Share:


Spatiotemporal changes of the habitat quality and the human activity intensity and their correlation in mountainous cities

    Huiqing Han Affiliation
    ; Yingjia Zhang Affiliation
    ; Yue Liu Affiliation
    ; Xin Yu Affiliation
    ; Junwen Wang Affiliation

Abstract

As the urbanization is being rapidly boosted, the urban habitat quality has been significantly disturbed by human activities through land use, which highly affects the urban ecological environment and sustainable development of social economy. However, the change characteristics of the habitat quality and human activities in different topographic gradients in rapidly urbanized mountainous cities remain unclear. Accordingly, Guiyang in China, is selected as the representative of typical mountain cities. The change characteristics of the habitat quality, the human activity intensity and their correlation in mountainous cities from 2000 to 2020, are analyzed using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, as well as the ArcGIS software based on the remote sensing interpretation data in 2000, 2010 and 2020. The results demonstrate that the overall habitat quality in Guiyang decreased by 0.0304, while the human activity intensity increased by 0.0287 from 2000 to 2020. The amount of changes of the habitat quality and the human activity intensity in Guiyang from 2010 to 2020, are higher than those from 2000 to 2010. The amount of changes of the habitat quality and the human activity intensity in Guiyang decreases with the increase of the slope. The central and southern parts of Guiyang are the highlight areas with a significant decline of habitat quality and significant increase of human activity intensity. The areas with an increased habitat quality and decreased human activity intensity are sporadically distributed. A significant negative correlation is reported between the change of the habitat quality and human activity intensity in Guiyang. In addition, a prominent spatial heterogeneity is identified in the local indicators of the spatial association (LISA) map. The significant increase in the artificial land and the decrease in the natural land as affected by the rapid urbanization, act as crucial factors leading to the decline of the habitat quality and the increase in the human activity intensity in mountainous cities.

Keyword : habitat quality, human activity intensity, spatial pattern, correlation, mountain city

How to Cite
Han, H., Zhang, Y., Liu, Y., Yu, X., & Wang, J. (2022). Spatiotemporal changes of the habitat quality and the human activity intensity and their correlation in mountainous cities. Journal of Environmental Engineering and Landscape Management, 30(4), 472–483. https://doi.org/10.3846/jeelm.2022.18054
Published in Issue
Nov 30, 2022
Abstract Views
481
PDF Downloads
347
Creative Commons License

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

References

Alaniz, A. J., Carvajal, M. A., Fierro, A., Vergara-Rodríguez, V., Toledo, G., Ansaldo, D., Moreira-Arce, D., Rojas-Osorio, A., & Vergara, P. M. (2021). Remote-sensing estimates of forest structure and dynamics as indicators of habitat quality for Magellanic woodpeckers. Eco-logical Indicators, 126, 107634. https://doi.org/10.1016/j.ecolind.2021.107634

Aneseyee, A. B., Noszczyk, T., Soromessa, T., & Elias, E. (2020). The InVEST habitat quality model associated with land use/cover changes: A quali-tative case study of the Winike watershed in the Omo-Gibe basin, southwest Ethiopia. Remote Sensing, 12(7), 1103. https://doi.org/10.3390/rs12071103

Anselin, L. (1995). Local indicators of spatial association – LISA. Geographical Analysis, 27(2), 93–115. https://doi.org/10.1111/j.1538-4632.1995.tb00338.x

Antwi, E. K., Krawczynski, R., & Wiegleb, G. (2008). Detecting the effect of disturbance on habitat diversity and land cover change in a post-mining area using GIS. Landscape & Urban Planning, 87(1), 22–32. https://doi.org/10.1016/j.landurbplan.2008.03.009

Bennett, M. M., & Smith, L. C. (2017). Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeco-nomic dynamics. Remote Sensing of Environment, 192, 176–197. https://doi.org/10.1016/j.rse.2017.01.005

Buddendorf, W. B., Jackson, F. L., Malcolm, I. A., Millidine, K. J., Geris, J., Wilkinson, M. E., & Soulsby, C. (2019). Integration of juvenile habitat quality and river connectivity models to understand and prioritise the management of barriers for Atlantic salmon populations across spatial scales. Science of the Total Environment, 655, 557–566. https://doi.org/10.1016/j.scitotenv.2018.11.263

Diaz, R. J., Solan, M., & Valente, R. M. (2004). A review of approaches for classifying benthic habitats and evaluating habitat quality. Journal of Envi-ronmental Management, 73(3), 165–181. https://doi.org/10.1016/j.jenvman.2004.06.004

Han, H. Q., & Dong, Y. X. (2017). Assessing and mapping of multiple ecosystem services in Guizhou Province, China. Tropical Ecology, 58, 331–346.

