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ID: 60052
Title: Early season monitoring of corn and soybeans with Terra SAR-X and RADARSAT-2
Author: H.McNairn, A. Kross, D.Lapen, R.Caves, J. Shang.
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. 28 252-259 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: TerraSAR-X, RADARSAT-2, Classification, Corn, Soybeans.
Abstract: Early and on-going crop production forecasts are important to facilitate food price stability for regions at risk, and for agriculture exporters, to set market value. Most regional and global efforts in forecasting rely on multiple sources of information from the field. With increased access to data from spaceborne Synthetic Aperture Radar (SAR), these sensors could contribute information on crop acreage. But these acreage estimates must be available early in the season to assist with production forecasts. This study acquired TerraSAR-X and RADARSAT-2 data over a region in eastern Canada dominated by economically important corn and soybean production. Using a supervised decision tree classifier, results determined that either sensor was capable of delivering highly accurate maps of corn and soybeans at the end of the growing season. Accuracies far exceeded 90%. Spatial and multi-temporal filtering approaches were compared and small improvements in accuracies were found by applying the multi-temporal filter to the RADARSAT-2 data. Of significant interest, this study determined that by using only three TerraSAR-X images corn could be accurately identified by the end of June, a mere six weeks after planting and at a vegetative growth stage (V6- sixth leaf collar developed ). However, soybeans required additional acquisitions given the variance in planting densities and planting dates in this region of Canada. In this case, accurate soybean classification required Terra SAR-X images until early August at the start of the reproductive stage (R5- seed development is beginning). Also important, by applying a multi-temporal filter accurate mapping (close to 90%) of corn and soybeans from RADARSAT-2 could occur five weeks earlier (by August 19) than if a spatial filter was used. Thus application of this filtering approach could accelerate delivery of crop inventory for this region of Canada. Corn and soybeans are important commodities both globally and within Canada. This study makes an important contribution as it demonstrates that TerraSAR-X can deliver acreage estimates of these two crops early enough to assist with in-season production forecasting.
Location: TE 15 New Biology Building
Literature cited 1: Agriculture and Agri-Food Canada, June 19, 2009. Corn: Situation and Outlook, Market Outlook Report, Vol. 1, number 2, Published on-line at http://www.agr.gc.ca/pol/mad-dam/index_e.php? s 1=pubs & s2=rmar&s3= php & page= rmar_01_02_2009-06-19 (last accessed 24.07.13). Agriculture and Agri-Food Canada, May 21, 2013. Canada: Outlook for Principal Field Crops, Published on-line at http://www.agr.gc.ca/pol/mad-dam/pubs/fco-ppc/pdf/fco-ppc_2013-05-21_eng.pdf (last accessed 24.07.13).
Literature cited 2: Baghdadi, N., Boyer, N., Todoroff, P., El Hajj, M., Begue, A., 2009. Potential of SAR sensors TerraSAR-X, ASAR/ENVISAT and PALSAR/ALOS for monitoring sugarcane crops on Reunion Island. Remote Sensing of Environment 113, 1724-1738. Ban, Y., 2003. Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crop. Canadian Journal of Remote Sensing 29, 518-526.

ID: 60051
Title: Historical extension of operational NDVI products for livestock insurance in Kenya.
Author: Anton Vrieling, Michele Meroni, Apurba Shee, Andrew G. Mude, Joshua Woodard, C.A.J.M. (Kees) de Bie, Felix Rembold.
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. 28 238-251 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: NDVI, AVHRR, SPOT, MODIS, Index insurance, Intercalibration.
Abstract: Droughts induce livestock losses that severely affect Kenyan pastoralists. Recent index insurance schemes have the potential of being a viable tool for insuring pastoralists against drought-related risk. Such schemes require as input a forage scarcity (or drought) index that can be reliably updated in near real-time, and that strongly relates to livestock mortality. Generally, a long record (>25 years) of the index is needed to correctly estimate mortality risk and calculate the related insurance premium. Data from current operational satellites used for large-scale vegetation monitoring span over a maximum of 15 years, a time period that is considered insufficient for accurate premium computation. This study examines how operational NDVI datasets compare to, and could be combined with the non-operational recently constructed 30-year GIMMS AVHRR record (1981-2011) to provide a near-real time drought index with a long term archive for the arid lands of Kenya. We compared six freely available, near -real time NDVI products: five from MODIS and one from SPOT -VEGETATION. Prior to comparison, all datasets were averaged in time for the two vegetative seasons in Kenya, and aggregated spatially at the administrative division level at which the insurance is offered. The feasibility of extending the resulting aggregated drought indices back in time was assessed using jackknifed R2 statistics (leave-one-year-out) for the overlapping period 2002-2011. We found that division -specific models were more effective than a global model for linking the division -level temporal variability of the index between NDVI products. Based on our results, good scope exists for historically extending the aggregated drought index, thus providing a longer operational record for insurance purposes. We showed that this extension may have large effects on the calculated insurance premium. Finally, we discuss several possible improvements to the drought index.
