GeoAI and Remote Sensing for Ecological Security and Sustainable Development in Arid Lands

Dear Colleagues,

Arid lands, characterized by scarce water resources, fragile ecosystems, and extreme climatic conditions, present significant challenges for ecological security and sustainable development. Human activities, climate change, and land degradation further exacerbate these challenges, threatening biodiversity, food security, and the livelihoods of millions. In recent years, advances in geospatial artificial intelligence (GeoAI) and remote sensing technologies have emerged as powerful tools to address these issues, offering new opportunities for monitoring, modeling, and managing arid landscapes with unprecedented precision and efficiency.

GeoAI integrates machine learning, big data analytics, and geographic information science (GIS) to extract actionable insights from vast amounts of remote sensing data. These technologies enable researchers and policymakers to detect environmental changes, assess land degradation, optimize water resource management, and develop adaptive strategies for mitigating ecological risks. The fusion of high-resolution satellite imagery, UAV-based observations, and AI-driven predictive models is revolutionizing environmental monitoring, providing critical support for sustainable land management, conservation efforts, and climate adaptation strategies in arid regions.

This Special Issue aims to bring together interdisciplinary research that explores the potential of GeoAI and remote sensing for tackling ecological and developmental challenges in arid lands. We invite contributions that demonstrate innovative methodologies, novel applications, and case studies showcasing how these technologies can enhance ecological security and foster sustainability in dryland regions across the globe.

Topics of Interest:

We welcome contributions on a wide range of topics including, but not limited to, the following:

• GeoAI applications in arid land monitoring (e.g., machine learning, deep learning, and spatial analysis techniques for environmental assessment).
• Remote sensing for ecological security (e.g., drought assessment, land degradation monitoring, and biodiversity conservation).
• Sustainable land and water management (e.g., precision agriculture, water resource monitoring, and desertification control using satellite and UAV imagery).
• Multi-sensor data fusion (e.g., combining optical, SAR, LiDAR, and thermal remote sensing for enhanced environmental insights).
• Climate change impact assessment (e.g., modeling arid land dynamics, climate resilience, and adaptation strategies).
• Urbanization and land-use changes in arid regions (e.g., GIS-based approaches for sustainable urban planning and land policy development).
• Early warning systems for environmental hazards (e.g., wildfire detection, dust storm prediction, and water scarcity assessment using AI-powered remote sensing tools).
• Innovative GeoAI and big data analytics (e.g., cloud computing, geospatial deep learning, and digital twins for arid ecosystem management).

Dr. Alim Samat
Dr. Jinjie Wang
Prof. Dr. Alimujiang Kasimu
Dr. Yang Liu
Dr. Wei Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Land is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• GeoAI
• remote sensing
• machine learning
• arid environments
• ecological security
• sustainable development
• environmental monitoring
• land degradation
• climate adaptation
• GIS
• water resource management