ID: 60067
Title: Development of an invasive species distribution model with fine-resolution remote sensing.
Author: Chunyuan Diao, Le 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. 30. 65-75 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Saltcedar, Species distribution model, Fine scale, Harmonic analysis, Spatial autocorrelation, Remote sensing.
Abstract: Saltcedar (Tamarix spp) is recognized as one of the most aggressively invasive species throughout the Western United States. Mapping its suitable habitat is of paramount importance to effective management, and thus, becomes a high priority for conservation practitioners. In previous studies, species distribution models (SDMs) have been applied to predicting the suitable habitats of saltcedar at national scale, but at coarser spatial resolution (1 km). Although such studies achieved some success, they are lacking of capability to accommodate fine-scale resolution environmental variables, and therefore, fail to uncover detailed spatial pattern of habitats. The objective of this study was to develop a remote sensing driven SDM so as to characterize suitable habitats of saltcedar at very fine spatial scale (30 m). We exploited several fine-scale environmental predictors through remote sensing images, and utilized the logistic regression model to analyze the species-habitat relationship by identifying influential factors with subset selection criteria. We also incorporated the spatial autocorrelation achieved a higher accuracy than that of regression only model. Among 10 environmental variables, the distance to the river and the phonological attributes summarized by the harmonic analysis were regarded as the most significant in predicting the invasive potential of saltcedar. We conclude that remote sensing driven SDM has potential to identify the suitable habitat of saltcedar at a fine scale and locate appropriate areas at high risk of saltcedar infestation, which could benefit the early control and proactive management strategies to a large extent.
Location: TE 15 New Biology Building
Literature cited 1: Andrew, M.E., Ustin, S.L., 2009. Habitat suitability modeling of an invasive plant with advanced remote sensing data. Diversity and Distributions 15, 627-640.
Arieira, J., Karssenberg, D., Jong, S.d., Addink, E., Nunes da Cunha, C., Skoien, J., 2011. Integrating field sampling, geostatistics and remote sensing to map wetland vegetation in the Pantanal, Brazil, Biogeosciences 8, 667-686.
Literature cited 2: Borcard, D., Legendre, P., 2002. All-scale spatial analysis of ecological data by means of principal coordinates of neighbor matrices. Ecological Modelling 153, 51-68.
Briggs, W., Henson, V., 1995. The DFT: An Owner ' s Manual for the Discrete Fourier Transform. Society for Industrial and Applied Mathematics, Philadelphia.
ID: 60066
Title: Extraction of multilayer vegetation coverage using airborne LiDAR discrete points with intensity information in urban areas: A case study in Nanjing City, China.
Author: Wenquan Han, Shuhe Zhao, Xuezhi Feng, Lei 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. 56-64 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Airborne LiDAR, Urban vegetation, Laser point intensity, Multilayer vegetation coverage, Median filter.
Abstract: Urban vegetation is of a strategic importance for the life quality in the increasing urbanized societies. However, it is still difficult to extract accurately urban vegetation vertical distribution with remote sensing images. This paper presented an effective method to extract multilayer vegetation coverage in urban areas using airborne Light Detection and Ranging (LiDAR) discrete points with intensity information. It was applied in Nanjing City, one of the ecological cities in China. Firstly, a median filtering algorithm based on discrete points was used to restrain high-frequency noise. The airborne LiDAR data intensities of different urban objects were analyzed and obtained three rules, which can distinguish between vegetation and non-vegetation in urban areas, after removing the influence of topography. According to the footprint size and principles of distribution of the point cloud, multilayer vegetation coverage, including trees, shrubs and grass, was achieved by the inverse distance weighting (IDW) interpolation method. The results show that the overall accuracy of the vegetation point classification is 94.57%, which is much accurate than that of the methods in TerraSolid software, through comparing with the investigation in the field and Digital Orthophoto Maps (DOM). This method proposed in our work can be applied to in the extraction of multilayer vegetation coverage in urban area.
Location: TE 15 New Biology Building
Literature cited 1: Chen, L., Zhao, S., Han, W., Li, Y., 2012. Building detection in an urban area using LiDAR data and Quickbird imagery. International Journal of Remote Sensing 16, 5135-5148.
Chiesura, A., 2004. The role of urban parks for the sustainable city. Landscape and Urban Planning 68, 129-138.
Literature cited 2: Felix, M., Caroline, N., Timothy, M., Ian, H.W., 2009. Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modeling. Remote Sensing of Environment 113, 2152-2163.
Hartfield, K.A., Landau, KI., Leeuwen, W.J.D., 2011. Fusion of high resolution aerial multispectral and LiDAR data: land cover in the context of urban mosquito habitat. Remote Sensing 3, 2364-2383.
ID: 60065
Title: Urban growth and environmental impacts in Jing-Jin-Ji, the Yangtze, River Delta and Pearl River Delta.
Author: Jan Haas, Yifang Ban.