Location: TE 15 New Biology Building
Literature cited 1: Anyamba, A., Chretein, J. -P., Small, J., Tucker, C.J., Formenty, P.B., Richardson, J.H., Britch, S.C., Schnabelf, D.C., Erickson, R.L., Linthicum, K.J., 2009. Prediction of a Rift Valley fever outbreak. Proceedings of the National Academy of Sciences of the United States of America 106, 955-959. Atzberger, C, Eilers, P.H.C., 2011. A time series for monitoring vegetation activity and phenology at 10-daily time steps covering largeparts of South America. International Journal of Digital Earth 4, 365-386.
Literature cited 2: Atzberger, C., Klisch, A., Mattiuzzi, M., Vuolo, F., 2014. Phenological metrics derived over the European continent from NDVI3g data and MODIS time series. Remote Sensing 6, 257-284. Baltagi, B.H., 2008. Econometric Analysis of Panel Data, fourth ed. John Wiley & Sons Ltd., Chichester, West Sussex, UK.

ID: 60050
Title: Combined use of multi-seasonal high and medium resolution satellite imagery for parcel-related mapping of cropland and grassland.
Author: T.Esch, A. Metz, M. Marconcini, M. Keil.
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. 28 230-237 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Multi-seasonal analysis, High and medium resolution data, Object-oriented classification, Grassland, Crop types.
Abstract: A key factor in the implementation of productive and sustainable cultivation procedures is the frequent and area-wide monitoring of cropland and grassland. In particular, attention is focused on assessing the actual status, identifying basic trends and mitigating major threats with respect to land-use intensity and its changes in agricultural and semi-natural areas. Here, multi-seasonal analyses based on satellite Earth observation (EO) data can provide area-wide, spatially detailed and up-to-date geo-information on the distribution and intensity of land use in agricultural and grassland areas. This study introduces an operational, application-oriented approach towards the categorization of agricultural cropland and grassland based on a novel scheme combining multi-resolution EO data with ancillary geo-information available from currently existing databases. In this context, multi-seasonal high (HR) and medium resolution (MR) satellite imagery is used for both a land parcel -based determination of crop types as well as a cropland and grassland differentiation, respectively. In our experimental analysis, two HR IRS-P6 LISS-3 images are first employed to delineate the field parcels in potential agricultural and grassland areas (determined according to the German Official Topographic Cartographic Information System -ATKIS). Next, a stack of seasonality indices is generated based on 5 image acquisitions (i.e., the two LISS scenes and three additional IRS -P6 A WiFS scenes). Finally, a C5.0 tree classifier is applied to identify main crop types and grassland based on the input imagery and the derived seasonality indices. The classifier is trained using sample points provided by the European Land Use/ Cover Area Frame Survey (LUCAS). Experimental results for a test area in Germany assess the effectiveness of the proposed approach and demonstrate that a multi-scale and multi-temporal analysis of satellite data can provide spatially detailed and thematically accurate geo-information on crop types and the cropland -grassland distribution, respectively.
Location: TE 15 New Biology Building
Literature cited 1: Adv, 2012. Arbeitsgemeinschaft der Vermessungs-verwaltungen der Lander der Bundesrepublik Deutschland: Erlauterungen zum ATKIS-Objektartenkatalog der Arbeitsgemeinschaft der Vermessungsverwaltungen der Lander der Bundesrepublik Deutschland, Available URL: http://www.atkis.de (accessed 28.04.12). Bailey, J.T., Boryan, C., 2010. Remote sensing uses in agriculture at the national agricultural statistics service. In: Proceedings of 5th Conference on Agricultural Statistics, Integrating Agriculture into the National Statistical System (ICAS-V), 12-15 October 2010, Kampala, Uganda.
Literature cited 2: Benz, U.C., Hofmann, P., Willhauck, G., Lingenfelder, M., 2004. Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing 58, 239-258. Blaes, X., Vanhalle, L., Defourny, P., 2005. Efficiency of crop identification based on optical and SAR image time series. Remote Sensing of Environment 96, 352-365.

ID: 60049
Title: Continuous field mapping of Mediterranean wetlands using sub-pixel spectral signatures and multi-temporal Landsat data.
Author: Julia Reschke, Christian Huttich.
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. 28 220-229 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Wetland mapping, Wetland -dynamics, Land use/ land cover (LULC) Landsat ETM+, Multivariate reflectance analysis, Random forest.
