Monitoring spring phenology with high temporal resolution terrestrial LiDAR measurements

被引:79
作者
Calders, Kim [1 ]
Schenkels, Tom [1 ]
Bartholomeus, Harm [1 ]
Armston, John [2 ,3 ]
Verbesselt, Jan [1 ]
Herold, Martin [1 ]
机构
[1] Wageningen Univ, Lab Geoinformat Sci & Remote Sensing, NL-6708 PB Wageningen, Netherlands
[2] Ecosci Precinct, Ctr Remote Sensing, Dept Sci Informat Technol Innovat & Arts, Dutton Pk, Qld 4102, Australia
[3] Univ Queensland, Sch Geog Planning & Environm Management, Joint Remote Sensing Res Program, Brisbane, Qld 4072, Australia
关键词
Terrestrial LiDAR; Vertical plant profiles; Vegetation structure; PAI; Phenology; LEAF-AREA INDEX; PULSED-LASER SYSTEMS; CANOPY GAP FRACTION; PART I; FOREST; PROFILES; TRENDS; ONSET;
D O I
10.1016/j.agrformet.2015.01.009
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
Vegetation phenology studies the timing of recurring seasonal dynamics and can be monitored through estimates of plant area index (PAL). Shifts in spring phenology are a key indicator for the effect of climate change, in particular the start of the growing season of forests. Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, is an active remote sensing technique and measures the forest structure with high spatial detail and accuracy. TLS provides information about the 3D distribution of canopy constituents and vertical plant profiles can be derived from these data. Vertical plant profiles describe the plant area per unit volume as a function of height, and can be used to used to monitor seasonal dynamics through PAL. Here, we present a TLS time series based on 48 measurement days of four sampling locations in a deciduous forest in the Netherlands. Vertical plant profiles are derived for each measurement and allow us to quantify not only total canopy integrated PAL, but also monitor PAI at specific horizontal layers. Sigmoidal models show a good fit to the derived total canopy integrated PAL time series (CV(RMSE) <2.4% and CCC >0.99). The start of season (SOS) based on these models occurs between March 29 and April 3, 2014, depending on the species composition. The SOS derived from the TLS data corresponds well with field observations and occurs 7-12 days earlier compared to the SOS estimate from the MODIS NDVI time series. This is mainly caused by the lower relative standard deviation for TLS measurements in leaf-off conditions (0.72% compared to 2.87% for the MODIS NDVI data), which allows us to significantly detect small changes in phenology earlier. TLS allows us to monitor PAI at specific horizontal layers and we defined an understorey, intermediate and upper canopy layer. Even though our study area had only a sparse understorey, small differences are observed in the SOS between the different layers. We expect that these phenological differences will be more pronounced in multi-layered forests and TLS shows the potential to study seasonal dynamics not only as a function of time, but also as a function of canopy height. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:158 / 168
页数:11
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