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ID: 60082
Title: Multitemporal landslides inventory map updating using spaceborne SAR analysis.
Author: C.Del Ventisette, G. Moretti, N. Casagli.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 238-246 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Landslides inventory, Surface deformation, SAR interferometry, Remote sensing, Valfurva.
Abstract: Deep seated gravitational slope deformation and slow moving landslides on large areas were analyzed by spaceborne SAR interferometry: a test site in the Italian Alps of about 300 Km2 was selected for updating pre-existing landslide inventory maps based on the advanced interferometric processing technique (A-DinSAR). SAR images from ERS-1/2 satellites (1995-2000) and from Envisat satellite (2002-2009) have been used, allowing the deferred -time analysis of past movements and the record of recent slope movements. In the multi-temporal updated landslide inventory database, the characteristics of the landslides were highlighted: geometry, state of activity, typology, monitoring systems, interventions, source of information and the updating time and actions. Furthermore, for each landslide area, the occurrence of persistent scatterers points and the statistical description of their velocities were reported. This methodology may allow the systematic updating of landslides inventory maps keeping all information on each landslide, becoming the basic tool for the realization and updating of thematic maps such as the landslide susceptibility map.
Location: TE 15 New Biology Building
Literature cited 1: Agliardi, F., Crosta, G., Zanchi, A., 2001. Structural constraints on deep-seated slope deformation kinematics. Engineering Geology 59 (1-2), 83-102. Bianchini, S., Cigna, F., Del Ventisette, C., Moretti, S., Casagli, N., 2012. Detecting and monitoring landslide phenomena with Terra SAR-X persistent scatteres data: the gimigliano case study in Calabria Region (Italy) International Geoscience and Remote Sensing Symposium (IGARSS), 982-985 (art.no.6351237).
Literature cited 2: Bianchini, S., Cigna, F., Righini, G., Proietti, C., Casgli, N., 2012a. Landslide hotspot mapping by means of persistent scatterer interferometry. Environmental Earth Sciences, http://dx.doi.org/10.1007/s12665-012-1559-5. Bianchini, S., Cigna. F., Del Ventisette, C., Moretti, S., Casagli, N., 2012b. Detecting and monitoring landslide phenomena with TerraSAR-X persistent scatterers data: the gimigliano case study in Calabria Region (Italy) In: International Geoscience and Remote Sensing Symposium (IGARSS).

ID: 60081
Title: Effect of bulk chemistry in the spectral variability of igneous rocks in VIS-NIR region: Implications to remote compositional mapping.
Author: Archana M. Nair, George Mathew.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 2227-237 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: VIS-NIR, Reflectance spectroscopy, Rock spectra, Remote sensing, Compositional mapping.
Abstract: In the present study, a range of igneous rocks with weight percentage of silica ranging from 45 % to 70% were used to generate reflectance spectra in the VIS-NIR region. The laboratory generated reflectance spectra of these rocks were used to study the effect of chemical composition and mineralogy on the spectral properties. The characteristic spectral features were evaluated based on the mineralogical and chemical characteristics of the rocks. The main spectral features in the VIS-NIR region are the 0.07 ?m absorption band due to the inter valance charge transfer between Fe2+ and Fe3+ termed as Band F, the 1?m broad absorption band from Fe2+ at the octahedral sites in pyroxene termed as Band I, the 1.9 ?m and 2.3 ?m narrow absorption bands due to H2o or OH functional group in hydrated minerals. The 2 ?m absorption feature (Band ii; Cloutis and Gaffey, 1991) is observed as a weak feature in all the mafic rocks. The analysis of Band I with the bulk chemistry and mineralogy, we observed a positive correlation to the bulk Ca abundance. Rocks with high bulk calcic content exemplify Band I as a prominent spectral feature towards longer wavelength. Consequently, basalt, gabbro and anorthositic rocks show Band I as a strong feature. However, rocks with low bulk Calcic content show Band I as a weak absorption feature observed towards shorter wavelength. Thus, igneous rocks of alkaline affinity have subdued Band I feature that appears towards shorter wavelength. The analysis of Band F with the bulk chemistry and mineralogy showed a positive correlation to the bulk Fe abundance. The results of the present study have implications towards remote compositional mapping and lithological discrimination for planetary studies.
Location: TE 15 New Biology Building
Literature cited 1: Adams, J.B., 1974. Visible and near-infrared diffuse reflectance spectras of pyroxenes as applied to remote sensing of solid objects in the solar system. J. Geophys. Res. 79, 4829-4836. Bandfield, J.L., 2006. Extended surface exposures of granitoid compositions in Syrtis Major, Mars, Geophys, Res. Lett., http:// dx.doi.org/10.1029/2005 GLO25559.
