Optimal attributes for the object based detection of giant reed in riparian habitats: A comparative study between Airborne High Spatial Resolution and WorldView-2 imagery

Maria Rosário Fernandes1, Francisca C. Aguiar1, João M.N. Silva1, Maria Teresa Ferreira1, José M.C. Pereira1
1Universidade de Lisboa, Instituto Superior de Agronomia, Centro de Estudos Florestais, Tapada da Ajuda, 1349-017 Lisboa, Portugal

Tài liệu tham khảo

Adam, 2009, Spectral discrimination of papyrus vegetation (Cyperus papyrus L.) in swamp wetlands using field spectrometry, ISPRS J. Photogram. Rem. Sens., 64, 612, 10.1016/j.isprsjprs.2009.04.004 Aguiar, 2013, Plant invasions in the rivers of the Iberian Peninsula, South-Western Europe – a review, Plant Biosyst., 147, 1107, 10.1080/11263504.2013.861539 Aguiar, 1996, Perception of aquatic weed problems by water resources managers. A Percepção da Vegetação Aquática Infestante pelas Entidades Gestoras dos Recursos Hídricos, Rev. Ciênc. Agr., 19, 35 Aguiar, 2007, Alien and endemic flora on reference and non-reference sites from Mediterranean type-streams of Portugal, Aquat. Conserv. Mar. Freshwater Ecosyst., 17, 335, 10.1002/aqc.776 Aksoy, 2010, Automatic mapping of linear woody vegetation features in agricultural landscapes using very high resolution imagery, IEEE Trans. Geosci. Rem. Sens., 48, 511, 10.1109/TGRS.2009.2027702 Andrew, 2008, The role of environmental context in mapping plants with hyperspectral image data, Remote Sens. Environ., 112, 4301, 10.1016/j.rse.2008.07.016 Baker, 2007, Effects of stream map resolution on measures of riparian buffer distribution and nutrient potential, Landsc. Ecol., 27, 973, 10.1007/s10980-007-9080-z Belluco, 2006, Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing, Remote Sens. Environ., 105, 54, 10.1016/j.rse.2006.06.006 Benz, 2004, Multiresolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information, ISPRS J. Photogram. Rem. Sens., 58, 239, 10.1016/j.isprsjprs.2003.10.002 Blaschke, 2010, Object based image analysis for remote sensing, ISPRS J. Photogram. Rem. Sens., 65, 2, 10.1016/j.isprsjprs.2009.06.004 Breiman, 1996, Bagging predictors, Mach. Learn., 26, 123, 10.1007/BF00058655 Breiman, 1984 Canty, 2007 Canty, 2008, Automatic radiometric normalization of multitemporal satellite imagery with the iteratively re-weighted MAD transformation, Remote Sens. Environ., 112, 1025, 10.1016/j.rse.2007.07.013 Canty, 2004, Automatic radiometric normalization of multitemporal satellite imagery, Remote Sens. Environ., 91, 441, 10.1016/j.rse.2003.10.024 Carleer, 2005, Assessment of very high spatial resolution satellite image segmentation, Photogramm. Eng. Rem. Sens., 71, 1285, 10.14358/PERS.71.11.1285 Congalton, 2002, Evaluating remotely sensed techniques for mapping riparian vegetation, Comput. Electron. Agric., 37, 113, 10.1016/S0168-1699(02)00108-4 Cushman, 2010, Community-level consequences of invasion: impacts of exotic clonal plants on riparian vegetation, Biol. Invasions, 12, 2765, 10.1007/s10530-009-9682-2 Desclee, 2006, Forest change detection by statistical objectbased method, Rem. Sens. Environ., 102, 1, 10.1016/j.rse.2006.01.013 Dikshit, 1996, Textural classification for ecological research using ATM images, Int. J. Remote Sens., 17, 887, 10.1080/01431169608949054 DiPietro, 2002, Mapping the invasive plant Arundo donax at Camp Pendleton Marine Base using AVIRIS Dronova, 2011, Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China, Remote Sens. Environ., 115, 3220, 10.1016/j.rse.2011.07.006 Dudley, 2000, Arundo donax, 53 Dufour, 2013, Monitoring restored riparian vegetation: how can recent developments in remote sensing sciences help?, Knowledge Manage. Aquat. Ecosyst., 410, 10, 10.1051/kmae/2013068 Everitt, 2004, Canopy spectra of giant