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Automatic habitat classification methods based on satellite images: A practical assessment in the NW Iberia coastal mountains

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Abstract

Although remote sensing is increasingly in use for habitat mapping, traditional image classification methods tend to suffer shortcomings due to non-normality of spectral signatures, as well as overlapping and heterogeneity in radiometric responses of natural and semi natural vegetation. Methods using non-parametric classifiers and object-oriented analysis have been suggested as possible solutions for overcoming these limitations. In this paper, we aimed at evaluating the performance of some of these techniques for the European Natura 2000 network of protected areas habitats mapping. For this purpose, we tested different methods of supervised image classification in the Northern Mountains of Galicia, Spain, an area included in the Natura 2000 network, which is characterized by a highly heterogeneous landscape. Methods involved the use of maximum likelihood and nearest neighbour decision rules in per-pixel and per-object classification analyses on Landsat TM imagery. Per-object classifications were completed using the segment mean and segment means plus standard deviation feature spaces. The results showed the existence of significant differences in the accuracies for the different methodologies, their strengths and weaknesses and identified the most adequate approach for habitat mapping. Analyses pointed out that significant improvements in accuracy were achieved only under certain combinations of per-object analysis, non-parametric classifiers and high dimensionality feature space.

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References

  • Armitage, R. P., Kent, M., & Weaver, R. E. (2004). Identification of the spectral characteristics of British semi-natural upland vegetation using direct ordination: A case study from Dartmoor, UK. International Journal of Remote Sensing, 25, 3369–3388.

    Article  Google Scholar 

  • Armitage, R. P., Weaver, R. E., & Kent, M. (2000). Remote sensing of semi-natural upland vegetation: The relationship between species composition and spectral response. In R. Alexander, & A. C. Millington (Eds.) Vegetation mapping. from patch to planet (pp. 159–176). Chichester: John Wiley & Sons.

    Google Scholar 

  • Baatz, M., Benz, U., Dehghani, S., Heynen, M., Höltje, A., Hofmann, P., Lingenfelder, I., Mimler, M., Sohlbach, M., Weber, M., & Willhauck, G. (2004). ECognition Professional User Manual 4. (München: Definiens Imaging).

  • Bardgett, R. D., Marsden, J. H., & Howard, D. C. (1995). The extent and condition of heather on moorland in the uplands of England and Wales. Biological Conservation, 71, 155–161.

    Article  Google Scholar 

  • Baudry, J., Bunce, R. G. H., & Burel, F. (2000). Hedgerows: An international perspective on their origin, function and management. Journal of Environmental Management, 60, 7–22.

    Article  Google Scholar 

  • Bellman, R. E. (1961). Adaptive control processes: a guided tour. Princeton, NJ: Princeton University Press.

    Google Scholar 

  • Benz, U. C., Hofmann, P., Willhauck, G., Lingenfelder, I., & Heynen, M. (2004). Multi-resolution, object-oriented fuzzy analysis of remote sensing data for GIS-ready information. ISPRS Journal of Photogrammetry and Remote Sensing, 58, 239–258.

    Article  Google Scholar 

  • Bielsa, I., Pons, X., & Bunce, B. (2005). Agricultural abandonment in the North Eastern Iberian Peninsula: The use of basic landscape metrics to support planning. Journal of Environmental Planning and Management, 48, 85–102.

    Article  Google Scholar 

  • Bishop, Y. M. M., Fienberg, S. E., & Holland, P. W. (1975). Discrete multivariate analysis: theory and practice. Massachusetts: MIT Press, Cambridge.

    Google Scholar 

  • Blaschke, T., Conradi, M., & Lang, S. (2001). Multi-scale image analysis for ecological monitoring of heterogeneous, small structured landscapes. Proceedings of SPIE. Remote Sensing for Environmental Monitoring, GIS Applications, and Geology. Toulouse (France) 18–21 September 2001, pp, 35–44.

