Effects of changing scales on landscape patterns and spatial modeling under urbanization

    Jinming Yang Affiliation
    ; Shimei Li   Affiliation
    ; Jingwei Xu Affiliation
    ; Xiaojie Wang Affiliation
    ; Xiaoguang Zhang Affiliation


Spatial scale is an eternal topic in landscape pattern related analysis. This paper examined the spatial scale effect of landscape pattern changes and their relationships with urbanization indicators in Qingdao using a series of sampling blocks. The results indicated that, with the increasing block scale, the mean patch density and aggregation within a block decreased, whereas the diversity increased. Furthermore, the expanding scale amplified the mean change ratio of landscape metrics and eliminated local drastic changes and regional variation trends along an urban-to-rural gradient, which would be obvious at a finer block scale. Meanwhile, the adjusted R2 of GWR (Geographically Weighted Regression) models increased with an increasing block size, especially when the block scale changed from 1 km to 5 km. Odd-numbered block scales performed better than even-numbered block scales.

Keyword : spatial scale, block size, urbanization, landscape patterns, geographically weighted regression (GWR)

How to Cite
Yang, J., Li, S., Xu, J., Wang, X., & Zhang, X. (2020). Effects of changing scales on landscape patterns and spatial modeling under urbanization. Journal of Environmental Engineering and Landscape Management, 28(2), 62-73.
Published in Issue
Mar 23, 2020
Abstract Views
PDF Downloads
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.


Ali, R., Bakhsh, K., & Yasin, M. A. (2019). Impact of urbanization on CO2 emissions in emerging economy: Evidence from Pakistan. Sustainable Cities and Society, 48, 101553.

Alibakhshi, Z., Ahmadi, M., & Farajzadeh Asl, M. (2019). Modeling biophysical variables and land surface temperature using the GWR model: Case study-Tehran and its satellite cities. Journal of the Indian Society of Remote Sensing, 48, 59–70.

Barros, J., Tavares, A., Monteiro, M., & Santos, P. (2018). PeriUrbanization and Rurbanization in Leiria City: The importance of a planning framework. Sustainability, 10(7), 2501.

Baugh, K., Elvidge, C. D., Ghosh, T., & Ziskin, D. (2010). Development of a 2009 stable lights product using DMSP-OLS data. Proceedings of the Asia-Pacific Advanced Network Meeting.

Bihamta, N., Soffianian, A., Fakheran, S., & Gholamalifard, M. (2014). Using the SLEUTH urban growth model to simulate future urban expansion of the Isfahan Metropolitan Area, Iran. Journal of the Indian Society of Remote Sensing, 43(2), 407–414.

Dadashpoor, H., & Salarian, F. (2018). Urban sprawl on natural lands: Analyzing and predicting the trend of land use changes and sprawl in Mazandaran city region, Iran. Environment, Development and Sustainability, 22, 593–614 (2020).

Dadashpoor, H., Azizi, P., & Moghadasi, M. (2019). Land use change, urbanization, and change in landscape pattern in a metropolitan area. Science of the Total Environment, 655, 707–719.

Defense Meteorological Satellite Program (DMSP). (n.d.). National Centers for Environmental Information.

Deng, J. S., Wang, K., Hong, Y., & Qi, J. G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and Urban Planning, 92(3–4), 187–198.

Dormann, C. F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carré, G., & Lautenbach, S. (2013). Collinearity: A review of methods to deal with it and a simulation study evaluating their performance. Ecography, 36(1), 27–46.

Dormann, C. F., McPherson, J. M., Araújo, M. B., Bivand, R., Bolliger, J., Carl, G., Davies, R. G., Hirzel, A., Jetz, W., Daniel Kissling, W., Kühn, I., Ohlemüller, R., Peres‐Neto, P. R., Reineking, B., Schröder, B., Schurr, F. M., & Wilson, R. (2007). Methods to account for spatial autocorrelation in the analysis of species distributional data: A review. Ecography, 30(5), 609–628.

Du, S., Wang, Q., & Guo, L. (2014). Spatially varying relationships between land-cover change and driving factors at multiple sampling scales. Journal of Environmental Management, 137, 101–110.

Elvidge, D. C., Ziskin, D., Baugh, E. K., Tuttle, T. B., Ghosh, T., Pack, W. D., & Zhizhin, M. (2009). A fifteen year record of global natural gas flaring derived from satellite data. Energies, 2(3), 595–622.