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. 42-55 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Urban growth, Land use/land cover (LULC), Ecosystem services, Landscape metrics, Environmental impact, Random forest.
Abstract: This study investigates land cover changes, magnitude and speed of urbanization and evaluates possible impacts on the environment by the concepts of land scape metrics and ecosystem services in China ' s three largest and most urban agglomerations: Jing-Jin-Ji, the Yangtze River Delta and the Pearl River Delta. Based on the classification of six Landsat TM and HJ-1A/B remotely sensed space-borne optical satellite image mosaics with a superior random forest decision tree ensemble classifier, a total increase in urban land about 28,000 km2 could be detected alongside a simultaneous decrease in natural land cover classes and cropland. Two urbanization indices describing both speed and magnitude of urbanization were derived and ecosystem services were calculated with a valuation scheme adapted to the Chinese market based on the classification results from 1990 and 2010 for the predominant land cover classes affected by urbanization: forest, cropland, wetlands, water and aquaculture. The speed and relative urban growth in Jing-Jin-Ji was highest, followed by the Yangtze River Delta and Pearl River Delta, resulting in a continuously fragmented landscape and substantial decreases in ecosystem service values of approximately 18.5 billion CNY with coastal wetlands and agriculture being the largest contributors. The results indicate both similarities and differences in urban-regional development trends implicating adverse effects on the natural and rural landscape, not only in the rural-urban fringe, but also in the cities ' important hinterlands as a result of rapid urbanization in China.
Location: TE 15 New Biology Building
Literature cited 1: Aguilera, F., Valenzuela, L.M., Botequilha-Leitao, A., 2011. Landscape metrics in the analysis of urban land use patterns: a case study in a Spanish metropolitan area. Landsc. Urban Plan. 99 (3-4), 226-238.
Ban, Y., Jacob, A., 2013. Object-based fusion of multitemporal multi-angle ENVISAT ASAR and HJ-1 multispectral data for urban land-cover mapping. IEEE Trans. Geosci. Rem. Sens. 51 (4), 1998-2006.
Literature cited 2: Ban, Y., Yousif, O.A., 2012. Multitemporal spaceborne SAR data for urban change detection in China. IEEE J. Sel. Top. Appl. Earth Obs. Rem. Sens. 5 (4), 1087-1094.
Breiman, L., 2001. Random Forests. Mach. Learn 45 (1), 5-32.
ID: 60064
Title: Performance and effects of land cover type on synthetic surface reflectance data and NDVI estimates for assessment and monitoring of semi-arid rangeland.
Author: Edward M. Olexa, Rick L. Lawrence.
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. 30-41 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Landsat, MODIS, Rangeland, Remote sensing, STARFM.
Abstract: Federal land management agencies provide stewardship over much of the rangelands in the arid and semi-arid western United States, but they often lack data of the proper spatiotemporal resolution and extent needed to assess range conditions and monitor trends. Recent advances in the blending of complementary, remotely sensed data could provide public lands managers with the needed information. We applied the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) to five Landsat TM and concurrent Terra MODIS scenes, and used pixel-based regression and difference image analyses to evaluate the quality of synthetic reflectance and NDVI products associated with semi-arid rangeland. Predicted red reflectance data consistently demonstrated higher accuracy, less bias, and stronger correlation with observed data than did analogous near-infrared (NIR) data. The accuracy of both bands tended to decline as the lag between base and prediction dates increased: however, mean absolute errors (MAE) were typically ? 10%. The quality of area-wide NDVI estimates was less consistent than either spectral band, although the MAE of estimates predicted using early season base pairs were ? 10% throughout the growing season. Correlation between known and predicted NDVI values and agreement with the 1:1 regression line tended to decline as the prediction lag increased. Further analyses of NDVI predictions, based on a 22 June base pair and stratified by land cover/land use (LCLU), revealed accurate estimates through the growing season; however, inter-class performance varied. This work demonstrates the successful application of the STARFM algorithm to semi-arid rangeland; however, we encourage evaluation of STARFM ' s performance on a per product basis, stratified by LCLU, with attention given to the influence of base pair selection and the impact of the time lag.
Location: TE 15 New Biology Building
Literature cited 1: Andelman, S., Gillem, K., Groves, C., Hansen, C., Humke, J., Klahr, T., Kramme, L., Moseley, B., Reid, M., Vander Schaaf, D., Coad, M., Deforest, C., Macdonald, C., Baumgarther, J., Hak, J., Hobbs, S., Lunte, L., Smith, L., Soper, C., 1999. The Columbia Plateau Ecoregional Assessment: A Pilot Effort in Ecoregional Conservation. The Nature Conservancy, Seattle, Washington.
Bailey, R.G., 1995. Description of the Ecoregions of the United States, second ed. U.S. Department of Agriculture, Forest Service, Washington, Dc.