  • Blaschke, T., & Strobl, J. (2001). What’s wrong with pixels? Some recent developments interfacing remote sensing and GIS. GeoBIT/GIS, 4, 12–17.

    Google Scholar 

  • Blondel, J. (1979). Biogéographie et écologie. Paris: Masson.

    Google Scholar 

  • Bock, M. (2003). Remote sensing and GIS-based techniques for the classification and monitoring of biotopes: Case examples for a wet grass- and moor land area in Northern Germany. Journal for Nature Conservation, 11, 145–155.

    Google Scholar 

  • Bock, M., Xofis, P., Mitchley, J., Rossner, G., & Wissen, M. (2005a). Object-oriented methods for habitat mapping at multiple scales—Case studies from Northern Germany and Wye Downs, UK. Journal for Nature Conservation, 13, 75–89.

    Article  Google Scholar 

  • Bock, M., et al. (2005b). Spatial indicators for nature conservation from European to local scale. Ecological Indicators, 5(4), 322–338.

    Article  Google Scholar 

  • Bouhier, A. (1979). La Galice, essai geographique d’un vieux complexe agraire. Dissertation. France: Université de Poitiers, Vendée.

    Google Scholar 

  • Boyd, D. S., Sanchez-Hernandez, C., & Foody, G. M. (2006). Mapping a specific class for priority habitats monitoring from satellite sensor data. International Journal of Remote Sensing, 27(13), 2631–2644.

    Article  Google Scholar 

  • Bradbury, P., Howard, D. C., Bunce, R. G. H., & Deane, G. C. (1989). Production of maps and estimates of area. In R. G. H. Bunce (Ed.) Heather in England and Wales (p. 5−17). London: HMSO.

    Google Scholar 

  • Burnett, C., Aaviksoo, K., Lang, S., Langanke, T. & Blaschke, T. (2003). An object-based methodology for mapping mires using high resolution imagery. Ecohydrological Processes in Northern Wetlands. Tallinn, Estonia, 30 June–4 July 2003. 6 pp.

  • Burnett, C., & Blaschke, T. (2003). A multi-scale segmentation/object relationship modelling methodology for landscape analysis. Ecological Modelling, 168, 233–249.

    Article  Google Scholar 

  • C.P.T.O.P.V. (1995). Mapa topográfico de Galicia Escala 1:5000. Consellería de Política Territorial, Obras Públicas e Vivenda. Xunta de Galicia.

  • Calvo-Iglesias, M. S., Fra-Paleo, U., Crecente-Maseda, R., & Diaz-Varela, R. A. (2006). Directions of change in land cover and landscape patterns from 1957 to 2000 in agricultural landscapes in NW Spain. Environmental Management, 38, 921–933.

    Article  Google Scholar 

  • Cayuela, L., Golicher, J. D., Salas Rey, J., & Rey Benayas, J. M. (2006). Classification of a complex landscape using Dempster-Shafer theory of evidence. International Journal of Remote Sensing, 27, 1951–1971.

    Article  Google Scholar 

  • Cherrill, A. J., Lane, A., & Fuller, R. M. (1994). The use of classified landsat-5 thematic mapper imagery in the characterization of landscape composition: A case study in Northern England. Journal of Environmental Management, 40, 357–377.

    Article  Google Scholar 

  • Chuvieco, E. (2002). Teledetección ambiental. La observación de la tierra desde el espacio. Barcelona: Editorial Ariel.

    Google Scholar 

  • Cohen, J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–40.

    Article  Google Scholar 

  • Congalton, R. G. (1991). A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, 35–46.

    Article  Google Scholar 

  • Congalton, R. G., & Green, K. (1999). Assessing the accuracy of remotely sensed data: principles and practices. Boca Raton, Florida: Lewis Publishers.

    Google Scholar 

  • Cortijo, F. J., & Pérez de la Blanca, N. (1997). A comparative study of some non-parametric spectral classifiers. Applications to problems with high-overlapping training sets. International Journal of Remote Sensing, 18, 1259–1275.

