Canadian Journal of Remote Sensing

Leaf chlorophyll is central to the exchange of carbon, water and energy between the biosphere and the atmosphere. Solar radiation, harvested by chlorophyll molecules, is converted into stored chemical energy through the process of photosynthesis, which forms the basis of life on earth.  As such, the abundance of chlorophyll in leaves and canopies, and its distribution in time and space is central to the functioning of terrestrial ecosystems. Leaf chlorophyll content can be used to indicate plant responses to biotic and abiotic stress, it is an important parameter in regional and global carbon models, and it can highlight areas of plant disturbance. Monitoring leaf chlorophyll content under changing climatic conditions is paramount for understanding ecosystem responses to environmental change.

Advances in sensor technologies, novel platform innovations and new data analysis techniques have given rise to new opportunities for research in the remote sensing of leaf chlorophyll, along with an increased focus on ecosystem functioning and the biochemical drivers that underpin plant physiological processes. However, accounting for confounding vegetation structural properties (e.g. leaf area index, leaf angle distribution) on the accuracy of leaf chlorophyll content retrievals remains a complex challenge.

In this Article Collection, we welcome studies that use remote sensing data to model leaf chlorophyll content across all observational scales and experimental designs, from ground-based studies, through to tower observations and drone, airborne and satellite platforms. We encourage the submission of papers covering both methods-based approaches of chlorophyll retrieval (e.g., statistical, process-based, machine learning) and applied studies using remotely-sensed chlorophyll content to investigate, for example: plant-environment interactions, environmental change, the integration of leaf chlorophyll into terrestrial biosphere models and crop models, and guiding management decisions and precision agriculture.

Guest Advisor Biographies:

Dr Holly Croft is a UKRI Future Leaders Fellow and a Senior Research Fellow in the School of Biosciences at the University of Sheffield, UK. Her research is focused on deriving plant physiological information from remotely sensed data to better understand plant-environment interactions, improve modelled estimates of plant productivity and to detect plant biotic and abiotic stress.  She uses remote sensing data, acquired from a range of platforms from UAVs through to satellites, ground-based field experiments and novel analytical methods to improve our understanding of vegetation dynamics.

Dr Cheryl Rogers is a postdoctoral fellow in the School of Earth, Environment & Society at McMaster University. Her research focuses on remote sensing of the terrestrial carbon cycle. Her research focus includes monitoring processes that control the exchange of carbon between vegetation and the atmosphere, assessing carbon stocks in the earth’s biosphere, and understanding the linkages between vegetation physiological processes and the spectral signals observable from space.

Dr Rong Wang is an associate professor in the School of Geographical Sciences, Fujian Normal University. Her primary research interests are remote sensing of vegetation and terrestrial carbon cycle. She is currently working on inversion land surface vegetation parameters, applying these parameters for carbon cycle modelling and understanding how terrestrial carbon stocks change under the changing climate.

Prof Yuhong He is a Professor in the Department of Geography, Geomatics and Environment at the University of Toronto Mississauga (UTM). Her research focuses on investigating changes that have occurred in natural (grasslands, forests, wetlands) or managed (farmlands and urban) systems using remote sensing, machine learning, and ecosystem modelling.

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisors for this collection will not be handling the manuscripts. Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is 30 June 2024.

We encourage the submission of papers covering both methods-based approaches of chlorophyll retrieval (e.g., statistical, process-based, machine learning) and applied studies using remotely-sensed chlorophyll content to investigate, for example: plant-environment interactions, environmental change, the integration of leaf chlorophyll into terrestrial biosphere models and crop models, and guiding management decisions and precision agriculture.

Instructions for Authors