Feng, Y., & Liu, Y. (2015). Fractal dimension as an indicator for quantifying the effects of changing spatial scales on landscape metrics. Ecological Indicators, 53, 18–27.

Feng, Y., Liu, Y., & Tong, X. (2018). Spatiotemporal variation of landscape patterns and their spatial determinants in Shanghai, China. Ecological Indicators, 87, 22–32.

Fotheringham, A. S., Brunsdon, C., & Charlton, M. E. (2002). Geographically weighted regression: The analysis of spatially varying relationships. Wiley.

Gao, J., & Li, S. (2011). Detecting spatially non-stationary and scale-dependent relationships between urban landscape fragmentation and related factors using Geographically Weighted Regression. Applied Geography, 31(1), 292–302.

Herold, M., Goldstein, N. C., & Clarke, K. C. (2003). The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote Sensing of Environment, 86(3), 286–302.

Herold, M., Scepan, J., & Clarke, K. C. (2002). The Use of remote sensing and landscape metrics to describe structures and changes in urban land uses. Environment and Planning A: Economy and Space, 34(8), 1443–1458.

Hou, L., Wu, F., & Xie, X. (2020). The spatial characteristics and relationships between landscape pattern and ecosystem service value along an urban-rural gradient in Xi’an city, China. Ecological Indicators, 108, 105720.

Jiao, M., Hu, M., & Xia, B. (2019). Spatiotemporal dynamic simulation of land-use and landscape-pattern in the Pearl River Delta, China. Sustainable Cities and Society, 49, 101581.

Koch, J., Dorning, M. A., Van Berkel, D. B., Beck, S. M., Sanchez, G. M., Shashidharan, A., Smart, L. S., Zhang, Q., Smith, J. W., & Meentemeyer, R. K. (2019). Modeling landowner interactions and development patterns at the urban fringe. Landscape and Urban Planning, 182, 101–113.

Li, C., & Zhao, J. (2019). Investigating the spatiotemporally varying correlation between urban spatial patterns and ecosystem services: A case study of Nansihu Lake Basin, China. ISPRS International Journal of Geo-Information, 8(8), 346.

Li, B., Chen, D., Wu, S., Zhou, S., Wang, T., & Chen, H. (2016). Spatio-temporal assessment of urbanization impacts on ecosystem services: Case study of Nanjing City, China. Ecological Indicators, 71, 416–427.

Li, F., Zheng, W., Wang, Y., Liang, J., Xie, S., Guo, S., Li, X., & Yu, C. (2019). Urban green space fragmentation and urbanization: A spatiotemporal perspective. Forests, 10(4), 333.

Li, H., Peng, J., Yanxu, L., & Yi’na, H. (2017). Urbanization impact on landscape patterns in Beijing City, China: A spatial heterogeneity perspective. Ecological Indicators, 82(Suppl C), 50–60.

Li, S., Zhao, Z., Miaomiao, X., & Wang, Y. (2010). Investigating spatial non-stationary and scale-dependent relationships between urban surface temperature and environmental factors using geographically weighted regression. Environmental Modelling & Software, 25(12), 1789–1800.

Liu, Z., He, C., Zhang, Q., Huang, Q., & Yang, Y. (2012). Extracting the dynamics of urban expansion in China using DMSPOLS nighttime light data from 1992 to 2008. Landscape and Urban Planning, 106(1), 62–72.

Luck, M., & Wu, J. (2002). A gradient analysis of urban landscape pattern: A case study from the Phoenix metropolitan region, Arizona, USA. Landscape Ecology, 17(4), 327–339.

Luo, X., & Peng, Y. (2016). Scale effects of the relationships between urban heat islands and impact factors based on a geographically-weighted regression model. Remote Sensing, 8(9), 760.

Mann, S. (2009). Institutional causes of urban and rural sprawl in Switzerland. Land Use Policy, 26(4), 919–924.

Marull, J., Font, C., & Boix, R. (2015). Modelling urban networks at mega-regional scale: Are increasingly complex urban systems sustainable? Land Use Policy, 43, 15–27.

Min, M., Lin, C., Duan, X., Jin, Z., & Zhang, L. (2019). Spatial distribution and driving force analysis of urban heat island effect based on raster data: A case study of the Nanjing metropolitan area, China. Sustainable Cities and Society, 50, 101637.

Peng, W., Wang, X., Li, X., & He, C. (2018). Sustainability evaluation based on the emergy ecological footprint method: A case study of Qingdao, China, from 2004 to 2014. Ecological Indicators, 85, 1249–1261.

