Predicting and mapping land cover/land use changes in Erbil /Iraq using CA-Markov synergy model
- PDF / 1,210,350 Bytes
- 14 Pages / 595.276 x 790.866 pts Page_size
- 54 Downloads / 288 Views
RESEARCH ARTICLE
Predicting and mapping land cover/land use changes in Erbil /Iraq using CA-Markov synergy model Nabaz R. Khwarahm 1
&
Sarchil Qader 2,3 & Korsh Ararat 4 & Ayad M. Fadhil Al-Quraishi 5
Received: 1 June 2020 / Accepted: 23 October 2020 # Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract One of the most dynamic components of the environment is land use land cover (LULC), which have been changing remarkably since after the industrial revolution at various scales. Frequent monitoring and quantifying LULC change dynamics provide a better understanding of the function and health of ecosystems. This study aimed at modelling the future changes of LULC for the Erbil governorate in the Kurdistan region of Iraq (KRI) using the synergy Cellular Automata (CA)-Markov model. For this aim, three consecutive-year Landsat imagery (i.e., 1988, 2002, and 2017) were classified using the Maximum Likelihood Classifier. From the classification, three LULC maps with several class categories were generated, and then change-detection analysis was executed. Using the classified (1988–2002) and (2002–2017) LULC maps in the hybrid model, LULC maps for 2017 and 2050 were modelled respectively. The model output (modelled 2017) was validated with the classified 2017 LULC map. The accuracy of agreements between the classified and the modelled maps were Kno = 0.8339, Klocation = 0.8222, Kstandard = 0.7491, respectively. Future predictions demonstrate between 2017 and 2050, built-up land, agricultural land, plantation, dense vegetation and water body will increase by 173.7% (from 424.1 to 1160.8 km2), 79.5% (from 230 to 412.9 km2), 70.2% (from 70.2 to 119.5 km2), 48.9% (from 367.2 to 546.9 km2) and 132.7% (from 10.7 to 24.9 km2), respectively. In contrast, sparse vegetation, barren land will decrease by 9.7% (2274.6 to 2052.8 km2), 18.4% (from 9463.9-7721 km2), respectively. The output of this study is invaluable for environmental scientists, conservation biologists, nature-related NGOs, decision-makers, and urban planners. Keywords CA-Markov . Change-detection . Prediction . Classification . Remote sensing . GIS
Introduction Land use and land cover changes have been shown to have a direct impact on the local, global environment, land
* Nabaz R. Khwarahm [email protected] 1
Department of Biology, College of Education, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq
2
WorldPop, Geography and Environmental Science, University of Southampton, Southampton, UK
3
Natural Resources Department, College of Agricultural Engineering Sciences, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq
4
Department of Biology, College of Science, University of Sulaimani, Sulaimani, Kurdistan Region, Iraq
5
Surveying and Geomatics Engineering Department, Faculty of Engineering, Tishk International University, Erbil 44001, Kurdistan Region, Iraq
degradation, and climate, which in turn reduces ecosystem services and functions (Karki et al. 2018; Tolessa et al. 2017). The intensity, speed, and de
Data Loading...