    Article  Google Scholar 

  • Cruickshank, M. M., & Tomlinson, R. W. (1996). Application of CORINE land cover methodology to the UK-some issues raised from Northern Ireland. Global Ecology and Biogeography Letters, 5, 235–248.

    Article  Google Scholar 

  • de Leeuw, J., Jia, H., Yang, L., Liu, X., Schmidt, K., & Skidmore, A. K. (2006). Comparing accuracy assessments to infer superiority of image classification methods. International Journal of Remote Sensing, 27, 223–232.

    Article  Google Scholar 

  • Devillers, P., & Devillers-Terschuren, J. (1996). A classification of palaeartic habitats. Strasbourg: Council of Europe Publishing.

    Google Scholar 

  • Dias, E., Elias, R. B., & Nunes, V. (2004). Vegetation mapping and nature conservation: A case study in Terceira Island (Azores). Biodiversity and Conservation, 13(8), 1519–1539.

    Article  Google Scholar 

  • Donoghue, D. N. M., & Mironnet, N. (2002). Development of an integrated geographical information system prototype for coastal habitat monitoring. Computers & Geosciences, 28(1), 129–141.

    Article  Google Scholar 

  • Dorren, L. K. A., Maier, B., & Seijmonsbergen, A. C. (2003). Improved Landsat-based forest mapping in steep mountainous terrain using object-based classification. Forest Ecology and Management, 183, 31–46.

    Article  Google Scholar 

  • Duda, R. O., Hart, P. E., & Stork, D. G. (2001). Pattern classification. New York: Willey.

    Google Scholar 

  • Egan, S., Smith, A., Robertson, D., & Waterhouse, A. (2000). Estimation of heather biomass using ground based methods for the calibration of remotely sensed data. Aspects of Applied Biology, 58, 1–9.

    Google Scholar 

  • Feise, R. (2002). Do multiple outcome measures require p-value adjustment? BMC Medical Research Methodology, 2(1), 8.

    Article  Google Scholar 

  • Foody, G. M. (1992). A fuzzy sets approach to the representation of vegetation continua from remotely sensed data: An example from lowland heath. Photogrammetric Engineering and Remote Sensing, 58, 221–225.

    Google Scholar 

  • Foody, G. M. (1996). Fuzzy modelling of vegetation from remotely sensed imagery. Ecological Modelling, 85, 3–12.

    Article  Google Scholar 

  • Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80, 185–201.

    Article  Google Scholar 

  • Gallego, F. J. (2001). Comparing CORINE land cover with a more detailed database in Arezzo (Italy). Towards Agri-environmental indicators, Topic report 6/2001. Copenhagen: European Environment Agency.

    Google Scholar 

  • Geneletti, D., & Gorte, B. G. H. (2003). A method for object-oriented land cover classification combining Landsat TM data and aerial photographs. International Journal of Remote Sensing, 24, 1273–1286.

    Article  Google Scholar 

  • Hansen, M. J., Franklin, S. E., Woudsma, C. G., & Woudsma, C. G. (2001). Caribou habitat mapping and fragmentation analysis using Landsat MSS, TM, and GIS data in the North Columbia Mountains, British Columbia, Canada. Remote Sensing of Environment, 77, 50–65.

    Article  Google Scholar 

  • Hardin, P. J. (1994). Parametric and nearest neighbor methods for hybrid classification. Photogrammetric Engineering & Remote Sensing, 60, 1439–1448.

    Google Scholar 

  • Hay, G. J., Blaschke, T., Marceau, D. J., & Bouchard, A. (2003). A comparison of three image-object methods for the multiscale analysis of landscape structure. ISPRS Journal of Photogrammetry & Remote Sensing, 57, 327–345.

