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Keyword: Landsat time series

A LandTrendr multispectral ensemble for forest disturbance detection

Publications Posted on: July 06, 2018
Monitoring and classifying forest disturbance using Landsat time series has improved greatly over the past decade, with many new algorithms taking advantage of the high-quality, cost free data in the archive.

How similar are forest disturbance maps derived from different Landsat time series algorithms?

Publications Posted on: September 27, 2017
Disturbance is a critical ecological process in forested systems, and disturbance maps are important for understanding forest dynamics. Landsat data are a key remote sensing dataset for monitoring forest disturbance and there recently has been major growth in the development of disturbance mapping algorithms.

Testing a Landsat-based approach for mapping disturbance causality in U.S. forests

Publications Posted on: August 21, 2017
In light of Earth's changing climate and growing human population, there is an urgent need to improve monitoring of natural and anthropogenic disturbanceswhich effect forests' ability to sequester carbon and provide other ecosystem services.

Shape selection in Landsat time series

Media Gallery Posted on: September 15, 2016
The tree canopy patterns in these time series Landsat map images, taken over a section of the central Rocky Mountains near Steamboat Springs, Colorado, provide information about canopy lost to disturbance events.

Shape selection in Landsat time series

Science Spotlights Posted on: September 01, 2016
There is new methodology for fitting ecologically feasible “shapes” to time series of Landsat imagery for modeling, mapping, and monitoring annual forest disturbance dynamics. Through a case study of fire, harvest and bark beetle outbreak, scientists illustrate how resultant fitted values and parameters can be fed into empirical models to map disturbance causal agent and tree canopy cover changes coincident with disturbance events through time.

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S

Publications Posted on: March 19, 2015
With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these plots are visited repeatedly through time there are large temporal gaps (e.g.

Improving estimates of forest disturbance by combining observations from Landsat time series with U.S. Forest Service Forest Inventory and Analysis data

Publications Posted on: September 12, 2014
With earth's surface temperature and human population both on the rise a new emphasis has been placed on monitoring changes to forested ecosystems the world over. In the United States the U.S. Forest Service Forest Inventory and Analysis (FIA) program monitors the forested land base with field data collected over a permanent network of sample plots. Although these plots are visited repeatedly through time there are large temporal gaps (e.g.

Detecting post-fire salvage logging with Landsat change maps and national fire survey data

Publications Posted on: October 29, 2012
In Canadian boreal forests, wildfire is the predominant agent of natural disturbance often with millions of hectares burning annually. In addition to fire, nearly one quarter of Canada's boreal forest is also managed for industrial wood production.

Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data

Publications Posted on: September 12, 2011
Information regarding the extent, timing andmagnitude of forest disturbance are key inputs required for accurate estimation of the terrestrial carbon balance. Equally important for studying carbon dynamics is the ability to distinguish the cause or type of forest disturbance occurring on the landscape.