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A Global Land Cover Climatology Using MODIS Data
by
Broxton, Patrick D.
, Sulla-Menashe, Damien
, Zeng, Xubin
, Troch, Peter A.
in
Advanced Very High Resolution Radiometer
/ Algorithms
/ Classification
/ Classified information
/ Climate
/ Climate models
/ Climatic zones
/ Climatology
/ Datasets
/ Decision trees
/ Distribution
/ Hydrometeorology
/ Interannual variability
/ Land
/ Land cover
/ MODIS
/ Parameterization
/ Parametrization
/ Pixels
/ Radiometers
/ Satellites
/ Shrublands
/ Spectroradiometers
/ Vegetation
/ Weather
/ Weather forecasting
2014
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A Global Land Cover Climatology Using MODIS Data
by
Broxton, Patrick D.
, Sulla-Menashe, Damien
, Zeng, Xubin
, Troch, Peter A.
in
Advanced Very High Resolution Radiometer
/ Algorithms
/ Classification
/ Classified information
/ Climate
/ Climate models
/ Climatic zones
/ Climatology
/ Datasets
/ Decision trees
/ Distribution
/ Hydrometeorology
/ Interannual variability
/ Land
/ Land cover
/ MODIS
/ Parameterization
/ Parametrization
/ Pixels
/ Radiometers
/ Satellites
/ Shrublands
/ Spectroradiometers
/ Vegetation
/ Weather
/ Weather forecasting
2014
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Do you wish to request the book?
A Global Land Cover Climatology Using MODIS Data
by
Broxton, Patrick D.
, Sulla-Menashe, Damien
, Zeng, Xubin
, Troch, Peter A.
in
Advanced Very High Resolution Radiometer
/ Algorithms
/ Classification
/ Classified information
/ Climate
/ Climate models
/ Climatic zones
/ Climatology
/ Datasets
/ Decision trees
/ Distribution
/ Hydrometeorology
/ Interannual variability
/ Land
/ Land cover
/ MODIS
/ Parameterization
/ Parametrization
/ Pixels
/ Radiometers
/ Satellites
/ Shrublands
/ Spectroradiometers
/ Vegetation
/ Weather
/ Weather forecasting
2014
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Journal Article
A Global Land Cover Climatology Using MODIS Data
2014
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Overview
Global land cover data are widely used in weather, climate, and hydrometeorological models. The Collection 5.1 Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Type (MCD12Q1) product is found to have a substantial amount of interannual variability, with 40% of land pixels showing land cover change one or more times during 2001–10. This affects the global distribution of vegetation if any one year or many years of data are used, for example, to parameterize land processes in regional and global models. In this paper, a value-added global 0.5-km land cover climatology (a single representative map for 2001–10) is developed by weighting each land cover type by its corresponding confidence score for each year and using the highest-weighted land cover type in each pixel in the 2001–10 MODIS data. The climatology is validated by comparing it with the System for Terrestrial Ecosystem Parameterization database as well as additional pixels that are identified from the Google Earth proprietary software database. When compared with the data of any individual year, this climatology does not substantially alter the overall global frequencies of most land cover classes but does affect the global distribution of many land cover classes. In addition, it is validated as well as or better than the MODIS data for individual years. Also, it is based on higher-quality data and is validated better than the Global Land Cover Characteristics database, which is based on 1 year of Advanced Very High Resolution Radiometer data and represents a widely used first-generation global product.
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