Literature cited 2: Blanco, L.J., Ferrando, C.A., Biurrun, F.N., 2009. Remote sensing of spatial and temporal vegetation patterns in two grazing systems. Rangeland Ecology and Management 62, 445-451.
Booth, D.T., Tueller, P.T., 2003. Rangeland monitoring using remote sensing. Arid Land Research and Management. 17, 455-451.
ID: 60063
Title: Detection of windthrown trees using airborne laser scanning.
Author: Mattias Nystrom, Johan Holmgren, Johan E.S. Fransson, Hakan Olsson
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. 21-29 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Storm damage, Downed logs, Template matching, Active surface, ALS, LiDAR.
Abstract: In this study, a method has been developed for the detection of windthrown trees under a forest canopy, using the difference between two elevation models created from the same high density (65 points/m2) airborne laser scanning data. The difference image showing objects near the ground was created by subtracting a standard digital elevation model (DEM) from a more detailed DEM created using an active surface algorithm. Template matching was used to automatically detect windthrown trees in the difference image. The 54 ha study area is located in hemi-boreal forest in southern Sweden (Lat. 58? 29`N, Long. 13? 38` E) and is dominated by Norway spruce (Picea abies) with 3.5 % deciduous species (mostly birch) and 1.7 % Scots pine (Pinus sylvestris). The result was evaluated using 651 field measured windthrown trees. At individual tree level, the detection rate was 38 % with a commison error of 36%, Much higher detection rates were obtained for taller trees; 89% of the trees taller than 27 m were detected . For pine the individual tree detection rate was 82%, most likely due to the more easily visible stem and lack of branches. When aggregating the results to 40 m square grid cells, at least one tree was detected in 77% of the grid cells which according to the field measurements contained one or more windthrown trees.
Location: TE 15 New Biology Building
Literature cited 1: Axelson, P., 1999.Processing of laser scanner data-algorithms and applications. ISPRS Journal of Photogrammetry & and Remote Sensing 54, 138-147.
Axelsson, P., 2000. DEM generation from laser scanner data using adaptive TIN models. International Archives of Photogrammetry & Remote Sensing 33, 110-117.
Literature cited 2: Ballard, D., Brown, C.M., 1982. Computer Vision, 1st ed. Prentice Hall, Engelwood Cliffs, New Jersey.
Bebber, D., Thomas, S., 2003. Prism sweeps for coarse woody debris. Canadian Journal of Forest Research 33, 1737-1743.
ID: 60062
Title: Mapping long -term temporal change in imperviousness using topographic maps.
Author: James D. Miller, Stephen Grebby.
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. 9-20 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Imperviousness, Urban, Remote sensing, Hydrology, Land use change.
Abstract: Change in urban land use and impervious surface cover are valuable sources of information for determining the environmental impacts of urban development. However, our understanding of these impacts is limited due to the general lack of historical data beyond the last few decades. This study presents two methodologies for mapping and revealing long-term change in urban land use and imperviousness from topographic maps. Method 1 involves the generation of maps of fractional impervious surface for direct computation of catchment -level imperviousness based on an urban extent index. Both methods are applied to estimate change in catchment imperviousness in a town in the South of England, at decadal intervals for the period 1960-2010. The performance of each method is assessed using contemporary reference data obtained from aerial photographs, with the results indicating that both methods are capable of providing good estimates of catchment imperviousness. Both methods reveal that peri-urban developments within the study area have undergone a significant expansion of impervious cover over the period 1960-2010, which is likely to have resulted in changes to the hydrological response of the previously rural areas. Overall, results of this study suggest that topographic maps provide a useful source of determining long-term change in imperviousness in the absence of suitable data, such as remotely sensed imagery. Potential applications of the two methods presented here include hydrological modeling, environmental investigations and urban planning.
Location: TE 15 New Biology Building
Literature cited 1: Amirsalari, F., Li, Li, J., Guan, X., Booty, W.G., 2013. Investigation of correlation between remotely sensed impervious surfaces and chloride concentrations. International Journal of Remote Sensing 34, 1507-1525.
Arnold, C.L., Gibbons, C.J., 1996. Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American Planning Association 62, 243-258.
Literature cited 2: Bauer, M.E., Heinert, N.J., Doyle, J.K., Yuan, F., 2004. Impervious surface mapping and change monitoring using Landsat remote sensing. In: ASPRS Annual Conference Proceedings, Denver, Colorado, May 2004.
Bayliss, A.C., Black, K.B., Fava-Verde, A., Kjeldsen, T.R., 2006. URBEXT2000 - a new FEH catchment descriptor: calculation, dissemination and application. In: Joint Defra/EA Flood and Coastal Erosion Risk management R & D Programme. R & D Technical Report FD 1919/TR., pp. 49.
ID: 60061
Title: Validation of the ASCAT Soil Water Index using in situ data from the international Soil Moisture Network.
