A cost-effective approach for improving the quality of soil sealing change detection from Landsat imagery

References

• Ahl D. E., Gower S.T., Burrows S. N., Shabanov N. V., Myneni R. B., Knyazikhin Y. (2006)—Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS. Remote Sensing of Environment, 104 (1): 88–95. doi: http://dx.doi.org/10.1016/j.rse.2006.05.003.
   Web of Science ®Google Scholar
• Alberti M., Weeks R., Coe S. (2004)—Urban Land Cover Change Analysis in Central Puget Sound. Photogrammetric Engineering & Remote Sensing, 70 (9): 1043–1052.
   Web of Science ®Google Scholar
• Blaschke T., Lang S., Hay G. J. (2008)—Object-Based Image Analysis. Spatial Concepts for Knowledge-Driven Remote Sensing Applications. Springer Berlin Heidelberg, pp. 817. doi: http://dx.doi.org/10.1007/978-3-540-77058-9.
   Google Scholar
• Beck P. S. A., Atzberger C., Hogda K. A., Johansen B., Skidmore A. K. (2006)—Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI. Remote Sensing of Environment, 100 (3): 321–334. doi: http://dx.doi.org/10.1016/j.rse.2005.10.021.
   Web of Science ®Google Scholar
• Capotorti G., Del Vico E., Lattanzi E., Tilia A., Celesti-Grapow L. (2013)—Exploring biodiversity in a metropolitan area in the Mediterranean region: The urban and suburban flora of Rome (Italy). Plant Biosystems, 147 (1): 174–185. doi: http://dx.doi.org/10.1080/11263504.2013.771715.
   Web of Science ®Google Scholar
• Ceccarelli T., Smiraglia D., Bajocco S., Rinaldo S., De Angelis A., Salvati L., Perini L. (2013)—Land cover data from Landsat single-date imagery: an approach integrating pixel-based and object-based classifiers. European Journal of Remote Sensing, 46: 699–717. doi: http://dx.doi.org/10.5721/EuJRS20134641.
   Web of Science ®Google Scholar
• 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 (5): 893–903. doi: http://dx.doi.org/10.1016/j.rse.2009.01.007.
   Web of Science ®Google Scholar
• Conchedda G., Durieux L., Mayaux P. (2008)—An object-based method for mapping and change analysis in mangrove ecosystems. ISPRS Journal of Photogrammetry and Remote Sensing, 63 (5): 578–589. doi: http://dx.doi.Org/10.1016/j.isprsjprs.2008.04.002.
   Web of Science ®Google Scholar
• Crist E. P., Cicone R. C. (1984)—A physically-based transformation of Thematic Mapper data—the TM Tasseled Cap. IEEE Transactions on Geosciences and Remote Sensing, 22 (3): 256–263. doi: http://dx.doi.org/10.1109/TGRS.1984.350619.
   Web of Science ®Google Scholar
• Duveiller G., Defourny P., Desclée B., Mayaux P. (2008)—Deforestation in Central Africa: Estimates at regional, national and landscape levels by advanced processing of systematically-distributed Landsat extracts. Remote Sensing of Environment, 112 (5): 1969–1981. doi: http://dx.doi.org/10.1016/j.rse.2007.07.026.
   Google Scholar
• Eckelmann W., Baritz R., Bialousz S., Bielek P., Carre F., Houšková B., Jones R. J. A., Kibblewhite M. G., Kozak J., Le Bas C., Tóth G., Tóth T., Várallyay G., Yli Halla M., Zupan M. (2006)—Common criteria for risk area identification according to soil threats. European Soil Bureau Research Report No. 20, EUR 22185 EN. Office for Official Publications of the European Communities, Luxembourg, pp. 94.
   Google Scholar
• Foody G. M. (2003)—Remote sensing of tropical forest environments: towards the monitoring of environmental resources for sustainable development. International Journal of Remote Sensing, 24 (20): 4035–4046. doi: http://dx.doi.org/10.1080/0143116031000103853.
