Frontiers in Remote Sensing is a multidisciplinary journal that seeks to bridge pioneering theoretical exploration and practical applications in the realm of remote sensing, ranging from spaceborne to airborne and unoccupied aerial system (UASs) and vehicle (UAVs) observations.

Led by Field Chief Editor, Dr. Jean-Pierre Wigneron (INRAE Bordeaux, France), and committed to advancing developments in the field by providing unrestricted access to articles and communicating scientific knowledge to researchers and the public, Frontiers in Remote Sensing explores all facets of remote sensing, focusing on major advances in the modeling, development and optimal use of various observation systems dedicated to the monitoring of land, oceans, atmosphere, and space at local and global scales, as well as the interpretation and application of data derived from these systems.

The journal aims to cover a wide array of topics, including but not limited to:

Fundamental theories of remote sensing
Sensor technologies, including instrumentation, calibration, and validation
Processing techniques for remote sensing data analysis, including model inversion, machine learning, data classification, data mining, and big data analytics
Single and multi-sensor data integration and fusion
Multi- and hyper-spectral data analysis
Passive and active remote sensing applications
Applications in environmental and ecological studies, as well as aimed at better understanding the various processes occurring in the different compartments of the biosphere - agriculture, forest management, urban planning, natural hazards, climate change, etc.
Remote sensing for resource exploration
Geospatial data science and spatial modelling
Spaceborne remote sensing missions and services

For manuscripts focusing on applications, the remote sensing perspective should hold significance prominence. The journal particularly welcomes analyses based on long-term time series that combine data from in-situ measurements, remote sensing observations, and model simulations. Analyses based on multiple, independent monitoring systems will be particularly appreciated, allowing for robust and statistically verified results. Manuscripts on advanced mathematical methods (including machine learning methods) dedicated to the analysis of images and time series are also welcome.

Frontiers in Remote Sensing welcomes original research articles as well as reviews on topics of general interest, perspectives, and opinion pieces if they present new perspectives in the main area of interest of our journal.

Authors

Frontiers in Remote Sensing

Multi- and Hyper-Spectral Imaging