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Keyword: change detection

Field attributes and satellite data for "How vegetation recovery and fuel conditions in past fires influences fuels and future fire management in five western U.S. ecosystems" (1st Edition)

Datasets Posted on: December 30, 2020
This data publication contains field and satellite observations at 1567 plots across wildfire extents that burned between the years 2000-2007, collected for Joint Fire Science Project ID: 14-1-02-27. Field attributes were measured between the years 2013-2016 and include a suite of vegetation, soil, and surface cover characteristics.

Field attributes and satellite data for "How vegetation recovery and fuel conditions in past fires influences fuels and future fire management in five western U.S. ecosystems" (2nd Edition)

Datasets Posted on: December 30, 2020
This data publication contains field and satellite observations at 1567 plots across wildfire extents that burned between the years 2000-2007, collected for Joint Fire Science Project ID: 14-1-02-27. Field attributes were measured between the years 2013-2016 and include a suite of vegetation, soil, and surface cover characteristics.

Continuous monitoring of land disturbance based on Landsat time series

Publications Posted on: August 17, 2020
We developed a new algorithm for COntinuous monitoring of Land Disturbance (COLD) using Landsat time series. COLD can detect many kinds of land disturbance continuously as new images are collected and provide historical land disturbance maps retrospectively. To better detect land disturbance, we tested different kinds of input data and explored many time series analysis techniques. We have several major observations as follows.

Locating forest management units using remote sensing and geostatistical tools in North-Central Washington, USA

Publications Posted on: June 22, 2020
In this study, we share an approach to locate and map forest management units with high accuracy and with relatively rapid turnaround. Our study area consists of private, state, and federal land holdings that cover four counties in North-Central Washington, USA (Kittitas, Okanogan, Chelan and Douglas).

Northwest Forest Plan—the first 10 years (1994-2003): status and trend of late-successional and old-growth forest.

Publications Posted on: June 22, 2020
We monitored the status and trend of late-successional and old-growth forest (older forest) on 24 million ac of land managed by the Forest Service, Bureau of Land Management, and National Park Service in the Northwest Forest Plan (the Plan) area between 1994 and 2003. We developed baseline maps from satellite imagery of older forest conditions at the start of the Plan.

Unmanned aerial vehicle-based rangeland monitoring: Examining a century of vegetation changes

Publications Posted on: September 10, 2019
Rangelands comprise a large component of the terrestrial land surface and provide critical ecosystem services, but they are degrading rapidly. Long-term rangeland monitoring with detailed, nonsubjective, quantitative observations can be expensive and difficult to maintain over time. Unmanned aerial vehicles (UAVs) provide an alternative means to gather unbiased and consistent datasets with similar details to field-based monitoring data.

Implementation of the LandTrendr algorithm on Google Earth Engine

Publications Posted on: July 06, 2018
The LandTrendr (LT) algorithm has been used widely for analysis of change in Landsat spectral time series data, but requires significant pre-processing, data management, and computational resources, and is only accessible to the community in a proprietary programming language (IDL). Here, we introduce LT for the Google Earth Engine (GEE) platform.

Mapping forest change using stacked generalization: An ensemble approach

Publications Posted on: July 06, 2018
The ever-increasing volume and accessibility of remote sensing data has spawned many alternative approaches for mapping important environmental features and processes. For example, there are several viable but highly varied strategies for using time series of Landsat imagery to detect changes in forest cover.

Mean composite fire severity metrics computed with Google Earth engine offer improved accuracy and expanded mapping potential

Publications Posted on: June 12, 2018
Landsat-based fire severity datasets are an invaluable resource for monitoring and research purposes. These gridded fire severity datasets are generally produced with pre- and post-fire imagery to estimate the degree of fire-induced ecological change.

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.

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