    Article  Google Scholar 

  • Hay, G. J., Castilla, G., Wulder, M. A., & Ruiz, J. R. (2005). An automated object-based approach for the multiscale image segmentation of forest scenes. International Journal of Applied Earth Observation and Geoinformation, 7, 339–359.

    Article  Google Scholar 

  • Hubert-Moy, L., Cotonnec, A., Le Du, L., Chardin, A., & Perez, P. (2001). A Comparison of parametric classification procedures of remotely sensed data applied on different landscape units. Remote Sensing of Environment, 75, 174–187.

    Article  Google Scholar 

  • Imbernon, J., & Branthomme, A. (2001). Characterization of landscape patterns of deforestation in tropical rain forests. International Journal of Remote Sensing, 22, 1753–1765.

    Article  Google Scholar 

  • Izco Sevillano, J., & Ramil Rego, P. (2001). Análisis y Valoración de la Sierra de O Xistral: un Modelo de Aplicación de la Directiva Hábitat en Galicia. Santiago de Compostela: Centro de Información e Tecnoloxía Ambiental. Consellería de Medio Ambiente. Xunta de Galicia.

  • Laliberte, J. R. (1996). Introductory digital image procesing. A remote sensing perspective. New Jersey: Prentice Hall.

    Google Scholar 

  • Laliberte, A. S., Rango, A., Havstad, K. M., Paris, J. F., Beck, R. F., Mcneely, R., & Gonzalez, A. L. (2004). Object-oriented image analysis for mapping shrub encroachment from 1937 to 2003 in southern New Mexico. Remote Sensing of Environment, 93, 198–210.

    Article  Google Scholar 

  • Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.

    Article  CAS  Google Scholar 

  • Langanke, T., Rossner, G., Vrscaj, B., Lang, S., & Mitchley, J. (2005). Selection and application of spatial indicators for nature conservation at different institutional levels. Journal for Nature Conservation, 13(2–3), 101–114.

    Article  Google Scholar 

  • Levin, S. A. (1992). The problem of pattern and scale in ecology: The Robert H. MacArthur Award lecture. Ecology, 73, 1943–1967.

    Article  Google Scholar 

  • Lillesand, T. M., & Kiefer, R. W. (1994). Remote sensing and image interpretation. New York: Wiley.

    Google Scholar 

  • Lobo, A. (1997). Image segmentation and discriminant analysis for the identification of land cover units in ecology. IEEE Transactions on Geoscience and Remote Sensing, 35, 1136–1145.

    Article  Google Scholar 

  • Lobo, A., Chic, O., & Casterad, A. (1996). Classification of Mediterranean crops with multisensor data: Per-pixel versus per-object statistics and image segmentation. International Journal of Remote Sensing, 17, 2385–2400.

    Article  Google Scholar 

  • Marceau, D. J., & Hay, G. J. (1999). Remote sensing contributions to the scale issue. Canadian Journal of Remote Sensing, 25, 357–366.

    Google Scholar 

  • McDonald, D., et al. (2000). Agricultural abandonment in mountain areas of Europe: Environmental consequences and policy response. Journal of Environmental Management, 59, 47–69.

    Article  Google Scholar 

  • McNemar, Q. (1947). Note on the sampling error of the difference between correlated proportions or percentages. Psychometrika, 12, 153–157.

    Article  Google Scholar 

  • Mehner, H., Cutler, M., Fairbairn, D., & Thompson, G. (2004). Remote sensing of upland vegetation: The potential of high spatial resolution satellite sensors. Global Ecology and Biogeography, 13, 359–369.

    Article  Google Scholar 

  • Millington, A. C., & Alexander, R. W. (2000). Vegetation mapping in the last three decades of the twentieth century. In R. Alexander, & A. C. Millington (Eds.) Vegetation mapping. from patch to planet (pp. 321–332). Chichester: John Willey & Sons, LTD).

    Google Scholar 

  • Mitchley, J., Price, M., & Tzanopoulos, J. (2006). Integrated futures for Europe’s mountain regions: Reconciling biodiversity conservation and human livelihoods. Journal of Mountain Science, 3, 276–286.

