First post - welcome
Oct 3, 2025
Hello! My name is Rachel, and I’m a postdoctoral researcher working at the intersection of remote sensing and ecology. My academic upbringing spans geography and biology, with a bit of environmental policy. My research has focused on understanding forest change using structural and spectral data from remote ensing time series. I’m particularly interested in the drivers, patterns, and impacts of forest dynamics, and how we can better monitor these processes in the the context of a changing climate.
This blog is a space where I’ll share research updates, reflections on ecological research, and practical tips for ecological modelling and working with remote sensing data. You can expect summaries of papers and reviews of books that I’m reading, notes from conferences and from the field, insights from my research projects, and (hopefully!) some short tutorials based on my teaching. I hope to make this a useful and accessible resource both for students who are new to ecology, ecological modelling and remote senisng, and for my fellow researchers.
So, what exactly is remote sensing and why is it an important tool in ecological research?
At its core, remote sensing is the science of collecting information about a surface or objects on a surface from a distance. Instead of collecting information in situ, remote sensing uses sensors on a platform (e.g., satellites, aircraft, uncrewed aerial vehicles (UAVs), handheld) to collect information from a distance. Spectral sensors capture reflected light across many wavelengths, often beyond what is visible with the naked eye, allowing us to detect differences in vegetation health. Sensors like lidar (light detection and ranging) capture structural information, revealing the three-dimensional shape of trees and forests. By collecting these data repeatedly over time, remote sensing time series allow us monitor forest change and track trends like growth.
Remote sensing has become a critical tool in ecology because it allows us to scale up from individual trees to entire landscapes, and to do so repeatedly over time. This means we can monitor ecological processes like forest growth across large areas and long timeframes in ways that ground-based measurements alone can’t capture. An additional strength of remote sensing is its ability to be integrated with other ecological data, such as dendrometer measurements, which enables us link the signals observable in remote sensing data to the underlying processes driving them. In an era of rapid change, this integration enables us not only to detect and map patterns of change, but to understand causes and anticipate consequences.