning data.
Author: Pankaj Kumar, Conor P. McElhinney, Paul Lewis, Timothy McCarthy,
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. 125-137 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Road markings, Mobile laser scanning, LiDAR, Automation, Extraction.
Abstract: Road markings are used to provide guidance and instruction to road users for safe and comfortable driving. Enabling rapid, cost effective and comprehensive approaches to the maintenance of route networks can be greatly improved with detailed information about location, dimension and condition of road markings. Mobile Laser Scanning (MLS) systems provide new opportunities in terms of collecting and processing this information. Laser scanning systems enable multiple attributes of the illuminated targeted to be recorded including intensity data. The recorded intensity data can be used to distinguish the road markings from other road surface elements due to their higher retro-reflective property. In this paper, we present an automated algorithm for extracting road markings from MLS data. We describe a robust and automated way of applying a range dependent thresholding function to the intensity values to extract road markings. We make novel use of binary morphological operations and generic knowledge of the dimensions of road markings to complete their shapes and remove other road surface elements introduced through the use of thresholding. We present a detailed analysis of the most applicable values required for the input parameters involved in our algorithm. We tested our algorithm on different road sections consisting of multiple distinct types of road markings. The successful extraction of these road markings demonstrates the effectiveness of our algorithms.
Location: TE 15 New Biology Building
Literature cited 1: Barber, D., Mills, J., Smithvoysey, S., 2008. Geometric validation of a ground-based mobile laser scanning system. ISPRS J. Photogram. Rem. Sens, 63 (1), 128-141.
Butler, D.A., 2011. Using GIS to automate the extraction of road markings for route corridor analysis. National University of Ireland Maynooth, pp. 1-78 (M.Sc. Dissertation).
Literature cited 2: Cahalane, C., Mccarthy, T., McElhinney, C.P., 2012. MIMIC: mobile mapping point density calculator. In: Proceedings of 3rd International Conference on Computing for Geospatial Research and Appications, Washington, 1-3 July, pp. 15: 1- 15: 9.
Cahalane, C., McElhinney, C.P., McCarthy, T., 2011. Calculating the effect of dual-axis scanner rotations and surface orientation on scan profiles. In: Proceedings of 7th International Symposium on Mobile Mapping Technology. Krakow, 13-16 June.
ID: 60109
Title: Detecting leaf nitrogen content in wheat with canopy hyperspetctrum under different soil backgrounds.
Author: X.Yao, H.Ren, Z.Cao, Y. Tian, W. Cao, Y.Zhu, T.Cheng.
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. 114-124 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Wheat canopy, Leaf nitrogen content, Vegetation coverage, Soil background, Spectral index, Detecting model.
Abstract: Hyperspectral sensing techniques can be effective for rapid, non-destructive detecting of the nitrogen (N) status in crop plants; however, their accuracy is often affected by the soil background. Under different fractions of soil background, the canopy spectra and leaf nitrogen content (LNC) in winter wheat (Triticum aestivum L) were obtained from field experiments with different N rates and planting densities over 3 growing seasons. Five types of vegetation index (Vis: normalized difference vegetation index (NDVI), ratio vegetation index ( RVI), soil adjusted vegetation index (SAVI), optimize soil adjusted vegetation index (OSAVI), and perpendicular vegetation index (PVI) were constructed based on three types of spectral information: (1) the original and the first derivative (FD) spectrum, (2) the spectrum adjusted with the vegetation coverage (FVcover ) and (3) the pure spectrum extracted by linear mixed model. Comprehensive relationships of above five types of VI with LNC were quantified for LNC detecting under different soil backgrounds.
The results indicated that all five types of VI were significantly affected by the soil background, with R2 values of around 0.55 for LNC detecting, with the OSAVI (R514, R469)L=0.04 producing the best performance of all five indices. However, based on the FVcover, the cover adjusted spectral index (CASI=NDVI(R513, R481) /(1+FVcover) produced the higher R2 value of 0.62 and the lower RRMSE of 13 %, and was less sensitive to the leaf area index (LAI), leaf dry weight (LDW), FVcover, and leaf nitrogen accumulation (LNA). The results demonstrate that the newly developed CASI could improve the performance of LNC estimation under different soil backgrounds.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J., Smith, M., Gillespie, A., 1993. Imaging spectroscopy: interpretation based on spectral mixture analysis. In: Pieters, C.M., Englert, P. (Eds), Remote Geochemical Analysis: Elemental and Mineralogical Composition, 7. Cambridge University Press, New York, pp 145-166.
Baret, F., Guyot, G., Major, D., 1989. TSAVI: a vegetation index which minimizes soil brightness effects on LAI and APAR estimation. In: Proc IGARRS ' 89. 12th Canadian Symposium on Remote Sensing vol. 3, No.1, Vancouver, Canada, pp. 1355-1358.
