Skip to main content

Advertisement

Log in

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan, China

  • Research Article
  • Published:
Earth Science Informatics Aims and scope Submit manuscript

Abstract

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Abedini MJ, Shaghaghian MR (2009) Exploring scaling laws in surface topography. Chaos, Solitons Fractal 42:2373–2383

    Article  Google Scholar 

  • Aguilera F, Valenzuela LM, Botequilha-Leitão A (2011) Landscape metrics in the analysis of urban land use patterns: a case study in a Spanish metropolitan area. Landsc Urban Plan 99:226–238

    Article  Google Scholar 

  • Albalawneh A, Chang TK, Huang CW, Mazahreh S (2015) Using landscape metrics analysis and analytic hierarchy process to assess water harvesting potential sites in Jordan. Environment 2:415–434

    Google Scholar 

  • Alberti M, Booth D, Hill K, Coburn B, Avolio C, Coe S, Spirandelli D (2007) The impact of urban patterns on aquatic ecosystems: an empirical analysis in Puget lowland sub-basins. Landsc Urban Plan 80:345–361

    Article  Google Scholar 

  • Banks-Leite C, Ewers RM, Metzger JP (2013) The confounded effects of habitat disturbance at the local, patch and landscape scale on understorey birds of the Atlantic Forest: implications for the development of landscape-based indicators. Ecol Indic 31:82–88

    Article  Google Scholar 

  • Chave J, Levin S (2004) Scale and scaling in ecological and economic systems. In: The economics of non-convex ecosystems. Springer, Dordrecht, pp 29–59

  • Chen J, Deng M, Mei XM, Chen TQ, Shao QB, Hong L (2014) Optimal segmentation of a high-resolution remote-sensing image guided by area and boudary. Int J Remote Sens 35:6914–6939

    Article  Google Scholar 

  • Dauwalter DC, Rahel FJ (2011) Patch size and shape influence the accuracy of mapping small habitat patches with a global positioning system. Environ Monit Assess 179:123–135

    Article  Google Scholar 

  • de Freitas MWD, Dos Santos JR, Alves DS (2013) Land-use and land-cover change processes in the upper Uruguay Basin: linking environmental and socioeconomic variables. Landsc Ecol 28:311–327

    Article  Google Scholar 

  • Deng XZ et al (2014) Downscaling the impacts of large-scale LUCC on surface temperature along with IPCC RCPs: a global perspective. Energies 7:2720–2739

    Article  Google Scholar 

  • Farina A (2008) Principles and methods in landscape ecology: towards a science of the landscape. Springer, Netherlands

    Google Scholar 

  • Feng YJ, Liu Y (2015) Fractal dimension as an indicator for quantifying the effects of changing spatial scales on landscape metrics. Ecol Indic 53:18–27

    Article  Google Scholar 

  • Frazier AE (2014) A new data aggregation technique to improve landscape metric downscaling. Landsc Ecol 29:1261–1276

    Article  Google Scholar 

  • Garbuzov M, Madsen A, Ratnieks FLW (2015) Patch size has no effect on insect visitation rate per unit area in garden-scale flower patches. Acta Oecol 62:53–57

    Article  Google Scholar 

  • García-Feced C, Saura S, Elena-Rosselló R (2010) Assessing the effect of scale on the ability of landscape structure metrics to discriminate landscape types in Mediterranean forest districts. Forest Syst 19:129–140

    Article  Google Scholar 

  • Gustafson EJ, Parker GR (1992) Relationships between landcover proportion and indices of landscape spatial pattern. Landsc Ecol 7:101–110

    Article  Google Scholar 

  • Hnatushenko VV, Vasyliev VV (2016) Remote sensing image fusion using ICA and optimized wavelet transform. ISPRS Archives 41:653

    Google Scholar 

  • Johnson DD, Howarth PJ (1987) The effects of spatial resolution on land cover/land use theme extraction from airborne digital data. Can J Remote Sens 13:68–74