Author: Christoph Paulik, Wouter Dorigo, Wolgang Wagner, Richard Kidd.
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. 1-8 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Soil moisture, Remote sensing, Validation, Soil Water Index.
Abstract: Soil moisture is an essential climate variable and a key parameter in hydrology, meteorology and agriculture. Surface Soil Moisture (SSM) can be estimated from measurements taken by ASCAT onboard Metop-A and have been successfully validated by several studies. Profile soil moisture, while equally important, cannot be directly measured by remote sensing but must be modeled. The Soil Water Index (SWI) product developed for near real time applications within the frame work of the GMES project geoland 2 aims to provide such a modeled profile estimate using satellite data as input. It is produced from ASCAT SSM estimates using a two-layer water balance model which describes the relationship between surface and profile soil moisture as a function of time. It provides daily global data about moisture conditions for eight characteristic time lengths representing different depths.
The objective of this work was to assess the overall quality of the SWI data. Furthermore
We tested the assumptions of the used water balance model and checked if ancillary information about topography, water fraction and noise information are useful for identifying observations of questionable quality. SWI data from January 1st 2007 until the end of 2011 was compared to in situ soil moisture data from 664 stations belonging to 23 observation networks which are available through the International Soil Moisture Network (ISMN). These stations delivered 2081 time series at different depths which were compared to the SWI values.
The average of the significant Pearson correlation coefficients was 0.54 while being greater than 0.5 for 64.4% of all time series. It was found that the characteristic time length showing the highest correlation increases with in situ observation depth, thus confirming the SWI model assumptions. Relationship of the correlation coefficients with topographic complexity, water fraction, in situ observation depth, and soil moisture noise were found.
Location: TE 15 New Biology Building
Literature cited 1: Albergel, C., de Rosnay, P., Gruhier, C., Munoz Sabater, J., Hasenauer, S., Isaksen, L, Kerr, Y., Wagner, W., 2012. Evaluation of remotely sensed and modeled soil moisture products using global ground-based in situ observations. Remote Sensing of Environment 118, 215-226.
Albergel, C., Dorigo, W., Balsamo, G., Munoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu, R., Wagner, W., 2013a. Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses. Remote Sensing of Environment 138, 77-89.
Literature cited 2: Albergel, C., Dorigo, W., Reichle, R.H., Balsamo, G., de Rosnay, P., Munoz Sabater, J., Isaksen, L., de Jeu, R., Wagner, W., 2013 b. Skill and global trend analysis of soil moisture from reanalyses and microwave remote sensing. Journal of Hydrome- teorology 14 (4), 1259-1277.
Albergel, C., Rudiger, C., Carrer, D., Calvet, J. -c., Fritz, N., Naeimi, V., Bartalis, Z., Hasenauer, S., 2009. An evaluation of ASCAT surface soil moisture products with in-situ observations in Southwestern France. Hydrology and Earth System Sciences 13 (February (2), 115-124.
ID: 60060
Title: Distance metric -based forest cover change detection using MODIS time series.
Author: Xiaoman Huang, Mark A. Friedl.
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. 29. 78-92 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: MODIS, Change detection, Distance metrics, Time series, Forest disturbance.
Abstract: More than 12 years of global observations are now available from NASA ' s Moderate Resolution Imaging Spectroradiometer (MODIS). At this time series grows, the MODIS archive provides new opportunities for identification and characterization of land cover at regional to global spatial scales and interannual to decadal temporal scales. In particular, the high temporal frequency of MODIS provides a rich basis for monitoring land cover dynamics. At the same time, the relatively coarse spatial resolution of MODIS (250-500 m) presents significant challenges for land cover change studies. In this paper, we present a distance metric-based change detection method for identifying changed pixels at annual time steps using 500 m MODIS time series data. The approach we describe uses distance metrics to measure (1) the similarity between a pixel ' s annual time series for pixels of the same land cover class and (2) the similarity between annual time series from different years at the same pixel. Pre-processing, including gap-filling, smoothing and temporal subsetting of MODIS 500 m Nadir BRDF-adjusted Reflectance (NBAR) time series is essential to the success of our method. We evaluated our approach using three case studies. We first explored the ability of our method to detect change in temperate and boreal forest training sites in North America and Eurasia. We applied our method to map regional forest change in the Pacific Northwest region of the United States, and in tropical forests of the Xingu River Basin in Mato Grosso, Brazil. Results from these case studies show that the method successfully identified pixels affected by logging and fire disturbance in temperate and boreal forest sites. Change detection results in the Pacific Northwest compared well with a Landsat-based disturbance map, yielding a producer ' s accuracy of 85 %. Assessment of change detection results for the Xingu River Basin demonstrated that detection accuracy improves as the fraction of deforestation within a MODIS pixel increases, but that relatively small changes in forest cover were still detectable from MODIS. Annually, over 80% of pixels with > 20% deforested area were correctly identified and the timing of change showed good agreement with reference data. Errors of commission were largely associated with pixels located at the edges of disturbance events and inadequate characterization of land cover changes unrelated to deforestation in the reference data. Although our case studies focused on forests, this method is not specific to detection of forest cover change and has the potential to be applied to other types of land cover change including urban and agricultural expansion and intensification.