Han, Y. W., Kang, W. M., Thorne, J., & Song, Y. (2019). Modeling the effects of landscape patterns of current forests on the habitat quality of histori-cal remnants in a highly urbanized area. Urban Forestry & Urban Greening, 41, 354–363. https://doi.org/10.1016/j.ufug.2019.04.015

He, J. H., Huang, J. L., & Li, C. (2017). The evaluation for the impact of land use change on habitat quality: A joint contribution of cellular automata scenario simulation and habitat quality assessment model. Ecological Modelling, 366, 58–67. https://doi.org/10.1016/j.ecolmodel.2017.10.001

Kantharajan, G., Yadav, A. K., Chandran, R., Singh, R. K., Mohindra, V., Krishnan, R., Kumar, K., Shukla, S. P., & Lal, K. K. (2022). Impact of ter-restrial protected areas on the fish diversity and habitat quality: Evidence from tropical river Pranhita, India. Journal for Nature Conservation, 68, 126187. https://doi.org/10.1016/j.jnc.2022.126187

Lan, T., Shao, G. F., Xu, Z. B., Tang, L. N., & Sun, L. (2021). Measuring urban compactness based on functional characterization and human activity intensity by integrating multiple geospatial data sources. Ecological Indicators, 121, 107177. https://doi.org/10.1016/j.ecolind.2020.107177

Lee, D. J, & Jeon, S. W. (2020). Estimating changes in habitat quality through land-use predictions: Case study of roe deer (Capreolus pygargus tian-schanicus) in Jeju island. Sustainability, 12(23), 1–18. https://doi.org/10.3390/su122310123

Li, F. X., Wang, L. Y., Chen, Z. J., Clarke, K. C., Li, M. C., & Jiang, P. H. (2018). Extending the SLEUTH model to integrate habitat quality into urban growth simulation. Journal of Environmental Management, 217, 486–498. https://doi.org/10.1016/j.jenvman.2018.03.109

Liang, F. C., & Liu, L. M. (2011). Quantitative analysis of human disturbance intensity of landscape patterns and preliminary optimization of ecological function regions: A case of Minqing county in Fujian Province. Resources Science, 33(6), 1138–1144 (in Chinese).

Liu, X. B., Wang, Y. K., & Li, M. (2021). How to identify future priority areas for urban development: An approach of urban construction land suitabil-ity in ecological sensitive areas. International Journal of Environmental Research and Public Health, 18(8), 4252. https://doi.org/10.3390/ijerph18084252

Liu, Y., Huang, X. J., Yang, H., & Zhong, T. Y. (2014). Environmental effects of land-use/cover change caused by urbanization and policies in South-west China Karst area – A case study of Guiyang. Habitat International, 44, 339–348. https://doi.org/10.1016/j.habitatint.2014.07.009

Pal, S., Talukdar, S., & Ghosh, R. (2020). Damming effect on habitat quality of riparian corridor. Ecological Indicators, 114, 106300. https://doi.org/10.1016/j.ecolind.2020.106300

Rahnama, M. R. (2021). Forecasting land-use changes in Mashhad Metropolitan area using Cellular Automata and Markov chain model for 2016–2030. Sustainable Cities and Society, 64, 102548. https://doi.org/10.1016/j.scs.2020.102548

Randhir, T. O., & Ekness, P. (2013). Water quality change and habitat potential in riparian ecosystems. Ecohydrology & Hydrobiology, 13(3), 192–200. https://doi.org/10.1016/j.ecohyd.2013.09.001

Sallustio, L., De Toni, A., Strollo, A., Di Febbraro, M., Casella, L., Geneletti, D., Munafò, M., Vizzarri, M., & Marchetti, M. (2017). Assessing habitat quality in relation to the spatial distribution of protected areas in Italy. Journal of Environmental Management, 201, 129–137. https://doi.org/10.1016/j.jenvman.2017.06.031

Sharp, R., Tallis, H. T., Ricketts, T., Guerry, A. D., Wood, S. A., Chaplin-Kramer, R., Nelson, E., Ennaanay, D., Wolny, S., Olwero, N., Vigerstol, K., Pennington, D., Mendoza, G., Aukema, J., Foster, J., Forrest, J., Cameron, D., Arkema, K., Lonsdorf, E., … Vogl, A. L. (2014). InVEST user’s guide: The Natural Capital Project. Stanford.