    Article  Google Scholar 

  • Juliani AW, Bies AJ, Boydston CR, Taylor RP, Sereno ME (2016) Navigation performance in virtual environments varies with fractal dimension of landscape. J Environ Psychol 47:155–165

    Article  Google Scholar 

  • Lambin EF et al (2001) The causes of land-use and land-cover change: moving beyond the myths. Glob Environ Chang 11:261–269

    Article  Google Scholar 

  • Li AN, Deng W, Kong B, Lu XN, Feng WL, Lei GB, Bai JH (2013) A study on wetland landscape pattern and its change process in Huang-Huai-Hai (3H) area. China. J Environ Inform 21:23–34

    Article  Google Scholar 

  • Lin ZM, Xia B, Dong WJ (2011) Analysis on temporal-spatial changes of land-use structure in Guangdong province based on information entropy. Trop Geogr 31:266–271

    Google Scholar 

  • Lü YH, Fu BJ (2000) Ecological scale and scaling. Acta Ecol Sin 21:2096–2105

    Google Scholar 

  • Lü YH, Feng XM, Chen LD, Fu BJ (2013) Scaling effects of landscape metrics: a comparison of two methods. Phys Geogr 34:40–49

    Article  Google Scholar 

  • Mandelbrot BB, Pignoni R (1983) The fractal geometry of nature. WH freeman, San Francisco

    Google Scholar 

  • McGarigal K, Marks BJ (1995) Spatial pattern analysis program for quantifying landscape structure (gen tech rep PNW-GTR-351). US Department of Agriculture, Forest Service, Pacific Northwest Research Station. http://www.umass.edu/landeco/pubs/mcgarigal.marks.1995.pdf

  • McGarigal K, Cushman SA, Neel MC, Ene E (2002) FRAGSTATS: spatial pattern analysis program for categorical maps. Computer software program produced by the authors at the University of Massachusetts, Amherst, Available at the following web site: http://www.umass.edu/landeco/research/fragstats/fragstats.html

  • Munroe DK, Müller D (2007) Issues in spatially explicit statistical land-use/cover change (LUCC) models: examples from western Honduras and the central highlands of Vietnam. Land Use Policy 24:521–530

    Article  Google Scholar 

  • Munroe DK, Croissant C, York AM (2005) Land use policy and landscape fragmentation in an urbanizing region: assessing the impact of zoning. Appl Geogr 25:121–141

    Article  Google Scholar 

  • Netzel P, Stepinski TF (2015) Pattern-based assessment of land cover change on continental scale with application to NLCD 2001–2006. IEEE Trans Geosci Remote Sens 53:1773–1781

    Article  Google Scholar 

  • Niesterowicz J, Stepinski TF (2016) On using landscape metrics for landscape similarity search. Ecol Indic 64:20–30

    Article  Google Scholar 

  • Peng J, Wang YL, Zhang Y, Wu JS, Li WF, Li Y (2010) Evaluating the effectiveness of landscape metrics in quantifying spatial patterns. Ecol Indic 10:217–223

    Article  Google Scholar 

  • Plexida SG, Sfougaris AI, Ispikoudis IP, Papanastasis VP (2014) Selecting landscape metrics as indicators of spatial heterogeneity—a comparison among Greek landscapes. Int J Appl Earth Obs Geoinf 26:26–35

    Article  Google Scholar 

  • Pourghasemi HR, Moradi HR, Aghda SMF, Sezer EA, Jirandeh AG, Pradhan B (2014) Assessment of fractal dimension and geometrical characteristics of the landslides identified in north of Tehran, Iran. Environ Earth Sci 71:3617–3626

    Article  Google Scholar 

  • Roberts WM, Fealy RM, Doody DG, Jordan P, Daly K (2016) Estimating the effects of land use at different scales on high ecological status in Irish rivers. Sci Total Environ 572:618–625

    Article  Google Scholar 

  • Rodriguez DA, Tomasella J (2016) On the ability of large-scale hydrological models to simulate land use and land cover change impacts in Amazonian basins. Hydrol Sci J 61:1831–1846

