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A LandTrendr multispectral ensemble for forest disturbance detection

Remote sensing of environment, 2018-02, Vol.205, p.131-140

2018

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Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data

Remote sensing (Basel, Switzerland), 2018-11, Vol.10 (11), p.1832

2018

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How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?

Forests, 2017-03, Vol.8 (4), p.98

2017

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Long-term forest health implications of roadlessness

Environmental research letters, 2020-10, Vol.15 (10), p.104023

Healey, Sean P

2020

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Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation

Remote sensing (Basel, Switzerland), 2020-09, Vol.12 (17), p.2840

2020

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Benefits of the free and open Landsat data policy

Remote sensing of environment, 2019-04, Vol.224, p.382-385

2019

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GEDI launches a new era of biomass inference from space

Environmental research letters, 2022-09, Vol.17 (9), p.95001

2022

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Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program

Remote sensing of environment, 2020-03, Vol.238, p.111261, Article 111261

2020

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Timeliness in forest change monitoring: A new assessment framework demonstrated using Sentinel-1 and a continuous change detection algorithm

Remote sensing of environment, 2022-07, Vol.276, p.113043, Article 113043

2022

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Implementation of the LandTrendr Algorithm on Google Earth Engine

Remote sensing (Basel, Switzerland), 2018-05, Vol.10 (5), p.691

2018

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The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography

Science of Remote Sensing, 2020-06, Vol.1, p.100002, Article 100002

2020

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Bringing an ecological view of change to Landsat-based remote sensing

Frontiers in ecology and the environment, 2014-08, Vol.12 (6), p.339-346

2014

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Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance

Remote sensing (Basel, Switzerland), 2020-05, Vol.12 (10), p.1673

2020

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Mapping forest change using stacked generalization: An ensemble approach

Remote sensing of environment, 2018-01, Vol.204, p.717-728

2018

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Statistical properties of hybrid estimators proposed for GEDI-NASA's global ecosystem dynamics investigation

Environmental research letters, 2019-06, Vol.14 (6), p.65007

2019

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The role of remote sensing in process-scaling studies of managed forest ecosystems

Forest ecology and management, 2015-11, Vol.355, p.109-123

2015

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Vicarious calibration of GEDI biomass with Landsat age data for understanding secondary forest carbon dynamics

Environmental research letters, 2024-04, Vol.19 (4), p.44062

2024

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

Remote sensing of environment, 2011-06, Vol.115 (6), p.1421-1433

2011

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A global time series dataset to facilitate forest greenhouse gas reporting

Environmental research letters, 2023-08, Vol.18 (8), p.84001

2023

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The national forest inventory in China： history- results -international context

Forest ecosystems, 2015-08, Vol.2 (4), p.288-303, Article 23

2015

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Use of models in large-area forest surveys： comparing model-assisted, model-based and hybrid estimation

Forest ecosystems, 2016-02, Vol.3 (2), p.153-163, Article 5

2016

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Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Remote sensing of environment, 2010-05, Vol.114 (5), p.1053-1068

2010

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A Comprehensive Forest Biomass Dataset for the USA Allows Customized Validation of Remotely Sensed Biomass Estimates

Remote sensing (Basel, Switzerland), 2020-12, Vol.12 (24), p.4141

2020

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Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay’s national forest inventory

Environmental research letters, 2023-08, Vol.18 (8), p.85001

2023

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Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection

Remote sensing of environment, 2005-08, Vol.97 (3), p.301-310

2005

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A LandTrendr multispectral ensemble for forest disturbance detection

Generalized Hierarchical Model-Based Estimation for Aboveground Biomass Assessment Using GEDI and Landsat Data

How Similar Are Forest Disturbance Maps Derived from Different Landsat Time Series Algorithms?

Long-term forest health implications of roadlessness

Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation

Benefits of the free and open Landsat data policy

GEDI launches a new era of biomass inference from space

Quality control and assessment of interpreter consistency of annual land cover reference data in an operational national monitoring program

Timeliness in forest change monitoring: A new assessment framework demonstrated using Sentinel-1 and a continuous change detection algorithm

Implementation of the LandTrendr Algorithm on Google Earth Engine

The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography

Bringing an ecological view of change to Landsat-based remote sensing

Diversity of Algorithm and Spectral Band Inputs Improves Landsat Monitoring of Forest Disturbance

Mapping forest change using stacked generalization: An ensemble approach

Statistical properties of hybrid estimators proposed for GEDI-NASA's global ecosystem dynamics investigation

The role of remote sensing in process-scaling studies of managed forest ecosystems

Vicarious calibration of GEDI biomass with Landsat age data for understanding secondary forest carbon dynamics

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

A global time series dataset to facilitate forest greenhouse gas reporting

The national forest inventory in China： history- results -international context

Use of models in large-area forest surveys： comparing model-assisted, model-based and hybrid estimation

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

A Comprehensive Forest Biomass Dataset for the USA Allows Customized Validation of Remotely Sensed Biomass Estimates

Estimating aboveground biomass density using hybrid statistical inference with GEDI lidar data and Paraguay’s national forest inventory

Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection

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