Abstract: Wetlands rank among the most diverse ecosystems on earth and function as important ecosystem service providers. Pressures on wetland ecosystems caused by human activities, such as land use transformations or agricultural intensification, lead to strong wetland degradation. Satellite-based wetland mapping still bears the most uncertainties compared to other land cover types mapping. Image classification techniques have to better adapt to specific wetland characteristics, such as spatial heterogeneity, seasonal dynamics and fuzzy transitions between different land cover classes. For this purpose, a pixel-based method for wetland delineation based on multi-temporal Landsat data in West Turkey was developed and analyzed. In addition to common vegetation indices and texture measures, the usefulness of seasonal indices was tested. Multi-temporal Landsat imagery was combined with high resolution satellite data to extract sub-pixel information of coastal and inland wetland classes based on a random forest regression algorithm. The classification achieved an overall accuracy of 79.02%. In addition to the hard wetland classification the mapping framework provides a map of fractional cover information of different wetland classes including information about fuzzy spatial transitions of highly heterogeneous distribution patterns of wetland habitats and related intra-annual seasonal dynamics. Mapping spatio-temporal wetland dynamics at continuous field scales increases the applicability of Landsat-derived maps for local-scale ecosystem monitoring and environmental management on habitat level.
Location: TE 15 New Biology Building
Literature cited 1: Adam, E., Mutanga, O., Rugege, D., 2010. Multispectral and hyperspectral remote sensing for identification and mapping of wetland vegetation: a review. Wet-lands Ecology and Management 18 (3), 281-296. Archer, K., Kimes, R., 2008. Empirical characterization of random forest variable importance measures. Computational Statistics & Data Analysis 52 (4), 2249-2260.
Literature cited 2: Baker, C, Lawrence, R., Montagne, C., Patten, D., 2006. Mapping wetlands and riparian areas using Landsat ETM+ imagery and decision -tree -based models. Wetlands 26, 465-474. Bartsch, A., Trofaier, A., Hayman, G., Sabel, D., Schlaffer, S., Clark, D., Blyth, E., 2012. Detection of open water dynamics with ENVISAT ASAR in support of land surface modeling at high latitudes, Biogeosciences 9, 703-714.

ID: 60048
Title: Multi-frequency, polarimetric SAR analysis for archaeological prospection.
Author: Christopher Stewart, Rosa Lasaponara, Giovanni Schiavon.
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. 28 211-219 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Archaeology, SAR, PALSAR, RADARSAT-2, Prospection, Polarimetry.
Abstract: The aim of this study is to assess the sensitivity to buried archaeological structures of C- and L-band Synthetic Aperture Radar (SAR) in various polarisations. In particular, single and dual polarised data from thephased Array type L-band SAR (PALSAR) sensor on-board the Advanced Land Observing Satellite (ALOS) is used, together with quadruple polarized (quad pol) data from the SAR sensor on Radarsat-2. The study region includes an isolated area of open fields in the eastern outskirts of Rome where buried structures are documented to exist. Processing of the SAR data involved multitemporal averaging, analysis of target decompositions, study of the polarimetric signatures over areas of suspected buried structures and changes of the polarimetric bases in an attempt to enhance their visibility. Various ancillary datasets were obtained for the analysis, including geological and lithological charts, meteorological data, Digital Elevation Models (DEMs) optical imagery and an archaeological chart. For the Radarsat-2 data analysis, results show that the technique of identifying the polarimetric bases that yield greatest backscatter over anomaly features, and subsequently changing the polarimetric bases of the time series, succeeded in highlighting features of interest in the study area. It appeared possible that some of the features could correspond with structures documented on the reference archaeological chart, but there was not a clear match between the chart and the results of the Radarsat-2 analysis. A similar conclusion was reached for the PALSAR data analysis. For the PALSAR data, the volcanic nature of the soil may have hindered the visibility of traces of buried features. Given the limitations of the accuracy of the archaeological chart and the spatial resolution of both the SAR datasets, further validation would be required to draw any precise conclusions on the sensitivity of the SAR data to buried structures. Such a validation could include geophysical prospection or excavation.
Location: TE 15 New Biology Building
Literature cited 1: Blom, R., Clapp, N., J. Hedges, G., 1997. Space technology and the discovery of the lost city of Ubar. In: Paper read at IEEE Aerospace Conf. February 1-8. Boerner, W.M., Mott, H., Luneburg, E., Livingston, C., Brisco, B., Brown, R.J., Paterson, J.S. with contributions by Cloude, S.R., Krogager, E., Lee, J.S. Schuler, D.L., Van Zyl, J.J., Randall, D., Budkewitsch, P., Pottier, E., 1998. Polarimetry in radar remote sensing: basic and applied concepts, Chapter 5 in Henderson, F.M. Lewis, A.J. (Eds), Principles and Applications of Imaging Radar, vol 2 of Manual of Remote Sensing Reyerson, R.A. (Ed), third ed., John Wiley & Sons, New York, 1998.
Literature cited 2: Brivio, P.A., Pepe, M., Tomason, R., 2000. Multispectral and multiscale remote sensing data for archaeological prospecting in an alpine alluvial plain. Journal of Cultural Heritage 1, 155-164. Cigna, F., Tapete, D., Lasaponara, R., Masini, N., 2013. Amplitude change detection with ENVISAT ASAR to image the cultural landscape of the Nasca Region, Peru. Archaeological Prospection 20, 117-131.

