An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data
Published 2014 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
An Automated Approach to Map the History of Forest Disturbance from Insect Mortality and Harvest with Landsat Time-Series Data
Authors
Keywords
-
Journal
Remote Sensing
Volume 6, Issue 4, Pages 2782-2808
Publisher
MDPI AG
Online
2014-03-26
DOI
10.3390/rs6042782
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Conterminous U.S. and Alaska Forest Type Mapping Using Forest Inventory and Analysis Data
- (2013) B. Ruefenacht et al. PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING
- Estimating carbon emissions from forest degradation: implications of uncertainties and area sizes for a REDD+ MRV system
- (2012) Daniel Plugge et al. CANADIAN JOURNAL OF FOREST RESEARCH
- Managing production forests for timber production and carbon emission reductions under the REDD+ scheme
- (2012) Nophea Sasaki et al. ENVIRONMENTAL SCIENCE & POLICY
- Global characterization and monitoring of forest cover using Landsat data: opportunities and challenges
- (2012) John R. Townshend et al. International Journal of Digital Earth
- Detecting post-fire salvage logging from Landsat change maps and national fire survey data
- (2012) Todd A. Schroeder et al. REMOTE SENSING OF ENVIRONMENT
- Repeated insect outbreaks promote multi-cohort aspen mixedwood forests in northern Minnesota, USA
- (2011) Michael Reinikainen et al. FOREST ECOLOGY AND MANAGEMENT
- Snow-covered Landsat time series stacks improve automated disturbance mapping accuracy in forested landscapes
- (2011) Kirk M. Stueve et al. REMOTE SENSING OF ENVIRONMENT
- Mapping wildfire and clearcut harvest disturbances in boreal forests with Landsat time series data
- (2011) Todd A. Schroeder et al. REMOTE SENSING OF ENVIRONMENT
- A Large and Persistent Carbon Sink in the World's Forests
- (2011) Y. Pan et al. SCIENCE
- An inventory-based analysis of Canada's managed forest carbon dynamics, 1990 to 2008
- (2010) G. STINSON et al. GLOBAL CHANGE BIOLOGY
- Estimating the reduction in gross primary production due to mountain pine beetle infestation using satellite observations
- (2010) Nicholas C. Coops et al. INTERNATIONAL JOURNAL OF REMOTE SENSING
- Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches
- (2010) Scott L. Powell et al. REMOTE SENSING OF ENVIRONMENT
- Estimating burn severity from Landsat dNBR and RdNBR indices across western Canada
- (2010) Nicholas O. Soverel et al. REMOTE SENSING OF ENVIRONMENT
- Monitoring the impacts of mountain pine beetle mitigation
- (2009) Michael A. Wulder et al. FOREST ECOLOGY AND MANAGEMENT
- Sampling designs for accuracy assessment of land cover
- (2009) Stephen V. Stehman INTERNATIONAL JOURNAL OF REMOTE SENSING
- Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations
- (2009) Bruce D. Cook et al. REMOTE SENSING OF ENVIRONMENT
- Estimating accuracy of land-cover composition from two-stage cluster sampling
- (2009) Stephen V. Stehman et al. REMOTE SENSING OF ENVIRONMENT
- Calibration and validation of the relative differenced Normalized Burn Ratio (RdNBR) to three measures of fire severity in the Sierra Nevada and Klamath Mountains, California, USA
- (2009) Jay D. Miller et al. REMOTE SENSING OF ENVIRONMENT
- Comparison of two types of forest disturbance using multitemporal Landsat TM/ETM+ imagery and field vegetation data
- (2009) Martin Hais et al. REMOTE SENSING OF ENVIRONMENT
- A new data fusion model for high spatial- and temporal-resolution mapping of forest disturbance based on Landsat and MODIS
- (2009) Thomas Hilker et al. REMOTE SENSING OF ENVIRONMENT
- An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks
- (2009) Chengquan Huang et al. REMOTE SENSING OF ENVIRONMENT
- Surface temperature change of spruce forest as a result of bark beetle attack: remote sensing and GIS approach
- (2008) Martin Hais et al. EUROPEAN JOURNAL OF FOREST RESEARCH
- The effect of spatial autocorrelation and class proportion on the accuracy measures from different sampling designs
- (2008) DongMei Chen et al. ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
- Spatial-Temporal Modeling of Forest Gaps Generated by Colonization From Below- and Above-Ground Bark Beetle Species
- (2008) Jun Zhu et al. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
- Mountain pine beetle and forest carbon feedback to climate change
- (2008) W. A. Kurz et al. NATURE
- Using multitemporal Landsat TM imagery to establish land use pressure induced trends in forest and woodland cover in sections of the Soutpansberg Mountains of Venda region, Limpopo Province, South Africa
- (2008) Christopher Munyati et al. Regional Environmental Change
- North American forest disturbance mapped from a decadal Landsat record
- (2008) Jeffrey G. Masek et al. REMOTE SENSING OF ENVIRONMENT
- Estimation of insect infestation dynamics using a temporal sequence of Landsat data
- (2008) Nicholas R. Goodwin et al. REMOTE SENSING OF ENVIRONMENT
- Effects of atmospheric variation on AVHRR NDVI data
- (2008) Jyoteshwar R. Nagol et al. REMOTE SENSING OF ENVIRONMENT
- Causes of interannual variability in ecosystem–atmosphere CO2 exchange in a northern Wisconsin forest using a Bayesian model calibration
- (2007) Daniel M. Ricciuto et al. AGRICULTURAL AND FOREST METEOROLOGY
- North American vegetation dynamics observed with multi-resolution satellite data
- (2007) C NEIGH et al. REMOTE SENSING OF ENVIRONMENT
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started