Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites

Photogrammetric point clouds (PPCs) provide a source of three-dimensional (3-D) remote sensing data that is well-suited to use over small areas that are within the scope of observation by unmanned aerial vehicles (UAVs). We compared PPC-based structural metrics to traditional ground surveys conducte...
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Autor*in:	Jennifer N. Hird [verfasserIn] Alessandro Montaghi [verfasserIn] Gregory J. McDermid [verfasserIn] Jahan Kariyeva [verfasserIn] Brian J. Moorman [verfasserIn] Scott E. Nielsen [verfasserIn] Anne C. S. McIntosh [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	unmanned aerial vehicles photogrammetry point clouds vegetation structure vegetation height vegetation cover ecological recovery reclamation

Übergeordnetes Werk:	In: Remote Sensing - MDPI AG, 2009, 9(2017), 5, p 413
Übergeordnetes Werk:	volume:9 ; year:2017 ; number:5, p 413

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/rs9050413

Katalog-ID:	DOAJ018582753

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allfieldsSound	10.3390/rs9050413 doi (DE-627)DOAJ018582753 (DE-599)DOAJf47633eb836b4dfa85b4128e5ef0bed9 DE-627 ger DE-627 rakwb eng Jennifer N. Hird verfasserin aut Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Photogrammetric point clouds (PPCs) provide a source of three-dimensional (3-D) remote sensing data that is well-suited to use over small areas that are within the scope of observation by unmanned aerial vehicles (UAVs). We compared PPC-based structural metrics to traditional ground surveys conducted by field personnel in order to assess the capacity of PPC data to contribute to vegetation-reclamation surveys. We found good statistical agreement between key structural vegetation parameters, such as mean and maximum vegetation height, with PPC metrics successfully predicting most height and tree-diameter metrics using multivariate linear regression. However, PPC metrics were not as useful for estimating ground-measured vegetation cover. We believe that part of the issue lies in the mismatch between PPC- and ground-based measurement approaches, including subjective judgement on behalf of ground crews: a topic that requires more investigation. Our work highlights the emerging value of UAV-based PPCs to complement, and in some cases supplement, traditional ground-based sources of measured vegetation structure. unmanned aerial vehicles photogrammetry point clouds vegetation structure vegetation height vegetation cover ecological recovery reclamation Science Q Alessandro Montaghi verfasserin aut Gregory J. McDermid verfasserin aut Jahan Kariyeva verfasserin aut Brian J. Moorman verfasserin aut Scott E. Nielsen verfasserin aut Anne C. S. McIntosh verfasserin aut In Remote Sensing MDPI AG, 2009 9(2017), 5, p 413 (DE-627)608937916 (DE-600)2513863-7 20724292 nnns volume:9 year:2017 number:5, p 413 https://doi.org/10.3390/rs9050413 kostenfrei https://doaj.org/article/f47633eb836b4dfa85b4128e5ef0bed9 kostenfrei http://www.mdpi.com/2072-4292/9/5/413 kostenfrei https://doaj.org/toc/2072-4292 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2108 GBV_ILN_2111 GBV_ILN_2119 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4392 GBV_ILN_4700 AR 9 2017 5, p 413
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author	Jennifer N. Hird
spellingShingle	Jennifer N. Hird misc unmanned aerial vehicles misc photogrammetry misc point clouds misc vegetation structure misc vegetation height misc vegetation cover misc ecological recovery misc reclamation misc Science misc Q Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites
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topic_title	Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites unmanned aerial vehicles photogrammetry point clouds vegetation structure vegetation height vegetation cover ecological recovery reclamation
topic	misc unmanned aerial vehicles misc photogrammetry misc point clouds misc vegetation structure misc vegetation height misc vegetation cover misc ecological recovery misc reclamation misc Science misc Q
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title	Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites
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title_sort	use of unmanned aerial vehicles for monitoring recovery of forest vegetation on petroleum well sites
title_auth	Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites
abstract	Photogrammetric point clouds (PPCs) provide a source of three-dimensional (3-D) remote sensing data that is well-suited to use over small areas that are within the scope of observation by unmanned aerial vehicles (UAVs). We compared PPC-based structural metrics to traditional ground surveys conducted by field personnel in order to assess the capacity of PPC data to contribute to vegetation-reclamation surveys. We found good statistical agreement between key structural vegetation parameters, such as mean and maximum vegetation height, with PPC metrics successfully predicting most height and tree-diameter metrics using multivariate linear regression. However, PPC metrics were not as useful for estimating ground-measured vegetation cover. We believe that part of the issue lies in the mismatch between PPC- and ground-based measurement approaches, including subjective judgement on behalf of ground crews: a topic that requires more investigation. Our work highlights the emerging value of UAV-based PPCs to complement, and in some cases supplement, traditional ground-based sources of measured vegetation structure.
abstractGer	Photogrammetric point clouds (PPCs) provide a source of three-dimensional (3-D) remote sensing data that is well-suited to use over small areas that are within the scope of observation by unmanned aerial vehicles (UAVs). We compared PPC-based structural metrics to traditional ground surveys conducted by field personnel in order to assess the capacity of PPC data to contribute to vegetation-reclamation surveys. We found good statistical agreement between key structural vegetation parameters, such as mean and maximum vegetation height, with PPC metrics successfully predicting most height and tree-diameter metrics using multivariate linear regression. However, PPC metrics were not as useful for estimating ground-measured vegetation cover. We believe that part of the issue lies in the mismatch between PPC- and ground-based measurement approaches, including subjective judgement on behalf of ground crews: a topic that requires more investigation. Our work highlights the emerging value of UAV-based PPCs to complement, and in some cases supplement, traditional ground-based sources of measured vegetation structure.
abstract_unstemmed	Photogrammetric point clouds (PPCs) provide a source of three-dimensional (3-D) remote sensing data that is well-suited to use over small areas that are within the scope of observation by unmanned aerial vehicles (UAVs). We compared PPC-based structural metrics to traditional ground surveys conducted by field personnel in order to assess the capacity of PPC data to contribute to vegetation-reclamation surveys. We found good statistical agreement between key structural vegetation parameters, such as mean and maximum vegetation height, with PPC metrics successfully predicting most height and tree-diameter metrics using multivariate linear regression. However, PPC metrics were not as useful for estimating ground-measured vegetation cover. We believe that part of the issue lies in the mismatch between PPC- and ground-based measurement approaches, including subjective judgement on behalf of ground crews: a topic that requires more investigation. Our work highlights the emerging value of UAV-based PPCs to complement, and in some cases supplement, traditional ground-based sources of measured vegetation structure.
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title_short	Use of Unmanned Aerial Vehicles for Monitoring Recovery of Forest Vegetation on Petroleum Well Sites
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