Remote Sensing Applications in Monitoring Poplars: A Review

被引:0
|
作者
Mapuru, Morena J. [1 ,2 ]
Xulu, Sifiso [1 ]
Gebreslasie, Michael [1 ]
D'Amico, Giovanni
Mattioli, Walter
Chirici, Gherardo
机构
[1] Univ KwaZulu Natal, Sch Agr Earth & Environm Sci, Westville Campus, ZA-4000 Durban, South Africa
[2] South African Natl Pk, Sci Serv, ZA-8301 Kimberley, South Africa
来源
FORESTS | 2023年 / 14卷 / 12期
关键词
poplar; remote sensing; LiDAR; review; forest; ARTIFICIAL NEURAL-NETWORKS; LEAF-AREA INDEX; FOREST STANDS; CLASSIFICATION; CANOPY; LANDSCAPE; IMAGERY; TREES; PLANTATIONS; DENSITY;
D O I
10.3390/f14122301
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Given the ability of remote sensing to detect distinctive plant traits, it has emerged in recent decades as a useful and attractive research tool for forest trees such as poplars. Although poplars have been extensively studied using remote sensing over the past thirty years, no reviews have been conducted to understand the results of multiple applications. Here, we present a review and synthesis of poplar studies in this regard. We searched the Scopus, Google Scholar, and Science Direct databases and found 266 published articles, of which 148 were eligible and analyzed. Our results show a rapid increase in remote sensing-based poplar publications over the period of 1991-2022, with airborne platforms, particularly LiDAR, being predominantly used, followed by satellite and ground-based sensors. Studies are widespread in the Global North, accounting for more than two-thirds of studies. The studies took place mainly in agricultural landscapes, followed by forest areas and riparian areas, with a few in mountain and urban areas. Commonly studied biophysical parameters were mostly obtained from LiDAR data. On the other hand, spectral indicators have been widely used to monitor the health and vitality of poplar trees, integrating various machine learning algorithms. Overall, remote sensing has been widely used in poplar studies, and the increasing use of free satellite data and processing platforms is expected to pave the way for data-poor countries to monitor poplar in the Global South, where resources are mainly limited.
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页数:14
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