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Karst vegetation coverage detection using UAV multispectral vegetation indices and machine learning algorithm
Karst vegetation coverage detection using UAV multispectral vegetation indices and machine learning algorithm
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Karst vegetation coverage detection using UAV multispectral vegetation indices and machine learning algorithm

Pan, Wen ; Wang, Xiaoyu ; Sun, Yan ; Wang, Jia ; Li, Yanjie ; Li, Sheng

Plant methods, 2023-01, Vol.19 (1), p.7-7, Article 7 [Periódico revisado por pares]

England: BioMed Central Ltd

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2
An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation
An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation
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An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation

Fujimoto, Ayana ; Haga, Chihiro ; Matsui, Takanori ; Machimura, Takashi ; Hayashi, Kiichiro ; Sugita, Satoru ; Takagi, Hiroaki

Forests, 2019-08, Vol.10 (8), p.680 [Periódico revisado por pares]

Basel: MDPI AG

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3
Integration of Unmanned Aerial Vehicle Spectral and Textural Features for Accurate Above-Ground Biomass Estimation in Cotton
Integration of Unmanned Aerial Vehicle Spectral and Textural Features for Accurate Above-Ground Biomass Estimation in Cotton
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Integration of Unmanned Aerial Vehicle Spectral and Textural Features for Accurate Above-Ground Biomass Estimation in Cotton

Chen, Maoguang ; Yin, Caixia ; Lin, Tao ; Liu, Haijun ; Wang, Zhenyang ; Jiang, Pingan ; Ali, Saif ; Tang, Qiuxiang ; Jin, Xiuliang

Agronomy (Basel), 2024-06, Vol.14 (6), p.1313 [Periódico revisado por pares]

Basel: MDPI AG

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4
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data
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Modeling maize above-ground biomass based on machine learning approaches using UAV remote-sensing data

Han, Liang ; Yang, Guijun ; Dai, Huayang ; Xu, Bo ; Yang, Hao ; Feng, Haikuan ; Li, Zhenhai ; Yang, Xiaodong

Plant methods, 2019-02, Vol.15 (1), p.10-10, Article 10 [Periódico revisado por pares]

England: BioMed Central Ltd

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5
Wheat Yield Estimation Based on Unmanned Aerial Vehicle Multispectral Images and Texture Feature Indices
Wheat Yield Estimation Based on Unmanned Aerial Vehicle Multispectral Images and Texture Feature Indices
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Wheat Yield Estimation Based on Unmanned Aerial Vehicle Multispectral Images and Texture Feature Indices

Kang, Yiliang ; Wang, Yang ; Fan, Yanmin ; Wu, Hongqi ; Zhang, Yue ; Yuan, Binbin ; Li, Huijun ; Wang, Shuaishuai ; Li, Zhilin

Agriculture (Basel), 2024-01, Vol.14 (2), p.167 [Periódico revisado por pares]

Basel: MDPI AG

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6
Utilization of the Fusion of Ground-Space Remote Sensing Data for Canopy Nitrogen Content Inversion in Apple Orchards
Utilization of the Fusion of Ground-Space Remote Sensing Data for Canopy Nitrogen Content Inversion in Apple Orchards
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Utilization of the Fusion of Ground-Space Remote Sensing Data for Canopy Nitrogen Content Inversion in Apple Orchards

Zhang, Canting ; Zhu, Xicun ; Li, Meixuan ; Xue, Yuliang ; Qin, Anran ; Gao, Guining ; Wang, Mengxia ; Jiang, Yuanmao

Horticulturae, 2023-10, Vol.9 (10), p.1085 [Periódico revisado por pares]

Basel: MDPI AG

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7
Regional Monitoring of Leaf ChlorophyII Content of Summer Maize by Integrating Multi-Source Remote Sensing Data
Regional Monitoring of Leaf ChlorophyII Content of Summer Maize by Integrating Multi-Source Remote Sensing Data
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Regional Monitoring of Leaf ChlorophyII Content of Summer Maize by Integrating Multi-Source Remote Sensing Data

Tian, Hongwei ; Cheng, Lin ; Wu, Dongli ; Wei, Qingwei ; Zhu, Liming

Agronomy (Basel), 2023-08, Vol.13 (8), p.2040 [Periódico revisado por pares]

Basel: MDPI AG

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8
Estimation of Agronomic Characters of Wheat Based on Variable Selection and  Machine Learning Algorithms
Estimation of Agronomic Characters of Wheat Based on Variable Selection and  Machine Learning Algorithms
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Estimation of Agronomic Characters of Wheat Based on Variable Selection and  Machine Learning Algorithms

Wang, Dunliang ; Li, Rui ; Liu, Tao ; Sun, Chengming ; Guo, Wenshan

Agronomy (Basel), 2023-11, Vol.13 (11), p.2808 [Periódico revisado por pares]

Basel: MDPI AG

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9
Recognition of Plastic Film in Terrain-Fragmented Areas Based on Drone Visible Light Images
Recognition of Plastic Film in Terrain-Fragmented Areas Based on Drone Visible Light Images
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Recognition of Plastic Film in Terrain-Fragmented Areas Based on Drone Visible Light Images

Du, Xiaoyi ; Huang, Denghong ; Dai, Li ; Du, Xiandan

Agriculture (Basel), 2024-05, Vol.14 (5), p.736 [Periódico revisado por pares]

Basel: MDPI AG

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10
Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net
Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net
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Next-Generation Optical Sensing Technologies for Exploring Ocean Worlds - NASA FluidCam, MiDAR, and NeMO-Net

Chirayath, Ved ; Li, Alan

Frontiers in Marine Science, 2019-09, Vol.6 [Periódico revisado por pares]

Ames Research Center: Frontiers Media

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