reed and associated vegetation, J. Range Manage., 57, 561, 10.2307/4003988 Everitt, 2008, Comparison of QuickBird and SPOT 5 satellite imagery for mapping giant reed, J. Aquat. Plant Manage., 46, 77 Fernandes, 2011, Assessing riparian vegetation structure and the influence of land use using landscape metrics and geostatistical tools, Landsc. Urban Plann., 99, 166, 10.1016/j.landurbplan.2010.11.001 Fernandes, 2013, Spectral discrimination of giant reed (Arundo donax L.): a seasonal study in riparian areas, ISPRS J. Photogram. Rem. Sens., 80, 80, 10.1016/j.isprsjprs.2013.03.007 Franklin, 2001, Texture analysis of IKONOS panchromatic data for Douglas-fir forest age class separability in British Columbia, Int. J. Remote Sens., 22, 2627, 10.1080/01431160120769 Ge, 2008, Canopy assessment of biochemical features by ground-based hyperspectral data for an invasive species, giant reed (Arundo donax), Environ. Monit. Assess., 147, 271, 10.1007/s10661-007-0119-z Gergel, 2007, What is the value of a good map? An example using high spatial resolution imagery to aid riparian restoration, Ecosystems, 10, 688, 10.1007/s10021-007-9040-0 Goetz, 2006, Remote sensing of riparian buffers: past progress and future prospects, J. Am. Water Resour. Assoc., 42, 133, 10.1111/j.1752-1688.2006.tb03829.x Hamada, 2007, Detecting Tamarisk species (Tamarix spp.) in riparian habitats of Southern California using high spatial resolution hyperspectral imagery, Remote Sens. Environ., 109, 237, 10.1016/j.rse.2007.01.003 Herrera, 2003, Reduction of riparian arthropod abundance and diversity as a consequence of giant reed (Arundo donax) invasion, Biol. Invasions, 5, 167, 10.1023/A:1026190115521 Hestir, 2008, Identification of invasive vegetation using hyperspectral remote sensing in the California Delta ecosystem, Remote Sens. Environ., 112, 4034, 10.1016/j.rse.2008.01.022 Hsieh, 2001, Effect of spatial resolution on classification errors of pure and mixed pixels in remote sensing, IEEE Trans. Geosci. Rem. Sens., 39, 2657, 10.1109/36.975000 Johansen, 2007, Application of high spatial resolution satellite imagery for riparian and forest ecosystem classification, Remote Sens. Environ., 110, 29, 10.1016/j.rse.2007.02.014 Johnsson, 1994, Segment-based land-use classification from SPOT satellite data, Photogramm. Eng. Rem. Sens., 60, 47 Ke, 2010, Synergistic use of QuickBird multispectral imagery and LIDAR data for object-based forest species classification, Remote Sens. Environ., 114, 1141, 10.1016/j.rse.2010.01.002 Laba, 2008, Mapping invasive wetland plants in the Hudson River National Estuarine Research Reserve using QuickBird satellite imagery, Remote Sens. Environ., 112, 286, 10.1016/j.rse.2007.05.003 Laba, 2010, Use of textural measurements to map invasive wetlands plants in the Hudson River National Estuarine Research with IKONOS satellite imagery, Remote Sens. Environ., 114, 876, 10.1016/j.rse.2009.12.002 Laliberte, 2004, Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico, Remote Sens. Environ., 93, 198, 10.1016/j.rse.2004.07.011 Maillard, 2003, Comparing texture analysis methods through classification, Photogramm. Eng. Rem. Sens., 69, 357, 10.14358/PERS.69.4.357 Mallinis, 2008, Object-based classification using Quickbird imagery for delineating forest vegetation polygons in a Mediterranean test site, ISPRS J. Photogram. Rem. Sens., 63, 237, 10.1016/j.isprsjprs.2007.08.007 Möller, 2007, The comparison index: a tool for assessing the accuracy of image segmentation, Int. J. Appl. Earth Observ. Geoinf., 9, 311, 10.1016/j.jag.2006.10.002 Muller, 1997, Mapping riparian vegetation along rivers: old concepts and new methods, Aquat. Bot., 58, 411, 10.1016/S0304-3770(97)00049-1 Nielsen, 2007, The regularized iteratively reweighted MAD method for