Literature cited 2: Bandfield, J.L., Rogers, A.D., 2008. Olivine dissolution by acidic fluids in Argyre Planitia, Mars: evidence for a widespread process? Geology, http://dx.doi.org/10.1130/G24724A.1. Burns, R.G., 1993. Origin of electronic spectra of minerals in the visible to near infrared region .In: Pieters, C.M., Englert, P.A.J., (Eds), Remote Geochemical Analysis: Elemental and Mineralogical Composition. Cambridge University Press, Cambridge, pp. 1-28.

ID: 60080
Title: Remote sensing net primary productivity (NPP) estimation with the aid of GIS modeled shortwave radiation (SWR) In a Southern African Savanna.
Author: Godfrey Pachavo, Amon Murwira.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 217-226 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Remote sensing, NPP, MODIS, GIS, SWR, DMP.
Abstract: We tested whether and to what extent a remote sensing net primary productivity (NPP) estimation model based on the moderate resolution imaging spectroradiometer (MODIS) data and GIS modeled shortwave radiation can be used to estimate NPP in a southern African Savanna landscape. To accomplish this, we compared the results of our model with results obtained using an established rainfall-NPP regression model developed by Lieth and Whittaker (1975) for the savanna landscape, as well as the dry matter productivity (DMP) remotely sensed model. Results show that our model estimates do not significantly (p> 0.05) differ with results from the Lieth regression model with an R2 of 0.67. In addition, results showed that our remotely sensed NPP correlated significantly (p>0.05) with the DMP results (Pearson Correlation) R=0.91). These results suggest that we can successfully model African Savanna NPP using MODIS remotely sensed data in combination with GIS modeled clear sky and topographically based shortwave radiation (SWR) flux.
Location: TE 15 New Biology Building
Literature cited 1: Chenje, I., Jhonson, R., 1998. The state of the Environment of the Southern Africa. Maseru, Harare, SADC. Esri, 1998. ArcView GIS 3.2. Environmental Systems Research Institute, Redlands, CA.
Literature cited 2: Goetz, S., Prince, S., Small, J., G leason, A., 2000. Interannual variability of global terrestrial primary production: results of a model driven with satellite observations. Journal of Geophysical Research 105 (D15). Grace, J., Jose, S.J., Meir, P., Miranda, H.S., Montes, R.A., 2006. Productivity and carbon fluxes of tropical savannas. Journal of Biogeography 33, 387-400.

ID: 60079
Title: Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data.
Author: Christopher E. Churches, Peter J. Wampler, Wanxiao Sun, Andrew J. Smith.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 203-216 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Land cover, Deforestation, Image normalization, FAO, Supervised classification, Fuzzy classification.
Abstract: This study uses 2010-2011 Landsat Thematic Mapper (TM) imagery to estimate total forested area in Haiti. T he thematic map was generated using radiometric normalization of digital numbers by a modified normalization method utilizing pseudo-invariant polygons(PIPs), followed by supervised classification of the mosaicked image using the Food and Agriculture Organization (FAO) of the United Nations Land Cover Classification System. Classification results were compared to other sources of land-cover data produced for similar years, with an emphasis on the statistics presented by the FAO. Three global land cover datasets (GLC2000, Globcover, 2009, and MODIS MCDI 12 Q1), and a national-scale dataset (a land cover analysis by Haitian National Centre for Geospatial Information (CNIGS) were reclassified and compared. According to our classification, approximately 32.3% of Haiti ' s total land area was tree covered in 2010-2011. This result was confirmed using an error-adjusted area estimator, which predicted a tree covered area of 32.4%. Standardization to the FAO ' s forest cover class definition reduces the amount of tree cover of our supervised classification to 29.4%. This result was greater than the reported FAO value of 4% and the value for the recoded GLC2000 dataset of 7.0%, but is comparable to values for the three other recoded datasets: MCDI 12 Q1 (21.1%), Globcover (2009) (26.9%), and CNIGS (19.5%). We propose that at coarse resolutions, the segmented and patchy nature of Haiti ' s forests resulted in a systematic underestimation of the extent of forest cover. It appears the best explanation for the significant difference between our results, FAO statistics, and compared datasets is the accuracy of the datasets is the accuracy of the data sources and the resolution of the imagery used for land cover analyses. Analysis of recoded global datasets and results from this study suggest a strong linear relationship (R2= 0.996 for tree cover) between spatial resolution and land cover estimates.
Location: TE 15 New Biology Building
Literature cited 1: Aide, T.M., Clark, M.L., Grau, H.R., Lopez-Carr, D., Levy, M.A ., Redo, D., Bonilla-Moheno, M., Riner,G., Andrade-Nunez, M.J., Muniz,M., 2102. Deforestation and reforestation of Latin America and the Caribbean (2001-2010). Biotropica 45 (2), 262-271. Alvarez-Berrios, N.L., Redo, D.J., Aide, T.M., Clark, M.L., Grau, R., 2013. Land Change in the Greater Antilles between 2001 and 2010. Land 2 (20, 81-107.