Riitters, K. H., O’Neill, R. V., Hunsaker, C. T., Wickham, J. D., Yankee, D. H., Timmins, S. P., & Jackson, B. L. (1995). A factor analysis of landscape pattern and structure metrics. Landscape Ecology, 10(1), 23–39.

Shen, S., Yue, P., & Fan, C. (2019). Quantitative assessment of land use dynamic variation using remote sensing data and landscape pattern in the Yangtze River Delta, China. Sustainable Computing: Informatics and Systems, 23, 111–119.

Shen, W., Jenerette, G. D., Wu, J., & Gardner, R. H. (2004). Evaluating empirical scaling relations of pattern metrics with simulated landscapes. Ecography, 27(4), 459–469.

Su, S., Jiang, Z., Zhang, Q., & Zhang, Y. (2011). Transformation of agricultural landscapes under rapid urbanization: A threat to sustainability in Hang-Jia-Hu region, China. Applied Geography, 31(2), 439–449.

Su, S., Ma, X., & Xiao, R. (2014). Agricultural landscape pattern changes in response to urbanization at ecoregional scale. Ecological Indicators, 40, 10–18.

Sun, X., Crittenden, J. C., Li, F., Lu, Z., & Dou, X. (2018). Urban expansion simulation and the spatio-temporal changes of ecosystem services, a case study in Atlanta Metropolitan area, USA. Science of the Total Environment, 622–623, 974–987.

Tan, M., Li, X., Xie, H., & Lu, C. (2005). Urban land expansion and arable land loss in China – a case study of Beijing–Tianjin–Hebei region. Land Use Policy, 22(3), 187–196.

Tian, P., Cao, L., Li, J., Pu, R., Shi, X., Wang, L., & Shao, S. (2019). Landscape grain effect in Yancheng Coastal Wetland and its response to landscape changes. International Journal of Environmental Research and Public Health, 16(12), 2225.

Torres, A., Jaeger, J. A. G., & Alonso, J. C. (2016). Multi-scale mismatches between urban sprawl and landscape fragmentation create windows of opportunity for conservation development. Landscape Ecology, 31(10), 2291–2305.

Wang, K., Zhang, C., Chen, H., Yue, Y., Zhang, W., Zhang, M., Qi, X., & Fu, Z. (2019). Karst landscapes of China: Patterns, ecosystem processes and services. Landscape Ecology, 34(12), 2743–2763.

Weng, Y.-C. (2007). Spatiotemporal changes of landscape pattern in response to urbanization. Landscape and Urban Planning, 81(4), 341–353.

Wu, J. (2004). Effects of changing scale on landscape pattern analysis: Scaling relations. Landscape Ecology, 19(2), 125–138.

Wu, J., Shen, W., Sun, W., & Tueller, P. T. (2002). Empirical patterns of the effects of changing scale on landscape metrics. Landscape Ecology, 17(8), 761–782.

Xiao, H., Liu, Y., Li, L., Yu, Z., & Zhang, X. (2018). Spatial variability of local rural landscape change under rapid urbanization in Eastern China. ISPRS International Journal of GeoInformation, 7(6), 231.

Xu, C., Zhao, S., & Liu, S. (2019). Spatial scaling of multiple landscape features in the conterminous United States. Landscape Ecology, 35, 223–247.

Xu, X., Liu, J., Zhang, S., Li, R., Yan, C., & Wu, S. (2018). China’s land use remote sensing mapping system (CNLUCC) dataset. Resource and Environment Data cloud platform.

Yang, J., Li, S., & Lu, H. (2019). Quantitative influence of landuse changes and urban expansion intensity on landscape pattern in Qingdao, China: Implications for urban sustainability. Sustainability, 11(21), 6174.

Zhang, M., & Rasiah, R. (2013). Qingdao. Cities, 31, 591–600.

Zhang, Q., & Seto, K. C. (2011). Mapping urbanization dynamics at regional and global scales using multi-temporal DMSP/ OLS nighttime light data. Remote Sensing of Environment, 115(9), 2320–2329.

Zhang, Q., & Su, S. (2016). Determinants of urban expansion and their relative importance: A comparative analysis of 30 major metropolitans in China. Habitat International, 58, 89–107.

Zhou, W., & Cao, F. (2020). Effects of changing spatial extent on the relationship between urban forest patterns and land surface temperature. Ecological Indicators, 109, 105778.