Location: TE 15 New Biology Building
Literature cited 1: Achard, F., Eva, H.D., Mayaux, P., Stibig, H.-J., Belward, A., 2004. Improved estimates of net carbon emissions from land cover change in the tropics for the 1990. Global Biogeochemical Cycles 18 (2), GB 2008.
Angelici, G., Bryant, N., 1977. A land use change monitoring system based on LAND SAT. In: LARS Symposia.
Literature cited 2: Arvor, D., Meirelles, M., Vargas, R., Skorupa, L., Fidalgo, E., Dubreuil, V., Herlin, I., Berroir, J.-P., 2010. Monitoring land use changes around the indigenous lands of the Xingu Basin in Mato Grosso, Brazil. In: Proceedings of IGARSS ' 10.
Baccini, A., Goetz, S.J., Walker, W.S., Laporte, N.T., Sun, M., Sulla-Menashe, D., Hackler, J., Beck, P.S.A., Dubayah, R., Friedl, M.A., Samanta, S., Houghton, R.A., 2012. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change 2 (3), 1182-185.
ID: 60059
Title: Empirical models for estimating the suspended sediment concentration in Amazonian white water rivers using Landsat 5/TM.
Author: Otavio C. Montanher, Evlyn M.L.M. Novo, Claudio C.F. Barbosa, Camilo D. Renno, Thiago S.F. Silva.
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. 29. 67-77 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Top of atmosphere reflectance, Multiple regressions, Geology of the Amazon, Fluvial sediments, Spectral bands, Band ratios.
Abstract: Suspended sediment yield is a very important environmental indicator within Amazonian fluvial systems, especially for rivers dominated by inorganic particles, referred to as white water rivers. For vast portions of Amazonian rivers, suspended sediment concentration (SSC) is measured infrequently or not at all. However, remote sensing techniques have been used to estimate water quality parameters worldwide, from which data for suspended matter is the most successfully retrieved. This paper presents empirical models for SSC retrieval in Amazonian white water rivers using reflectance data derived from Landsat 5/TM. The models use multiple regression for both the entire dataset (global model, N=504) and for five segmented datasets (regional models) defined by general geological features of drainage basins. The models use VNIR bands, band ratios, and the SWIR band 5 as input. For the global model, the adjusted R2 is 0.76, while the adjusted R2 values for regional models vary from 0.77 to 0.89, all significant (p-value < 0.0001). The regional models are subjected to the leave- one-out cross validation technique, which presents robust results. The findings show that both the average error of estimation and the standard deviation increase as the SSC range increases. Regional models were more accurate when compared with the global model, suggesting changes in optical properties of water sampled at different sampling stations. Results confirm the potential for the estimation of SSC from Landsat /TM historical series data for the 1980s and 1990s, for which the in situ database is scarce. Such estimates supplement the SSC temporal series, providing a more comprehensive SSC temporal series which may show environmental dynamics yet unknown.
Location: TE 15 New Biology Building
Literature cited 1: Aalto, R., Dunne, T., Guyot, J.L., 2006. Geomorphic controls on Andean denudation dates. Journal of Geology 114, 85-99.
Aranuvachapun, S., Walling, D.E., 1988. Landsat-MSS radiance as a measure of suspended sediment in the lower Yellow River (Hwang Ho). Remote Sensing of Environment 25, 145-165.
Literature cited 2: Baby, P., Guyot, J.L., Herail, G., 2009. Tectonic control of erosion and sedimentation in the Amazon Basin of Bolvia. Hydrological Processes 23, 3225-3229.
Chander, G., Markham, B.L., Helder, D.L., 2009. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment 113, 893-903.
ID: 60058
Title: Environmental monitoring of EI Hierro Island Submarine volcano, by combining low and high resolution satellite imagery.
Author: F. Eugenio, J. Martin, J. Marcello, E. Fraile- Nuez.
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. 29. 53-66 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: El Hierro Island, Underwater volcanic eruption, Environmental impact, Low/high resolution satellite images, Chlorophyll-a, Diffuse attenuation coefficient.
