Temporal Trajectories of HR/VHR Pixels and Detection of Land Take Processes

Corrado Iannucci

DOI 10.7160/aol.2016.080104
No 1/2016, March
pp. 37-44

Iannucci, C. (2016) “Temporal Trajectories of HR/VHR Pixels and Detection of Land Take Processes", AGRIS on-line Papers in Economics and Informatics, Vol. 8, No. 1, pp. 37 - 44. ISSN 1804-1930. DOI 10.7160/aol.2016.080104.

Abstract

An increasing share of people and economic activities are attracted by the cities. This fact shows positive aspects and at the same time causes challenges, mainly in reference to the soil whose ecosystem services can be disrupted when the land cover is modified. Therefore, urbanization is a critical issue for the land management.Contrasting the urban sprawl (i.e. the spontaneous, unplanned process transforming vegetated land covers into artificial ones) is relevant for soil protection in terms of minimizing the land take. Remote sensing technologies have provided support (with an ex-post approach) to understand urban sprawl as a process and to assess its impacts on the sustainability of land management. The current availability of high-resolution/ very-high-resolution (HR/VHR) satellite data suggests to explore a different approach, aiming to deploy timely adequate countermeasures.The analysis of the urban sprawl processes pinpoints how the induced land cover changes show some specific patterns; moreover, distinctive trajectories in the space of multitemporal / multispectral imagery data can be elicited, relying also upon vegetation indices as the Normalized Difference Vegetation Index (NDVI). Accordingly, suitable precursors of urban sprawl processes can be detected. Such precursors can support a novel ex-ante approach in preventing the consolidation of the outcomes of the urban sprawl processes.

Keywords

Sustainable land management, urbanization, land cover change, remote sensing, satellite imagery, spatio-temporal trajectories, urban sprawl.

