Deep Learning in Environmental Remote Sensing: Enhancing Ecosystem Monitoring

Dear Colleagues,

Deep learning is rapidly reshaping the field of environmental remote sensing, opening new frontiers for the monitoring and management of ecosystems. This Special Issue, “Deep Learning in Environmental Remote Sensing: Enhancing Ecosystem Monitoring,” centers on the latest research, methodologies, and real-world applications where deep learning technologies drive more effective and timely ecosystem observation.

We welcome contributions that demonstrate how advanced deep learning models—such as Large Language Models (LLMs), diffusion models, multimodal AI, geoembedding, and emerging neural network architectures—are being used to monitor, analyze, and predict ecosystem changes. Key areas of interest include habitat mapping, biodiversity assessment, vegetation health monitoring, detection of land and water changes, and early warning systems for environmental disturbances.

This issue encourages submissions that address practical challenges in ecosystem monitoring, including, but not limited to, dealing with heterogeneous and multi-source remote sensing data, improving spatial and temporal resolution, and enhancing the interpretability and reliability of deep learning outputs for environmental decision-making. Studies that integrate deep learning with ecological models or traditional remote sensing techniques, as well as those presenting case studies of ecosystem applications at local, regional, or global scales, are especially welcomed.

By assembling cutting-edge research and practical solutions, this Special Issue aims to advance the capabilities of deep learning in environmental remote sensing, empowering scientists, practitioners, and policymakers to better understand, protect, and sustainably manage our ecosystems.

Dr. Zhe Wang
Dr. Chao Fan
Dr. Sanaz Salati
Dr. Marshall (Xiaogang) Ma
Dr. Xiang Que
Dr. Hui 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. 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.