Abstract: El Hierro Island, located at the Canary Islands Archipelago in the Atlantic coast of North Africa, has been rocked by thousands of tremors and earthquakes since July 2011. Finally, an underwater volcanic eruption started 300 m below sea level on October 10, 2011. Since then, regular multidisciplinary monitoring has been carried out in order to quantify the environmental impacts caused by the submarine eruption. Thanks to this natural tracer release, multisensorial satellite imagery obtained from MODIS and MERIS sensors have been processed to monitor the volcano activity and to provide information on the concentration of biological, chemical and physical marine parameters. Specifically, low resolution satellite estimations of optimal diffuse attenuation coefficient (K d) and chlorophyll -a (Chl-a) concentration under these abnormal conditions have been assessed. These remote sensing data have played a fundamental role during field campaigns guiding the oceanographic vessel to the appropriate sampling areas. In addition, to analyze El Hierro submarine volcano area, WorldView-2 high resolution satellite spectral bands were atmospherically and deglinted processed prior to obtain a high-resolution optimal diffuse attenuation coefficient model. This novel algorithm was developed using a matchup data set with MERIS and MODIS data, in situ transmittances measurements and a seawater radiative transfer model. Multisensor and multitemporal imagery processed from satellite remote sensing sensors have demonstrated to be a powerful tool for monitoring the submarine volcanic activities, such as discolored seawater, floating material and volcanic plume, having shown the capabilities to improve the understanding of submarine volcanic processes.
Location: TE 15 New Biology Building
Literature cited 1: Eugenio, F., Martin, J., Marcello, J., Bermejo, J.A., 2012. Atmospheric correction models for high resolution WorldView -2 multispectral imagery: a case study in Canary Islands, Spain. In: Proceedings SPIE Remote Sensing, Edimburgh, September.
Fraile-Nuez, E., Gonzalez-Davila, M., Santana-Casiano, J.M., Aristegui, J., AlonsoGonzalez, I.J., Hernandez-Leon, S., Blanco, M.J., Rodriguez-santana, A., Hernandez-Guerra, A., Gelado-Caballero, M.D., Eugenio, F., Marcello, J., de Armas, D., Dominguez-Yanes, J.F., Montero, M.F., Laetsch, D.R., Vellez-Belchi, P., Ramos, A., Ariza, A.V., Comas-Rodriguez, I., Benitez-Barrios, V.M., 2012. The submarine volcano eruption at the Island of El Hierro: physical-chemical perturbation and biological response. Scientific Reports 2, 486.
Literature cited 2: Joyce, K., Belliss, S., Samsonov, S., McNeill, S., Glassey, P., 2009. A review of the status of satellite remote sensing and image processing techniques for mapping natural hazards and disasters. Progress in Physical Geography 33 (2), 183-207.
Kay, S., Hedley, J., Lavender, S., 2009. Sun glint correction of high and low spatial resolution images of aquatic scenes: a review of methods for visible and near-infrared wavelengths. Remote Sensing 1, 697-730.
ID: 60057
Title: A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada.
Author: Catherine Champagne, Heather Mc Nairn, Bahram Daneshfar, Jiali 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. 29. 44-52 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: None
Abstract: Land cover and land use classifications from remote sensing are increasingly becoming institutionalized framework data sets for monitoring environmental change. As such, the need for robust statements of classification accuracy is critical. This paper describes a method to estimate confidence in classification accuracy using a bootstrap approach. Using the method, it was found that classification accuracy and confidence, while closely related, can be used in complementary ways to provide additional information on map accuracy and define groups of classes and to inform the reference sampling strategies. Overall classification accuracy increases with an increase in the number of fields surveyed, where the width of classification confidence bounds decreases. Individual class accuracies and confidence were non-linearly related to the number of fields surveyed. Results indicate that some classes can be estimated accurately and confidently with fewer numbers of samples, where as others require larger reference data sets to achieve satisfactory results. This approach is an improvement over other approaches for estimating class accuracy and confidence as it uses repetitive sampling to produce a more realistic estimate of the range in classification accuracy and confidence that can be obtained with different reference data inputs.
Location: TE 15 New Biology Building
Literature cited 1: Carfagna, E., Gallego, F.J., 2005. Using remote sensing for agricultural statistics. International Statistical Review 73, 389-404.
Chen, D.M., Stow, D., 2002. The effect of training strategies on supervised classification at different spatial resolutions. Photogrammetric Engineering & Remote Sensing 68, 1155-1161.
Literature cited 2: Congalton, R.G., Green, K., 1999. Assessing the accuracy of Remotely Sensed Data: Principles and Practices. Lewis, Boca Raton, F.L, 137 pp.
DiCiccio, T.J., Efron, B., 1996. Bootstrap confidence intervals. Statistical Science 11, 189-212.
ID: 60056
Title: Quantification of anthropogenic and natural changes in oil sands mining infrastructure land based on RapidEYE and SPOT5.
Author: Ying Zhang, Bert Guindon, Nicholas Lantz, Todd Shipman, Dennis Chao, Don Raymond.
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. 29. 31-43 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Extraction of land changes, Change detection, Land disturbance, Mining land, Reclamation, Regrowth.
