Multisource Remote Sensing Data Fusion and Applications in Vegetation Monitoring (Second Edition)

Dear Colleagues,

The monitoring and characterization of vegetation ecosystems represents a cornerstone of global environmental research, underpinning efforts to address climate change, biodiversity loss, and sustainable land management. Traditional approaches relying on field-based inventories or single-sensor remote sensing have long provided critical insights, but their limitations, such as restricted spatial coverage, temporal infrequency, or spectral constraints, have fueled the need for more holistic methodologies. Multisource remote sensing data fusion has emerged as a transformative approach for advancing vegetation monitoring, enabling synergistic insights that surpass the capabilities of individual sensors.

This Special Issue explores cutting-edge methodologies for integrating heterogeneous datasets, including optical, radar, LiDAR, hyperspectral, and thermal infrared imagery, from satellite, aerial, and ground-based platforms. By combining complementary spatial, spectral, and temporal resolutions, contributors are expected to address critical challenges in vegetation ecosystems, such as biodiversity conservation, carbon cycle dynamics, land-use change, and disturbance resilience.

This Special Issue advances this frontier by curating cutting-edge research that bridges technical innovation and ecological application. By fostering cross-disciplinary dialog, it aims to catalyze solutions for one of Earth’s most pressing challenges: sustaining vegetation ecosystems in the Anthropocene. The issue supports the journal's core objective of advancing remote sensing innovations for environmental monitoring and sustainability.

We welcome submissions of original research, reviews, and case studies. Articles may address, but are not limited to, the following topics:

• Vegetation parameter estimation (e.g., biomass, leaf area index, species composition)
• Ecosystem service monitoring (pollination, soil erosion control, water regulation)
• Disturbance detection and recovery (wildfires, droughts, invasive species)
• Carbon flux modeling and sequestration potential mapping
• Precision agriculture and crop health diagnostics
• Urban vegetation mapping and heat island mitigation
• Biodiversity hotspot identification and connectivity analysis
• Climate change impacts on phenology and range shifts
• Fusion algorithms for cross-sensor calibration and uncertainty reduction
• Machine learning-driven upscaling from local plots to global datasets
• Policy-relevant applications (e.g., REDD+ monitoring, habitat restoration planning)

Dr. Dong Liu
Dr. Jiakui Tang
Dr. Qing Zhang
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-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.