    Article  Google Scholar 

  • Monserud, R. A., & Leemans, R. (1992). Comparing global vegetation maps with the Kappa statistic. Ecological Modelling, 62, 275–293.

    Article  Google Scholar 

  • Muñoz Sobrino, C., Ramil-Rego, P., Gómez-Orellana, L., & Díaz Varela, R. A. (2005). Palynological data on major Holocene climatic events in NW Iberia. Boreas, 34, 1–20.

    Article  Google Scholar 

  • Ozesmi, S. L., & Bauer, M. E. (2002). Satellite remote sensing of wetlands. Wetlands Ecology and Management, 10, 381–402.

    Article  Google Scholar 

  • Pal, M., & Mather, P. M. (2003). An assessment of the effectiveness of decision tree methods for land cover classification. Remote Sensing of Environment, 86, 554–565.

    Article  Google Scholar 

  • Palo, A., & Kikas, T. (2003). Methodological problems of compiling digital vegetation site types maps: Case of Saare County, Estonia. Journal for Nature Conservation, 11(3), 135–144.

    Article  Google Scholar 

  • Paola, J. D., & Schowengerdt, R. A. (1995). A detailed comparison of backpropagation neural network and maximum-likelihood classifiers for urban land use classification. IEEE Transactions on Geoscience and Remote Sensing, 33, 981–996.

    Article  Google Scholar 

  • Parkyn, L., & Stoneman, R. (1997). The Scottish raised bog land cover survey. In L. Parkyn, R. E. Stoneman, & H. A. P. Lingram (Eds.) Conserving peatlands (pp. 193–203). Wallingford: CAB International. Scottish Wildlife Trust.

    Google Scholar 

  • Pavlenko, T. (2003). On feature selection, curse-of-dimensionality and error probability in discriminant analysis. Journal of Statistical Planning and Inference, 115, 565–584.

    Article  Google Scholar 

  • Pedroni, L. (2003). Improved classification of landsat thematic mapper data using modified prior probabilities in large and complex landscapes. International Journal of Remote Sensing, 24, 91–113.

    Article  Google Scholar 

  • Poulin, M., Careau, D., Rochefort, L., & Desrochers, A. (2002). From satellite imagery to peatland vegetation diversity: how reliable are habitat maps? Conservation ecology, 6, Article 16. Retrieved June 15, 2005, from http://www.consecol.org/vol6/iss2/art16.

  • Ramil-Rego, P., Rodríguez Guitián, M. A., & Rodríguez Oubiña, J. (1996). Valoración de los Humedales Continentales del NW Ibérico: Caracterización Hidrológica, Geomorfológica y Vegetacional de las Tuberas de las Sierras Septentrionales de Galicia. In A. Pérez Alberti, & A. Martínez Cortizas (Eds.) Avances en la Reconstrucción Paleoambiental de las Áreas de Montaña Lucenses. Monografías G.E.P. 1 (pp. 165–187). Lugo: Deputación Provincial de Lugo. Servicio de Publicacións).

    Google Scholar 

  • Reid, E., & Quarmby, N. (2000). Determining the composition of the blanquet bogs of Scotland using landsat thematic mapper. In R. Alexander, & A. C. Millington (Eds.) Vegetation mapping. From patch to planet (pp. 159–176). Chichester: John Willey & Sons, LTD.

    Google Scholar 

  • Reid, E., Ross, S. Y., Thomson, D. B. A., & Lindsay, R. A. (1997). From sphagnum to satellite: Towards a comprehensive inventory of the blanket mires of Scotland. In L. Parkyn, R. E. Stoneman, & H. A. P. Lingram (Eds.) Conserving peatlands (pp. 204–216). Wallingford: CAB International; Scottish Wildlife Trust.

