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Updated: Jun 17, 2025

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon
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Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

Published on: October 16, 2018

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在土壤异质性较高的地区降低土壤湿度:基于集体学习的解决方案,具有连续和并行学习者

Mandi Zheng1, Zhong Liu2, Jiahui Li2

  • 1College of Land Science and Technology, China Agricultural University, Beijing 100193, China; Key Laboratory of Arable Land Conservation in North China, Ministry of Agriculture and Rural Affairs, Beijing 100193, China; Institute of Agriculture Resources and Environment Sciences, Tianjin Academy of Agricultural Sciences, Tianjin 300100, China.

The Science of the total environment
|August 10, 2024
PubMed
概括

这项研究使用MODIS和海拔数据开发了增强的土壤湿度监测技术,为吉林省实现了可靠的1公里分辨率的土壤湿度产品. 渐变增强决策树模型在缩小土壤湿度数据方面表现出卓越的性能.

关键词:
缩小规模的缩小规模.组合学习学习 组合学习在SMAP中,我们可以使用SMAP.土壤水分 土壤水分三重配置分析三重配置分析

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