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Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain)

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Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain)

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Hermosilla, T.; Díaz Manso, J.; Ruiz Fernández, LÁ.; Recio Recio, JA.; Fernández-Sarría, A.; Ferradáns Nogueira, P. (2012). Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain). Applied Geomatics. 4(4):245-255. doi:10.1007/s12518-012-0087-z

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/58196

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Title: Analysis of parcel-based image classification methods for monitoring the activities of the Land Bank of Galicia (Spain)
Author:
UPV Unit: Universitat Politècnica de València. Departamento de Ingeniería Cartográfica Geodesia y Fotogrametría - Departament d'Enginyeria Cartogràfica, Geodèsia i Fotogrametria
Issued date:
Abstract:
[EN] The abandonment of agricultural plots entails a low economic productivity of the land and a higher vulnerability to wildfires and degradation of affected areas. In this sense, the local government of Galicia is promoting ...[+]
Subjects: Mapping Agriculture , High-resolution imagery , Change detection , Object-based classification
Copyrigths: Reserva de todos los derechos
Source:
Applied Geomatics. (issn: 1866-9298 )
DOI: 10.1007/s12518-012-0087-z
Publisher:
Springer Verlag (Germany)
Publisher version: http://dx.doi.org/10.1007/s12518-012-0087-z
Thanks:
The authors appreciate the collaboration and support provided by Xunta de Galicia, Sociedade para o Desenvolvemento Comarcal de Galícia, and Banco de Terras de Galicia. The financial support provided by the Spanish ...[+]
Type: Artículo

References

Arikan M (2004) Parcel-based crop mapping through multi-temporal masking classification of landsat 7 images in Karacabey, Turkey. Int Arch Photogramm Remote Sens Spat Inf Sci 35:1085–1090

Balaguer A, Ruiz LA, Hermosilla T, Recio JA (2010) Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Comput Geosci 36(2):231–240

Balaguer-Besser A, Hermosilla T, Recio JA, Ruiz LA (2011) Semivariogram calculation optimization for object-oriented image classification. Model Sci Educ Learn 4(7):91–104 [+]
Arikan M (2004) Parcel-based crop mapping through multi-temporal masking classification of landsat 7 images in Karacabey, Turkey. Int Arch Photogramm Remote Sens Spat Inf Sci 35:1085–1090

Balaguer A, Ruiz LA, Hermosilla T, Recio JA (2010) Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification. Comput Geosci 36(2):231–240

Balaguer-Besser A, Hermosilla T, Recio JA, Ruiz LA (2011) Semivariogram calculation optimization for object-oriented image classification. Model Sci Educ Learn 4(7):91–104

Blaschke T (2010) Object based image analysis for remote sensing. ISPRS J Photogramm 65(1):2–16

Cohen Y, Shoshany M (2000) Integration of remote sensing, GIS and expert knowledge in national knowledge-based crop recognition in Mediterranean environment. Int Arch Photogramm Remote Sens 33(Part B7):280–286

Congalton R (1991) A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens Environ 37(1):35–46

Dadhwal VK, Singh RP, Dutta S, Parihar JS (2002) Remote sensing based crop inventory: a review of Indian experience. Trop Ecol 43(1):107–122

De Wit AJW, Clevers JGPW (2004) Efficiency and accuracy of per-field classification for operational crop mapping. Int J Remote Sens 25:4091–4112

Del Frate F, Pacifici F, Solimini D (2008) Monitoring urban land cover in Rome, Italy, and its changes by single-polarization multitemporal SAR images. IEEE J Sel Top Appl Earth Obs Remote Sens 1:87–97

Díaz-Manso JM, Ferradáns-Nogueira P (2011) Modelo de uso actual da terra. In: Cobelle-Rico EJ, Diaz-Manso JM, Crecente-Maseda R, Martínez-Rivas EM (eds) Mercado e Mobilidade de Terras en Galícia, 1st edn. Servizo de Publicacións e Intercambio Científico, Santiago de Compostela, Spain, pp 31–44

Dupas CA (2000) SAR and LANDSAT TM image fusion for land cover classification in the Brazilian Atlantic Forest Domain. Int Arch Photogramm Remote Sens XXXIII(Part B1):96–103

El Kady M, Mack CB (1992) Remote sensing for crop inventory of Egypt’s old agricultural lands. Int Arch Photogramm Remote Sens 29:176–185

Everitt BS, Dunn G (2001) Applied multivariate data analysis, 2nd edn. Edward Arnold, London

Haralick RM, Shanmugam K, Dinstein I (1973) Texture features for image classification. IEEE Transact Syst Man Cybern 3(6):610–622

