Assessment of development trend and land use change in Qom province using remote sensing technology

Abstract

AbstractIntroduction: Land-use change is an important factor in changing the hydrologic processes and biodiversity. It has significant environmental consequences at local, regional, and global scales. Although many studies have been conducted for revealing the land-use change worldwide, its impact on the hydrologic processes, water resources, water supply, and water consumption is poorly understood.Methods: The present research is an effort to use remote sensing techniques for investigating land-use change in Qom province during the last three decades. Qom province, located in the west of the Dasht-e-Kavir desert with vulnerable water resources, has been subject of a rapid development process in recent decades so water resources require more attention. Here, Maximum Likelihood Classification (MLC) and Decision Tree Classification (DTC) were used to show the role of the classification method in the results.Findings: The results showed that “drought” and “increasing number of farmers”, with an average score of 3.56 and 3.45 respectively on a scale of 1 to 5, are considered as the main causes of agricultural water conflict. From the farmers’ view, the priority for reducing water conflicts was the participation of farmers in managing water wells and negotiating with farmers around the water. On a scale of 13 to 65 with an average of 38.51, the perceived agricultural water conflict was at the medium level. By increasing farm distance from the well, area of agricultural rental land, and annual income from non-agricultural activities, the perception of agricultural water conflict increased. However, by increasing owned agricultural land area and agricultural income, the perception of agricultural water conflict decreased. The main strategy used by farmers to manage agricultural water conflict was “control”, in which coercion and force are used to manage conflict. The “problem-solving” and “avoidance” strategies were the second and third priorities respectively.

Keywords

• remote sensing
• land-use
• qom province
• decision tree
• maximum likelihood