Big Earth Data

Arid lands cover a substantial portion, approximately 30–40%, of the Earth's surface. However, these regions face significant challenges due to human activities and the impacts of climate change. Issues such as water scarcity, land degradation, desertification, biodiversity loss, food insecurity, poverty, and conflicts pose significant obstacles to the sustainable development of arid lands and the well-being of their inhabitants.

In response to these pressing concerns, the United Nations 2030 Agenda for Sustainable Development has established 17 Sustainable Development Goals (SDGs) with 169 targets. Many of these goals are closely tied to the issues and opportunities of arid lands, such as SDG 2 (Zero Hunger), SDG 6 (Clean Water and Sanitation), SDG 13 (Climate Action), SDG 15 (Life on Land), and SDG 17 (Partnerships for the Goals).

Earth observation (EO) emerges as a powerful tool for monitoring, understanding, and managing arid lands. Its ability to provide timely, accurate, and comprehensive insights into both natural and human-induced dynamics in these regions is unparalleled. By leveraging EO, we can enhance the implementation and assessment of SDGs in arid lands by providing indicators, benchmarks, trends, and projections across various facets of sustainable development. These include land cover and use, water resources and quality, wetland conservation and management, vegetation productivity and diversity, soil moisture and erosion, climate variability and extremes, as well as human activities and impacts.

However, the effective utilization of EO for arid lands and SDGs faces several challenges. These include the complex and heterogeneous nature of arid land systems, the scarcity and unreliability of ground data, diversity and incompatibility of EO data sources and products, integration and analysis of multi-source and multi-scale EO data, and as well as the dissemination and application of EO intelligence for decision-making and policy formulation.

Amidst these challenges, the rapid advancements in data science and artificial intelligence (AI) present new opportunities and innovations for EO in arid lands and SDGs. Big data technologies provide the infrastructure for the storage, organization, and processing of vast and diverse EO data, including satellite imagery, aerial photography, drone imagery, and ground-based sensor data. Meanwhile, AI techniques, including machine learning and deep learning, have the potential to enhance the extraction, fusion, and interpretation of EO insights, empowering collective efforts towards sustainable development in arid lands.

Potential topics include (but are not limited to) the following:

• EO data processing methods
• Land use and cover change
• Urbanization processes
• Agricultural survey and grassland monitoring
• Disaster monitoring and early warning
• Land degradation processes and desertification development
• Environmental health diagnosis and ecological safety assessment
• Landscape ecology and ecosystem services
• Biodiversity measuring and evaluation
• Water resource investigation and environmental assessment

Important Dates

• December 1, 2024  Submission deadline
• Febuary 1, 2025  Decision to authors
• April 1, 2025  Revised paper submission
• June 1, 2025  Publication

Manuscript Submission Information

All submissions will undergo a full peer review and acceptance is not guaranteed. Please visit the Instructions for Authors page before submitting your manuscript. Once you have finished preparing your manuscript, please submit it through the Taylor & Francis Submission Portal, ensuring that you select the appropriate Special Issue. Publication charges (APCs) will be waived for invited manuscripts submitted to Big Earth Data. Authors who need a waiver code should contact the Editorial Office ([email protected]) before submitting.

Instructions for Authors