Song, S. X., Liu, Z. F., He, C. Y., & Lu, W. L. (2020). Evaluating the effects of urban expansion on natural habitat quality by coupling localized shared socioeconomic pathways and the land use scenario dynamics-urban model. Ecological Indicators, 112, 106071. https://doi.org/10.1016/j.ecolind.2020.106071

Sun, X. Y., Jiang, Z., Liu, F., & Zhang, D. Z. (2019). Monitoring spatio-temporal dynamics of habitat quality in Nansihu Lake basin, eastern China, from 1980 to 2015. Ecological Indicators, 102, 716–723. https://doi.org/10.1016/j.ecolind.2019.03.041

Sun, Y. X., Liu, S. L., Shi, F. M., An, Y., Li, M. Q., & Liu, Y. X. (2020). Spatio-temporal variations and coupling of human activity intensity and ecosystem services based on the four-quadrant model on the Qinghai-Tibet Plateau. Science of The Total Environment, 743, 140721. https://doi.org/10.1016/j.scitotenv.2020.140721

Tang, F., Fu, M. C., Wang, L., & Zhang, P. T. (2020). Land-use change in Changli County, China: Predicting its spatio-temporal evolution in habitat quality. Ecological Indicators, 117(1), 106719. https://doi.org/10.1016/j.ecolind.2020.106719

Upadhaya, S., & Dwivedi, P. (2019). Conversion of forestlands to blueberries: Assessing implications for habitat quality in Alabaha river watershed in Southeastern Georgia, United States. Land Use Policy, 89, 104229. https://doi.org/10.1016/j.landusepol.2019.104229

Van Dolah, R. F., Hyland, J. L., Holland, A. F., Rosen, J. S., & Snoots, T. R. (1999). A benthic index of biological integrity for assessing habitat qual-ity in estuaries of the southeastern USA. Marine Environmental Research, 48(4–5), 269–283. https://doi.org/10.1016/S0141-1136(99)00056-2

Xu, Y., Xu, X. R., & Tang, Q. (2016). Human activity intensity of land surface: Concept, methods and application in China. Journal of Geographical Sciences, 26, 1349–1361. https://doi.org/10.1007/s11442-016-1331-y

Yang, Y. Y. (2021). Evolution of habitat quality and association with land-use changes in mountainous areas: A case study of the Taihang Mountains in Hebei Province, China. Ecological Indicators, 129, 107967. https://doi.org/10.1016/j.ecolind.2021.107967

Yohannes, H., Soromessa, T., Argaw, M., & Dewan, A. (2021). Spatio-temporal changes in habitat quality and linkage with landscape characteristics in the Beressa watershed, Blue Nile basin of Ethiopian highlands. Journal of Environmental Management, 281, 111885. https://doi.org/10.1016/j.jenvman.2020.111885

Zhang, T. Z., Gao, Y., Li, C., Xie, Z., Chang, Y. Y., & Zhang, B. L. (2020a). How human activity has changed the regional habitat quality in an eco-economic zone: Evidence from Poyang Lake Eco-Economic Zone, China. International Journal of Environmental Research and Public Health, 17(17), 6253. https://doi.org/10.3390/ijerph17176253

Zhang, X. R., Song, W., Lang, Y. Q., Feng, X. M., Yuan, Q. Z., & Wang, J. T. (2020b). Land use changes in the coastal zone of China’s Hebei Prov-ince and the corresponding impacts on habitat quality. Land Use Policy, 99, 104957. https://doi.org/10.1016/j.landusepol.2020.104957

Zhu, C. M., Zhang, X. L., Zhou, M. M., He, S., Gan, M. Y., Yang, L. X., & Wang, K. (2020). Impacts of urbanization and landscape pattern on habitat quality using OLS and GWR models in Hangzhou, China. Ecological Indicators, 117(3), 106654. https://doi.org/10.1016/j.ecolind.2020.106654

Zlinszky, A., Heilmeier, H., Balzter, H., Czúcz, B., & Pfeifer, N. (2015). Remote sensing and GIS for habitat quality monitoring: New approaches and future research. Remote Sensing, 7(6), 7987–7994. https://doi.org/10.3390/rs70607987