    Google Scholar 

  • Roberts, D. A., Gardner, R. H., Church, R., Ustin, S., Scheer, G., & Green, R. O. (1998). Mapping Chaparral in the Santa Monica mountains using multiple endmember spectral mixture models. Remote Sensing of Environment, 56, 267–279.

    Article  Google Scholar 

  • Robertson, D., Egan, S., Waterhouse, A., Smith, A., Holland, J. P., & Gooding, R. F. (2003). Characterisation of Calluna vulgaris dominant moorland using remote sensing with Landsat TM. In Buchreithner (Ed.) A decade of trans-european remote sensing co-operation (pp. 377–382). Rotterdam: Balkema.

    Google Scholar 

  • Rodríguez Guitián, M. A. (2004). Aplicación de Criterios Botánicos para a Proposta de Modelos de Xestión Sustentable das Masas Arborizadas Autóctonas do Subsector Galaico-Asturiano Septentrional. Dissertation. Departemento de Producción Vexetal. Escola Politécnica Superior. Universidade de Santiago de Compostela.

  • Roughgarden, J., Running, S. W., & Matson, P. A. (1991). What does remote sensing do for ecology? Ecology, 72, 1918–1922.

    Article  Google Scholar 

  • Schmidt, K. S., & Skidmore, A. K. (2003). Spectral discrimination of vegetation types in a coastal wetland. Remote Sensing of Environment, 85, 92–108.

    Article  Google Scholar 

  • Shoshany, M. (2002). Landscape fragmentation and soil cover changes on south- and north-facing slopes during ecosystems recovery: An analysis from multi-date air photographs. Geomorphology, 45, 3–20.

    Article  Google Scholar 

  • S.I.T.G.A. (2000). Fotografía aérea do SITGA. Sistema de Información Territorial de Galicia. Sociedade para o Desenvolvemento Comarcal. Consellería de Política Agroalimentaria e Desenvolvemento Rural. Santiago de Compostela.

  • Skidmore, A. K., Forbes, G. W., & Carpenter, D. J. (1988). Non-parametric test of overlap in multispectral classification. International Journal of Remote Sensing, 9, 777–785.

    Article  Google Scholar 

  • Smith, J. H., Stehman, S. V., Wickham, J. D., & Yang, L. (2003). Effects of landscape characteristics on land-cover class accuracy. Remote Sensing of Environment, 84, 342–349.

    Article  Google Scholar 

  • Song, C., & Woodcock, C. E. (2003). Monitoring forest succession with multitemporal Landsat images: Factors of uncertainty. IEEE Transactions on Geoscience and Remote Sensing, 41(11), 2557–2567.

    Article  Google Scholar 

  • Song, C., Woodcock, C. E., Seto, K. C., Lenney, M. P., & Macomber, S. A. (2001). Classification and change detection using landsat TM data: When and how to correct atmospheric effects? Remote Sensing of Environment, 75, 230–244.

    Article  Google Scholar 

  • Stehman, S. V. (1997). Selecting and interpreting measures of thematic classification accuracy. Remote Sensing of Environment, 62, 77–89.

    Article  Google Scholar 

  • Stehman, S. V. (1999). Basic probability sampling designs for thematic map accuracy assessment. International Journal of Remote Sensing, 20, 2423–2441.

    Article  Google Scholar 

  • Stehman, S. V. (2001). Statistical rigor and practical utility in thematic map accuracy assessment. Photogrammetric Engineering and Remote Sensing, 67, 727–734.

    Google Scholar 

  • Tapiador, F. J., & Casanova, J. L. (2003). Land use mapping methodology using remote sensing for the regional planning directives in Segovia, Spain. Landscape and Urban Planning, 62, 103–115.

    Article  Google Scholar 

  • Thomas, V., Treitz, P., Jelinski, D., Miller, J., Lafleur, P., & Mccaughey, J. H. (2003). Image classification of a northern peatland complex using spectral and plant community data. Remote Sensing of Environment, 84, 83–99.

