Simulation of land use/land cover changes and urban expansion in Estonia by a hybrid ANN-CA-MCA model and utilizing spectral-textural indices View Full Text


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Article Info

DATE

2022-07-13

AUTHORS

Najmeh Mozaffaree Pour, Oleksandr Karasov, Iuliia Burdun, Tõnu Oja

ABSTRACT

Over the recent two decades, land use/land cover (LULC) drastically changed in Estonia. Even though the population decreased by 11%, noticeable agricultural and forest land areas were turned into urban land. In this work, we analyzed those LULC changes by mapping the spatial characteristics of LULC and urban expansion in the years 2000–2019 in Estonia. Moreover, using the revealed spatiotemporal transitions of LULC, we simulated LULC and urban expansion for 2030. Landsat 5 and 8 data were used to estimate 147 spectral-textural indices in the Google Earth Engine cloud computing platform. After that, 19 selected indices were used to model LULC changes by applying the hybrid artificial neural network, cellular automata, and Markov chain analysis (ANN-CA-MCA). While determining spectral-textural indices is quite common for LULC classifications, utilization of these continues indices in LULC change detection and examining these indices at the landscape scale is still in infancy. This country-wide modeling approach provided the first comprehensive projection of future LULC utilizing spectral-textural indices. In this work, we utilized the hybrid ANN-CA-MCA model for predicting LULC in Estonia for 2030; we revealed that the predicted changes in LULC from 2019 to 2030 were similar to the observed changes from 2011 to 2019. The predicted change in the area of artificial surfaces was an increased rate of 1.33% to reach 787.04 km2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km2 of forest lands and the increase of agricultural lands by 14.90 km2 and wetlands by 9.31 km2. These findings can develop a proper course of action for long-term spatial planning in Estonia. Therefore, a key policy priority should be to plan for the stable care of forest lands to maintain biodiversity. More... »

PAGES

584

References to SciGraph publications

  • 2017-06-13. An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain in ARABIAN JOURNAL OF GEOSCIENCES
  • 2018-02-14. Reading past landscapes: combining modern and historical records, maps, pollen-based vegetation reconstructions, and the socioeconomic background in LANDSCAPE ECOLOGY
  • 2021-03-31. Toward digital agricultural mapping in Africa: evidence of Northern Nigeria in ARABIAN JOURNAL OF GEOSCIENCES
  • 2019-05-06. Urban growth boundaries delineation coupling ecological constraints with a growth-driven model for the main urban area of Chongqing, China in GEOJOURNAL
  • 2019-04-09. Prediction of landscape pattern changes in a coastal river basin in south-eastern China in INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
  • 2020-02-26. Simulating spatial–temporal urban growth of a Moroccan metropolitan using CA–Markov model in SPATIAL INFORMATION RESEARCH
  • 2020-10-18. Assessment of urban sprawl using landscape metrics and Shannon’s entropy model approach in town level of Barrackpore sub-divisional region, India in MODELING EARTH SYSTEMS AND ENVIRONMENT
  • 2021-04-17. Urban classification using preserved information of high dimensional textural features of Sentinel-1 images in Tabriz, Iran in EARTH SCIENCE INFORMATICS
  • 2021-02-23. Multi-layer perceptron-Markov chain-based artificial neural network for modelling future land-specific carbon emission pattern and its influences on surface temperature in SN APPLIED SCIENCES
  • 2015-02-07. Predicting Spatial and Decadal LULC Changes Through Cellular Automata Markov Chain Models Using Earth Observation Datasets and Geo-information in ENVIRONMENTAL PROCESSES
  • 2019-05-18. Dynamic simulation of land use change based on logistic-CA-Markov and WLC-CA-Markov models: a case study in three gorges reservoir area of Chongqing, China in ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
  • 2019-01-14. Detection and prediction of land use/land cover change using spatiotemporal data fusion and the Cellular Automata–Markov model in ENVIRONMENTAL MONITORING AND ASSESSMENT
  • 2015-07-30. Simulating land use change by integrating landscape metrics into ANN-CA in a new way in FRONTIERS OF EARTH SCIENCE
  • 2008-12-25. The status, conservation and sustainable use of Estonian wetlands in WETLANDS ECOLOGY AND MANAGEMENT
  • 2020-08-16. Monitoring land use changes and its future prospects using cellular automata simulation and artificial neural network for Ahmedabad city, India in GEOJOURNAL
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/s10661-022-10266-7

    DOI

    http://dx.doi.org/10.1007/s10661-022-10266-7

    DIMENSIONS

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    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/35829789


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