Environmental Researches

Environmental Researches

Utilization of Fourier Transform and Landscape Metrics for Landscape Health Assessment

Document Type : Original Article

Authors
Niloufar Islamzadeh 1
Ali Reza Mikaieli Tabrizi 2
Abdolrassoul Salmanmahiny 3
Rasul Ghorbani 4
1 PhD of Land use Planning, Faculty of Environmental Sciences, Gorgan University, Iran
2 Associate Professor, Faculty of Environmental Sciences, Gorgan University, Iran
3 Professor, Faculty of Environmental Sciences, Gorgan University, Iran
4 Professor, Faculty of Fisheries Sciences, Gorgan University, Iran
10.22034/eiap.2025.216581
Abstract
In large and inaccessible natural areas, ground surveys and close assessment of landscape health becomes difficult or even impossible. In these circumstances, remote sensing data provide an inexpensive solution. The first step in assessing landscape health through remote sensing data is selection of indicators that can be derived from this imagery. Landscape health can be directly assessed using Fourier transform on satellite imagery or indirectly through image classification and then measurement of relevant landscape metrics on the classified maps. In this study, in addition to the discrete landscape metrics of land use, the Fourier transform method through frequency assessment of the images were used to assess the health status of the landscape in part of the Golestan Province. Through multi-temporal analysis, images of different times were also compared to study the change in the health status of the landscape. The results of discrete metrics and continuous Fourier approaches were similar. Fragmentation, heterogeneity and complexity at the landscape level as well as vegetation level increased during the period 1984 to 2016, leading to lower landscape integrity and connectivity. The health of the landscape appears to have declined due to increased non-uniformity of landuse types. The continuous approach in this study, namely the Fourier analysis also confirmed the changes and the decreasing trends in landscape health for the studied time period. Therefore, we conclude that both discrete and continuous Fourier methods can be used in landscape health assessment of the study area.
Keywords
Health
Landscape
Remote Sensing
Fourier Transform
Metric
Subjects
Ahern, j. & Andre, L. 2003. Applying landscape ecological concepts and metrics in sustainable landscape planning. Landscape & Urban Planning. 59(1): 65-93.
Baguette, M & Dyck H. V. 2007. Landscape connectivity and animal behavior: functional grain as a key determinant for dispersal. Landscape Ecology. 22(1): 1117–1129.
Clive, A. M. A. & Teresa, J. E. 2002. Testing landscape metrics as indicators of habitat loss and fragmentation in continuous eucalypt forests (Queensland, Australia). Landscape Ecology. 17(3): 711–728.
Cooley, J. W. & Tukey. J. W. 2022. Complex Fourier Series. Mathematics of Computation 22: 111–119.
De Bie, H. 2012. Clifford Algebras, Fourier Transforms, and Quantum Mechanics. Mathematical Methods in the Applied Sciences. 35(1): 2198–2228.
Emch, M. J. W. 2023. Forest Cover Change in the Toledo District, Belize from 1999 to 2019: A Remote Sensing Approach. The Professional Geographer 19(4): 206–217.
Farina, A. 2006 b. Principle and methods in landscape ecology: Toward a science of landscape. 2nd ed. Springer. Dordrecht.
Forman, R. T. T. 1995. Land mosaics: The ecology of landscapes and regions. Cambridge University press, USA.
Fourier, J. B. J. 1822. Théorie Analytique De La Chaleur. Paris: Didot.
Gergel, S. E. M. & Turner, G. 2002. Learning Landscape Ecology: A Practical Guide to Concepts and Techniques. Springer. New York.