    Article  Google Scholar 

  • Thomson, D. C., & Klassen, G. H. (1980). Caribou habitat mapping in the southern district of Keewatin, N.W.T.: An application of digital Landsat data. Journal of Applied Ecology, 17, 125–138.

    Article  Google Scholar 

  • Tortora, R. (1978). A note on sample size estimation for multinomial populations. American Statistician, 32, 100–102.

    Article  Google Scholar 

  • Trodd, N. M. (1996). Analysis and representation of heathland vegetation from near-ground level remotely-sensed data. Global Ecology and Biogeography Letters, 5, 206–216.

    Article  Google Scholar 

  • Vandenbroucke, D., Neys, L., Peedell, S., & Rizo, J. (2002). Land cover and land use in the NATURA 2000 network using LUCAS data, European Commission, Joint Research Centre (DG JRC), Institute for Environment and Sustainability (IES) Land Management Unit, Ispra.

  • Van Der Sande, C. J., De Jong, S. M., & De Roo, A. P. J. (2003). A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment. International Journal of Applied Earth Observation and Geoinformation, 4, 217–229.

    Article  Google Scholar 

  • Viswanath, P., Murty, N., & Bhatnagar, S. (2005). Overlap pattern synthesis with an efficient nearest neighbor classifier. Pattern Recognition, 38, 1187–1195.

    Article  Google Scholar 

  • Wardley, N. W., Milton, E. J., & Hill, C. T. (1987). Remote-sensing of structurally complex semi-natural vegetation—An example from heathland. International Journal of Remote Sensing, 8, 31–42.

    Article  Google Scholar 

  • Weaver, R. E. (1987). Spectral separation of moorland vegetation in airborne thematic mapper data. International Journal of Remote Sensing, 8, 43–55.

    Article  Google Scholar 

  • Weiers, S., Bock, M., Wissen, M., & Rossner, G. (2004). Mapping and indicator approaches for the assessment of habitats at different scales using remote sensing and GIS methods. Landscape and Urban Planning, 67, 43–65.

    Article  Google Scholar 

  • Wilkinson, G. G. (2005). Results and implications of a study of fifteen years of satellite image classification experiments. IEEE Transactions on Geoscience and Remote Sensing, 43, 433–440.

    Article  Google Scholar 

  • Wright, G. G., Sibbald, A. R., & Allison, J. S. (1997). The integration of a satellite spectral analysis into a heather moorland management model (HMMM): The case of Moidach More, northeast Scotland, U.K. International Journal of Remote Sensing, 18, 2319–2336.

    Article  Google Scholar 

  • Wu, C., & Murray, A. T. (2003). Estimating impervious surface distribution by spectral mixture analysis. Remote Sensing of Environment, 84, 493–505.

    Article  Google Scholar 

  • Zonneveld, I. S. (1988). Observation means and platforms. In A. W. Küchler, & I. S. Zonneveld (Eds.)Vegetation mapping (pp. 233–248). Dordrech: Kluwer Academic Publishers.

    Google Scholar 

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  1. I.B.A.D.E.R. Departamento de Botánica. GI 1934 TTB, Universidade de Santiago de Compostela, Lugo, Spain

    R. A. Díaz Varela & P. Ramil Rego

  2. Departamento de Enxeñería Agroforestal, Universidade de Santiago de Compostela, Lugo, Spain

    S. Calvo Iglesias

  3. Departamento Bioloxía Vexetal e Ciencias do Solo, Universidade de Vigo, Vigo, Spain

    C. Muñoz Sobrino

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  1. R. A. Díaz Varela
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  3. S. Calvo Iglesias
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  4. C. Muñoz Sobrino
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Díaz Varela, R.A., Ramil Rego, P., Calvo Iglesias, S. et al. Automatic habitat classification methods based on satellite images: A practical assessment in the NW Iberia coastal mountains. Environ Monit Assess 144, 229–250 (2008). https://doi.org/10.1007/s10661-007-9981-y

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