Synergy of very high resolution optical and radar data for object-based olive grove mapping

References

• Alchanatis , V. 2005 . Weed detection in multispectral images of cotton fields . Computers and Electronics in Agriculture , 47 ( 3 ) : 243 – 260 .
   Google Scholar
• Amarsaikhan , D. 2007 . The integrated use of optical and InSAR data for urban land-cover mapping . International Journal of Remote Sensing , 28 ( 6 ) : 1161 – 1171 .
   Web of Science ®Google Scholar
• Archer , K.J. and Kimes , R.V. 2008 . Empirical characterization of random forest variable importance measures . Computational Statistics and Data Analysis , 52 : 2249 – 2260 .
   Web of Science ®Google Scholar
• Arzandeh , S. and Wang , J.F. 2002 . Texture evaluation of RADARSAT imagery for wetland mapping . Canadian Journal of Remote Sensing , 28 ( 5 ) : 653 – 666 .
   Web of Science ®Google Scholar
• Baatz , M. and Schäpe , A. 2000 . “ Multiresolution segmentation – an optimization approach for high quality multi-scale segmentation ” . In Angewandte Geographische Informationsverarbeitung XII , Beiträge zum AGIT Symposium Salsburg 2000 Edited by: Strbl , J. 12 – 23 . Karlsruhe : Herbert Wichmann Verlag .
   Google Scholar
• Belluco , E. 2006 . Mapping salt-marsh vegetation by multispectral and hyperspectral remote sensing . Remote Sensing of Environment , 105 ( 1 ) : 54 – 67 .
   Web of Science ®Google Scholar
• Blaes , X. , Vanhalle , L. and Defourny , P. 2005 . Efficiency of crop identification based on optical and SAR image time series . Remote Sensing of Environment , 96 ( 3–4 ) : 352 – 365 .
   Web of Science ®Google Scholar
• Boyce , M.S. 2002 . Evaluating resource selection functions . Ecological Modelling , 157 ( 2–3 ) : 281 – 300 .
   Web of Science ®Google Scholar
• Breiman , L. 2001 . Random forests . Machine Learning , 45 : 5 – 32 .
   Web of Science ®Google Scholar
• Breiman , L. 1984 . Classification and regression trees , New York : Chapman and Hall .
   Google Scholar
• Bush , T.F. and Ulaby , F.T. 1978 . Evaluation of radar as a crop classifier . Remote Sensing of Environment , 7 ( 1 ) : 15 – 36 .
   Google Scholar
• Chini , M. , Pierdicca , N. and Emery , W.J. 2009 . Exploiting SAR and VHR optical images to quantify damage caused by the 2003 Bam Earthquake . IEEE Transactions on Geoscience and Remote Sensing , 47 : 145 – 152 .
   Web of Science ®Google Scholar
• Cleve , C. 2008 . Classification of the wildland-urban interface: a comparison of pixel- and object-based classifications using high-resolution aerial photography . Computers Environment and Urban Systems , 32 ( 4 ) : 317 – 326 .
   Web of Science ®Google Scholar
• Cohen , J. 1960 . A coefficient of agreement for nominal scales . Educational and Psychological Measurement , 20 : 37 – 46 .
   Web of Science ®Google Scholar
• Corbane , C. 2008 . Rapid urban mapping using SAR/optical imagery synergy . Sensors , 8 ( 11 ) : 7125 – 7143 .
   PubMed Web of Science ®Google Scholar
• Dai , X. and Khorram , S. 1998 . A hierarchical methodology framework for multisource data fusion in vegetation classification . International Journal of Remote Sensing , 19 ( 18 ) : 3697 – 3701 .
   Web of Science ®Google Scholar
• Fawcett , T. 2006 . An introduction in ROC analysis . Pattern Recognition Letters , 27 : 861 – 874 .
   Web of Science ®Google Scholar
• Fielding , A.H. and Bell , J.F. 1997 . A review of methods for the assessment of prediction errors in conservation presence/absence models . Environmental Conservation , 24 ( 1 ) : 38 – 49 .
   Web of Science ®Google Scholar
• Franklin , S.E. 2000 . Incorporating texture into classification of forest species composition from airborne multispectral images . International Journal of Remote Sensing , 21 ( 1 ) : 61 – 79 .
   Web of Science ®Google Scholar
• Gibson , K.D. 2004 . Detection of weed species in soybean using multispectral digital images . Weed Technology , 18 ( 3 ) : 742 – 749 .
   Google Scholar
• Gitas , I.Z. , Mitri , G.H. and Ventura , G. 2004 . Object-based image classification for burned area mapping of Creus Cape, Spain, using NOAA-AVHRR imagery . Remote Sensing of Environment , 92 : 409 – 413 .