Hermosilla T, Almonacid J, Fernández-Sarría A, Ruiz LA, Recio JA (2010) Combining features extracted from imagery and lidar data for object-oriented classification of forest areas. Int Arch Photogramm Remote Sens Spat Inf Sci 38(4/C7)

Hernández Orallo J, Ramírez Quintana MJ, Ferri Ramírez C (2004) Introducción a la minería de datos. Pearson Educación S.A, Madrid

Homer C, Huang C, Yang L, Wylie B, Coan M (2004) Development of a 2001 National Land-Cover Database for the United States. Photogramm Eng Remote Sens 70:829–840

Huberty CJ (1994) Applied discriminant analysis. Wiley, New York

Laws KI (1985) Goal-directed texture image segmentation. Appl Artif Intel II, SPIE 548:19–26

Ormeci C, Alganci U, Sertel E (2010) Identification of crop areas using SPOT-5 data, FIG Congress 2010 Facing the Challenges—building the capacity. Sydney, Australia, pp 11–16

Peled A, Gilichinsky M (2004) GIS-driven analyses of remotely sensed data for quality assessment of existing land cover classification. Int Arch Photogramm Remote Sens Spat Inf Sci 35

Peled A, Gilichinsky M (2010) Knowledge-based classification of land cover for the quality assessment of GIS database. Int Arch Photogramm Remote Sens Spat Inf Sci 38:217–222

Perveen F, Nagasawa R, Ali S, Husnain (2008) Evaluation of ASTER spectral bands for agricultural land cover mapping using pixel-based and object-based classification approaches. Int Arch Photogramm Remote Sens Spat Inf Sci 37(4-C1)

Petit CC, Lambin EF (2002) Impact of data integration technique on historical land-use/land-cover change: comparing historical maps with remote sensing data in the Belgian Ardennes. Landsc Ecol 17:117–132

Quinlan JR (1993) C4.5: Programs for machine learning. Kaufmann, San Francisco

Rabe A, van der Linden S, Hostert P (2010) imageSVM, Version 2.1. www.hu-geomatics.de

Recio JA, Hermosilla T, Ruiz LA, Fernández-Sarría A (2011) Historical land use as a feature for image classification. Photogramm Eng Remote Sens 77(4):377–387

Ruiz LA, Fernández-Sarría A, Recio JA (2004) Texture feature extraction for classification of remote sensing data using wavelet decomposition: a comparative study. Int Arch Photogramm Remote Sens Spat Inf Sci 35(B4):1109–1115

Ruiz LA, Recio JA, Hermosilla T, Fdez. Sarriá A (2009) Identification of agricultural and land cover database changes using object-oriented classification techniques. 33rd International Symposium on Remote Sensing of Environment, May 4–8, Stresa (Italy)

Ruiz LA, Recio JA, Fernández-Sarría A, Hermosilla T (2011) A feature extraction software tool for agricultural object-based image analysis. Comput Electron Agric 76(4):284–296

Tansey K, Chambers I, Anstee A, Denniss A, Lamb A (2009) Object-oriented classification of very high resolution airborne imagery for the extraction of hedgerows and field margin cover in agricultural areas. Appl Geogr 29(2):145–157

van der Linden S, Rabe A, Wirth F, Suess S, Okujeni A, Hostert P (2010) imageSVM regression, application manual: imageSVM version 2.1. Humboldt-Universität zu Berlin, Germany

Vapnik VN (1998) Statistical learning theory. Wiley, New York

Walsh SJ, McCleary AL, Mena CF, Shao Y, Tuttle JP, Gonzalez A, Atkinson R (2008) QuickBird and Hyperion data analysis of an invasive plant species in the Galapagos Islands of Ecuador: implications for control and land use management. Remote Sens Environ 112(5):1927–1941

Walter V (2004) Object-based classification of remote sensing data for change detection. ISPRS J Photogramm Remote Sens 58:225–238

Walter V (2005) Object-based evaluation of lidar and multiespectral data for automatic change detection in GIS databases. Geo-Inf Syst 18:10–15

Zaragozí, B, Rabasa, A, Rodríguez-Sala, JJ, Navarro, JT, Belda, A, Ramón, A (2012) Modelling farmland abandonment: A study combining GIS and data mining techniques. Agric Ecosys Environ 155:124–132

Zhang S, Liu X (2005) Realization of data mining model for expert classification using multi-scale spatial data. Int Arch Photogramm Remote Sens Spat Inf Sci 26(4/W6):107–111

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