Colour harmony of land cover as intangible environmental resource (Vooremaa landscape protection area, Estonia)
DOI:
https://doi.org/10.26565/2410-7360-2017-46-11Keywords:
colour harmony, land cover, remote sensing, intangible environmental resourcesAbstract
Formulation of the problem. Colours of land cover, as a component of topological visual phenomena of environment, are accessible for study with modern remote sensing, so the problem of the given research is to quantify the colouristic harmony of land cover within the study area in Estonia, using known methods of its assessment.
The purpose of the article. Quantification of colour harmony of land cover, using remote sensing data and substantiated techniques.
Methods. A criterion of colour harmony after Albert Munsell (1921) [21] was applied. He proposed to keep the balance between the colour strength of particular hue (product of value and chroma in his colour system) and the area of this hue.
,
where M is the total number of colours within some zone or floating circle; CSn – colour strength, calculated as chroma of colour n × value of colour n; An is the area of colour n.
Also criterion after Palmer & Schloss (2011) was applied: colour pairs, more similar in hue and with lower saturation, tend to be harmonious [24].
Results. Maps of spatial distribution of colour harmony of land cover within Vooremaa landscape protection area were compiled after Munsell (1921) and Schloss & Palmer (2011) for summer (14.06.2016) and autumn (20.10.2016) seasons. Water bodies, forests and wetlands have the highest scores of both colour harmonies, while some crop fields (mainly with saturated young or depressed vegetation and open soil) have the lowest colour harmony scores. Maps show the tendency to the decreasing of the colour harmony of land cover with an increasing of colour contrasts in the end of the cropping season.
Scientific novelty and practical significance. Besides numerous studies of colours of perceived environment, there are no attempts to examine the land cover with some colour harmony criteria, using remote sensing data. The proposed techniques allow evidence-based and cost-effective way of monitoring of perceived environment in the context of colour harmony dynamics under the influence of natural and land use factors.
References
Amer, R., Kusky, T., Reinert, P. C., & Ghulam, A. (2009). Image processing and analysis using landsat etm imagery for lithological mapping at fawakhir, central eastern desert of Egypt. Paper presented at the ASPRS 2009 Annual Conference, Baltimore, Maryland.
Antrop, M. (2000). Geography and landscape science. Belgeo, (1-2-3-4), 9-36. http://dx.doi.org/ 10.4000/belgeo.13975
3. Bell, S. (2004). Elements of visual design in the landscape. London: Spon Press.
Chamaret, C. (2016). Color harmony: experimental and computational modeling (Doctoral dissertation, Université Rennes 1).
Chapana, R. S. H. (2012). The Relative Influence of Solar Radiative and Solar Geomagnetic Variation on the Dynamics of the Polar Upper Mesosphere (Master's thesis, Institutt for fysikk).
Chervanyov, I. G., & Karasiov, O. O. (2015). The intangible natural resources (INR) in the aspects of natural capital of new geography: some perspectives for Ukraine. Visnyk Kharkivskoho natsionalnoho universytetu imeni VN Karazina, ceriia «Heolohiia. Heohrafiia. Ekolohiia», 42 (1157), 106-110.
Clay, G. R., & Daniel, T. C. (2000). Scenic landscape assessment: the effects of land management jurisdiction on public perception of scenic beauty. Landscape and urban planning, 49(1), 1-13.
De Groot, R. S., Wilson, M. A., & Boumans, R. M. (2002). A typology for the classification, description and valuation of ecosystem functions, goods and services. Ecological economics, 41(3), 393-408.
Déjeant-Pons, M. (2006). The European landscape convention. Landscape Research, 31(4), 363-384.
10. Escadafal, R., Girard, M. C., & Courault, D. (1989). Munsell soil color and soil reflectance in the visible spectral bands of Landsat MSS and TM data. Remote Sensing of Environment, 27(1), 37-46.