   Web of Science ®Google Scholar
• Gong , P. , Marceau , D.J. and Howarth , P.J. 1992 . A comparison of spatial feature-extraction algorithms for land use classification with SPOT HRV data . Remote Sensing of Environment , 40 ( 2 ) : 137 – 151 .
   Web of Science ®Google Scholar
• Gonzalez , J. Applying image analysis and probabilistic techniques for counting olive trees in high-resolution satellite images . Proceedings of the 9th International Conference on Advanced Concepts for Intelligent Vision Systems . Edited by: Blane-Talon , J. , Philips , W. , Popescu , D. and Scheunders , P. pp. 920 – 931 . Berlin/Heidelberg : Springer . Lecture notes in computer science: advanced concepts for intelligent vision systems doi 10.1007/978-3-540-74607-2
   Google Scholar
• Gougeon , F.A. and Leckie , D.G. 2006 . The individual tree crown approach applied to Ikonos images of a coniferous plantation area . Photogrammetric Engineering and Remote Sensing , 72 ( 11 ) : 1287 – 1297 .
   Web of Science ®Google Scholar
• Gray , C.J. 2008 . Utility of multispectral imagery for soybean and weed species differentiation . Weed Technology , 22 ( 4 ) : 713 – 718 .
   Web of Science ®Google Scholar
• Haralick , R.M. , Shanmugan , K. and Dinstein , I. 1973 . Textural features for image classification . IEEE Transactions on Systems, Man, and Cybernetics , 3 : 610 – 621 .
   Web of Science ®Google Scholar
• Hegarat-Mascle , S.L. , Bloch , I. and Vadal-Madjar , D. 1997 . Application of Dempster-Shafer evidence theory to unsupervised classification in multisource remote sensing . IEEE Transactions on Geoscience and Remote Sensing , 3 ( 5 ) : 1018 – 1031 .
   Google Scholar
• Hill , M.J. 2005 . Integration of optical and radar classifications for mapping pasture type in Western Australia . IEEE Transactions on Geoscience and Remote Sensing , 43 ( 7 ) : 1665 – 1681 .
   Web of Science ®Google Scholar
• Hosmer , D.W. and Lemeshow , S. 2000 . Applied logistic regression , 2nd , Chichester : Wiley .
   Google Scholar
• Johansen , K. 2007 . Application of high spatial resolution satellite imagery for riparian and forest ecosystem classification . Remote Sensing of Environment , 110 ( 1 ) : 29 – 44 .
   Web of Science ®Google Scholar
• Kohavi , R. and Provost , F. 1998 . Glossary and terms. Editorial for the special issue on applications of machine learning and knowledge discovery process . Machine Learning , 30 ( 2–3 ) : 271 – 274 .
   Google Scholar
• Kuplich , T.M. 2006 . Classifying regenerating forest stages in Amazonia using remotely sensed images and a neural network . Forest Ecology and Management , 234 ( 1–3 ) : 1 – 9 .
   Google Scholar
• Leckie , D.G. 2005 . Automated tree recognition in old growth conifer stands with high resolution digital imagery . Remote Sensing of Environment , 94 ( 3 ) : 311 – 326 .
   Web of Science ®Google Scholar
• Lillesand , T.M. , Kiefer , R.W. and Chipman , J.W. 2004 . Remote sensing and image interpretation , 763 New York : John Wiley & Sons .
   Google Scholar
• Liu , C.R. 2005 . Selecting thresholds of occurrence in the prediction of species distributions . Ecography , 28 ( 3 ) : 385 – 393 .
   Web of Science ®Google Scholar
• Mehner , H. 2004 . Remote sensing of upland vegetation: the potential of high spatial resolution satellite sensors . Global Ecology and Biogeography , 13 : 359 – 369 .
   Web of Science ®Google Scholar
• Pekkarinen , A. 2002 . Image segment-based spectral features in the estimation of timber volume . Remote Sensing of Environment , 82 ( 2–3 ) : 349 – 359 .
   Google Scholar
• Pekkarinen , A. , Reithmaier , L. and Strobl , P. 2009 . Pan-European forest/non-forest mapping with Landsat ETM plus and CORINE Land Cover 2000 data . ISPRS Journal of Photogrammetry and Remote Sensing , 64 ( 2 ) : 171 – 183 .
   Web of Science ®Google Scholar
• Peña-Barrágan , J.M. 2004 . Assessing land-use in olive groves from aerial photographs . Agriculture, Ecosystem & Environment , 103 : 117 – 122 .
