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      Improving Accuracy Estimation of Forest Aboveground Biomass Based on Incorporation of ALOS-2 PALSAR-2 and Sentinel-2A Imagery and Machine Learning: A Case Study of the Hyrcanian Forest Area (Iran)

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      Remote Sensing

      MDPI AG

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          High-resolution global maps of 21st-century forest cover change.

          Quantification of global forest change has been lacking despite the recognized importance of forest ecosystem services. In this study, Earth observation satellite data were used to map global forest loss (2.3 million square kilometers) and gain (0.8 million square kilometers) from 2000 to 2012 at a spatial resolution of 30 meters. The tropics were the only climate domain to exhibit a trend, with forest loss increasing by 2101 square kilometers per year. Brazil's well-documented reduction in deforestation was offset by increasing forest loss in Indonesia, Malaysia, Paraguay, Bolivia, Zambia, Angola, and elsewhere. Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally. Boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms. These results depict a globally consistent and locally relevant record of forest change.
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            Red and photographic infrared linear combinations for monitoring vegetation

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              The WEKA data mining software

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                Author and article information

                Journal
                Remote Sensing
                Remote Sensing
                MDPI AG
                2072-4292
                February 2018
                January 25 2018
                : 10
                : 2
                : 172
                Article
                10.3390/rs10020172
                © 2018
                Product
                Self URI (article page): http://www.mdpi.com/2072-4292/10/2/172

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