Literature cited 2: Bannister, M.E., 2003. Agroforestry adoption in Haiti: the importance of household and farm characteristics. Agroforestry Systems 57 (2), 149-157, http:/dx.doi.org/10.1023/A: 1023973623247. Bartholome, E., Belward, A.S., 2005. GLC2000: a new approach to global land cover mapping from Earth observation data: International Journal of Remote Sensing 26(9), 1959-1977.

ID: 60078
Title: Assessment of the EUMETSAT LSA-SAF evapotranspiration product for drought monitoring in Europe.
Author: Guadalupe Sepulcre-Canto, Jurgen Vogt, Alirio Arboleda, Tiberiu Antofie.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 190-202 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Evapotranspiration, Water stress, Drought, LSA-SAF, EUMETSAT, EDO.
Abstract: Evapotranspiration is a key parameter for water stress assessment as it is directly related to the moisture status of the soil-vegetation system and describes the moisture transfer from the surface to the atmosphere. With the launch of the Meteosat Second Generation geostationary satellites and the setup of the Satellite Application facilities, it became possible to operationally produce evapotranspiration data with high spatial and temporal evolution of the potential of the evapotranspiration (ET) product from the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA-SAF) for drought assessment and monitoring in Europe. To assess the potential of this product, the LSA-SAF ET was used as input for the ratio of ET to reference evapotranspiration (ETo), the latter estimated from the ECMWF interim reanalysis. In the analysis two case studies were considered corresponding to the drought episodes of spring/summer 2007 and 2011. For these case studies, the ratio ET/ETo was compared with meteorological drought indices (SPI, SPIE, and Sc-PDSI for 2007 and SPI for 2011) as well as with the anomalies of the fraction of absorbed photosynthetic active radiation (fAPAR) derived from remote sensing data. The meteorological and remote sensing indicators were taken from the European Drought Observatory (EDO) and CARPATCLIM climatological atlas. Results show the potential of ET/ETo to characterize soil moisture variability, and to give additional information to fAPAR and to precipitation distribution for drought assessment. The main limitations of the proposed ratio for drought characterization are discussed, including options to overcome them. These options include the use of filters to discriminate areas with a low percentage vegetation cover or areas that are not in their growing period and the use of evapotranspiration without water restriction (ETwwr), obtained as output of the LSA-SAF model instead of ETo. The ET/ETwwr ratio was tested by comparing its accumulated values per growing period with the winter wheat yield values per country published by Eurostat. The results point to the potential of using the remote sensing based LSA-SAF evapotranspiration and ET/ETwwr ratio for vegetation monitoring at large scale, especially in areas where data is generally lacking.
Location: TE 15 New Biology Building
Literature cited 1: Alley, W.M., 1984. The Palmer Droughts Severity Index: Limitations and assumptions. Journal of Climate and Applied Meteorology 23, 1100-1109. Anderson, M.C., Hain, C., Waedlow, B., Pimstein, A., Mecikalski, J.R., Kutas, P., 2011. Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United states. Journal of Climate 24, 2025-2044.
Literature cited 2: Anderson, M.C., Norman, J.M., Diak, G.R., Kustas, W.P., Mecikalski, J.R., 1997. A two-source time -integrated model for estimating surface fluxes using thermal infrared remote sensing. Remote Sensing of Environment 60, 195-216. Balsamo, G., Viterbo, P., Beijaars, A., Van den Hurk, B., Hirschi, M., Beets, A.K., Scipal, K., 2009. A revised hydrology for the ECMWF model: verification from field site to terrestrial water storage and impact in the integrated forecast system. Journal of Hydrometeorology 10 (3), 623-643.

ID: 60077
Title: Modeling the spatial distribution of above -ground carbon in Mexican coniferous forests using remote sensing and a geostatistical approach.
Author: J. Mauricio Galeana-Pizana, Alejandra Lopez-Caloca, Penelope Lopez-Quiroz, Jose Luis Silvan-Cardensa, Stephane Couturier.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 179-189 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Above-ground biomass, Interferometric coherence, Spatial autocorrelation, Regression-Kriging, Coniferous forest, Mexico.
Abstract: Forest conservation is considered an option for mitigating the effect of greenhouse gases on global climate, hence monitoring forest carbon pools at global and local levels is important. The present study explores the capability of remote-sensing variables (vegetation indices and textures derived from SPOT5; backscattering coefficient and interferometric coherence of ALOSPALSAR images) for modeling the spatial distribution of above-ground biomass in the Environmental Conservation Zone of Mexico City. Correlation and spatial autocorrelation coefficients were used to select significant explanatory variables in fir and pine forests. The correlation for interferometric coherence in HV polarization was negative, with correlations coefficients r=-0.83 for the fir and r=-0.75 for the pine forests. Regression-krigings showed the least root mean square error among the spatial interpolation methods used, with 37.75 tC/ha for fir forests and 29.15 tC/ha for pine forests. The results showed that a hybrid geospatial method, based on interferometric coherence data and a regression-kriging interpolator, has good potential for estimating above-ground biomass carbon.