Gounaridis, D.; George, N. Z. & Sotirios, K. 2014. Quantifying spatio-temporal patterns of forest fragmentation in Hymettus Mountain, Greece a Computers. Environment and Urban Systems. 46(2): 35–44.
Grohmann, C. H. 2024. Morphometric Analysis in Geographic Information Systems (2). Computers & Geosciences 10(1): 10–19.
Hilty, J.A.; Lidicker, J.r.WZ & Merenlender, A.M 2006. Corridor Ecology: The Science and Practice of Linking Landscapes for Biodiversity Conservation. Island press. Washington DC.
Jorgensen, S.E.; Costanza, R. & Xu, F.L. 2005. Hand Book of Ecological Indicators for Assessment of Ecosystem Health. CRC Press.
Koffi, K.J.; Deblauwe, V.; Sibomana, S.; Neuba, D.F.R.; Champluvier, D., DE Canniere.; Barbier, N.; Traore, D.; Habonimana, B.; E. Robbrecht, E.; Lejoly, J.; Bogaret, J. 2007. Spatial Pattern Analysis as a Focus of Landscape Ecology to Support Evaluation of Human Impact on Landscape and Diversity. Landscape Ecological Applications in Man-Influenced Areas, Linking Man and Nature Systems
Lausch, A.; Blaschke, T.; Haase, D.; Herzog, F.; Syrbe, R.U.; Tischendorf, L. & Walz. 2015. Understanding and quantifying landscape structure – A review on relevant process characteristics, data models and landscape metrics. Ecological Modelling. 295(2): 31–41.
Leitao, A.B.; Miller, j.; Ahern, J. & McGarigal, K. 2006. Measuring Landscapes: A Planners Handbook. Island Press. Washington D.C.
Mahiny, A. S. 2007. Patch Metrics as Surrogates of Structural Complexity of Remnant Vegetation. Geocomputation Conference. Ireland.
McGarigal, K. & Marks, B. J. 1995. FRAGSTATS: spatial pattern analysis program for quantifying landscape structure. Gen. Tech. Rep. PNW-GTR-351. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station.
McGarigal, K. & Cushman, S.A. 2005. The gradient concept of landscape structure. In: Wiens, J., Moss, M. (Eds.), Issues and Perspectives in Landscape Ecology. Cambridge University Press.
McGarigal, K.; Tagil, S. & Cushman, S. 2009. Surface metrics: an alternative to patch metrics for the quantification of landscape structure. Landscape Ecology. 24(3): 433–450.
Ndubisi, F. 2002. Ecological Planning: A Historical and Comparative Synthesis (Center Books on Contemporary Landscape Design). The Jhons Hopkins University press. Baltimore and London.
Ploton, P.; Pélissier, C.; Proisy, T.; Flavenot, N.; Barbier, S.; Rai, N. & Couteron, P. 2012. Assessing above Ground Tropical Forest Biomass using Google Earth Canopy Images. Ecological Applications. 22(3): 993–1003.
Proisy, C.; Couteron, P. & Fromard, F. 2007. Predicting and Mapping Mangrove Biomass from Canopy Grain Analysis using Fourier-Based Textural Ordination of IKONOS Images. Remote Sensing of Environment, 109(3): 379–392.
Rocchini, D.; Metz, M.; Ricotta, C.; Landa, M..; Frigeri, A. & Neteler, M. 2013. Fourier transforms for detecting multitemporal landscape fragmentation by remote sensing. International Journal of Remote Sensing. 34(24): 8907–8916.
Rocchini, D., Anand, K. S. He, V. Amici, B. Kleinschmit, M. Förster, S. Schmidtlein, H. Feilhauer, A. Ghisla, M. Metz, and M. Neteler. 2023. Mapping of Ecosystem by Remote Sensing.” Computers & Geosciences. 10(1): 150–165.
Rocchini, D. 2024. Remote Sensing in Ecology. Trends in Ecology & Evolution 11(1): 99–111.
Singh, M.; Malhi, Y. & Bhagwat, S. 2014. Biomass estimation of mixed forest landscape using a Fourier transform texture-based approach on very-high-resolution optical satellite imagery. International Journal of Remote Sensing, 35(9): 3331–3349.
Turnhout, E.; Hisschemoller, M. & Eijsackers, H. 2007. Ecological indicators: between two fires of science and policy. Ecological Indicators. 7(1): 215-228.
Environmental Researches
Volume 15, Issue 30
Recerches
March 2025
Pages 19-35