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

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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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).”

Southwest Forestry UniversityKunmingPeople’s Republic of ChinaAsiaAlgorithmsCyborgsEmerging TechnologiesMa chine LearningRemote Sensing

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(MAY.1)