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Data for: Tracking the temporal dynamics of insect defoliation by high-resolution radar satellite data

Citation

Bae, Soyeon et al. (2021), Data for: Tracking the temporal dynamics of insect defoliation by high-resolution radar satellite data, Dryad, Dataset, https://doi.org/10.5061/dryad.9w0vt4bgr

Abstract

1. Quantifying tree defoliation by insects over large areas is a major challenge in forest management, but it is essential in ecosystem assessments of disturbance and resistance against herbivory. However, the trajectory from leaf-flush to insect defoliation to refoliation in broadleaf trees is highly variable. Its tracking requires high temporal- and spatial-resolution data, particularly in fragmented forests.

2. In a unique replicated field experiment manipulating gypsy moth Lymantria dispar densities in mixed-oak forests, we examined the utility of publicly accessible satellite-borne radar (Sentinel-1) to track the fine-scale temporal trajectory of defoliation. The ratio of backscatter intensity between two polarizations from radar data of the growing season constituted a canopy development index (CDI) and a normalized CDI (NCDI), which were validated by optical (Sentinel-2) and terrestrial laser scanning (TLS) data as well by intensive caterpillar sampling from canopy fogging.

3. The CDI and NCDI strongly correlated with optical and TLS data (Spearman’s ρ=0.79 and 0.84, respectively). The ∆NCDIDefoliation (A-C) significantly explained caterpillar abundance (R2=0.52). The NCDI at critical time-steps and ΔNCDI related to defoliation and refoliation well discriminated between heavily and lightly defoliated forests.

4. We demonstrate that the high spatial and temporal resolution and the cloud independence of Sentinel-1 radar potentially enable spatially unrestricted measurements of the highly dynamic canopy herbivory. This can help monitor insect pests, improve the prediction of outbreaks, and facilitate the monitoring of forest disturbance, one of the high priority Essential Biodiversity Variables, in the near future.

Methods

1. Data acquisition

Sentinel-1 C-band SAR data and Sentinel-2 optical data were obtained from the ESA Scientific Hub (https://scihub.copernicus.eu/).
Terrestrial laser scanning was conducted to track the forest canopy structure in three dimensions before and after insect defoliation. 


2. Data processing

For the Sentinel-1 data, all available level-1 GRDH products by the IW mode were pre-processed using the Sentinel Application Platforms (SNAP) Sentinel-1 Toolbox software and transformed to γ0 (see the Supplementary Note S 3.2 in Bae et al. (2019) and the batch processing graph at https://github.com/So-YeonBae/Sentinel1-Biodiversity). The γ0 values of the VV and VH polarizations were converted to dB as 10×log10⁡γand their time-series values were smoothed using the Gaussian window function.
The difference between the smoothed values of VV and VH, defined herein as the canopy development index (CDI, unit: dB), was computed.
The normalized CDI (NCDI) was calculated by dividing the time-series CDI values at each plot by the minimum CDI value during the leaf-off season.
Four critical time-steps (A, B, C, and D) indicating prominent phenological transitions were selected from the 18 time-steps of the NCDI of the 12-day composite time-series data. These four critical time-steps were used to calculate two indices related to defoliation and two indices related to refoliation. 

Please find the details from Bae et al. (2021)  "Tracking the temporal dynamics of insect defoliation by high-resolution radar satellite data"

Usage Notes

Each tab contains the data for making each figure in "Tracking the temporal dynamics of insect defoliation by high-resolution radar satellite data" (Bae et al.).

Original paper DOI: 10.1111/2041-210X.13726

Funding

Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten, Award: ST357

Bayerisches Staatsministerium für Ernährung, Landwirtschaft und Forsten, Award: Z073

National Research Foundation of Korea, Award: 2020R1A6A3A03038391