Tree's detection & health's assessment from ultra-high resolution UAV imagery and deep learning-Reference-Cited by-同舟云学术

Tree's detection & health's assessment from ultra-high resolution UAV imagery and deep learning

Published:2022-03-12 Issue:25 Volume:37 Page:10459-10479
ISSN:1010-6049
Container-title:Geocarto International
language:en
Short-container-title:Geocarto International

Author:

Șandric Ionuț¹^ORCID,Irimia Radu¹^ORCID,Petropoulos George P.²^ORCID,Anand Akash³,Srivastava Prashant K.³^ORCID,Pleșoianu Alin⁴,Faraslis Ioannis⁵,Stateras Dimitrios⁶,Kalivas Dionissios

Affiliation:

1. Faculty of Geography, University of Bucharest, Bucharest, Romania

2. Department of Geography, Harokopio University of Athens, Athens, Greece

3. Prashant K. Srivastava Institute of Environment and Sustainable Development, Banaras Hindu University, Varanasi, India

4. Professional services, ESRI Romania, Bucharest, Romania

5. Department of Environmental Sciences, School of Technology, University of Thessaly, Larisa, Greece

6. Department of Land Resources and Agricultural Engineering, Agricultural University of Athens, Greece

Publisher

Informa UK Limited

Subject

Water Science and Technology,Geography, Planning and Development

Link

https://www.tandfonline.com/doi/pdf/10.1080/10106049.2022.2036824

Reference54 articles.

1. UAV-Based Photogrammetry and Integrated Technologies for Architectural Applications—Methodological Strategies for the After-Quake Survey of Vertical Structures in Mantua (Italy)

2. Use of Hyperion for Mangrove Forest Carbon Stock Assessment in Bhitarkanika Forest Reserve: A Contribution Towards Blue Carbon Initiative

3. A review of vegetation indices

4. Immediate Changes in Organic Matter and Plant Available Nutrients of Haplic Luvisol Soils Following Different Experimental Burning Intensities in Damak Forest, Hungary

5. Mapping heat and traffic stress of urban park vegetation based on satellite imagery - A comparison of Bucharest, Romania and Leipzig, Germany

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