References

  1. Aleksandrowicz, S., Turlej, K., Lewiński, S. and Bochenek, Z. (2014) "Change detection algorithm for the production of land cover change maps over the European Union countries", Remote Sensing, Vol. 6, pp. 5976-5994. ISSN 2072-4292.
  2. Anderson, J. R., Hardy, E. E., Roach, J. T. and Witmer, R. E. (1976) "A Land Use and Land Cover Classification System for Use with Remote Sensor Data", Geological Survey Professional Paper 964. Washington DC: US Government Printing Office.
  3. Bhatta, B. (2010) "Analysis of Urban Growth and Sprawl from Remote Sensing Data". Berlin DE: Springer Verlag. ISBN 978-3-642-05299-6.
  4. Blaschke, T. (2010) "Object based image analysis for remote sensing", ISPRS Journal of Photogrammetry and Remote Sensing. Vol. 65, pp. 2–16. ISSN 0924-2716.
  5. Coppin, P. R. and Bauer, M. E. (1994) "Processing of multitemporal Landsat TM imagery to optimize extraction of forest cover", IEEE Transactions on Geoscience and Remote Sensing. Vol. 32, No. 4, pp. 918-927. ISSN, 0196-2892.
  6. Coppin, P., Jonckheere, I. ., Nackaerts, K., Muys, B. and Lambin, E. "Digital change detection methods in ecosystem monitoring: a review", Int. J. Remote Sensing. Vol. 25, No. 9, pp. 1565-1596. ISSN 2072-4292.
  7. EC (2011) "Roadmap to a Resource Efficient Europe". Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions. COM(2011) 571 Final. Brussels BE: European Commission.
  8. EEA (2006) "Urban Sprawl in Europe. The Ignored Challenge". EEA Report No. 10/2006. Luxembourg LU: Office for Official Publications of the European Communities.
  9. EEA (2007) "CLC2006 Technical Guidelines". EEA Report No 17/2007. Luxembourg LU: Office for Official Publications of the European Communities.
  10. EEA (2013) "Natural Resources and Human Well-being in a Green Economy"- Environmental Indicator Report 2013. Copenhagen DK: European Environment Agency.
  11. EEA (2015) "The European Environment State and Outlook 2015", Synthesis Report. Copenhagen DK: European Environment Agency.
  12. Gizzi, S., Giovacchini, A. and Iannucci, C. (1980) "Remote sensing and agriculture: a national program in Italy. Some technical aspects". In Proc. 14th Int. Symposium on the Remote Sensing of Environment, S. José, Costa Rica. Ann Arbor MI: Environmental Research Institute of Michigan, Vol. 2, pp. 763-772.
  13. Hussain, M., Chen, D., Cheng, A., Wei, H. and Stanley, D. (2013) "Change detection from remotely sensed images: From pixel-based to object-based approaches", ISPRS Journal of Photogrammetry and Remote Sensing, vol. 80, pp. 91–106. ISSN 0924-2716.
  14. INSPIRE (2007) Directive 2007/2/EC of the European Parliament and of the Council of 14th March 2007 establishing an Infrastructure for Spatial Information in the European Community (INSPIRE), Official Journal of the European Union, Vol. L 108, pp. 1-14. ISSN 1977-0677.
  15. INSPIRE LC (2013) "D2.8.II.2 INSPIRE Data Specification on Land Cover – Technical Guidelines", [Online] Available: http://inspire.ec.europa.eu/documents/Data_Specifications/INSPIRE_ DataSpecification_LC_v3.0.pdf [Accessed June 10, 2015].
  16. INSPIRE LU (2013) "D2.8.III.4 INSPIRE Data Specification on Land Use – Technical Guidelines". [Online] Available: http://inspire.ec.europa.eu/documents/Data_Specifications/INSPIRE_ DataSpecification_LU_v3.0.pdf [Accessed June 15, 2015].
  17. Ji, W., Ma, J., Twibell, R. W. and Underhill, K. (2006) "Characterizing urban sprawl using multi- stage remote sensing images and landscape metrics", Computers, Environment and Urban Systems, Vol. 30, No. 6, pp. 861-879. ISSN 0198-9715. DOI 10.1016/j.compenvurbsys.2005.09.002.
  18. Kauth, R. J. and Thomas, G. S.(1976) "The tasseled cap – A graphic description of the spectral- temporal development of agricultural crops as seen by Landsat", In Proc. Symposium on Machine Processing of Remotely Sensed Data, Laboratory for Applications of Remote Sensing. West Lafayette IN: Purdue University.
  19. Nouri, H., Beecham, S., Anderson, S. and Nagler, P. (2014) "High spatial resolution WorldView-2 imagery for mapping NDVI and its relationship to temporal urban landscape evapotranspiration factors", Remote Sensing, Vol. 6, pp. 580-602. ISSN 2072-4292.
  20. Pan, Z., Huang, J., Zhou, Q., Wang, L., Cheng, Y., Zhang, H., Blackburn, G. A., Yan, J. and Liu, J. (2015) "Mapping crop phenology using NDVI time-series derived from HJ-1A/B data", International Journal of Applied Earth Observation and Geoinformation, vol. 34, pp. 188-197. ISSN 0303-2434.
  21. Pointereau, P., Coulon, F., Girard, P., Lambotte, M., Stuczynski, T., Sánchez Ortega, V. and Del Rio, A. "Analysis of Farmland Abandonment and the Extent and Location of Agricultural Areas that are Abandoned or are in Risk to be Abandoned", IES Joint Research Centre. Luxembourg LU: Office for Official Publications of the European Communities.
  22. Schwartz, M. D. (Ed.), (2013) "Phenology: an Integrative Environmental Science". Dordrecht NL: Springer Netherlands.
  23. Skidmore, A. K., Bijker, W., Schmidt, K. and Kumar, L. (1997) "Use of remote sensing and GIS for sustainable land management", ITC Journal. Vol.3/4, pp. 302-315. ISSN 2405-9595.
  24. Turner, S. (Ed.) (2002) Proceedings of the Technical Workshop on Indicators for Soil Sealing, 26th to 27th March 2001. Technical Report No. 80. Copenhagen DK: European Environmental Agency.
  25. UNDESA (2012) "World Urbanization Prospects", the 2011 Revision. New York, NY: United Nations, Department of Economic and Social Affairs, Population Division.

Full paper

  Full paper (.pdf, 291.96 KB).