11. Gittings, J. A., Raitsos, D. E., Racault, M. F., Brewin, R. J. W., Pradhan, Y., Sathyendranath, S., & Platt, T. (2017). Seasonal phytoplankton blooms in the Gulf of Aden revealed by remote sensing. Remote Sensing of Environment, 189, 56-66. doi:10.1016/j.rse.2016.10.043
12. Granö, J. G. (1997). Pure geography. O. Granö, & A. Paasi (Eds.). Baltimore, MD: Johns Hopkins University Press.
13. Hands, D. E., & Brown, R. D. (2002). Enhancing visual preference of ecological rehabilitation sites. Landscape and Urban Planning, 58(1), 57-70.
14. Haralick, R. M., & Shanmugam, K. (1973). Textural features for image classification. IEEE Transactions on systems, man, and cybernetics, 3(6), 610-621.
15. Irish, R. R. (2000). Landsat 7 science data users handbook. National Aeronautics and Space Administration, Report, 2000, 415-430.
16. Jabari, S., Zhang, Y., Suliman, A., & Ieee. (2014). Stereo-based building detection in very high resolution satellite imagery using ihs color system. 2014 Ieee International Geoscience and Remote Sensing Symposium (Igarss), 2301-2304. doi:10.1109/igarss.2014.6946930
17. Junge, X., Schüpbach, B., Walter, T., Schmid, B., & Lindemann-Matthies, P. (2015). Aesthetic quality of agricultural landscape elements in different seasonal stages in Switzerland. Landscape and Urban Planning, 133, 67-77.
18. Koutsias, N., Karteris, M., & Chuvieco, E. (2000). The use of intensity-Hue-saturation transformation of Landsat-5 Thematic Mapper data for burned land mapping. Photogrammetric Engineering and Remote Sensing, 66(7), 829-839.
19. Lengen, C. (2015). The effects of colours, shapes and boundaries of landscapes on perception, emotion and mentalising processes promoting health and well-being. Health & place, 35, 166-177.
20. Lessel, J., & Ceccato, P. (2016). Creating a basic customizable framework for crop detection using Landsat imagery. International Journal of Remote Sensing, 37(24), 6097-6107.
21. Munsell, A. H. (1915). Atlas of the Munsell color system. Wadsworth, Howland & Company, Incorporated, Printers.
22. NASA. (2013). Electromagnetic Spectrum - Introduction. Retrieved 3 June 2017, from https://imagine.gsfc.nasa.gov/science/toolbox/emspectrum1.html
23. Pekel, J.-F., Vancutsem, C., Bastin, L., Clerici, M., Vanbogaert, E., Bartholomé, E., & Defourny, P. (2014). A near real-time water surface detection method based on HSV transformation of MODIS multi-spectral time series data. Remote sensing of environment, 140, 704-716.
24. Schloss, K. B., & Palmer, S. E. (2011). Aesthetic response to color combinations: preference, harmony, and similarity. Attention, Perception, & Psychophysics, 73(2), 551-571.
25. Schüpbach, B., Junge, X., Lindemann-Matthies, P., & Walter, T. (2016). Seasonality, diversity and aesthetic valuation of landscape plots: An integrative approach to assess landscape quality on different scales. Land Use Policy, 53, 27-35.
26. Semyonov–Tyan-Shansky, V. P. (1928). Rayon and Strana.
27. Stobbelaar, D. J., & Hendriks, K. (2007). Seasonality of agricultural landscapes: reading time and place by colours and shapes. In Seasonal landscapes (pp. 103-126): Springer.
28. Swetnam, R. D., Harrison-Curran, S. K., & Smith, G. R. Quantifying visual landscape quality in rural Wales: A GIS-enabled method for extensive monitoring of a valued cultural ecosystem service. Ecosystem Services. doi:http://dx.doi.org/10.1016/j.ecoser.2016.11.004
29. Toolson, E. (2017). Human Cone Action Spectra. Retrieved 3 June 2017, from https://www.unm.edu/~toolson/human_cone_response.htm
30. USGS (2017). USGS Open-File Report 2006-1195: Munsell Color Code. Pubs.usgs.gov. Retrieved 3 June 2017, from https://pubs.usgs.gov/of/2006/1195/htmldocs/munsellcode.htm
31. Zanter, K. (2005). Landsat 8 (L8) data users handbook. LSDS-1574 Version, 1.
Downloads
Published
Issue
Section
License
Copyright (c) 2017 О. О. Karasov
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
