Remote Sensing Monitoring of Urban Vegetation

Dear Colleagues,

Urban vegetation is among the most cost-effective nature-based solutions for improving livability—cooling hot neighborhoods, enhancing air quality, reducing flood risk, and supporting urban biodiversity. Yet these benefits are shaped not only by city-scale greening patterns but also by broader urban–watershed interactions, including upstream land-cover change, hydrological connectivity, and regional climate extremes. Meanwhile, green spaces and surrounding landscapes are rapidly changing under urban expansion, heatwaves, droughts, pests, and management practices. Capturing such multi-scale dynamics with field surveys alone is challenging due to cost, accessibility constraints, and limited temporal coverage. Remote sensing is reshaping how we observe vegetation and ecosystem functions across cities and their contributing watersheds, powered by high-resolution satellite and UAV imagery, LiDAR point clouds, advanced SAR techniques, hyperspectral and thermal sensors, and rapidly evolving AI-driven analytics. Together, these advances enable a shift from static maps toward scalable, repeatable, and increasingly timely monitoring of vegetation structure, condition, change, and the associated ecosystem services.

This Special Issue, “Remote Sensing Monitoring of Urban Vegetation”, invites cutting-edge contributions that develop and apply remote sensing methods to deliver robust, scalable, and actionable products for urban vegetation and related ecosystem functions. In addition to city-focused studies, we welcome work that links urban vegetation to watershed-scale ecological processes and ecosystem service assessments, such as flood regulation, water quality protection, carbon storage, habitat support, and heat-mitigation services, particularly when remote sensing enables spatially explicit quantification and uncertainty-aware valuation. The topic aligns closely with the scope of Remote Sensing by emphasizing innovations in sensor technologies, algorithm development, time-series analysis, multi-source fusion, validation strategies, uncertainty quantification, and reproducible geospatial workflows. We particularly welcome studies that bridge methodological advances with real-world applications and decision needs in planning, conservation, and sustainability.

We welcome original research articles, reviews, and technical notes on (but not limited to) the following:

(i) Urban vegetation mapping and change detection using multi-temporal imagery;

(ii) Street-tree and canopy cover inventories;

(iii) 3D and vertical-structure retrieval of urban vegetation (e.g., canopy height, crown metrics, biomass) using LiDAR (airborne/UAV/spaceborne) and photogrammetry, complemented by advanced SAR (InSAR/PolInSAR/TomoSAR), with multi-sensor fusion and validation;

(iv) Vegetation health, stress, and traits from hyperspectral/thermal data;

(v) Multi-sensor and cross-scale fusion (satellite–UAV–ground) and time-series assimilation;

(vi) AI/ML and foundation-model approaches,

(vii) Uncertainty quantification;

(viii) Use of physical-based approaches (e.g., radiative transfer models),

(ix) Benchmarking, open datasets, and reproducible pipelines;

(x) Urban ecosystem services linked to cooling, carbon, resilience, and environmental equity;

(xi) Ecosystem service modeling and (eco-)economic valuation across urban–peri-urban–watershed gradients, including spatially explicit assessment of regulating services (e.g., flood mitigation, erosion control, water purification) and their uncertainty, attribution, and policy relevance.

Submissions that provide transferable methods, rigorous validation, and clear implications for planning and sustainability are especially encouraged.

Dr. Ying Sun
Dr. Liming Du
Dr. Haiying Wang
Dr. Chengbin Deng
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.

• urban vegetation
• urban forests and street trees
• canopy structure and canopy height
• LiDAR (airborne/UAV/spaceborne)
• InSAR/PolInSAR/TomoSAR
• multi-sensor fusion
• time-series monitoring and change detection
• ecosystem services assessment and spatial decision support
• deep learning/foundation models
• validation and uncertainty quantification