• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

测量蒿属草原牧场的植被覆盖度:方法比较

Measuring plant cover in sagebrush steppe rangelands: a comparison of methods.

作者信息

Seefeldt Steven S, Booth D Terrance

机构信息

Agricultural Research Service, United States Sheep Experiment Station, United States Department of Agriculture, Dubois, Idaho 83423, USA.

出版信息

Environ Manage. 2006 May;37(5):703-11. doi: 10.1007/s00267-005-0016-6.

DOI:10.1007/s00267-005-0016-6
PMID:16485162
Abstract

Methods that are more cost-effective and objective are needed to detect important vegetation change within acceptable error rates. The objective of this research was to compare visual estimation to three new methods for determining vegetation cover in the sagebrush steppe. Fourteen management units at the US Sheep Experiment Station were identified for study. In each unit, 20 data collection points were selected for measuring plant cover using visual estimation, laser-point frame (LPF), 2 m above-ground-level (AGL) digital imagery, and 100-m AGL digital imagery. In 11 of 14 management units, determinations of vegetation cover differed (P < 0.05). However, when combined, overall determinations of vegetation cover did not differ. Standard deviation, corrected sums of squares, coefficient of variation, and standard error for the 100 m AGL method were half as large as for the LPF and less than the 2-m AGL and visual estimate. For the purpose of measuring plant cover, all three new methods are as good as or better than visual estimation for speed, standard deviation, and cost. The acquisition of a permanent image of a location is an important advantage of the 2 and 100 m AGL methods because vegetation can be reanalyzed using improved software or to answer different questions, and changes in vegetation over time can be more accurately determined. The reduction in cost per sample, the increased speed of sampling, and the smaller standard deviation associated with the 100-m AGL digital imagery are compelling arguments for adopting this vegetation sampling method.

摘要

需要更具成本效益且客观的方法,以便在可接受的误差率范围内检测重要的植被变化。本研究的目的是将目视估计法与三种测定蒿属植物草原植被覆盖度的新方法进行比较。在美国绵羊实验站确定了14个管理单元进行研究。在每个单元中,选择20个数据收集点,使用目视估计法、激光点框(LPF)、离地2米(AGL)的数字图像以及离地100米(AGL)的数字图像来测量植被覆盖度。在14个管理单元中的11个单元中,植被覆盖度的测定结果存在差异(P < 0.05)。然而,综合来看,植被覆盖度的总体测定结果并无差异。100米AGL方法的标准差、校正平方和、变异系数以及标准误差仅为LPF方法的一半,且小于2米AGL方法和目视估计法。就测量植被覆盖度而言,在速度、标准差和成本方面,所有这三种新方法与目视估计法一样好或更优。获取某一位置的永久图像是2米和100米AGL方法的一个重要优势,因为可以使用改进的软件重新分析植被情况或回答不同问题,并且能够更准确地确定植被随时间的变化。与100米AGL数字图像相关的每个样本成本降低、采样速度提高以及标准差更小,这些都是采用这种植被采样方法的有力理由。

相似文献

1
Measuring plant cover in sagebrush steppe rangelands: a comparison of methods.测量蒿属草原牧场的植被覆盖度:方法比较
Environ Manage. 2006 May;37(5):703-11. doi: 10.1007/s00267-005-0016-6.
2
Using open-source software and digital imagery to efficiently and objectively quantify cover density of an invasive alien plant species.利用开源软件和数字图像,高效、客观地量化入侵外来植物物种的盖度。
J Environ Manage. 2020 Jul 15;266:110519. doi: 10.1016/j.jenvman.2020.110519. Epub 2020 Apr 29.
3
Measuring plant diversity in the tall threetip sagebrush steppe: influence of previous grazing management practices.测量高茎三尖蒿属灌木草原的植物多样性:以往放牧管理措施的影响。
Environ Manage. 2003 Aug;32(2):234-45. doi: 10.1007/s00267-003-0073-7.
4
Detection of goat herding impact on vegetation cover change using multi-season, multi-herd tracking and satellite imagery.利用多季节、多群跟踪和卫星图像检测放牧对植被覆盖变化的影响。
Sci Total Environ. 2023 Oct 15;895:164830. doi: 10.1016/j.scitotenv.2023.164830. Epub 2023 Jun 23.
5
Integrating drone imagery with existing rangeland monitoring programs.将无人机图像与现有的牧场监测计划相结合。
Environ Monit Assess. 2020 Apr 6;192(5):269. doi: 10.1007/s10661-020-8216-3.
6
Rangeland Condition Monitoring: A New Approach Using Cross-Fence Comparisons of Remotely Sensed Vegetation.牧场状况监测:一种利用遥感植被跨围栏比较的新方法。
PLoS One. 2015 Nov 13;10(11):e0142742. doi: 10.1371/journal.pone.0142742. eCollection 2015.
7
Modeling vegetation heights from high resolution stereo aerial photography: an application for broad-scale rangeland monitoring.利用高分辨率立体航空摄影建模植被高度:在大范围牧场监测中的应用
J Environ Manage. 2014 Nov 1;144:226-35. doi: 10.1016/j.jenvman.2014.05.028. Epub 2014 Jun 25.
8
Impact of habitat-specific GPS positional error on detection of movement scales by first-passage time analysis.栖息地特定 GPS 位置误差对首次通过时间分析检测运动尺度的影响。
PLoS One. 2012;7(11):e48439. doi: 10.1371/journal.pone.0048439. Epub 2012 Nov 7.
9
Methodological considerations of terrestrial laser scanning for vegetation monitoring in the sagebrush steppe.用于鼠尾草草原植被监测的地面激光扫描方法学考量
Environ Monit Assess. 2017 Oct 23;189(11):578. doi: 10.1007/s10661-017-6300-0.
10
An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP.一种从数字图像估算绿色植被覆盖分数的自动化(新型)算法:UIP-MGMEP。
Environ Monit Assess. 2018 Oct 30;190(11):687. doi: 10.1007/s10661-018-7075-7.

引用本文的文献

1
Integrating drone imagery with existing rangeland monitoring programs.将无人机图像与现有的牧场监测计划相结合。
Environ Monit Assess. 2020 Apr 6;192(5):269. doi: 10.1007/s10661-020-8216-3.
2
The roles of dimensionality, canopies and complexity in ecosystem monitoring.维度、冠层和复杂性在生态系统监测中的作用。
PLoS One. 2011;6(11):e27307. doi: 10.1371/journal.pone.0027307. Epub 2011 Nov 3.
3
Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.从遥感数据和模拟建模预测黄石国家公园生态系统中的碳通量。

本文引用的文献

1
Precision measurements from very-large scale aerial digital imagery.
Environ Monit Assess. 2006 Jan;112(1-3):293-307. doi: 10.1007/s10661-006-1070-0.
Carbon Balance Manag. 2011 Aug 11;6:3. doi: 10.1186/1750-0680-6-3.
4
Ground-cover measurements: assessing correlation among aerial and ground-based methods.地被植物测量:评估航空测量法与地面测量法之间的相关性。
Environ Manage. 2008 Dec;42(6):1091-100. doi: 10.1007/s00267-008-9110-x. Epub 2008 Apr 30.