جستجو شبکه علمی ایران

جستجو

Adaptive Integrated Land Management Framework (AILMF): A Data-Driven Model for Optimizing Land Uses in Iran s Arid and Semi-Arid Regions

shahpour ebrahimi¹

Abstract :
Sustainable land management in arid and semi-arid regions has emerged as one of the most pressing challenges of the twenty-first century, particularly in countries facing severe water scarcity, increasing anthropogenic pressures, and accelerating climate change impacts. Iran, where a substantial proportion of the territory is characterized by dryland ecosystems, requires innovative and adaptive approaches to optimize land-use allocation while preserving ecological integrity and supporting socio-economic development.This study introduces the Adaptive Integrated Land Management Framework (AILMF), a comprehensive data-driven model designed to optimize multiple land uses in Iran s arid and semi-arid regions. Unlike conventional land management approaches that primarily focus on one or two dimensions of land suitability, the proposed framework integrates ecological, environmental, socio-economic, and technological dimensions into a unified decision-support system.The framework consists of four interconnected layers: (1) a data acquisition layer integrating remote sensing, Geographic Information Systems (GIS), soil, climatic, and socio-economic datasets; (2) an analytical layer employing machine learning algorithms and ecological capacity assessments; (3) a multi-criteria optimization layer for land-use allocation and scenario simulation; and (4) a monitoring and feedback layer enabling continuous model updating and adaptive management.The proposed framework provides a dynamic mechanism for identifying optimal land-use configurations while simultaneously improving economic productivity, ecological sustainability, and social equity. Furthermore, it enables environmental risk assessment, climate change adaptation, and strategic resource allocation under uncertainty.The principal contribution of this study lies in its interdisciplinary integration of spatial data science, machine learning, ecological resilience, and adaptive governance into a single operational framework. The model may serve as a transferable reference framework for sustainable land management in dryland ecosystems worldwide and support evidence-based decision-making at both regional and national scales.

Keywords : adaptive land management land use optimization arid regions semi arid regions ecological capacity assessment machine learning

زبان مقاله : انگلیسی
محور مقاله : مهندسی محیط زیست و محیط زیست شهری
محل انتشار : چهارمین کنفرانس بین المللی پژوهش های کاربردی در مهندسی عمران، معماری و شهرسازی
آدرس وب سایت کنفرانس : icarcau.com
کد IOI مقاله : ABKD-ABGKFZ
لینک مستقیم مقاله : https://isnac.ir/ABKD-ABGKFZ
نمایش چکیده فارسی : https://isnac.ir/SA/ABKD-ABGKFZ

مشاهده چکیده

(برای نویسندگان مقاله)

مشاهده چکیده

(برای نویسندگان مقاله)

جستجو

Adaptive Integrated Land Management Framework (AILMF): A Data-Driven Model for Optimizing Land Uses in Iran s Arid and Semi-Arid Regions

shahpour ebrahimi¹

سایر مقالات ارائه دهنده

سایر مقالات محل انتشار

جستجو

Adaptive Integrated Land Management Framework (AILMF): A Data-Driven Model for Optimizing Land Uses in Iran s Arid and Semi-Arid Regions

shahpour ebrahimi1

سایر مقالات ارائه دهنده

سایر مقالات محل انتشار

shahpour ebrahimi¹