Literature cited 2: Blackmer, T., Schepers, J., Varvel, G., Walter -Shea, E., 1996. Nitrogen deficiency detection using reflected shortwave radiation from irrigated corn canopies. Agron.J. 88 (1), 1-5
Chen, X., Vierling, L., 2006. Spectral mixture analyses of hyperspectral data acquired using a tethered balloon Remote Sens. Environ. 103 (3), 338-350.
ID: 60108
Title: Quantifying winter wheat residue biomass with a spectral angle index derived from China Environmental Satellite data.
Author: Miao Zhang, Bingfang Wu, Jihua Meng.
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. 105-113 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Crop residue biomass, Winter wheat, Spectral angle index, Field spectrometry, China Environmental Satellite (HJ-1B).
Abstract: Quantification of crop residue biomass on cultivated land is essential for studies of carbon cycling of agroecosystems, soil-atmospheric carbon exchange and Earth systems modeling. Previous focus on estimating crop residue cover (CRC) while limited research exists on quantifying crop residue biomass. This study takes advantage of the high temporal resolution of the China Environmental Satellite (HJ-1) data and utilizes the band configuration features of HJ-1B data to establish spectral angle indices to estimate crop residue biomass. Angles formed at the NIRIRS vertex by the three vertices at R, NIRIRS, and SWIR (ANIRIRS) of HJ-1B can effectively indicate winter wheat residue biomass. A coefficient of Determination (R2) of 0.811 was obtained between measured winter wheat residue biomass and ANIRIRS derived from simulated HJ-1B reflectance data. The ability of ANIRIRS for quantifying winter wheat residue biomass using HJ-1B satellite data was also validated and evaluated. Results indicate that ANIRIRS performed well in estimating winter wheat residue biomass with different residue treatments; the root mean square error (RMSE) between measured and estimated residue biomass was 0.038 kg/m2. ANIRIRS is a potential method for quantifying winter wheat residue biomass at a large scale due to wide swath width (350 km) and four-day revisit rate of the HJ-1 satellite. While ANIRIRS can adequately estimate winter wheat residue biomass at different residue moisture conditions, the feasibility of ANIRIRS for winter wheat residue biomass estimation at different fractional coverage of green vegetation and different environmental conditions (soil type, soil moisture content, and crop residue type) needs to be further explored.
Location: TE 15 New Biology Building
Literature cited 1: Aase, J.K., Tanaka, D.L., 1991. Reflectance from four wheat residues cover densities as influenced by three soil backgrounds. Agron.J.83, 753-757.
Adams, J.B., Smith, M.O., Gillespie, A.R., 1989. Simple models for complex natural surfaces: a strategy for the hyperspectral era of remote sensing. In: IEEE International Geoscience Remote Sensing Symposium 89, IEEE Geoscience and Remote Sensing Society, New York, pp. 16-21.
Literature cited 2: Aguilar, J., Evans, R., Vigil, M., Daughtry, C.S.T., 2012. Spectral estimates of crop residue cover and density for standing and flat wheat stubble. Agron.J.104, 271-279.
Atmospheric Correction Module, 2009. QUAC and FLAASH User ' s Guide, Atmospheric Correction Module, Version 4.7, August, 2009 Edition, Available online: http://www.exelisvis.com/portals/o/pdfs/envi/Flaash_Module.pdf.
ID: 60107
Title: Geospatial scenario based modeling of urban and agricultural intrusions in Ramsar wetland Deepor Beel in Northeast India using a multi-layer perceptron neural network.
Author: Chitrini Mozumder, Nitin K. Tripathi.
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. 92-104 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Wetland conservation, Urban growth, Land use modelling, Sensitivity analysis, Multi-layer perceptron neural network, Deepor Beel.
Abstract: In recent decades, the world has experienced unprecedented urban growth which endangers of the green environment in and around urban areas. In this work, an artificial neural network (ANN) based model is developed to predict future impacts of urban and agricultural expansion on the uplands of Deepor Beel, a Ramsar wetland in the city area Guwahati, Assam, India, by 2025 and 2035 respectively. Simulations were carried out for three different transition rates as determined from the changes during 2001-2011, namely simple exploration, Markov Chain (MC), and system dynamic (SD) modeling, using projected population growth, which were further investigated based on three different zoning policies. The first zoning policy employed no restriction while the second conversion restriction zoning policy restricted urban-agricultural expansion in the Guwahati Municipal Development Authority (GMDA) proposed green belt, extending to a third zoning policy providing wetland restoration in the proposed green belt. The prediction maps were found to be greatly influenced by the transition rates and the allowed transitions from one class to another within each sub-model. The model outputs were compared GMDA land demand as proposed for 2025 whereby the land demand as produced by MC was found to best match the projected demand. Regarding the conservation of Deepor Beel, the Landscape Development Intensity (LDI) Index revealed that wetland restoration zoning policies may reduce the impact of urban growth on a local scale, but none of the zoning policies was found to minimize the impact on a broader base. The results from this study may assist the planning and reviewing of land use allocation within Guwahati city to secure ecological sustainability of the wetlands.
