Header

UZH-Logo

Maintenance Infos

Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing


Zheng, Zhaoju; Zeng, Yuan; Schuman, Meredith Christine; Jiang, Hailan; Schmid, Bernhard; Schaepman, Michael E; Morsdorf, Felix (2022). Individual tree-based vs pixel-based approaches to mapping forest functional traits and diversity by remote sensing. International Journal of Applied Earth Observation and Geoinformation, 114:103074.

Abstract

Plant ecology and biodiversity research have increasingly incorporated trait-based approaches and remote sensing. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on airborne LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait–trait relationships and functional diversity metrics obtained by the ITC- and pixel-based approaches at changing pixel size and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by airborne Pushbroom Hyperspectral Imager-3 (PHI-3) hyperspectral data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC-based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness also decreased with increasing pixel size, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, high-resolution pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.

Abstract

Plant ecology and biodiversity research have increasingly incorporated trait-based approaches and remote sensing. Compared with traditional field survey (which typically samples individual trees), remote sensing enables quantifying functional traits over large contiguous areas, but assigning trait values to biological units such as species and individuals is difficult with pixel-based approaches. We used a subtropical forest landscape in China to compare an approach based on airborne LiDAR-delineated individual tree crowns (ITCs) with a pixel-based approach for assessing functional traits from remote sensing data. We compared trait distributions, trait–trait relationships and functional diversity metrics obtained by the ITC- and pixel-based approaches at changing pixel size and extent. We found that morphological traits derived from airborne laser scanning showed more differences between ITC- and pixel-based approaches than physiological traits estimated by airborne Pushbroom Hyperspectral Imager-3 (PHI-3) hyperspectral data. Pixel sizes approximating average tree crowns yielded similar results as ITCs, but 95th quantile height and foliage height diversity tended to be overestimated and leaf area index underestimated relative to ITC-based values. With increasing pixel size, the differences to ITC-based trait values became larger and less trait variance was captured, indicating information loss. The consistency of ITC- and pixel-based functional richness also decreased with increasing pixel size, and changed with the observed extent for functional diversity monitoring. We conclude that whereas ITC-based approaches in principle allow partitioning of variation between individuals, genotypes and species, high-resolution pixel-based approaches come close to this and can be suitable for assessing ecosystem-scale trait variation by weighting individuals and species according to coverage.

Statistics

Citations

Dimensions.ai Metrics
8 citations in Web of Science®
8 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

82 downloads since deposited on 08 Dec 2022
51 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
08 Research Priority Programs > Global Change and Biodiversity
07 Faculty of Science > Department of Chemistry
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > Global and Planetary Change
Physical Sciences > Earth-Surface Processes
Physical Sciences > Computers in Earth Sciences
Physical Sciences > Management, Monitoring, Policy and Law
Uncontrolled Keywords:Management, Monitoring, Policy and Law, Computers in Earth Sciences, Earth-Surface Processes, Global and Planetary Change
Language:English
Date:1 November 2022
Deposited On:08 Dec 2022 16:29
Last Modified:28 May 2024 01:43
Publisher:Elsevier
ISSN:0303-2434
OA Status:Gold
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1016/j.jag.2022.103074
  • Content: Published Version
  • Language: English
  • Licence: Creative Commons: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)