ID: 60047
Title: Prior-knowledge-based spectral mixture analysis for impervious surface mapping.
Author: Jinshui Zhang, Chunyang He, YuYu Zhou, Shuang Zhu, Guanyuan Shuai
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. 28 201-210 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Impervious surface, V-I-S, Spectral mixture analysis, Prior-knowledge.
Abstract: In this study, we developed a prior -knowledge-based spectral mixture analysis (PKSMA) to map impervious surfaces by using endmembers derived separately for high -and low-density urban regions. First, an urban area was categorized into high -and low-density urban areas, using a multi-step classification method. Next, in high-density urban areas that were assumed to have only vegetation and impervious surfaces (ISs), the vegetation-impervious model (V-I) was used in a spectral mixture analysis (SMA) with three endmembers: vegetation, high albedo, and low albedo. In low-density urban areas, the vegetation -impervious -soil model (V-I-S) was used in an SMA analysis with four endmembers: high albedo, low albedo, soil, and vegetation. The fraction of IS with high and low albedo in each pixel was combined to produce the final IS map. The root mean-square error (RMSE) of the IS map produced using PKSMA was about 11.0% compared to 14.52% only using four-endmember SMA. Particularly in high-density urban areas, PKSMA (RMSE=6.47%) showed better performance than four-endmember (15.91%). The results indicate that PKSMA can improve IS mapping compared to traditional SMA by using appropriately selected endmembers and is particularly strong in high -density urban areas.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J.B., Sabol, D.E., Kapos, V., Almeida-Filho, R., Roberts, D.A., Smith, M.O., Gillespie, A.R., 1995, Classification of multiple images based on fractions of end-members: application to land-cover change in the Brazilian Amazon. Remote Sensing of Environment 52, 137-154. Al-Shalabi, M., Billa, L., Pradhan, B., Mansor, S., Al-Sharif, A.A., 2013. Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of sana ' s metropolitan city, Yemen. Environmental Earth Science 70, 425-437.
Literature cited 2: Anys, H., Bannari, A., He, D.C., Morin, D., 1994. Texture analysis for the mapping of urban areas using airborne MEIS-II images. In: Proc. First International Airborne Remote Sensing Conference and Exhibition, Strasbourg, France, pp. 231-245. Arnold Jr., C.L, Gibbons, C.J., 1996. Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American Planning Association 62 (2), 243-258.

ID: 60046
Title: Spatialization of electricity consumption of China using saturation-corrected DMSP-OLS data.
Author: Xin Cao, Jianmin Wang, Jin Chen, Feng Shi.
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. 28 193-200 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Electricity consumption, DMSP-OLS, GDP, Saturation -correction.
Abstract: Electricity is one of the most important components in energy consumption, which is directly related to economic growth, CO2 emission and global warming. This research intends to estimate spatial distribution of electricity consumption in China, the largest developing country, and analyze the temporal and spatial change of electricity consumption during 1994-2009. The spatial modeling is based on the total electricity consumption of each province and DMSP (Defense Meteorological Satellite program) -Operational Line-scan System (OLS) data, the latter provides the nighttime light information corresponding to electricity consumption, GDP and population. A simple method was developed to correct the saturated pixels with digital number of 63 in non-radiance -corrected DMSP-OLS data, using cities ' GDP data. The spatial electricity consumption maps were produced during 1994-2009, and they were validated by the electricity consumption records of 101 cities. Finally, the spatial -temporal changes of electricity consumption were analyzed. The results of this research can help to understand the regional discrepancy, especially rural and urban areas of China, of electricity consumption and economic development.
Location: TE 15 New Biology Building
Literature cited 1: Amaral, S., Camara, G., Miguel, A., Monteiro, V., Quintanilha, J.A., Elvidge, C.D., 2005. Estimating population and energy consumption in Brazilian Amazonia using DMSP night-time satellite data. Computer, Environment and Urban Systems 29, 179-195. Chand, T.R.K., Badarinath, K.V.S., Elvidge, C.D., Tuttle, B.T., 2009. Spatial characterization of electrical power consumption patterns over India using temporal DMSP-OLS night-time satellite data. International Journal of Remote Sensing 30, 647-661.
Literature cited 2: De Souza Filho, C.R., Zullo Jr., Elvidge, C., 2004. Brazil ' s 2001 energy crisis monitored from space International Journal of Remote Sensing 25, 2475-2482. Elvidge, C.D., Baugh, K.E., Hobson, V.H., Kihn, E.A., Kroehl, H.W., Davis, E.R, et al., 1997a. Satellite inventory of human settlements using nocturnal radiation emissions: a contribution for the global toolchest. Global Change Biology 3, 387-395.

ID: 60045
Title: Estimating soil moisture and the relationship with crop yield using surface temperature and vegetation index.
Author: M.E. Holzman, R. Rivas, M.C. Piccolo.
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. 28 181-192 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Soil moisture, MODIS, Optical-thermal, Crop yield forecasting, Remote sensing.