Location: TE 15 New Biology Building
Literature cited 1: Acosta-Mireles, M., Vargas-Hernandez, J., Velasquez-Martinez, A., Etcheves-Barra, J.D., 2002. Estimcion de la biomasa aerea mediante el uso de relaciones alometricas en seis species en Oaxaca, Mexico, Agrociencia, 725-736. Anselin, L., REey, S., 2010. Perspective on Spartial Data Analysis. Springer, USA, 290 p.
Literature cited 2: Avendano-Hernandez, D.M., Acosta-Mireles, M., Carrilllo-Anzures, F., Etchevers-Barra, J.D., 2009. Estimacion de biomasa y carbon en un bosque de Abies religiosa. Fitotecnia Mexicana, 233-238. Balzter, H., Rowland, C., Saich, P., 2007. Forest canopy height and carbon estimation at Monks Wood National Natura Reserve, UK using dual-wavelength SAR Interferometry. Remote Sensing of Environment 108, 224-239.

ID: 60076
Title: Fluorescence, PRI and canopy temperature for water stress detection in cereal crops.
Author: C.Panigada, M. Rossini, M. Meroni, C.Cilia, L.Busetto, S. Amaducci, M.Boschetti, S.Cogliati, V.Picchi, F. Pinto, A.Marchesi, R.Colombo.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 167-178 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Airborne, Water stress, Stress detection, Thermal, PRI, Fluorescence.
Abstract: Narrow-band multispectral remote sensing techniques and thermal imagery were investigated for water stress detection in cereal crops. Visible and near infrared AISA Eagle (Specim, Finland) and thermal AHS160 (Sensytech Inc., USA) imageries were acquired with an airborne survey on a farm-level experimental site where maize (Zea mays L.) and sorghum (Sorghum bicolor L) were grown with three different irrigation treatments. Vegetation biophysical and eco-physiological measurements were collected concurrently with the airborne campaign. Leaf fluorescence yield (?F/fm ' ) resulted to be a good indirect measure of water stress. Therefore, ? F/Fm ' measurements were compared against remotely sensed indicators: (i) the photochemical Reflectance Index (PRI), (ii) the sun-induced chlorophyll fluorescence at 760 nm (F760), retrieved by the Fraunhofer line depth method and (iii) the canopy temperature (Tc) calculated decoupling soil and vegetation contributions. Tc was related to ?F/Fm` with the highest determination coefficient (R2= 0.65), followed by PRI586 (reference band at 586 nm) (R2=0.51). The relationship with F760 was significant but weaker (R2=0.36). The coefficient of determination increased up to 0.54 when pigment concentration was considered by multiplying ?F/Fm` and chlorophyll content, confirming the close relationship between passive fluorescence signal, pigment content and light photosystem efficiency. PRI586, F760, and Tc extracted from the plots by the three remotely sensed indicators. This was confirmed by the visual observation of the PRI586, F760 and Tc maps, while sorghum plots, F760 and Tc appeared more sensitive to water stress compared to PRI586.
Location: TE 15 New Biology Building
Literature cited 1: Baldridge, A.M., Hook, S.J., Grove, C.I., Rivera, G., 2009. The ASTER spectral library version 2.0 Remote Sensing of Environment 113, 711-715. Ballester, C., Jimenez-Bello, M.A., Castel, J.R., Intrigliolo, D.S., 2013. Usefulness of thermography for plant water stress detection in citrus and persimmon trees. Agricultural and Forest Meteorology 168, 120-129.
Literature cited 2: Baluja, J., Diago, M.P., Balda, P., Zorer, R., Meggio, F., Morales, F., Tardaguila, J., 2012. Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrigation Science 30, 511-522. Berni, J.A.J., Zarco-Tejada, P.J., Squarez, L., Fereres, E., 2009a. Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing 47, 722-738.

ID: 60075
Title: Hierarchical Segmentation of urban satellite imagery.
Author: Bardia Yousefi, Seyed Mostafa Mirhassani, Alireza AhmadiFard, MohammadMehdi Hosseini.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 158-166 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Very high resolution satellite imagery, Gabor wavelet, Bayesian classifier, Relaxation labeling.
Abstract: This paper proposes a method to combine contextual, structural, and spectral information for classification. This method is an integrated method for automatically classifying urban-area objects in very high-resolution satellite imagery. The approach addresses three aspects. First, the Gabor wavelet is applied to the image along with morphological operations, with the sparsity of the outcome considered. A Bayesian classifier then categorizes the different classes, such as buildings, roads, open areas, and shadows. There are some false positives (wrong classification), and false negatives (non-classification) in the initial results. These results can be corrected by the relaxation labeling categorization of the unknown regions. The novelty of the proposed approach lies in the extensive use of spatiotemporal features considering the sparsity of urban objects. The results indicate improvements in classification through relaxation labeling compared with existing methods.
