Robotics & Machine Learning Daily News2024,Issue(MAY.1) :90-91.

Studies from Southwest Forestry University Further Understanding of Machine Lear ning (Remote Sensing Estimation of Forest Carbon Stock Based on Machine Learning Algorithms)

Robotics & Machine Learning Daily News2024,Issue(MAY.1) :90-91.

Studies from Southwest Forestry University Further Understanding of Machine Lear ning (Remote Sensing Estimation of Forest Carbon Stock Based on Machine Learning Algorithms)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Data detailed on artificial intelligence have bee n presented. According to news reporting fromKunming, People’s Republic of Chin a, by NewsRx journalists, research stated, “Improving the precision ofremote se nsing estimation and implementing the fusion and analysis of multi-source data a re crucial foraccurately estimating the aboveground carbon storage in forests. Using the Google Earth Engine (GEE)platform in conjunction with national forest resource inventory data and Landsat 8 multispectral remotesensing imagery, thi s research applies four machine learning algorithms available on the GEE platfor m:Random Forest (RF), Classification and Regression Trees (CART), Gradient Boos ting Trees (GBT), andSupport Vector Machine (SVM).”

Key words

Southwest Forestry University/Kunming/People’s Republic of China/Asia/Algorithms/Cyborgs/Emerging Technologies/Ma chine Learning/Remote Sensing

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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