Journal Article

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

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

2022

Overview

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 km 2 in total by 2030. Between 2019 and 2030, the other significant changes were the decrease of 34.57 km 2 of forest lands and the increase of agricultural lands by 14.90 km 2 and wetlands by 9.31 km 2 . 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.

• Publisher: Springer International Publishing,Springer Nature B.V
• Subject: Accuracy / Agricultural land / Algorithms / Artificial neural networks / Atmospheric Protection/Air Quality Control/Air Pollution / Biodiversity / Cellular automata / Cellular communication / Change detection / Classification / Cloud computing / Earth and Environmental Science / Ecology / Ecotoxicology / Environment / Environmental Management / Environmental monitoring / Environmental science / Estonia / Forecasting / forest land / Forests / Geography / hybrids / infancy / Internet / issues and policy / Land cover / Land use / Landsat / Landsat satellites / landscapes / Markov analysis / Markov chain / Markov chains / Modelling / Monitoring/Environmental Analysis / Neural networks / Remote sensing / Simulation / Spatial planning / Trends / Urban areas / Urban development / Urban sprawl / urbanization / Wetlands