Ecological Change with Multi-Scale Spatial-Temporal Remote Sensing Data

Dear Colleagues,

Ecosystems are facing significant challenges due to intensifying global climate change and human activities, impacting their structure, functions, and services. This necessitates the multi-scale spatiotemporal monitoring of ecological dynamics, a core issue in environmental science. The United Nations 2030 Agenda for Sustainable Development emphasizes the need to improve ecosystem protection and restoration, and the accurate monitoring and scientific assessment of ecological changes have become essential for achieving sustainable development goals. Ecological changes occur across multiple spatiotemporal scales, ranging from local ecosystem dynamics to global ecological patterns, all of which require high-precision, multi-dimensional data support. Remote sensing technology provides large-scale, high-frequency observational data, and when combined with multi-scale analytical methods, it can effectively reveal the driving mechanisms and response patterns of ecological changes. Research on ecological changes using multi-scale spatiotemporal remote sensing data further addresses the limitations of traditional remote sensing in temporal continuity and spatial detail. This approach not only enhances our understanding of complex ecosystem processes but also offers a scientific foundation for ecological conservation and sustainable development.

This Special Issue of Remote Sensing aims to highlight cutting-edge applications of multi-scale remote sensing data in ecological change research. It seeks to cover multi-source data fusion, driving factor analysis, and ecological management decision support, providing scientific evidence to address global ecological challenges—fully aligning with the journal's core objectives. Topics may span from local ecosystem analyses to global-scale ecological process studies. We encourage the submission of papers focusing on multi-scale spatiotemporal remote sensing data integration, cross-scale analytical methodologies, and investigations into ecological change processes and their impacts. By publishing high-quality research, this Special Issue hopes to foster interdisciplinary innovation between remote sensing, ecology, and related fields.

Articles may address, but are not limited to, the following topics: land ecological governance and ecological resilience enhancement; the collaborative analysis of multi-source data; the dynamic monitoring of ecological processes; driving mechanisms and model simulation; ecosystem service evaluation; multi-scale ecological evolution; and artificial intelligence and digital applications.

Prof. Dr. Linlin Cheng
Dr. Wei Tang
Dr. Deqin Fan
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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.