Abstract: Soil moisture availability affects rainfed crop yield. Therefore, the development of methods for pre-harvest yield prediction is essential for the food security. A study was carried out to estimate regional crop yield using the Temperature Vegetation Dryness Index (TVDI). Triangular scatters from land surface temperature (LST) and enhanced vegetation index (EVI) space from MODIS (Moderate Resolution Imaging Spectroradiometer) were utilized to obtain TVDI and to estimate soil moisture availability. Then soybean and wheat crops yield was estimated on four agro-climatic zones of Argentine Pampas. TVDI showed a strong correlation with soil moisture measurements, with R2 values ranged from 0.61 to 0.83 and also it was in agreement with spatial pattern of soil moisture. Moreover, results showed that TDVI showed that TVDI data can be used effectively to predict crop yield on the Argentine Pampas. Depending on the agro-climatic zone, R2 values ranged from 0.68 to 0.79 for soybean crop and 0.76 to 0.81 for wheat. The RMSE values were 366 and 380 kg ha -1 for soybean crop and 0.76 to 0.81 for wheat. The RMSE values were 366 and 380 kg ha-1 for soybean and they varied between 300 and 550 kg ha -1 in the case of wheat crop. When expressed as percentages of actual yield, the RMSE values ranged from 12 % to 13% for soybean and 14% to 22 % for wheat. The bias values indicated that the obtained models underestimated soybean and wheat yield Accurate crop grain yield forecast using the developed regression models was achieved one to three months before harvest. In many cases the results were better than others obtained using only a vegetation index, showing the aptitude of surface temperature and vegetation index combination to reflect the crop water condition. Finally, the analysis of a wide range of soil moisture availability allowed us to develop a generalized model of crop yield and dryness index relationship which could be applicable in other regions and crops at regional scale.
Location: TE 15 New Biology Building
Literature cited 1: Baez-Gonzalez, A.D., Chen, P., Tiscareno-Lopez, M., Srinivasan, R., 2002. Using satellite and field data with crop growth modeling to monitor and estimate corn yield in Mexico. Crop Sci. 42, 1943-1949. Balaghi, R., Tychon, B., Eerens, H., Jlibene, M., 2008. Empirical regression model using NDVI, rainfall and temperature data for the early prediction of wheat grain yields in Morocco. Int. J.Appl. Earth Obs. Geoinf. 10, 438-452.
Literature cited 2: Basnyat, P., McConkey, B., Lafond, G.R., Moulin, A., Pelcat, Y., 2004. Optimal time for remote sensing to relate to crop grain yield on the Canadian prairies.Can.J.Plant Sci. 84, 97-103. Batlivala, P.P., Ulaby, F.T., 1977. Feasibility of monitoring soil moisture using activity microwave Remote Sensing Laboratory Technical Report No. 264-12.

ID: 60044
Title: Retrieving canopy height and density of paddy rice from Radarsat-2 images with a canopy scattering model.
Author: Yuan Zhang, Xiaohui Liu, Shiliang Su, Cuizhen Wang.
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. 28 170-180 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Radarsat-2, Canopy scattering model, paddy rice, Canopy height and density.
Abstract: Quantification of rice biophysical properties is important not only for rice growth monitoring and cropping management, but for understanding carbon cycle in agricultural ecosystems. In this study, a rice canopy scattering model (RCSM) was firstly utilized to simulate rice backscatter with a root mean square error (RMSE) < 1 dB in comparison with the C-band, HH-polarization Radarsat-2 images. And then, by integrating the model with a generic algorithm optimization tools (GOAT), canopy height and density were separately retrieved from Radarsat-2 images acquired in three rice growth stages (elongation stage, heading stage and yellow ripening stage ). Accuracy analysis showed that the two parameters could be retrieved with the RMSE of 5.4 cm in height, and 26 (#/ m2) in density. The study demonstrated the potential of Radarsat-2 SAR data for quantitative mapping of biophysical parameters of paddy rice.
Location: TE 15 New Biology Building
Literature cited 1: Bouvet, A., Le Toan, T., 2011. Use of ENVISAT/ASAR wide-swath data for timely rice fields mapping in the Mekong River Delta. Remote Sensing of Environment 115 (4), 1090- 1101. Chakraborty, M., Manjunath, K.R., Panigrahy, S., Kundu, N., Parihar, J.S., 2005. Rice crop parameter retrieval using multi-temporal, multi-incidence angle Radarsat SAR data. ISPRS Journal of photogrammetry and Remote Sensing 59 (5), 310-322.
Literature cited 2: Chen, J., Lin, H., Liu, A., Shao, Y., Yang, L., 2006. A semiempirical backscattering model for estimation of leaf area index (LAI) of rice in Southern China. International Journal of Remote Sensing 27 (24), 5417-5425. De Castro, H.F., Cavalca, K.L., 2003. Availability optimization with genetic algorithm. International Journal of Reliability Management 20 (7), 847-863.

