Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method

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Journal of Geographic Information System

ISSN Print: 2151-1950
ISSN Online: 2151-1969

Website: https://www.scirp.org/journal/jgis/
E-mail: jgis@scirp.org

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Submission

"Review of Effective Vegetation Mapping Using the UAV (Unmanned Aerial Vehicle) Method"
written by Korehisa Kaneko, Seiich Nohara,
published by Journal of Geographic Information System, Vol.6 No.6, 2014

has been cited by the following article(s):

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[1]	Citation patterns of publications using unmanned aerial vehicles in ecology and conservation Journal of Unmanned Vehicle Systems, 2020 DOI:10.1139/juvs-2019-0013

[2]	Remotely sensed rivers in the Anthropocene: state of the art and prospects Earth Surface Processes and Landforms, 2020 DOI:10.1002/esp.4787

[3]	Supporting Urban Weed Biosecurity Programs with Remote Sensing Remote Sensing, 2020 DOI:10.3390/rs12122007

[4]	Methodology for optimizing quadrat size in sparse vegetation surveys: A desert case study from the Tarim Basin PLOS ONE, 2020 DOI:10.1371/journal.pone.0235469

[5]	An Integrated Object and Machine Learning Approach for Tree Canopy Extraction from UAV Datasets Journal of the Indian Society of Remote Sensing, 2020 DOI:10.1007/s12524-020-01240-2

[6]	A Novel Mosaic Method for UAV-Based Hyperspectral Images IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium, 2019 DOI:10.1109/IGARSS.2019.8900057

[7]	Using unmanned aerial vehicles for vegetation mapping and identification of botanical species in wetlands Landscape and Ecological Engineering, 2019 DOI:10.1007/s11355-018-00368-1

[8]	Vegetation monitoring via a novel push-broom-sensor-based hyperspectral device Journal of Physics: Conference Series, 2019 DOI:10.1088/1742-6596/1249/1/012007

[9]	Remote sensing of mangroves using unmanned aerial vehicles: current state and future directions Journal of Spatial Science, 2019 DOI:10.1080/14498596.2019.1627252

[10]	Using Airborne Hyperspectral Imaging Spectroscopy to Accurately Monitor Invasive and Expansive Herb Plants: Limitations and Requirements of the Method Sensors, 2019 DOI:10.3390/s19132871

[11]	Importance of machine learning for enhancing ecological studies using information-rich imagery Endangered Species Research, 2019 DOI:10.3354/esr00958

[12]	Geo-fencing Technique in Unmanned Aerial Vehicles for Post Disaster Management in the Internet of Things 2019 Second International Conference on Advanced Computational and Communication Paradigms (ICACCP), 2019 DOI:10.1109/ICACCP.2019.8882934

[13]	Monitoring the colonization of alluvial deposits using multitemporal UAV RGB ‐imagery Applied Vegetation Science, 2019 DOI:10.1111/avsc.12455

[14]	Coastal Dune Vegetation Mapping Using a Multispectral Sensor Mounted on an UAS Remote Sensing, 2019 DOI:10.3390/rs11151814

[15]	Evaluating the potential of multi-view data extraction from small Unmanned Aerial Systems (UASs) for object-based classification for Wetland land covers GIScience & Remote Sensing, 2018 DOI:10.1080/15481603.2018.1495395

[16]	Mapping grassland plant communities using a fuzzy approach to address floristic and spectral uncertainty Applied Vegetation Science, 2018 DOI:10.1111/avsc.12396

[17]	Coastal Dune Surveying Using a Low-Cost Remotely Piloted Aerial System (RPAS) Journal of Coastal Research, 2018 DOI:10.2112/JCOASTRES-D-17-00076.1

[18]	Estimation of fractional vegetation cover using mean-based spectral unmixing method 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 DOI:10.1109/IGARSS.2017.8127672

[19]	Optimizing the Timing of Unmanned Aerial Vehicle Image Acquisition for Applied Mapping of Woody Vegetation Species Using Feature Selection Remote Sensing, 2017 DOI:10.3390/rs9111130

[20]	MINI-UAV borne hyperspectral remote sensing: A review 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2017 DOI:10.1109/IGARSS.2017.8128354

[21]	A novel CMOS-compatible, monolithically integrated line-scan hyperspectral imager covering the VIS-NIR range Next-Generation Spectroscopic Technologies IX, 2016 DOI:10.1117/12.2230726

[22]	Overcoming the Challenges of Using Unmanned Aircraft for Bridge Inspections AIAA Atmospheric Flight Mechanics Conference, 2016 DOI:10.2514/6.2016-3396

[23]	The present state of coastal vegetation and microtopography at Ariakehama coast in the Seto Central Inland Sea using small unmanned aerial vehicle Journal of the Japanese Society of Revegetation Technology, 2016 DOI:10.7211/jjsrt.42.163

[24]	Quantitative Evaluation of Stereo Visual Odometry for Autonomous Vessel Localisation in Inland Waterway Sensing Applications Sensors, 2015 DOI:10.3390/s151229892

[25]	Automated Identification of River Hydromorphological Features Using UAV High Resolution Aerial Imagery Sensors, 2015 DOI:10.3390/s151127969

[26]	Investigation and analysis on current status of the tsunami-stricken coastal forest using high-resolution images prepared by unmanned aerial vehicle Journal of the Japanese Society of Revegetation Technology, 2015 DOI:10.7211/jjsrt.41.157