notes

planetiler-core/src/main/java/com/onthegomap/planetiler/contour/EsaWorldcover.java

@@ -1,10 +1,41 @@
 package com.onthegomap.planetiler.contour;
 
+import static java.util.Map.entry;
+
+import com.carrotsearch.hppc.IntIntHashMap;
+import com.carrotsearch.hppc.IntIntMap;
 import com.onthegomap.planetiler.config.PlanetilerConfig;
-import com.onthegomap.planetiler.util.Downloader;
+import java.awt.Color;
+import java.awt.image.BufferedImage;
 import java.io.IOException;
+import java.net.URL;
+import java.util.Map;
+import javax.imageio.ImageIO;
 
 public class EsaWorldcover {
+  // stack:
+  // nothing / built-up / moss / water
+
+  // 1: shrub / grass / herbacious wetland
+  // 2: crop
+  // 3: tree / mangrove
+  // 4: very tree / mangrove
+
+  // ice ?
+  private static final Map<Integer, String> colors = Map.ofEntries(
+    entry(new Color(0, 100, 0, 255).getRGB(), "treecover"),
+    entry(new Color(255, 187, 34, 255).getRGB(), "shrubland"),
+    entry(new Color(255, 255, 76, 255).getRGB(), "grassland"),
+    entry(new Color(240, 150, 255, 255).getRGB(), "cropland"),
+    entry(new Color(250, 0, 0, 255).getRGB(), "builtup"),
+    entry(new Color(180, 180, 180, 255).getRGB(), "bare"),
+    entry(new Color(240, 240, 240, 255).getRGB(), "snow"),
+    entry(new Color(0, 100, 200, 255).getRGB(), "water"),
+    entry(new Color(0, 150, 160, 255).getRGB(), "wetland"),
+    entry(new Color(0, 207, 117, 255).getRGB(), "mangrove"),
+    entry(new Color(250, 230, 160, 255).getRGB(), "moss")
+  );
+
   static String getCoord(double ilon, double ilat) {
     int lon = (int) (Math.floor(ilon / 3) * 3);
     int lat = (int) (Math.floor(ilat / 3) * 3);
@@ -16,12 +47,29 @@ public class EsaWorldcover {
 
   public static void main(String[] args) throws IOException {
     var config = PlanetilerConfig.defaults();
-    String entry = "ESA_WorldCover_10m_2021_v200_" + getCoord(-71.5, 42.2) + "_Map.tif";
+    String entry = "ESA_WorldCover_10m_2021_v200_" + getCoord(-72, 42) + "_Map.tif";
     String url = "https://esa-worldcover.s3.amazonaws.com/v200/2021/map/" + entry;
     // ESA_WorldCover_10m_2021_v200_N42W072_Map.tif
     System.err.println("Getting " + url);
-    try (var is = Downloader.openStream(url, config)) {
-      System.err.println(is.readAllBytes().length);
+    BufferedImage image = ImageIO.read(new URL(url));
+    System.err.println("width=" + image.getWidth());
+    System.err.println("height=" + image.getHeight());
+    IntIntMap counts = new IntIntHashMap();
+    int idx = 0;
+
+    int[] arr = new int[image.getWidth() * image.getHeight()];
+    image.getRGB(0, 0, image.getWidth(), image.getHeight(), arr, 0, image.getWidth());
+    System.err.println("got pixels");
+    for (int y = 0; y < image.getHeight(); y++) {
+      for (int x = 0; x < image.getWidth(); x++) {
+        int color = arr[idx];
+        counts.put(color, counts.getOrDefault(color, 0) + 1);
+        idx++;
+      }
+    }
+    for (var e : counts.keys()) {
+      System.err.println(e.value + " " + colors.get(e.value) + " " +
+        ((counts.get(e.value) * 100L) / ((long) image.getWidth() * image.getHeight())) + "%");
     }
   }
 }

planetiler-core/src/main/java/com/onthegomap/planetiler/contour/README.md

@@ -0,0 +1,47 @@
+# Raster DEM status
+
+## Contour Lines
+
+This appears to work fine with the following caveat:
+
+- AsterV3.java generates one contour shape from hi-res DEM then scales it down to lower zoom levels, this can result in
+  bad looking contour lines at low zooms. A better approach would be to downsample the DEM data to something appropriate
+  for each zoom level, then generate contour lines for that zoom.
+
+## Vector Hillshade
+
+Sort of works, caveats:
+
+- The polygons don't look right where the 1 degree tiles meet.
+- It would probably be better to adopt maplibre GL JS's hillshading algorithm which adds shadows based on the slope more
+  so than the aspect so you can see details better on south and southwest sides when the illumination is from
+  northwest: https://github.com/maplibre/maplibre-gl-js/blob/main/src/shaders/hillshade.fragment.glsl
+- It's _very_ slow
+
+## Landcover
+
+`EsaWorldcover.java` Doesn't do anything, but I did find out:
+
+- ESA worldcover dataset is hosted in a public S3 dataset so it's easy to download the 3 degree x 3 degree tiff
+  files https://registry.opendata.aws/esa-worldcover-vito/index.html
+- The values are encoded by unique colors - see `EsaWorldcover.java` for an example parsing them
+- We probably want to create "stacked" output polygons to create a greening effect when going from desert to grass to
+  forest, something like:
+  - omit built-up, moss, and water
+  - emit "ice" polygons
+  - emit a "greening stack" with:
+    - level 1 includes shrub/grass/herbacious wetland
+    - level 2 include all of level 1 plus also crop
+    - level 3 includes level 1 and 2 plus also tree and mangrove
+- Most vector landcover datasets I see in the wild don't include features <300m wide, so we can downsample this 10m
+  dataset at least 30x to get started with.
+- When downsampling, we probably want a bitmap for each output polygon, then consider a downsampled pixel a 1 if % of
+  matching raw input pixels within that output pixel is > 50% or so.
+
+The rough approach would look like:
+
+- generate bitmaps corresponding to each output polygon from raw input
+- downsample initial bitmaps 30x
+- vectorize, smooth, emit polygons
+- repeat until you get down to z0:
+  - downsample another 2x, then vectorize, smooth, and emit polygons at the lower zoom level