ID: 60043
Title: Estimation of real evapotranspiration and its variation in Mediterranean landscapes of central -southern Chile.
Author: L. Olivera-Guerra, C.Mattar, M., Galleguillos.
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. 28 160-169 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Evapotranspiration, Rainfed landscape, S-SEBI, ASTER.
Abstract: Evapotranspiration (ETd) is a key controller in the ecohydrological processes of semi-arid landscapes. This is the case of the dry land in the Chile ' s central -southern zone, where forestry, farming and livestock activities must adapt to precipitation with considerable year-on-year variations. In this study, the spatial distribution of ETd was estimated in relation to the land use map and physical parameters of the soil. The ETd was estimated through the Simplified Surface Energy Balance Index (S-SEBI) using data from weather stations and remote data provided by the ASTER and MODIS sensors for November 2004 and 2006, respectively. The spatial variability of ETd was compared among different plant types, soil textural classes and depths using non-parametric statistical tests. In this comparison, the highest rates of ETd were obtained in the forest covers with values of 7.3 ? 0.8 and 8.4 ? 0.8 mm d-1 for 2004 and 2006, respectively. The lowest values were estimated for pastures and shrublands with values of 3.5 ? 1.2 mm d-1 and for crops with rates of 4.4 ? 1.6 mm d-1. Comparison of the ETd of the native forest covers and plantations of exotic species showed statistically significant differences; however, no great variation was noted, at least in the study months. Additionally, the highest rates of ETd were found in the clay loam textures (6.0 ? 1.8 and 6.4 ? 2.0 mm d-1) and the lowest rates in the sandy loam soils (3.7 ? 1.6 and 3.9 ? 1.6 mm d-1) for 2004 and 2006, respectively. The results enable analysis of the spatial patterns of the landscape in terms of the relation between water consumption, ET and the biophysical characteristics of a Mediterranean ecosystem. These results form part of the creation of tools useful in the optimization of decision-making for the management and planning of water resources and soil use in territories with few measuring instruments.
Location: TE 15 New Biology Building
Literature cited 1: Abrams, M., 2000. International Journal of The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER): data products for the high spatial resolution imager on NASA ' s Terra platform. Int. J. Remote Sens. 21, 847-859. Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A., Holtslag, A.A.M., 1998. A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. J. Hydrol. 212-213, 198-212.
Literature cited 2: Birkinshaw, S.J., Bathurst, J.C., Iroume, A., Palacios, H., 2011. The effect of forest cover on peak flow and sediment discharge -an integrated field and modeling study in central-southern Chile. Hydrol. Process 25, 1284-1297. Boronina, A., Ramillien, G., 2008. Application of AVHRR imagery and GRACE measurements for calculation of actual evapotranspiration over the quaternary aquifer (Lake Chad basin) and validation of groundwater models. J. Hydrol. 348, 98-109.

ID: 60042
Title: Detection of flooded urban areas in high resolution Synthetic Aperture Radar images using double scattering.
Author: D.C. Mason, L. Giustarini, J. Garcia-Pintado, H.L. Cloke
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. 28 150-159 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Flood detection, Synthetic Aperture Radar, Urban area, Double scattering
Abstract: Flooding is a particular hazard in urban areas worldwide due to the increased risks to life and property in these regions. Synthetic Aperture Radar (SAR) sensors are often used to image flooding because of their all-weather day-night capability, and now possess sufficient resolution to image urban flooding. The flood extents extracted from the images may be used for flood relief management and improved urban flood inundation modeling. A difficulty with using SAR for urban flood detection is that, due to its side-looking nature, substantial areas of urban ground surface may not be visible to the SAR due to radar layover and shadow caused by buildings and taller vegetation. This paper investigates whether urban flooding can be detected in layover regions (where flooding may not normally be apparent) using double scattering between the (possibly flooded) ground surface and the walls of adjacent buildings. The method estimates double scattering strengths using a SAR image in conjunction with a high resolution LiDAR (Light Detection and Ranging) height map of the urban area. A SAR simulator is applied to the LiDAR data to generate maps of layover and shadow, and estimate the positions of double scattering curves in the SAR image. Observations of double scattering strengths were compared to the predictions from an electromagnetic scattering model, for both the case of a single image containing flooding, and a change detection case in which the flooded image was compared to an un-flooded image of the same area acquired with the same radar parameters. The method proved successful in detecting double scattering due to flooding in the single -image case, for which flooded double scattering curves were detected with 100% classification accuracy (albeit using a small sample set) and un-flooded curves with 91% classification accuracy . The same measures of success were achieved using change detection between flooded and un-flooded images. Depending on the particular flooding situation, the method could lead to improved detection of flooding in urban areas.
Location: TE 15 New Biology Building
Literature cited 1: Allan, R.P., Soden, B.J., 2008. Atmospheric warming and the amplification of precipitation extremes. Science 321 (5895), 1481-1484. Aronica, G., Bates, P.D., Horrit, M.S., 2002. Assessing the uncertainty in distributed model predictions using observed binary pattern information within Glue. Hydrol.Process. 16 (10), 2001-2016.
