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Supplementary material to quot;Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approachquot;

机译：“改善地上生物量地下森林的非代表性样品预测”的补充材料：组合机器学习和空间统计方法“

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Shaoqing Dai; Xiaoman Zheng; Lei Gao; Shudi Zuo; Qi Chen; Xiaohua Wei; Yin Ren;
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1. Spatial Upscaling of Aboveground Biomass Estimation using National Forest Inventory Data and Forest Type Map [J] . Eun-Sook Kim, Kyoung-Min Kim, Jung-Bin Lee, Journal of Korean Forest Society . 2011,第3期

机译：利用国家森林清单数据和森林类型图估算地上生物量的空间放大
2. Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms [J] . Elhadi Adam, Onisimo Mutanga, Riyad Ismail, Sensors . 2014,第8期

机译：人工林内物种间生物量预测：测试高空间分辨率星载多光谱RapidEye传感器和先进的机器学习算法的实用性
3. Improving aboveground biomass maps of tropical dry forests by integrating LiDAR, ALOS PALSAR, climate and field data [J] . J. Luis Hernández-Stefanoni, Miguel ángel Castillo-Santiago, Jean Francois Mas, Carbon balance and management . 2020,第1期

机译：通过整合LIDAR，Alos Palsar，Climate和现场数据，改善热带干燥林的地下生物量地图
4. ESTIMATION OF REGIONAL FOREST ABOVEGROUND BIOMASS COMBINING ICESAT-GLAS WAVEFORMS AND HJ-1A/HSI HYPERSPECTRAL IMAGERIES [C] . Yanqiu Xing, Sai Qiu, Jianhua Ding, ISPRS Congress . 2016

机译：地下生物量的估计ICESAT-GLAS波形和HJ-1A / HSI高光谱仪的估计
5. Application of Machine Learning and Statistical Learning Methods for Prediction In A Large-Scale Vegetation Map [D] . Brookey, Carla M. 2018

机译：机器学习和统计学习方法在大型植被图预测中的应用
6. Intra-and-Inter Species Biomass Prediction in a Plantation Forest: Testing the Utility of High Spatial Resolution Spaceborne Multispectral RapidEye Sensor and Advanced Machine Learning Algorithms [O] . Timothy Dube, Onisimo Mutanga, Elhadi Adam, 2014

机译：人工林内物种间生物量预测：测试高空间分辨率星载多光谱RapidEye传感器和先进的机器学习算法的实用性
7. Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approach [O] . Shaoqing Dai, Xiaoman Zheng, Lei Gao, 2019

机译：改善森林的非代表性样本预测地上生物量地图：组合机学习和空间统计方法

Supplementary material to quot;Improving non-representative-sample prediction of forest aboveground biomass maps: A combined machine learning and spatial statistical approachquot;

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