Abstract: Natural resources development, spanning exploration, production and transportation activities, alters local land surface at various spatial scales. Quantification of these anthropogenic changes, both permanent and reversible, is needed for compliance assessment and for development of effective sustainable management strategies. Multi-spectral high resolution imagery data from SPOT5 and RapidEye were used for extraction and quantification of the anthropogenic and natural changes for a case study of Alberta bitumen (oil sands) mining located in the Western Boreal Plains near Fort McMurray, Canada. Two test sites representative of the major Alberta bitumen production extraction processes, open pit and in situ extraction, were selected. A hybrid change detection approach, combining pixel -and object-based target detection and extraction, is proposed based on Change Vector Analysis (CVA). The extraction results indicate that the changed infrastructure landscapes of these two sites have different footprints linked with their differing oil sands production processes. Pixel-and object-based accuracy assessments have been applied for validation of the change detection results. For manmade disturbances, except for those fine linear features such as seismic lines, accuracies of about 80% have been achieved at the pixel level while, at the object level, these rise to 90-95%.
Since many disturbance features are transient, a new landscape index, entitled the re-growth Index, has been formulated at single object level specifically to monitor restoration of these features to their natural state. It is found that the temporal behavior of the Re-growth Index in an individual patch varies depending on the type of natural land cover. In addition, the Re-growth Index is also useful for assessing the detectability of disturbed sites.
Location: TE 15 New Biology Building
Literature cited 1: Alberta Environment, 2009. State of the Environment: Oil Sands Reclamation. www3.gov.ab.ca
Alberta Environment, 2012. Lower Athabasca Region Plan, 94 pp. http:// environment.alberta.ca.
Literature cited 2: Al-Khudhairy, D.H.A., Caravaggi, I., Giada, S., 2005. Structural damage assessments from Ikonos data using change detection, object-oriented segmentation, and classification techniques. Photogrammetric Engineering & Remote Sensing 71 (7), 825-837
Aronoff, S., Ross, W.A., 1982. Environmental monitoring of the Athabasca oil sands using landsat data. Photogrammetria 38 (3), 77-86.
ID: 60055
Title: Efficiency assessment of using satellite data for crop area estimation in Ukraine.
Author: Francisco Javier Gallego, Nataliia Kussul, Sergii Skakun, Oleksii Kravchenko, Andrii Shelestov, Olga Kussul.
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. 29. 22-30 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Remote sensing, Agriculture, Crop area, Classification, Ukraine.
Abstract: The knowledge of the crop area is a key element for the estimation of the total crop production of a country and, therefore, the management of agricultural commodities markets. Satellite data and derived products can be effectively used for stratification purposes and a-posteriori correction of area estimates from ground observations. This paper presents the main results and conclusions of the study conducted in 2010 to explore feasibility and efficiency of crop area estimation in Ukraine assisted by optical satellite remote sensing images. The study was carried out on three oblasts in Ukraine with a total area of 78, 500 km2. The efficiency of using images acquired by several satellite sensors (MODIS, Landsat-5/TM, AWiFS, LISS III, and Rapid Eye) combined with a field survey on a stratified sample of square segments for crop area estimation in Ukraine is assessed. The main criteria used for efficiency analysis are as follows: (i) relative efficiency that shows how much time the error of area estimates can be reduced with satellite images, and (ii) cost-efficiency that shows how much time the costs of ground surveys for crop area estimation can be reduced with satellite images. These criteria are applied to each satellite image type separately, i.e. no integration of images acquired by different sensors is made, to select the optimal dataset. The study found that only MODIS and Landsat-5/TM reached cost-efficiency thresholds while AWiFS, LISS-III, and RapidEye images, due to its high price, were not cost-efficient for crop area estimation in Ukraine at oblast level.
Location: TE 15 New Biology Building
Literature cited 1: Allen, J.D., 1990. A look at the remote sensing applications program of the national agricultural statistics service. J. Off. Stat. 6 (4), 393 -409.
Arino, O., Gross, D., Ranera, F., Bourg, L., Leroy, M., Bicheron, P., et al., 2007. Glob-Cover: ESA service for global land cover from MERIS. In: IEEE International Geoscience and Remote Sensing Symposium Igarss, Barcelona, Spain, 23-27 July, pp. 2412-2415.
Literature cited 2: Ban, Y., 2003. Synergy of multitemporal ERS and Landsat TM data for classification of agricultural crops. Can.J. Remote Sens. 29 (4), 518-526.
Bauer, M.E., Hixson, M.M., Davis, B.J., Etheridge, J.B., 1978. Area estimation of crops by digital analysis of Landsat data. Photogramm.Eng.Rem.Sens.44, 1033-1043.
ID: 60054
Title: Ecological site classification of semiarid rangelands: Synergistic use of Landsat and Hyperion imagery.
Author: Paula D. Blanco, Hector F. del Valle, Pablo J. Bouza, Graciela I. Metternicht, Leonardo A. Hardtke.
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. 29. 11-21 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Ecological site, Hyperion, Endmember selection, Mixture tuned matched filtering, logistic regression, networks, Land management.