Location: TE 15 New Biology Building
Literature cited 1: Ahmadi, F.F., Ebadi, H., 2009. An integrated photogrammetric and spatial database management system for producing fully structured data using aerial and remote sensing images. Sensors 9 (4), 2320-2333. Al Khudairy, D.H., Caravaggi, I., Glada, S., 2005. Structural damage assessments from IKONOS data using change detection, object-oriented segmentation, and classification techniques. Photogr. Eng. Remote Sensing 71 (7), 825-837
Literature cited 2: Araya, Y.H., Cabral, P., 2010. Analysis and modeling of urban land cover change in Setbal and Sesimbra, Portugal. Remote Sensing 2, 1549-1563. Aubrecht, C., Steinnocher, K., Hollaus, M., Wagner, W., 2008. Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use. Comput. Environ. Urban Syst. 33 (1), 15-25.

ID: 60074
Title: Oil spill detection using synthetic aperture radar images and feature selection in shape space.
Author: Yue Guo, Heng Zhen Zhang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 146-157 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: : SAR, Oil-spill, Lookalikes, Feature selection, Shape space.
Abstract: The major goal of the present study is to describe a method by which synthetic aperture radar (SAR) images of oil spills can be discriminated from other phenomena of similar appearance. The optimal features of these dark formations are here identified. Because different materials have different physical properties, they form different shapes. In this case, oil films and lookalike materials have different fluid properties. In this paper, 9 shape features with a total of 95 eigenvalues were selected. Using differential evolution feature selection (DEFS), similar eigenvalues were extracted from total space of oil spills and lookalike phenomena. This process assumes that these similar eigenvalues impair classification. These similar eigenvalues are removed from the total space, and the important eigenvalues (IEs), those useful to the discrimination of the targets, are identified. At least 30 eigenvalues were found to be inappropriate for classification of our shapes spaces. The proposed method was found to be capable of facilitating the selection of the top 50 IEs. This allows more accurate classification. Here, accuracy reached 94%. The results of the experiments show that this novel method performs well. It could also be made available to teams across the world very easily.
Location: TE 15 New Biology Building
Literature cited 1: Ai-Bin, J., 2009. Research on Visual Feature Analysis and Classification of Network Education Graphics Resources. Shandong Normal University. Danisi, A., Di Martino, G., Iodice, A., Riccio, D., Ruello, G., Tello, M., Mallorqui, J.J., Lopez-Martinez, C., 2007, SAR simulation of ocean scenes covered by oils slicks with arbitrary shapes. IGARSS 2007, 1314-1317.
Literature cited 2: Brekke, C., Solberg, A., 2005a. Oil spill detection by satellite remote sensing. Remote Sensing of Environment 95 (1), 1-13. Brekke, C., Solberg, A., 2005b. Feature extraction for oil spill detection based on SAR images. Lecture Notes in Computer Science 3540, 75-84, http://dx.doi.org/10.1007/b 137285.

ID: 60073
Title: Temporal dynamics of spatial heterogeneity over cropland quantified by time-series NDVI, near infrared and red reflectance of Landsat 8 OLI imagery.
Author: Yanling Ding, Kai Zhao. Xingming Zheng, Tao Jiang.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 139-145 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Spatial heterogeneity, Mean length variability, NDVI, Near infrared and red reflectance, Fractional vegetation cover.
Abstract: Spatial heterogeneity is an important characteristic of the land surface. Because multi-spectral bands are used to describe the land surface, an approach has to be established to characterize the surface spatial heterogeneity from multi-spectral remote-sensing observations. This work aims at quantifying the spatial heterogeneity of cropland using variograms for multi-temporal NDVI, near infrared (NIR) and red reflectance. A concept of mean length variability is proposed to compare the difference in spatial heterogeneity detected by variables with different magnitudes. The important temporal changes in spatial heterogeneity observed by NDVI, NIR and red bands over cropland are a result of changes in the fraction of vegetation cover. The results indicate the following: (1) the NIR and red variables detect a similar spatial heterogeneity of the cropland with similar values of the mean length variability before the sowing crops; (2) the NDVI, NIR and red values capture different degrees of spatial heterogeneity when vegetation is low; (3) over medium vegetation cover, the NDVI and NIR values capture similar spatial heterogeneity, which is low compared to the red band due to the homogeneity of soil; and (4) the spatial heterogeneity quantified by the NIR values is more heterogeneous than those of the NDVI and red values when vegetation cover is high. The red reflectance is sensitive to soil properties while the NIR reflectance responds to vegetation. The spatial heterogeneity of red reflectance decreases and that of the NIR reflectance increases with the growth of vegetation. The NDVI value shows the greatest heterogeneity in the early stage of crop growth. With an increase in the image pixel size, the spatial heterogeneity quantified by the mean length variability of the NDVI, NIR and red variables tends to be the same.