   Web of Science ®Google Scholar
• Peters , J. 2007 . Random forests as a tool for ecohydrological distribution modelling . Ecological Modelling , 207 : 304 – 318 .
   Web of Science ®Google Scholar
• Peters , J. 2008 . Wetland vegetation distribution modelling for the identification of constraining environmental variables . Landscape Ecology , 23 (9), 1049–1065
   Google Scholar
• Pohl , C. and Van Genderen , J.L. 1998 . Multisensor image fusion in remote sensing: concepts, methods and applications . International Journal of Remote Sensing , 19 ( 5 ) : 823 – 854 .
   Web of Science ®Google Scholar
• Pontius , R.G. Jr and Schneider , L. 2001 . Land-use change model validation by a ROC method for the Ipswitch watershed, Massachusetts, USA . Agriculture, Ecosystem & Environment , 85 ( 1–3 ) : 239 – 248 .
   Web of Science ®Google Scholar
• Satalino , G. 2009 . Wheat crop mapping by using ASAR AP data . IEEE Transactions on Geoscience and Remote Sensing , 47 ( 2 ) : 527 – 530 .
   Google Scholar
• Smara , Y. , Belhadj-Aissa , A. and Sansal , B. 1998 . Multisource ERS-1 and optical data for vegetal cover assessment and monitoring in a semi-arid region of Algeria . International Journal of Remote Sensing , 19 ( 18 ) : 3551 – 3568 .
   Web of Science ®Google Scholar
• Soh , L.K. and Tsatsoulis , C. 1999 . Texture analysis of SAR sea ice imagery using gray level co-occurrence matrices . IEEE Transactions on Geoscience and Remote Sensing , 37 ( 2 ) : 780 – 795 .
   Web of Science ®Google Scholar
• Solberg , A.H.S , Jain , A.K. and Taxt , T. 1994 . Multisource classification of remotely-sensed data – fusion of Landsat TM and SAR images . IEEE Transactions on Geoscience and Remote Sensing , 32 ( 4 ) : 768 – 778 .
   Web of Science ®Google Scholar
• Sugumaran , R. , Pavuluri , M.K. and Zerr , D. 2003 . The use of high-resolution imagery for identification of urban climax forest species using traditional and rule-based classification approach . IEEE Transactions on Geoscience and Remote Sensing , 41 ( 9 ) : 1933 – 1939 .
   Google Scholar
• Tuominen , S. and Pekkarinen , A. 2005 . Performance of different spectral and textural aerial photograph features in multi-source forest inventory . Remote Sensing of Environment , 94 : 256 – 268 .
   Web of Science ®Google Scholar
• Ulaby , F.T. , Li , R.Y. and Shanmugan , K.S. 1982 . Crop classification using airborne radar and Landsat data . IEEE Transactions on Geoscience and Remote Sensing , 20 ( 1 ) : 42 – 51 .
   Google Scholar
• Van Coillie , F.M.B. , Verbeke , L.P.C. and De Wulf , R.R. 2007 . Feature selection by genetic algorithms in object-based classification of IKONOS imagery for forest mapping in Flanders, Belgium . Remote Sensing of Environment , 110 : 476 – 487 .
   Web of Science ®Google Scholar
• Van Coillie , F.M.B. , Verbeke , L.P.C. and De Wulf , R.R. 2008 . “ Semi-automatic forest stand delineation using wavelet based segmentation of very high resolution optical imagery ” . In Object-based image analysis: spatial concepts for knowledge-driven remote sensing applications , Edited by: Blaschke , T. , Lang , S. and Hay , G. 237 – 256 . Berlin/Heidelberg : Springer . Lecture notes in geoinformation and cartography
   Google Scholar
• Vescovi , F.D. and Gomarasca , M.A. 1999 . Integration of optical and microwave remote sensing data for agricultural land use classification . Environmental Monitoring and Assessment , 58 ( 2 ) : 133 – 149 .
   Google Scholar
• Wang , L. 2004 . Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama . Remote Sensing of Environment , 91 ( 3–4 ) : 432 – 440 .
   Web of Science ®Google Scholar
• Waske , B. and van der Linden , S. 2008 . Classifying multilevel imagery from SAR and optical sensors by decision fusion . IEEE Transactions on Geoscience and Remote Sensing , 46 ( 5 ) : 1457 – 1466 .
   Web of Science ®Google Scholar
• Westra , T. , Crabbe , S. and De Wulf , R.R. Study of ecosystem dynamics in Sahelian floodplains using Envisat ASAR C-band data . Proceedings of the 2007 Envisat Symposium . April 23–27 , Montreux, Switzerland.
   Google Scholar