Application of a land use change model to guide regional planning and development in the south basin of the Urmia Lake, Iran

Latif Mohammadzadeh, Mansour Ghanian*, Somayeh Shadkam, Gül Özerol, Afshin Marzban

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Farmers have to make decisions to adapt to climate change and reduce environmental vulnerability. If these decisions are made incorrectly, irreversible changes can take place that threaten environmental, social and economic sustainability of agriculture. This study applies a land use change model to guide regional agricultural land use planning, with a focus on the case of the south basin of the Urmia Lake, NW Iran, using data from Landsat images, statistics, questionnaire and checklist. The findings indicate the significant changes in the five factors, namely rainfall, humidity, minimum temperature, average temperature and maximum temperature. For example, the rainfall decreased more than 10 mm and the average temperature has increased by 3.5 °C in the last 30 years. The results of factor analysis showed that the studied variables were grouped into eight factors. These factors explained 57.4% of the variance of the determinant factors of farmers' behavior on climate change in the study area. The results obtained from supervised classification showed that all land uses have undergone many changes. The irrigated agriculture and rainfed agriculture have increased 79.43% and 82.5%, respectively, while water bodies, dense grass and woodlands, and sparse grass have declined sharply in the south basin of Urmia Lake. The forecasted results for the year 2027 show that if the existing situation continues, more crises will be faced in terms of land use change, since irrigated agriculture and rainfed agriculture are expected to grow by nearly 9000 ha and more than 1000 ha, respectively.

Original languageEnglish
Article number545
Number of pages18
JournalEnvironmental earth sciences
Volume80
Issue number17
Early online date14 Aug 2021
DOIs
Publication statusPublished - 2021

Keywords

  • Climate change
  • CLUE-s model
  • Factor analysis
  • Farmers' behavior
  • Logistic regression
  • Supervised classification

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