Abstract: Ecological sites are the basic entity used in rangeland health assessment. This study evaluates the synergistic use of multi-and hyper-spectral satellite imagery for sub-pixel classification of ecological sites in semiarid rangelands. Hyperion and Landsat enhanced thematic mapper (ETM) data are included in a two-step procedure to mapping ecological sites in Patagonian rangelands of Argentina. Firstly, mixture tuned matched filtering and logistic regression analyses are used for Hyperion data processing to obtain ecological sit probability images in the area covered by hyperspectral imagery. Secondly, artificial neural networks are applied to model the relationships between the spectral response patterns of Landsat and the probability images from Hyperion, and used to map ecological sites over the entire study area. Overall classification accuracy was 81% (Kappa= 0.77) with relatively high accuracies for all ecological sites demonstrating that their spectral signatures are sufficiently distinct to be detectable. Better accuracies were obtained for shrub steppes with desert pavement (producer ' s and user ' s accuracies of 89% and 84 %, respectively), and shrub-grass steppes associated to tertiary calcareous outcrops (producer ' s and user ' s accuracies of 100% and 86%, respectively), while poorer accuracies resulted for shrub-grass steppes on old alluvial plains (producer ' s and user ' s accuracies of 75% and 56%, respectively). Fuzzy maps of ecological sites as presented in this research can provide rangeland managers with a tool to stratify the landscape and organize ecological information for rangeland health assessment and monitoring, prioritizing and selecting appropriate management actions, and promoting the recovery of areas degraded in these environments.
Location: TE 15 New Biology Building
Literature cited 1: Arsenault, E., Bonn, F., 2005. Evaluation of soil erosion protective cover by crop residues using vegetation indices and spectral mixture analysis of multispectral and hyperspectral data. Catena 62 (2-3), 157-172.
Aspinall, R.J., 2002. Use of logistic regression for validation of maps of the spatial distribution of vegetation species derived from high spatial resolution hyper-spectral remotely sensed data. Ecol. Model. 157, 301-312.
Literature cited 2: Ballantine, J.A.C., Okin, G.S., Prentiss, D.E., Roberts, D.A., 2005. Mapping north African landforms using continental -scale unmixing of MODIS imagery. Remote Sens. Environ. 47, 470-483.
Barros, V., Rivero, M.M., 1982. Mapas de Probabilidad de precipitation en la Provincia del Chubut, Contribucion N? 54. CENPAT-CONICET, Chubut, Argentina.
ID: 60053
Title: Remote estimation of grassland gross primary production during extreme meteorological seasons.
Author: Micol Rossini, Micro Migliavacca, Marta Galvagno, Michele Meroni, Sergio Cogliati, Edoardo Cremonese, Francesco Fava, Anatoly Gitelson, Tommaso Julitta, Umberto Morra di Cella, Consolata Siniscalco, Roberto 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. 29. 1-10 (2014).
Subject: APPLIED EARTH OBSERVATION AND GEOINFORMATION.
Keywords: Gross primary production, Vegetation index, PRI, Grassland, Extreme events, Potential photosynthetically active, radiation.
Abstract: Different models driven by remotely sensed vegetation indexes (VIS) and incident photosynthetically active radiation (PAR) were developed to estimate gross primary production (GPP) in subalpine grassland equipped with an eddy covariance flux tower. Hyperspectral reflectance was collected using an automatic system designed for high temporal frequency acquisitions for three consecutive years, including one (2011) characterized by a strong reduction of the carbon sequestration rate during the vegetative season. Models based on remotely sensed and meteorological data were used to estimate GPP, and a cross-validation approach was used to compare the predictive capabilities of different model formulations. Vegetation indexes designed to be more sensitive to chlorophyll content explained most of the variability in GPP in the ecosystem investigated, characterized by a strong seasonal dynamic. Model performances improved when including also PARpotential defined as the maximal value of incident PAR under clear sky conditions in model formulations. Best performing models are based entirely on remotely sensed data. This finding could contribute to the development of methods for quantifying the temporal variation of GPP also on a broader scale using current and future satellite sensors.
Location: TE 15 New Biology Building
Literature cited 1: Balzarolo, M., Anderson, K., Nichol, C., Rossini, M., Vescovo, L., Arriga, N., et al., 2011. Ground -based optical measurements at European flux sites: a review of methods, instruments and current controversies. Sensors 11, 7954-7981.
Bates, D.M., Watts, D.G., 1988. Nonlinear regression analysis and its applications. John Wiley& Sons, New York.
Literature cited 2: Beer, C., Reichstein, M., Tomelleri, E., Ciais, P., Jung, M., Carvalhais, N., et al., 2010. Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate. Science 329, 834-838.
Beniston, M., 2005. Mountain climates and climatic change: an overview of processes focusing on the European Alps. Pure and Applied Geophysics 162, 1587-1606.