geotiff-to-geojson.sh

#!/bin/bash
#
# Requires:
#   - gdal_sieve.py
#   - ogr2ogr (GDAL)
#        - topojson (node.js)

# Grab the relative directory for source file.
# SRC_DIR=`dirname $0`

# Which raster to compress.
ORG_FILE="20180913_171834_1009_3B_AnalyticMS.tif"

# Final output file.
OUTPUT_FILE="20180913_171834_1009_3B_AnalyticMS.json"

echo "Processing $ORG_FILE."

# Where to output the new file.
TMP_DIR=./tmp

# The amount of times the file should be passed over.
ITERATIONS=3

# Threshold for each iteration.
THRESHOLD=40

# TopoJSON area threshold for simplification.
TOPO_COMPRESSION=0.000005

# Setup internal vars.
_CUR=$THRESHOLD
_COMPRESSION=$(($ITERATIONS * $THRESHOLD))

rm -rf $TMP_DIR
mkdir -p $TMP_DIR

# Start sieve passes.
gdal_sieve.py -st $THRESHOLD -4 $ORG_FILE $TMP_DIR/output-"$THRESHOLD".tiff

while [ $_CUR -le $_COMPRESSION ]; do
    let _PREV=$_CUR
    let _CUR=$_CUR+$THRESHOLD
    echo "Compressing output-$_PREV.tiff into $_CUR.tiff"
    gdal_sieve.py -st $THRESHOLD -4 "$TMP_DIR/output-$_PREV.tiff" \
        "$TMP_DIR/output-$_CUR.tiff"
    rm "$TMP_DIR/output-$_PREV.tiff"
done

# Raster to vector.
gdal_polygonize.py $TMP_DIR/output-"$_CUR".tiff \
    -f "GPKG" $TMP_DIR vector n

# Change shapefile to geojson without the 0 layer, which is water.
ogr2ogr -f "GeoJSON" -where "n != 0" "$TMP_DIR/geojson.json" $TMP_DIR/vector.gpkg

# Convert to compressed TopoJSON.
topojson -o $OUTPUT_FILE \
    --no-stitch-poles \
    -s $TOPO_COMPRESSION \
    -p -- "$TMP_DIR/geojson.json"

# Clean up.
rm -rf $TMP_DIR