Location: TE 15 New Biology Building
Literature cited 1: Allen, W.A., Richardson, A.J., 1968. Interaction of light with plant canopy. Journal of the optical Society of America 58 (8), 1023-1028. Burgheimer, J., Wilske, B., Maseyk, K., Karnieli, A., Zaddy, E., Yakir, D., Kesselmeier, J., 2006. Relationships between Normalized Difference Vegetation Index (NDVI) and carbon fluxes of biologic soil crusts assessed by ground measurements. Journal of Arid Environment 64, 651-669.
Literature cited 2: Chen, P.Y., Chen, C.H., Hsu, N.S., Wu, C.M., Wen, J.C., 2012. Influence of heterogeneity on unsaturated hydraulic properties: 1. Local heterogeneity and scale effect. Hydrological processes 22 (1), 61-78. Currah, P.J., Atkinson, P.M., 1998. Geostatistics and remote sensing. Progress in Physical Geography. 22 (1), 61-78.

ID: 60072
Title: Bayesian area-to -point Kriging using expert knowledge as informative priors.
Author: Phuong N. Truong, Gerard B.M. Heuvelink, Edzer Pebesma.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 128-138 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Spatial disaggregation, Area-to-point kriging, Informative Bayesian area-to-point, estimator, Statistical expert elicitation, Expert knowledge, Area-to-point conditional simulation.
Abstract: Area-to-point (ATP) kriging is a common geostatistical framework to address the problem of spatial disaggregation or downscaling from block support observations (BSO) to point support (poS) predictions for continuous variables. This approach requires that the poS variogram is known. Without poS observations, the parameters of the poS variogram cannot be deterministically estimated from BSO, and as a result, the poS variogram parameters are uncertain. In this research, we used Bayesian ATP conditional simulation to estimate the poS variogram parameters from expert knowledge and BSO, and quantify uncertainty of the poS variogram parameters and disaggregation outcomes. We first clarified that the nugget parameter of the poS variogram cannot be estimated from only BSO. Next, we used statistical expert elicitation techniques to elicit the poS variogram parameters from expert knowledge. These were used as informative priors in a Bayesian inference of the poS variogram from BSO and implemented using a Markov chain Monte Carlo algorithm. ATP conditional simulation was done to obtain stochastic simulations at point support. MODIS (Moderate Resolution Imaging Spectroradiometer) atmospheric temperature profile data were used in an illustrative example. The outcomes from the Bayesian ATP inference for the Matern variogram model parameters confirmed at the posterior distribution of the nugget parameter was effectively the same as its prior distribution; for the other parameters, the uncertainty was substantially decreased when BSO were introduced the Bayesian ATP estimator. This confirmed that expert knowledge brought new information to infer the nugget effect at poS while BSO only brought new information to infer the other parameters. Bayesian ATP conditional simulations provided a satisfactory way to quantify parameters and model uncertainty propagation through spatial disaggregation.
Location: TE 15 New Biology Building
Literature cited 1: Albert, J., 2009. Bayesian Computation with R. Springer, New York. Atkinson, P.M., 2013. Downscaling in remote sensing. Int. J. Appl. Earth Obs. Geoinf. 22, 106-114.
Literature cited 2: Chib, S., Greenberg, E., 1995. Understanding the Metropolis-Hastings algorithm.Am.Stat.49, 327-335. Chiles, J.P., Delfiner, P., 1999. Geostatistics: Modeling Spatial Uncertainty. Wiley Series in probability and Statistics. Wiley, New York.

ID: 60071
Title: Aquatic vegetation indices assessment through radiative transfer modeling and linear mixture simulation.
Author: Paolo Villa, Alijafar Mousivand, Mariano Bresciani.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 113-127 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Vegetation indices, Remote sensing, Sensitivity analysis, Radiative transfer models, NDAVI, WAVI.