    Article  Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  Google Scholar 

  • Saaty TL (2008) Decision making with the analytic hierarchy process. Int. J Serv Sci 1:83–98

    Google Scholar 

  • Shi P, Zhang Y, Li ZB, Li P, Xu GC (2017) Influence of land use and land cover patterns on seasonal water quality at multi-spatial scales. Catena 151:182–190

    Article  Google Scholar 

  • Strahler AH, Woodcock CE, Smith JA (1986) On the nature of models in remote sensing. Remote Sens Environ 20:121–139

    Article  Google Scholar 

  • Torras O, Martín-Queller E, Saura S (2009) Relating landscape structure, environment and management to biodiversity indicators estimated from forest inventory data in Catalonia (NE Spain). Forest Syst 18:322–337

    Article  Google Scholar 

  • Treitz P, Howarth P (2000) High spatial resolution remote sensing data for forest ecosystem classification: an examination of spatial scale. Remote Sens Environ 72:268–289

    Article  Google Scholar 

  • Turner MG (1989) Landscape ecology: the effect of pattern on process. Annu Rev Ecol Syst 20:171–197

    Article  Google Scholar 

  • Urban DL (2005) Modeling ecological processes across scales. Ecology 86:1996–2006

    Article  Google Scholar 

  • Vaidya OS, Kumar S (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29

    Article  Google Scholar 

  • Vamsee AM, Kamala P, Martha TP, Kumar KV, Amminedu E (2018) A tool assessing optimal multi-scale image segmentation. J Indian Soc Remote 46:31–41

    Article  Google Scholar 

  • Weber MA, Ringold PL (2015) Priority river metrics for residents of an urbanized arid watershed. Landsc Urban Plan 133:37–52

    Article  Google Scholar 

  • Wei W, Chen LD, Yang L, Fu BJ, Sun RH (2012) Spatial scale effects of water erosion dynamics: complexities, variabilities, and uncertainties. Chin Geogr Sci 22:127–143

    Article  Google Scholar 

  • Welch R (1982) Spatial resolution requirements for urban studies. Int J Remote Sens 3:139–146

    Article  Google Scholar 

  • Werner DH, Werner PL (1995) On the synthesis of fractal radiation patterns. Radio Sci 30:29–45

    Article  Google Scholar 

  • Woodcock CE, Strahler AH (1987) The factor of scale in remote sensing. Remote Sens Environ 21:311–332

    Article  Google Scholar 

  • Yarlagadda A, Murthy JVR, Prasad MHMK (2014) Particle swarm optimized optimal threshold value selection for clustering based on correlation fractal dimension. Appl Math 5:1615

    Article  Google Scholar 

  • Zawadzki J, Cieszewski CJ, Zasada M, Lowe RC (2005) Applying geostatistics for investigations of forest ecosystems using remote sensing imagery. Silva Fenn 39:599

    Article  Google Scholar 

  • Zhao WW, Fu BB, Chen LD (2003) The effects of grain change on landscape indices. Quaternary Sci 23:326–333 (In Chinese)

    Google Scholar 

  • Zhao J, Chen X, Bao AM, Zhang C, Shi WL (2009) A method for choice of optimum scale on land use monitoring in Tarim River basin. J Geogr Sci 19:340–350

    Article  Google Scholar 

  • Zhou ZX, Li J (2015) The correlation analysis on the landscape pattern index and hydrological processes in the Yanhe watershed, China. J Hydrol 524:417–426

    Article  Google Scholar 

Download references

Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 41571514), and the Wuhan Science and Technology Plan Program under Grant 2016010101010023.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jiejun Huang.

Ethics declarations

Conflicts of interest

The authors declare that they have no conflict of interest.

Additional information

Communicated by: H. A. Babaie

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Huang, Q., Huang, J., Zhan, Y. et al. Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan, China. Earth Sci Inform 11, 567–578 (2018). https://doi.org/10.1007/s12145-018-0348-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12145-018-0348-4

Keywords

Navigation