Understanding long-term changes in urban-rural forest communities using Landsat trajectories and hemispherical photography

Authors: Mitchell T. Bonney*, University of Toronto - Mississauga, Yuhong He, University of Toronto - Mississauga
Topics: Remote Sensing, Land Use and Land Cover Change, Physical Geography
Keywords: Landsat, time-series, hemispherical photography, forest, urban-rural, remote sensing, disturbance
Session Type: Paper
Day: 4/7/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Buchanan, Marriott, Mezzanine Level
Presentation File: No File Uploaded


Temperate forest communities, especially those on the edge of major population centers, have undergone dramatic changes since the mid-1900s. This is due to various natural and anthropogenic drivers, including human development, insect disturbance and storm damage. Vegetation indices (VIs) derived from Landsat satellite data, along with appropriate ground validation, have the ability to quantify these changes over time and space. Our research utilizes Landsat data (1972-2018), along with in situ hemispherical photography and forest inventory information, to monitor forest growth and decline across the Credit Valley Watershed. This area is a complex urban-rural landscape in southern Ontario, west of Toronto, Canada. Landsat trajectory algorithms (e.g. LandTrendR and LandsatLinkR) aid in the calculation of VI trajectories and the extension of the time-series to 1972. Relationships between VI values and in situ variables (e.g., leaf area index, canopy cover, basal area) collected in the same year provide ground validation for these remote sensing changes. Results indicate that forests have undergone numerous short-term stages of growth and decline in response to different drivers, and that these trajectories vary spatially across the study area and in terms of forest community type. This study is significant for the Landsat remote sensing community in terms of relating VI trajectories to drivers across an urban-rural landscape and in the use of ground validation across many forest communities and contexts. In addition, forest managers in southern Ontario will be using these results to monitor their local forests and adopt appropriate management policies.

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