Literature cited 2: Bates, P.D., Wilson, M., Horritt, M.S., Mason, D.C., Holden, N., Currie, A., 2006. Reach scale floodplain inundation dynamics observed using airborne SAR imagery.J. Hydrol. 328 (1-2), 306-318. Canny, J.F., 1986. A computational approach to edge detection. IEEE. Trans. Pattern Anal.Mach. Intell. 8 (6), 679-698.

ID: 60041
Title: Forest tree species discrimination in western Himalaya using EO-1 Hyperion.
Author: Rajee George, Hitendra Padalia, S.P.S. Kushwaha.
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. 28 140-149 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Hyperspectral, Hyperion, Species discrimination, Himalaya, SVM, SAM.
Abstract: The information acquired in the narrow bands of hyperspectral remote sensing data has potential to capture plant species spectral variability, thereby improving forest tree species mapping. This study assessed the utility of spaceborne EO-1 Hyperion data in discrimination and classification of broadleaved evergreen and conifer forest trees species in western Himalaya. The pre-processing of 242 bands of Hyperion data resulted into 160 noise-free and vertical stripe corrected reflectance bands. Of these, 29 bands were selected through step-wise exclusion of bands (Wilk ' s Lambda). Spectral Angle Mapper (SAM) and support Vector Machine (SVM) algorithms were applied to the selected bands to assess their effectiveness in classification. SVM was also applied to broadband data (Landsat TM) to compare the variation in classification accuracy. All commonly occurring six gregarious tree species, viz., White oak, brown oak, Chir pine, blue pine, cedar and fir in western Himalaya could be effectively discriminated. SVM produced a better species classification (overall accuracy 82.27%, kappa statistic 0.79) than SAM (overall accuracy 74.68%, kappa statistic 0.70). It was noticed that classification accuracy achieved with Hyperion bands was significantly higher than Landsat TM bands (overall accuracy 69.62%, kappa statistic 0.65). Study demonstrated the potential utility of narrow spectral bands of Hyperion data in discriminating tree species in a hilly terrain.
Location: TE 15 New Biology Building
Literature cited 1: Asner, G.P., 2008. Hyperspectral remote sensing of canopy chemistry, physiology and biodiversity in tropical rain forests. In: Kalascska, M., Arturo Sanchez-Azofeifa, G. (Eds), Hyperspectral Remote Sensing of Tropical and Sub-Tropical Forests. CRC press Taylor and Francis group, Boca Raton, London, New York, pp. 161-196. Asner, G.P., Heidebrecht, K.B., 2002. Spectral unmixing of vegetation, soil and drycarbon cover in arid regions: Comparing multispectral and hyper-spectral observations. International Journal of Remote Sensing 23, 3939-3958.
Literature cited 2: Champion, H.G., Seth, S.K., 1968. A Revised Survey of the Forest Types of India. Govt. of India Press, New Delhi. Chan, J.C.W., Palinckx, D., 2008. Evaluation of Random Forest and Adaboost tree based ensemble classification and spectral band selection for ecotope mapping using airborne hyperspectral imagery. Remote Sensing of Environment 112, 2999-3011.

ID: 60040
Title: Conservation and Sustainable Management of Wetland Ecosystems in Western Ghats.
Author: T V Ramachandra, Ananth Hegde Ashisar, Shri Shri Gangadharendra Saraswati Swamiji, M D Subhash Chandran, Harish R Bhat, Harish Krishnamurthy, M A Khan, Sreevidya, Vijai Krishna R, Prakash Mesta, Bharath H Aithal, Rajasri Ray, Durga M. Mahapatra, Ga
Editor: T V Ramachandra
Year: 2015
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Sahyadri Conservation Series 47, Envis Technical Report 87
Subject: Proceedings Lake 2014
Keywords: Conservation, Sustainable Management , Wetland ecosystems
Abstract: Symposium focusing on lakes popularly known as ?Lake Symposium? was initiated by the Energy & Wetlands Research Group at Centre for Ecological Sciences, Indian Institute of Science, Bangalore in the year 1998. The theme was broadened in 2000 (Lake 2000) with a wider participation of education institutions, Governmental and non - Governmental organisations, etc. The basic idea of the symposium was to bring out the trends in ecosystem conservation, restoration and management including the hydrological, bio-physical, people ' s participation and the role of non-governmental, educational and the governmental organizations and the future research needs. Lake 2014 will be the 9th Biennial Lake Conference focussing on ?Conference on Conservation and Sustainable Management of Wetland Ecosystemsin Western Ghats?. The theme of world wetlands day 2014 is ?Wetlands and Agriculture: Placing a focus on the need for the wetland and agricultural sectors (and the water sector too of course) to work together for the best shared outcomes? and this conference provides a unique opportunity to increase understanding of the role of wetlands in sustaining the food production and challenges faced by these fragile ecosystems.
