Dear Colleagues,

In continuation to earlies issue, this issue is focused on the advancement of remote sensing technologies for forest monitoring.

Vegetation is an assemblage of plant species and the ground cover they provide. It is a broad  term, without specific reference to particular taxa, life forms, structure, spatial extent, or any geographical characteristics. Vegetation, which occupy about one-third of the terrestrial surface of Earth, play an indispensable role in monitoring global climate change and ecosystem dynamics. The health of forests has been affected in recent years by various stress factors, such as forest fragmentation and deforestation, biodiversity loss, climate change, invasive species, drought, and unsustainable management. In this situation, quantitative appraisal of biophysical and biochemical parameters is imperative since it can provide a direct assessment and prediction of vegetation health and sustainability.

Earth Observation aids in the spatiotemporally explicit retrieval of biophysical and biochemical parameters in both the optical and microwave domain. This information can be utilized to monitor and forecast short- and long-term changes in forest ecosystems that occur due to different factors. Different methods have been explored to retrieve vegetation biophysical/biochemical parameters, such as parametric regression (including vegetation indices, shape indices, and spectral transformations), nonparametric regression (including linear and nonlinear machine learning regression algorithms), physically based methods (including inversion of radiative transfer models (RTMs) using numerical optimization and look-up table approaches), and hybrid regression methods (that combine RTM simulations with machine learning regression methods).

This Special Issue will cover vegetation monioting and management using advanced remote sensing technologies. This further includes evaluation of different techniques for the retrieval of different biophysical/biochemical parameters using available Earth Observation data- Optical, Hyperspectral, LiDAR, Microwave- or multi-soruce- multi-sensors. We invite you to contribute a research article to this Special Issue on one of the following topics (but not limited to);

• Vegetation monitoring: forests, grasslands, urban green cover, wetland vegetation or related theme. Cropland monitoring is also considered with similar paramters and assessment.
• retrieval of biophysical parameters, viz. LAI, vegetation water content, height, biomass, DBH, etc.;
• measurement of biochemical parameters, viz. chlorophyll, pigments, etc.;
• radiative transfer models in the retrieval of biophysical/biochemical parameters;
• establishment of relationships between in situ measured biophysical/biochemical parameters and ground-measured data;
• airborne or spaceborne hyperspectral data in the retrieval of biophysical/biochemical parameters;
• LiDAR and RADAR remote sensing in the estimation of biophysical variables;
• relation of biophysical/biochemical parameters to climatic factors;
• biophysical/biochemical parameter retrieval from an Unmanned Autonomous Vehicle (UAV).
• Wetlands’ emergent hydrophytes and their mapping, advanced technology.
• Forest fire analysis, simulation and modelling using advanced techniques.

Dr. Prem Chandra Pandey
Prof. Dr. Onisimo Mutanga
Dr. Prashant Srivastava
Dr. Mukunda Dev Behera
Guest Editors

Manuscript Submission Information

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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.

• biophysical parameters
• biochemical parameters
• multi-sensors
• LiDAR
• UAV-AS-drones
• microwave
• hyperspectral