   Web of Science ®Google Scholar
• Gargano D., Mingozzi A., Massolo A., Rinaldo S., Bernardo L. (2012)—Patterns of vegetation cover/dynamics in a protected Mediterranean mountain area: Influence of the ecological context and protection policy. Plant Biosystems, 146 (1): 9–18. doi: http://dx.doi.org/10.1080/11263504.2011.641689.
   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 Geonformation, 7 (4): 339–359. doi: http://dx.doi.org/10.1016/j.jag.2005.06.005.
   Web of Science ®Google Scholar
• Huang C., Wylie B., Yang L., Homer C., Zylstra G. (2002)—Derivation of a tasselled cap transformation based on Landsat 7 at satellite reflectance. International Journal of Remote Sensing, 23 (8): 1741–1748. doi: http://dx.doi.org/10.1080/01431160110106113.
   Web of Science ®Google Scholar
• Jensen J. R. (2004)—Introductory Digital Image Processing: A Remote Sensing Perspective. 3rd Ed, Prentice Hall, Upper Saddle River, New Jersey, pp.526.
   Google Scholar
• Johnson M. P. (2001)—Environmental impacts of urban sprawl: a survey of the literature and proposed research agenda. Environment and Planning, 33 (4): 717–735. doi: http://dx.doi.org/10.1068/a3327.
   Web of Science ®Google Scholar
• Kumar D. (2011)—Monitoring Forest Cover Changes Using Remote Sensing and GIS: A Global Prospective. Research Journal of Environmental Science, 5 (2): 105–123. doi: http://dx.doi.org/10.3923/rjes.2011.124.133.
   Google Scholar
• Lu D., Weng Q. (2004)—Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery. Photogrammetric Engineering & Remote Sensing, 70 (9): 1053–1062.
   Web of Science ®Google Scholar
• Myint S.W., Gober P., Brazel A., Grossman-Clarke S., Weng Q. (2011)—Per-pixel vs. object-based classification of urban land cover extraction using high spatial resolution imagery. Remote Sensing of Environment, 115 (5): 1145–1161. doi: http://dx.doi.org/10.1016/j.rse.2010.12.017.
   Web of Science ®Google Scholar
• Pettorelli N., Vik J., Mysterud A., Gaillard J., Tucker C., Stenseth N. (2005)—Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 20 (9): 503–510. doi: http://dx.doi.org/10.1016/j.tree.2005.05.011.
   PubMed Web of Science ®Google Scholar
• Salvati L., Sateriano A., Bajocco S. (2013)—To grow or to sprawl? Land Cover Relationships in a Mediterranean City Region and implications for land use management. Cities, 30: 113–121. doi: http://dx.doi.org/10.1016/j.cities.2012.01.007.
   Web of Science ®Google Scholar
• Salvati L., Zitti M. (2005)—Land degradation in the Mediterranean basin: linking biophysical and economic factors into an ecological perspective. Biota—International Journal of Biology and Ecology, 5: 67–77.
   Google Scholar
• Song C., Woodcock C., Seto K., Pax Lenney M., Macomber S. (2001)—Classification and change detection using Landsat TM data: When and how to correct atmospheric effects? Remote Sensing of Environment, 75 (2): 230–244. doi: http://dx.doi.org/10.1016/S00344257(00)00169-3.
   Web of Science ®Google Scholar
• Stathakis D., Perakis K., Savin I. (2012)—Efficient segmentation of urban areas by the VIBI. International Journal of Remote Sensing, 33 (20): 6361–6377. doi: http://dx.doi.org/10.1080/01431161.2012.687842.
   Web of Science ®Google Scholar
• Wylie B. K., Meyer D. J., Tieszen L. L., Mannel S. (2002)—Satellite mapping of surface biophysical parameters at the biome scale over the North American grasslands: a case of study. Remote Sensing of Environment, 79 (2–3): 266–278. doi: http://dx.doi.org/10.1016/S0034-4257(01)00278-4.
   Google Scholar
• Zhang X., Friedl M. A., Schaaf C. B., Strahler A. H., Hodges J. C. F., Gao F., Reed B. C., Huete A. (2003)—Monitoring vegetation phenology using MODIS. Remote Sensing of Environment, 84 (3): 471–475. doi: http://dx.doi.org/10.1016/S0034-4257(02)00135-9.
   Web of Science ®Google Scholar