東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Rangeland Inventory and Monitoring w...

Gillan, Jeffrey K.

Linked to FindBook

Google Book

Amazon

博客來

Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery./
Author:	Gillan, Jeffrey K.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	157 p.
Notes:	Source: Dissertations Abstracts International, Volume: 80-11, Section: B.
Contained By:	Dissertations Abstracts International80-11B.
Subject:	Range management. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13865070
ISBN:	9781392159620

Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery.
Gillan, Jeffrey K.

Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 157 p.

Source: Dissertations Abstracts International, Volume: 80-11, Section: B.

Thesis (Ph.D.)--The University of Arizona, 2019.

This item must not be sold to any third party vendors.

Publicly managed rangelands today are seeing higher demand from society for the goods and services they can provide, including livestock production, wildlife habitat, myriad forms of recreation, and ecosystem services. Adaptively managed multiple-use lands could benefit from more objective and synoptic data to evaluate ecosystem function and to carry out and defend land health assessments that allow or exclude certain land use activities. Field methods to measure critical soil and vegetation indicators are well-established and becoming standardized across jurisdictions. However, field methods have two main limitations: 1) most can only observe small portions of the landscape, which may produce an incomplete picture of the status and trend of rangeland health; and 2) field methods cannot measure some indicators very well or not at all. This research focused on developing methods to measure soil and vegetation characteristics from unmanned aerial system (commonly known as drones) imagery, which can observe significantly more land than their field counterparts. I demonstrated the measurement of one soil (erosion/deposition) and four vegetation (forage utilization, fractional cover, vegetation height, canopy gaps) indicators using drone imagery and compared each with established field methods. The results show that drone imagery methods can serve as a complement to field methods or even a replacement in some cases. I found that drone imagery methods can precisely map topographic change and forage utilization across extents not previously possible. Imagery methods can outperform field methods for vegetation heights and canopy gaps in some vegetation communities. Drone-imagery indicators have matured to the point where they can start being integrated into adaptive land management. An online space dedicated to sharing imagery workflows amongst the range community could quicken the pace of identifying best practices to facilitate the transition toward this technology. Adopting drone-based inventory and monitoring data, however, will not replace field skills in plant identification, knowledge of vegetation phenology and succession, and logical interpretation of the data for land health assessments.

ISBN: 9781392159620Subjects--Topical Terms:

647222
Range management.

Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery.
LDR:03304nmm a2200325 4500 001 2210800
005 20191121124313.5
008 201008s2019 ||||||||||||||||| ||eng d
020 $a 9781392159620
035 $a (MiAaPQ)AAI13865070
035 $a (MiAaPQ)arizona:17049
035 $a AAI13865070
040 $a MiAaPQ $c MiAaPQ
100 1 $a Gillan, Jeffrey K. $3 3437938
245 1 0 $a Rangeland Inventory and Monitoring with Unmanned Aerial System Imagery.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2019
300 $a 157 p.
500 $a Source: Dissertations Abstracts International, Volume: 80-11, Section: B.
500 $a Publisher info.: Dissertation/Thesis.
500 $a Advisor: Leeuwen, Willem J.D. van.
502 $a Thesis (Ph.D.)--The University of Arizona, 2019.
506 $a This item must not be sold to any third party vendors.
520 $a Publicly managed rangelands today are seeing higher demand from society for the goods and services they can provide, including livestock production, wildlife habitat, myriad forms of recreation, and ecosystem services. Adaptively managed multiple-use lands could benefit from more objective and synoptic data to evaluate ecosystem function and to carry out and defend land health assessments that allow or exclude certain land use activities. Field methods to measure critical soil and vegetation indicators are well-established and becoming standardized across jurisdictions. However, field methods have two main limitations: 1) most can only observe small portions of the landscape, which may produce an incomplete picture of the status and trend of rangeland health; and 2) field methods cannot measure some indicators very well or not at all. This research focused on developing methods to measure soil and vegetation characteristics from unmanned aerial system (commonly known as drones) imagery, which can observe significantly more land than their field counterparts. I demonstrated the measurement of one soil (erosion/deposition) and four vegetation (forage utilization, fractional cover, vegetation height, canopy gaps) indicators using drone imagery and compared each with established field methods. The results show that drone imagery methods can serve as a complement to field methods or even a replacement in some cases. I found that drone imagery methods can precisely map topographic change and forage utilization across extents not previously possible. Imagery methods can outperform field methods for vegetation heights and canopy gaps in some vegetation communities. Drone-imagery indicators have matured to the point where they can start being integrated into adaptive land management. An online space dedicated to sharing imagery workflows amongst the range community could quicken the pace of identifying best practices to facilitate the transition toward this technology. Adopting drone-based inventory and monitoring data, however, will not replace field skills in plant identification, knowledge of vegetation phenology and succession, and logical interpretation of the data for land health assessments.
590 $a School code: 0009.
650 4 $a Range management. $3 647222
650 4 $a Remote sensing. $3 535394
690 $a 0777
690 $a 0799
710 2 $a The University of Arizona. $b Natural Resources. $3 1020934
773 0 $t Dissertations Abstracts International $g 80-11B.
790 $a 0009
791 $a Ph.D.
792 $a 2019
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13865070