---
title: "India electrification trends with VIIRS"
description: >
  Download VIIRS/Black Marble annual composites, extract panel statistics
  by state, and plot electrification trends over time.
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{India electrification trends with VIIRS}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r setup, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment  = "#>",
  dev.args = list(bg = "transparent")
)
```


## Get a NASA Earthdata token

1. Register at <https://urs.earthdata.nasa.gov/>
2. Go to Profile → Generate Token
3. `Sys.setenv(EARTHDATA_TOKEN = "YOUR_TOKEN")`, or pass the token directly to `earthdata_token("TOKEN")`

Tiles are cached in `tools::R_user_dir("lightson", "cache")` after the first
download; `cache_clear()` removes them.

## Quick workflow

```{r ten-lines, eval = FALSE}
library(lightson)

token <- earthdata_token()
rasters <- ntl_download(region = "IND", years = 2015:2025, token = token)
districts <- get_india_admin(level = "district")
panel <- extract_panel(rasters, districts)
plot_ntl_trend(panel, region = "Lucknow")
```

## Use your own shape/boundary file

`extract_panel()` accepts any `sf` object:

```{r custom-boundary, eval = FALSE}
library(sf)
my_districts <- sf::read_sf("~/github/bharatviz/public/India_LGD_districts.geojson")
panel2 <- extract_panel(rasters, my_districts, id_col = "district_name")
```

See the *Custom geometry* vignette for a complete walkthrough using bharatviz
boundaries with Bhuvan NTL rasters, which need only ISRO's public API.