Location: TE 15 New Biology Building
Literature cited 1: None
Literature cited 2: None

ID: 60039
Title: Remote sensing of vegetation cover dynamics and resilience across southern Africa.
Author: A. Harris, A.S. Carr, J. Dash.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 28 131-139 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Remote sensing, Trend analysis, Land degradation, NDVI, AVHRR, Africa.
Abstract: Southern Africa supports a significant portion of the world ' s floral biodiversity but predicted changes in climate are likely to cause adverse impacts on the region ' s ecosystems and biodiversity. Knowledge regarding the resilience of vegetation cover is important for understanding the potential impact of anthropic or climatic change. The length of time vegetation cover takes to recover from disturbances can provide an indication of ecosystem resilience. We investigated spatial and temporal patterns in the persistence of vegetation cover across southern Africa (1982-2006) and used persistence probability plots to estimate decay times of NDVI trends as a means to characterize the potential resilience of key southern African biomes. Patterns of positive and negative NDVI trend persistence were spatially coherent, indicating collective dynamic behavior of vegetation cover. Persistence probability plots indicated differences in resilience between biomes. Mean recovery times from negative NDVI trends were shorter than for positive trends in the Savanna and Nama Karoo, whereas the succulent Karoo exhibited the shortest mean lifetime for positive NDVI trends and one of the longest mean lifetimes for negative trend survival, implying potentially slow recovery from environmental disturbance. The results show the potential of satellite-time series data for monitoring vegetation cover resilience in semi-arid regions.
Location: TE 15 New Biology Building
Literature cited 1: Beck, H.E., McVicar, T.R., vanDijk, A.I.J.M., Schellekens, J., de Jeu, R.A.M., Bruijnzeel, L.A., 2011. Global evaluation of four AVHRR-NDVI data sets: intercomparison and assessment against Landsat imagery. Remote Sens. Environ. 115, 2547-2563. Coppola, R., Cuomo, V., D ' Emilio, M., Lanfredi, M., Liberti, M., Macchiato, M., Simoneillo, T., 2009. Terrestrial vegetation cover activity as a problem of fluctuating surfaces. Int.J. J.Mod.Phys. B 23, 5444-5452.
Literature cited 2: de Jong, R., de Bruin, S., de Wit, A., Schaepman, M.E., Dent, D.L., 2011. Analysis of monotonic greening and browning trends from global NDVI time-series. Remote Sen. Environ. 115, 692-702. Dlamini, W.M., 2011. Bioclimatic modeling of southern African bioregions and biomes using Bayesian networks. Ecosystems 14, 366-381.

ID: 60038
Title: Area-based and location -based validation of classified image objects.
Author: Timothy G. Whiteside, Stefan W. Maier, Guy S. Boggs.
Editor: F.D.van der Meer
Year: 2014
Publisher: Elsevier B.V.
Source: Centre for Ecological Sciences
Reference: APPLIED EARTH OBSERVATION AND GEOINFORMATION. Vol. 28 117-130 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION
Keywords: Geographic object- based image analysis, Validation, Accuracy assessment.
Abstract: Geographic object-based image analysis (GEOBIA) produces results that have both thematic and geometric properties. Classified objects not only belong to particular classes but also have spatial properties such as location and shape. Therefore, any accuracy assessment where quantification of area is required must (but often does not) take into account both thematic and geometric properties of the classified objects. By using location -based and area-based measures to compare classified objects to corresponding reference objects, accuracy information for both thematic and geometric assessment is available. Our methods provide location-based and area-based measures with application to both a single -class feature detection and a multi-class object-based land cover analysis. In each case the classification was compared to a GIS layer of associated reference data using randomly selected sample areas. Error is able to be pin-pointed spatially on per-object, per class and per-sample area bases although there is no indication whether the errors exist in the classification product or the reference data. This work showcases the utility of the methods for assessing the accuracy of GEOBIA derived classifications provided the reference data is accurate and comparable scale.
Location: TE 15 New Biology Building
Literature cited 1: Baatz, M., Schape, A., 2000. Multiresolution segmentation -an optimization approach for high quality multi-scale image segmentation. In: Strobl, J., Blaschke, T., Griesebner, G. (Eds.), Angewandte Geographische Informationsverarbeitung XIII. Wichmann-Verlag, Heidelberg, pp. 12-23. Benz, U., Hofmann,P., Willhauck, G., Lingenfelder, I., Heynen, M., 2004. Multi-resolution, object -oriented fuzzy analysis of remote sensing data for GIS -ready information. ISPRS Journal of Photogrammetry and Remote Sensing 58, 239-258.
Literature cited 2: Beyer, H.L., 2004. Hawth ' s analysis tools for ArcGIS, http://www.spatialecology. Com/htools (last accessed 08.12.13). Blaschke, T., 2010. Object based image analysis for remote sensing. ISPRS Journal of Photogrammetry and Remote Sensing 58, 239-258.