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Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating

机译：组合多源远程感测数据和基于过程的森林地上生物量更新的模型

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Xiaoman Lu; Guang Zheng; Colton Miller; Ernesto Alvarado;
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年度 2017
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1. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating [J] . Xiaoman Lu, Guang Zheng, Colton Miller, Sensors . 2017,第9期

机译：结合多源遥感数据和基于过程的森林地上生物量更新模型
2. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating [J] . Xiaoman Lu, Guang Zheng, Colton Miller, Sensors . 2017,第9期

机译：结合多源遥感数据和基于过程的森林地上生物量更新模型
3. Integration of multi-resource remotely sensed data and allometric models for forest aboveground biomass estimation in China [J] . Huang Huabing, Liu Caixia, Wang Xiaoyi, Remote Sensing of Environment: An Interdisciplinary Journal . 2019,第期

机译：中国多资源远程感测数据与森林地上地上生物量估计的数值模型集成
4. Assessing remotely-sensed aboveground biomass estimates in the Sierra National Forest [C] . Chopping Mark, Duchesne Rocio, North Malcolm IEEE International Geoscience and Remote Sensing Symposium . 2014

机译：评估塞拉利昂国家森林中的遥感地上生物量估计
5. Modelling Forest Inventory and Biophysical Variables for an Uneven-Aged Forest Using Multi-Source Remotely-Sensed Data [D] . Shang, Chen. 2018

机译：使用多源遥感数据对高龄不等森林的森林清单和生物物理变量进行建模
6. Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating [O] . Xiaoman Lu, Guang Zheng, Colton Miller, 2017

机译：结合多源遥感数据与基于过程的森林地上生物量更新模型
7. Assessment of Forest Aboveground Biomass Stocks and Dynamics with Inventory Data, Remotely Sensed Imagery and Geostatistics [O] . Viana Helder 2011

机译：利用清单数据，遥感影像和地统计学评估森林地上生物量和动态
8. Quantifying Forest Aboveground Carbon Pools and Fluxes Using Multi-Temporal Lidar a Report on Field Monitoring, Remote Sensing MMV, GIS Integration, and Modeling Results for Forestry Field Validation Test to Quantify Aboveground Tree Biomass and Carbon. [R] . Spangler, L., Vierling, L. A., Stand, E. K., 2011

机译：使用多时间激光雷达量化森林地上碳库和通量报告现场监测，遥感mmV，GIs集成和林业领域验证测试模型结果，以量化地上树木生物量和碳。

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating

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