change detection in multi- and hyperspectral data, IEEE Trans. Image Process., 16, 463, 10.1109/TIP.2006.888195 Nielsen, 1998, Multivariate alteration detection (MAD) and MAF postprocessing in multispectral, bitemporal image data: new approaches to change detection studies, Remote Sens. Environ., 64, 1, 10.1016/S0034-4257(97)00162-4 Papazoglou, 2005, Photosynthesis and growth responses of giant reed (Arundo donax L.) to the heavy metals Cd and Ni, Environ. Int., 31, 243, 10.1016/j.envint.2004.09.022 Pearlstine, 2005, Textural discrimination of an invasive plant, Schinus terebinthifolius, from low altitude aerial digital imagery, Photogramm. Eng. Rem. Sens., 71, 289, 10.14358/PERS.71.3.289 Peña-Barragán, 2011, Object-based crop identification using multiple vegetation indices, textural features and crop phenology, Remote Sens. Environ., 115, 1301, 10.1016/j.rse.2011.01.009 Pengra, 2007, Mapping an invasive plant, Phragmites australis, in coastal wetlands using the EO-1 Hyperion hyperspectral sensor, Remote Sens. Environ., 108, 74, 10.1016/j.rse.2006.11.002 Pinto, 2012, Distribuição de cana (Arundo donax) no Algarve e contributos para a sua gestão Pu, 2012, A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species, Remote Sens. Environ., 124, 516, 10.1016/j.rse.2012.06.011 Puissant, 2005, The utility of texture analysis to improve per-pixel classification for high to very high spatial resolution imagery, Int. J. Remote Sens., 26, 733, 10.1080/01431160512331316838 Radoux, 2008, Quality assessment of segmentation results devoted to object-based classification Robinson, 2002 Rossa, 1998, Arundo donax L. (Poaceae) – a C3 species with unusually high photosynthetic capacity, Bot. Acta, 111, 216, 10.1111/j.1438-8677.1998.tb00698.x Sá, 2003, Assessing the feasibility of sub-pixel burned area mapping in Miombo woodlands of northern Mozambique using MODIS imagery, Int. J. Remote Sens., 24, 1783, 10.1080/01431160210144750 Safavian, 1991, A survey of decision tree classifier methodology, IEEE Trans. Syst. Man Cybern., 21, 660, 10.1109/21.97458 Schmidt, 2003, Spectral discrimination of vegetation types in a costal wetland, Remote Sens. Environ., 85, 92, 10.1016/S0034-4257(02)00196-7 Silva, 2011, Control of giant reed Arundo donax on Vila Franca do Campo Islet, Azores, Portugal, Conserv. Evid., 8, 93 Tso, 2009 Underwood, 2003, Mapping nonnative plants using hyperspectral imagery, Remote Sens. Environ., 86, 150, 10.1016/S0034-4257(03)00096-8 Underwood, 2007, A comparison of spatial and spectral image resolution for mapping invasive plants in coastal California, Environ. Manage., 39, 63, 10.1007/s00267-005-0228-9 Vaiphasa, 2007, A hyperspectral band selector for plant species discrimination, ISPRS J. Photogram. Rem. Sens., 62, 225, 10.1016/j.isprsjprs.2007.05.006 Xie, 2008, Object-based target search using remotely sensed data: a case study in detecting invasive exotic Australian Pine in south Florida, ISPRS J. Photogram. Rem. Sens., 63, 647, 10.1016/j.isprsjprs.2008.04.003 Yamagata, 1993, Classification of wetland vegetation by texture analysis methods using ERS-1 and JERS-1 images, 1614 Yang, 2007, Integrated of remote sensing and geographic information systems in riparian vegetation delineation and mapping, Int. J. Rem. Sens., 28, 353, 10.1080/01431160600726763 Yang, 2012, Applying six classifiers to airborne hyperspectral imagery for detecting giant reed, Geocarto Int., 27, 413, 10.1080/10106049.2011.643321 Yu, 2006, Object-based detailed vegetation classification with airborne high spatial resolution remote sensing imagery, Photogramm. Eng. Rem. Sens., 72, 799, 10.14358/PERS.72.7.799 Zhang, 1997, Evaluation and comparison of different segmentation algorithms, Pattern Recogn. Lett., 18, 963, 10.1016/S0167-8655(97)00083-4