Location: TE 15 New Biology Building
Literature cited 1: Agarwal, C., Green, G.M., Grove, J.M., Evans, T.P., Schweik, C.M., 2002. A Review and Assessment of Land-Use Change Models: Dynamics of Space, Time, AND Human Choice. Gen.Tech.Rep.NE-297. U.S. Department of Agriculture, Forest Service, Northeastern Research Station, Newtown Square, PA, 61 pp.
Arsanjani, J.J., Helbich, M., Kainz, W., Darvishi Boloorani, A., 2013. Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. Int. J. Appl. Earth Obs.Geoinf.21, 265-275.
Literature cited 2: Bell, E.J., 1974.Markov analysis of land use change-an application of stochastic processes to remotely sensed data. Socio-Econ.Plann.Lit.22 (4), 311-316.
BenDor, T., Brozovic, N., Pallathucheril, V.G., 2008. The social impacts of wetland mitigation policies in the United States. J. Plann. Lit. 22 (4), 341-357.
ID: 60106
Title: Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery.
Author: Maria Rosaria Fernandes, Francisca C. Aguiar, Joao M.N. Silva, Maria Teresa Ferreira, Jose M.C. Pereira.
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. 79-91 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Alien species, Riparian corridors, Arundo donax, OBIA, Geometric metrics, WorldView-2.
Abstract: Giant reed in an aggressive invasive plant of riparian ecosystems in many sub sub-tropical and warm-temperate regions, including Mediterranean Europe. In this study we tested a set of geometric, spectral and textural attributes in an object based image analysis (OBIA) approach to map giant reed invasions in riparian habitats. Bagging Classification and Regression Tree were used to select the optimal attributes and to build the classification rules sets. Mapping accuracy was performed using landscape metrics and the Kappa coefficient to compare the topographical and geometry similarity between the giant reed patches obtained with the OBIA map and with a validation map derived from on-screen digitizing. The methodology was applied in two high spatial resolution images: an airborne multispectral imagery and the newly WorldView-2 imagery. A temporal coverage of the airborne multispectral images was radiometrically calibrated with the IR-Mad transformation and used to assess the influence of the phonological variability of the invader.
We found that optimal attributes for giant reed OBIA detection are a combination of spectral, geometric and textural information, with different scoring selection depending on the spectral and spatial characteristics of the imagery. WorldView-2 showed higher mapping accuracy (Kappa coefficient of 77% ) and spectral attributes, including the newly yellow band, were preferentially selected, although a tendency to overestimate the total invaded area, due to the low spatial resolution (2m of pixel size vs. 50 cm) was observed. When airborne images were used, geometric attributes were primarily selected and a higher spatial detail of the invasive patches was obtained, due to the higher spatial resolution. However, in highly heterogeneous landscapes, the low spectral resolution of the airborne images (4 bands instead of the 8 of WorldView-2) reduces the capability to detect giant reed patches. Giant reed displays peculiar spectral and geometric traits, at leaf, canopy and stand level, which makes the OBIA approach a very suitable technique for management purposes.
Location: TE 15 New Biology Building
Literature cited 1: Adam, E., Mutanga, O., 2009. Spectral discrimination of papyrus vegetation (Cyperus papyrus L) in swamp wetlands using field spectrometry. ISPRS J.Photogram.Rem.Sens.64 (6), 612-620
Aguir, F.C., Ferreira, M.T., 2013. Plant invasions in the rivers of the Iberian Peninsula, South-Western Europe- a review. Plant Biosyst. 147 (4), 1107-1119.
Literature cited 2: Aguiar, F.C., Moreira, I., Ferreira, M.T., 1996. Perception of aquatic weed problems by water resources managers. A Percepcao da Vegetacao Aquatica Infestante pelas Entidades Gestoras dos Recursos Hidricos.Rev.Cienc.Agr. 19 (4), 35-56.
Aguiar, F.C., Ferreira, M.T., Albuquerque, A., Moreira, I., 2007. Alien and endemic flora on reference and non-reference sites from Mediterranean type-streams of Portugal. Aquat. Conserv. Mar. Freshwater Ecosyst. 17 (4), 335-347.