Detection and prediction of land use changes and population dynamics in the Gorganrud River basin, Iran

Abstract

Analyzing land use/land cover change is a fundamental tool for evaluating the environmental consequences of human activities. This research was conducted to detect and predict likely land use changes in the Gorganrud River basin, Iran, and to estimate past and future population growth as a driving force in land use change and degradation. First, land use maps for 1999, 2009, and 2017 were prepared. Then, the likely land use changes for 2030 and 2040 were predicted using the Land Change Modeler (LCM) in TERRSET software. Results indicate that the percentage of changes in agricultural and residential areas, bare lands, and semi‐dense forests from 1999 to 2017 were +4.2, +0.62, +1.76, and +3.15, respectively, while the percentage of changes in rangelands, dense forests, and water bodies were −8.7, −0.37, and −0.63. Analysis of changes from 2017 to 2040 indicates that the percentage of changes in croplands, dense forests, and bare lands may reach −4.42, −2.35, and −2.74, respectively. Conversely, the area of rangelands, semi‐dense forests, water bodies, and residential areas would likely increase by +7.78%, +1.02%, +0.04%, and + 0.7%, respectively. The population density in 2011 and 2016 was 94 and 97 persons/km2, respectively, whereas the 5‐year population growth rate was 3.5%. Better conservation practices to prevent deforestation and inappropriate growth of residential areas, in line with forest replantation to prevent the conversion of semi‐dense forests into rangelands, are some of the management strategies required in the study area. Population control and redistribution are other prescribed actions based on the research findings.

Selected Driver Variables for the Simulation of Land-Use and Land-Cover Change for the Republic of Djibouti: A Study from Semi-Arid Region

“…Another study in Saudi Arabia, which utilized the LCM MLP-NN algorithm to predict LULC for 2040, resulted in an overall accuracy of 88% (Alqadhi et al, 2021). The other research conducted by Ghonchepour et al (2023) in the Gorganrud River basin, Iran, obtained higher validation results for the 2040 LULC map and correlated with the predicted population as a main driving force in such changes. They further concluded that other driver variables should be considered to identify the driving forces behind such a transition so that effective management strategies can be utilized.…”

Python-based Population Forecasting with Standard Deviation Analysis

“…Written by Kilburn KH, Thornton JC and Hanscom B. In this paper, researchers argue that brain function testing is conceptually similar to lung function testing..The authors used these tests to evaluate 293 adults from three unexposed groups in different regions of the United States..Subjects were contacted randomly from the voter registration rolls and compensated for their time..The tests included balance, reaction time, strength, hearing, visual performance and cognitive recall, perceptual motor and memory functions..The regression equations simulate the performance of each test and the effect of demographic factors..The resulting prediction equations will help researchers conduct quantitative tests on chemically exposed individuals and others with brain damage [3].…”