Abstract: Although spectral vegetation indices (Vis) have been widely used for remote sensing of vegetation in general, such indices have been traditionally targeted at terrestrial, more than aquatic, vegetation. This study introduces two new VIs specifically targeted at aquatic vegetation: NDAVI and WAVI and assesses their performance in capturing information about aquatic vegetation features by comparison with preexisting performance in capturing information about aquatic vegetation features by comparison with preexisting indices: NDVI, SAVI and EVI. The assessment methodology is based on: (i) theoretical radiative transfer modeling of vegetation canopy-backgrounds coupling, and (ii) spectral linear mixture simulation based on real-case endmembers. Two study areas, Lake Garda and Lakes of Mantua, in Northern Italy, and a multisensory dataset have been exploited for our study. Our results demonstrate the advantages of the new indices. In particular, NDAVI and WAVI sensitivity scores to LAI and LIDF parameters were generally higher than pr-existing indices ' ones. Radiative transfer modeling and real-case based linear mixture simulation showed a general positive, non-linear correlation of vegetation indices with increasing LAI and vegetation fractional cover (FC), more marked for NDVI and NDAVI. Moreover, NDAVI and WAVI show enhanced capabilities in separating terrestrial from aquatic vegetation response, compared to pre-existing indices, especially of NDVI. The new indices provide good performance in distinguishing aquatic from terrestrial vegetation: NDAVI over low density vegetation (LAI< 0.7-1.0, FC<40-50%), and WAVI over medium-high density vegetation (LAI>1.0, FC> 50%). Specific vegetation indices can therefore improve remote sensing applications for aquatic vegetation monitoring.
Location: TE 15 New Biology Building
Literature cited 1: Asrar, G., Myneni, R.B., Li, Y., Kanemasu, E.T., 1989. Measuring and modeling spectral characteristics of a tallgrass prairie. Remote Sensing of Environment 27 (2), 143-155. Bacour, C., Jacquemoud, S., Tourbier, Y., Dechambre, M., Frangi, J.P., 2002. Design and analysis of numerical experiments to compare four canopy reflectance models. Remote Sensing of Environment 79, 72-83.
Literature cited 2: Borja, A., Elliott, M., Henriksen, P., Marba, N., 2013. Transitional and Coastal waters ecological status assessment: advances and challenges resulting from implementing the European Water Framework Directive. Hydrobiologia 704, 213-229. Bresciani, M., Stroppiana, D., Fila, G.L., Montagna, M., Giardino, C., 2009. Monitoring reed vegetation in environmentally sensitive areas in Italy.European Journal of Remote Sensing 41 (2, 125-137.

ID: 60070
Title: High Nature value farmland identification from satellite imagery, a comparison of two methodological approaches.
Author: Gerard Hazeu, Pavel Milenov, Bas Pedroli, Vessela Samoungi, Michiel Van Eupen, Vassil Vassilev.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 98-112 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: HNV farmland, Monitoring, Mapping, Remote sensing, Netherlands, Bulgaria.
Abstract: While the identification of High Nature Value (HNV) farmland is possible using the difference types of spatial information categories available at European scale, most data used is still too coarse and therefore only provides an approximate estimate of the presence of HNV farmland. This paper describes two promising methods using remote sensing-one for HNV farmland identification and one for change detection within HNV farmland. The performance of the two methods is demonstrated by detailed results for two case studies-the Netherlands for the HNV farmland identification, and Bulgaria for change detection within HNV farmland. An estimation of the presence of HNV farmland or of HNV farmland change can well be based on high -resolution satellite imagery, but the classification method must be adapted to regional characteristics such as field size and type of landscape. The temporal variability and bio-climatological characteristics across Europe do not allow for a simple European classification of HNV farmland. Also comparison between years is complicated because of the large impact of seasonal variation in the land cover expression and the complexity of the HNV farmland definitions. Although HNV farmland detection methods are promising, remote sensing alone does not yet provide the appropriate tools for adequate monitoring.
Location: TE 15 New Biology Building
Literature cited 1: Andersen, E., Baldock, D., Bennett, H., Beaufoy, G., Bignal, E., Brouwer, F., Elbersen, B., Eiden, G., Godeschalk, F., Jones, G., McCracken, D., Nieuwenhuizen, W., van, Eupen, M., Hennekens, S., Zervas, G., 2003. Developing a High Nature Value Farming area indicator. Report to the European Environment Agency, Copenhagen. Beaufoy, G., Jones, G., De Rijck, K., Kazakova, Y., 2008. High Nature Value farmlands: recognizing the importance of South East European landscapes (Bulagaria & Romania). In: WWF Danube-Carpathian Programme and European Forum on Nature Conservation and Pastoralism.
Literature cited 2: Cooper, T., Arblaster, K., Baldock, D., Farmer, M., Beaufoy, G., Jones, G., Poux, X., McCracken, D., Bignal, E., Elbersen, B., Wascher, D., Angelstam, P., Roberge, J-M., Pointerau, P., Seffer, J., Galvanek, D., 2007. Final report for the study on HNV indicators for evaluation. Report for the European Commission, DG Agriculture, contract notice 2006-G4-04. Institute for European Environmental Policy (IEEP), London, pp.190. Definiens, 2005. Definiens eCognition Version 5 Object Oriented Image Analysis User 5 Guide. Definiens AG, Munich.

ID: 60069
Title: Variation analysis of lake extension in space and time from MODIS images using random sets.
Author: Xi Zhao, Alfred Stein, Xiang Zhang, Lian Feng, Xiaoling Chen.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 86-97 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Water extent, Spatial- temporal pattern, Variation, Random spread process, Random set, Multitemporal images.
