Satellite Assessment of Forest Health in Drought Conditions: A Novel Approach Combining Defoliation and Discolouration

During the summer of 2022, heat waves exacerbated drought conditions across Europe, significantly deteriorating Slovakia’s forest health (FH). The main symptoms were defoliation and discolouration (mainly browning). According to the literature, completely brown leaves/needles are considered defoliation, and premature yellowing halts assimilation and reduces production. Thus, evaluating FH based solely on defoliation may underestimate the impact severity. To address this issue, we proposed a formula that integrates both defoliation and discolouration metrics. Then, by linking terrestrial and satellite data (a mosaic from Sentinel-2 and Landsat 9), regression models were developed using two-phase sampling to estimate defoliation, discolouration, and their combination. In the first phase, the Gram–Schmidt transformation of four satellite mosaic bands was used to derive two orthogonal components: one optimized for FH estimation (NSC2) and one for eliminating the influence of species composition on FH classification (NSC1). In the second phase, ground data were collected for the construction of a regression and to improve the first-phase results. The NSC2 component showed a strong correlation with defoliation, discolouration, and their combination. The standard error of the estimate was ±9.7% and the R2 was 0.83 for the combined symptoms, which enabled a detailed assessment of the intensity of forest damage. Our method is independent of tree species and has potential in FH assessments of temperate forests in Europe.

Authors

Institutions

Publication Details

Journal
Forests
Published
2024-09-06
DOI
https://doi.org/10.3390/f15091567
Citations
3
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
1.38
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Satellite Assessment of Forest Health in Drought Conditions: A Novel Approach Combining Defoliation and Discolouration

Bohdan Konôpka, Peter Surový, Juliána Chudá, Tomáš Bucha et al.
3 citations
Forests
Remote Sensing in Agriculture
1.38
article

Satellite Assessment of Forest Health in Drought Conditions: A Novel Approach Combining Defoliation and Discolouration

Bohdan Konôpka, Peter Surový, Juliána Chudá, Tomáš Bucha, Pavel Pavlenda, Julián Tomaštík
article en
3 citations

Abstract

During the summer of 2022, heat waves exacerbated drought conditions across Europe, significantly deteriorating Slovakia’s forest health (FH). The main symptoms were defoliation and discolouration (mainly browning). According to the literature, completely brown leaves/needles are considered defoliation, and premature yellowing halts assimilation and reduces production. Thus, evaluating FH based solely on defoliation may underestimate the impact severity. To address this issue, we proposed a formula that integrates both defoliation and discolouration metrics. Then, by linking terrestrial and satellite data (a mosaic from Sentinel-2 and Landsat 9), regression models were developed using two-phase sampling to estimate defoliation, discolouration, and their combination. In the first phase, the Gram–Schmidt transformation of four satellite mosaic bands was used to derive two orthogonal components: one optimized for FH estimation (NSC2) and one for eliminating the influence of species composition on FH classification (NSC1). In the second phase, ground data were collected for the construction of a regression and to improve the first-phase results. The NSC2 component showed a strong correlation with defoliation, discolouration, and their combination. The standard error of the estimate was ±9.7% and the R2 was 0.83 for the combined symptoms, which enabled a detailed assessment of the intensity of forest damage. Our method is independent of tree species and has potential in FH assessments of temperate forests in Europe.

ForestsVol. 15(9)
Czech University of Life Sciences Prague (CZ), Technická univerzita vo Zvolene (SK), National Forest Centre (SK)
Openalex Percentile: Top 18%
Remote Sensing in Agriculture
1.38
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.