Remote Sensing and Lidar Data for Forest Monitoring

Dear Colleagues,

In the past, remote sensing has been shown to contribute significantly to a better understanding of both the natural and built environment. With LiDAR remote sensing making it possible to collect 3D coordinates of objects with extremely high accuracy, many fields such as geosciences, urban studies, and vegetation mapping have been given the opportunity to develop further.

LiDAR sensors onboard different platforms (e.g., terrestrial, airborne, UAV, satellite, backpack, and handheld) have been widely used in various biomes, especially over large and remote areas. So far, one of the main applications of LiDAR data is to provide a reliable estimation of biomass and carbon stock as well as information related to different forest parameters (e.g., diameter at breast height and basal area, tree height, and canopy base height), resulting in significant contributions to sustainable forest management and climate change mitigation.

Recent developments in forest research include the integration of LiDAR with other remote sensing data at different scales, as well as the use of machine learning and deep learning to extract semantic information about different forest attributes.

This Special Issue on “Remote Sensing and LiDAR Data for Forest Monitoring” welcomes papers focusing on remote sensing applications based on LiDAR data for forest ecosystem monitoring. The scope of topics to be discussed includes but is not limited to the following:

• LiDAR-based approaches for forest ecology and management.
• Forest biomass estimation using LiDAR data or multisource approaches (including LiDAR).
• New methods in LiDAR processing for forest attribute retrieval.
• Machine learning and deep-learning approaches for forest information retrieval from LiDAR data.
• Multisensor approaches and data fusion for forest ecosystem monitoring.
• Multitemporal LiDAR approaches for forest change monitoring.
• New approaches in forest damage detection methods employing LiDAR data.

Prof. Dr. Ioannis Gitas
Dr. Dimitris Stavrakoudis
Dr. Patricia Oliva
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.