Abstract: Understanding inundation in wetlands may benefit from a joint variation analysis in changes of size, shape, position and extent of water bodies. In this study, we modeled wetland inundation as a random spread process and used random sets to characterize stochastic properties of water body extents. Periodicity, trend and random components were captured by monthly and yearly random sets that were derived from multitemporal images. The covering-Distance matrix and related operators summarized and visualized the spatial pattern and quantified the similarity of different inundation stages. The study was carried out on the Poyang Lake wetland area in China, and MODIS images for a period of eleven years were used. Results revealed that substantial seasonal dynamic pattern of the inundation and a subtle interannual change in its extension from 2000 to 2010. Various spatial properties including the size, shape, position and extent are visible: areas of high flooding risk are very elongated and locate along the water channel; few of the inundation areas tend to be more circular and spread extensively; the majority of the inundation areas have various extent and size in different month and year. Large differences in the spatial distribution of inundation extents were shown to exist between months from different seasons. A unique spatial pattern occurred during those months that a dramatic flooding or recession happened. Yearly random sets gave detailed information on the spatial distributions of inundation frequency and showed a shrinking trend from 2000 to 2009. 2003 is the partition year in the declining trend and 2010 breaking the trend as an abnormal year. Besides, probability bounds were derived from the model for a region that was attacked by flooding. This ability of supporting decision making is shown in a simple management scenario. We conclude that a random sets analysis is a valuable addition to a frequency analysis that quantifies inundation variation in space and time.
Location: TE 15 New Biology Building
Literature cited 1: Barndorff-Nielsen, O., Kendall, W., Lieshout, M., (Eds), 1999. Stochastic Geometry: Likelihood and Computation. Chapman & Hall/ CRC, Boca Raton, Fla., London. Benke, A., Chaubey, I., Milton, G., Dunn, E., 2000. Flood pulse dynamics of an unregulated river floodplain in the southeastern us coastal plain. Ecology 81, 2730-2741.
Literature cited 2: Bryant, R.G., Rainey, M.P., 2002. Investigation of flood inundation on playas within the zone of Chotts, using a time-series of AVHRR. Remote Sensing of Environment 82, 360-375. Cressie, N., 1993. Statistics for Spatial Data. Wiley-Interscience, New York, pp. 725-803.

ID: 60068
Title: Detecting pruning of individual stems using Airborne Laser Scanning data captured from an Unmanned Aerial Vehicle.
Author: Luke Wallace, Christopher Watson, Arko Lucieer.
Editor: F.D.van der Meer
Year: 2014
Publisher: Centre for Ecological Sciences
Source: Centre for Ecological Sciences
Reference: Applied Earth Observation and Geoinformation. Vol. 30. 76-85 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Laser Scanning, Unmanned Aerial Vehicle, Forest management, Pruning, Change detection.
Abstract: Modern forest management involves implementing optimal pruning regimes. These regimes aim to achieve the highest quality timber in the shortest possible rotation period. Although a valuable addition to forest management activities, tracking the application of these treatments in the field to ensure best practice management is not economically viable. This paper describes the use of Airborne Laser Scanner (ALS) data to track the rate of pruning in a Eucalyptus globules stand. Data is obtained from an Unmanned Aerial Vehicle (UAV) and we describe automated processing routines that provide a cost-effective alternative to field sampling. We manually prune a 500 m2 plot to 2.5 m above the ground at rates between 160 and 660 stems/ha. Utilising the high density ALS data, we first derived crown base height (CBH) with an RMSE of 0.60 m at each stage of pruning. Variability in the measurement of CBH resulted in both false positive (mean rate of 11%) and false negative detection (3.5%), however, detected rates of pruning of between 96% and 125 % of the actual rate of pruning were achieved. The successful automated detection of pruning within this study highlights the suitability of UAV laser scanning as a cost-effective tool for monitoring forest management activities.
Location: TE 15 New Biology Building
Literature cited 1: Alcorn, P.J., Bauhas, J., Thomas, D.S., James, R.N., Smith, R.G.B., Nicotra, A.B., 2008. Photosynthetic response to green crown pruning in young plantation-grown Eucalyptus pilularis and E. cloeziana. Forest Ecology and Management 255 (11), 3827-3838. Axelsson, P., 1999. Processing of laser scanner data algorithms and applications. ISPRS Journal of Photogrammetry and Remote Sensing 54 (2-3), 138-147.
Literature cited 2: Ben-Arie, J.R., Hay, G.J., Powers, R.P., Castilla, G., St-onge, B., 2009. Development of a pit filling algorithm for lidar canopy height models. Computers and Geosciences 35 (9), 1940-1949. Bollandsas, O., 2013. Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data. Statistical Methods and Applications 22 (1), 113-129.