plekhanovaelena/alan_arctic

Trend analysis of Artificial lights at nights (ALAN) in the Arctic.

Artificial light at night in the Arctic

Data

The consistent and corrected nighttime light (CCNL) dataset is based on DMSP and available as GeoTIFF format at https://zenodo.org/record/6644980

Global Human Settlement Layer (GHSL) Population grid for the years 1995, 2000, 2005, and 2010 is available as Mollweide projection with 1000 m resolution at https://ghsl.jrc.ec.europa.eu/download.php?ds=pop

Database of Global Administrative Areas (GADM 4.1) is available at https://gadm.org/download_country.html

Code

Required packages: terra, raster, rgdal, tictoc, reshape, ggplot2

Data preparation

ALAN. We downloaded CCNL rasters for each year from Zenodo repository, stacked and cropped them above 45°N and filtered out the auroras via following scripts

downloading_ALAN_layers.R

stacking_and_cropping_ALAN_layers.R

filtering_of_auroras.R

Human settlement. We downladed Global Human Settlement Layer (GHSL) via the following script. We then reprojected it to the standard WGS 84 coordinate system using QGIS 3.28.0.

downloading_human_set_data.R

Stats for ALAN area and development during 1992-2013 (Figure 1, Table 1, Suppl. Table 2)

We calculated total lit area for each region and subregion for each year. We then calculated ARIMA slope and p-value and the annual growth in ALAN extent.

calculating_lit_area_per_year_and_growth.R

We plotted Figure 1 with plotting_Fig1.R

We calculated total area, newly lit area and ALAN intensity-based annual growth rate in human activity for regions and subregions. Additionally, we calculate the percent of significantly increasing/decreasing area to total area based on the ALAN intensity trend map (see the next section).

calculating_areas_stats.R

We calculated proportion of lit areas containing human settlement to the total lit area for each region and subregion.

calculating_proportion_of_inhabited_lit_areas.R

We then created Table 1 and Supplementary table 2 with creating_tables.R

Creating ALAN trend maps (Figure 2,3)

We calculated and saved ARIMA slope and p-value for each pixel of CCNL data across 1992-2013. The code is parallelized to 32 cores for computational efficiency and takes about 5h to run on 32 cores, 32GB RAM.

calculating_arima_slope_pval.R