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Chlorophyll content estimation in an open-canopy conifer forest with Sentinel-2A and hyperspectral imagery in the context of forest decline
- Source :
- Remote sensing of environment, 223, 320-335, Digital.CSIC. Repositorio Institucional del CSIC, instname
- Publication Year :
- 2019
-
Abstract
- With the advent of Sentinel-2, it is now possible to generate large-scale chlorophyll content maps with unprecedented spatial and temporal resolution, suitable for monitoring ecological processes such as vegetative stress and/or decline. However methodological gaps exist for adapting this technology to heterogeneous natural vegetation and for transferring it among vegetation species or plan functional types. In this study, we investigated the use of Sentinel-2A imagery for estimating needle chlorophyll (Ca+b) in a sparse pine forest undergoing significant needle loss and tree mortality. Sentinel-2A scenes were acquired under two extreme viewing geometries (June vs. December 2016) coincident with the acquisition of high-spatial resolution hyperspectral imagery, and field measurements of needle chlorophyll content and crown leaf area index. Using the high-resolution hyperspectral scenes acquired over 61 validation sites we found the CI chlorophyll index R750/R710 and Macc index (which uses spectral bands centered at 680 nm, 710 nm and 780 nm) had the strongest relationship with needle chlorophyll content from individual tree crowns (r2 = 0.61 and r2 = 0.59, respectively; p 0.7 for June and >0.4 for December; p
- Subjects :
- Chlorophyll
010504 meteorology & atmospheric sciences
Geography & travel
0208 environmental biotechnology
Soil Science
Red edge
Context (language use)
02 engineering and technology
01 natural sciences
Article
chemistry.chemical_compound
Atmospheric radiative transfer codes
Radiative transfer
Computers in Earth Sciences
Leaf area index
0105 earth and related environmental sciences
Remote sensing
ddc:910
Sentinel-2A
Crown (botany)
Hyperspectral imaging
Geology
Vegetation
Forest decline
020801 environmental engineering
Hyperspectral
chemistry
Environmental science
Subjects
Details
- Language :
- English
- ISSN :
- 00344257 and 18790704
- Database :
- OpenAIRE
- Journal :
- Remote sensing of environment, 223, 320-335, Digital.CSIC. Repositorio Institucional del CSIC, instname
- Accession number :
- edsair.doi.dedup.....0ee33a1c4c1e5ac74bb8c73129dceaef