PDAL GreyhoundWriter Javascript example

_readme.md

Scripting writers.greyhound

These instructions assume that node.js is installed installed natively. PDAL/Entwine/Greyhound pieces are done via Docker.

Index Autzen with Entwine

Assuming ~/entwine is the storage location for Entwine-indexed data:

docker run -it -v ~/entwine:/opt/data connormanning/entwine build \
    -i http://entwine.io/sample-data/autzen.laz \
    -o /opt/data/autzen

Start Greyhound with /write permissions

Create ~/entwine/config.json with contents: { "allowWrite": true }.

Launch Greyhound:

docker run -it -v ~/entwine:/opt/data -p 8080:8080 connormanning/greyhound:alpine \
    -c /opt/data/config.json

Run buffered/tiled ground algorithm with Node.js

This example runner simply builds 36 pipelines that split the dataset into a 6x6 grid with a 20% overlapping buffer on each tile, and shells out PDAL's docker container to run each segment serially. It's a proof of concept only and not meant to be scaled to anything production-worthy.

This pipeline runs the SMRF algorithm as well as assigning incrementing values to the BufferedTile dimension for each tile of the 6x6 grid using PDAL's assign filter.

Install dependencies:

npm install lodash request-promise

Run:

node ground.js

Look at results

Ground visualization

Tiling visualization

ground.js

var _ = require('lodash');
var request = require('request-promise');
var exec = require('child_process').execSync;
var fs = require('fs');

var read = { "type": "readers.greyhound", "url": null, "buffer": 0.2 };
var ground = { "type": "filters.smrf" };
var ferry = { "type": "filters.ferry", "dimensions":
    "Classification=BufferedSmrf, Classification=BufferedTile" };
var assign = { "type": "filters.assign", "assignment": null };
var write = { "type": "writers.greyhound", "name": "ConnorBufferedSmrf", "dims":
    ["BufferedSmrf", "BufferedTile"] };

var base = 'http://localhost:8080/resource/autzen/';

var steps = 6;

request({ uri: base + 'info', json: true })
.then((info) => {
    var minx = info.bounds[0];
    var miny = info.bounds[1];
    var maxx = info.bounds[3];
    var maxy = info.bounds[4];
    var width = maxx - minx;
    var depth = maxy - miny;

    var t = 0;
    for (var i = 0; i < steps; ++i) {
        for (var j = 0; j < steps; ++j) {
            var bounds = [
                minx + (width / steps) * i,
                miny + (depth / steps) * j,
                minx + (width / steps) * (i + 1),
                miny + (depth / steps) * (j + 1)
            ];

            var pipeline = [
                _.merge(read, {
                    url: base + 'read?bounds=' + JSON.stringify(bounds)
                }),
                ground,
                ferry,
                _.merge(assign, { assignment: 'BufferedTile[:]=' + t }),
                write
            ]

            var f = t + '.json';
            console.log(f);
            console.log(pipeline);
            fs.writeFileSync(f, JSON.stringify({ pipeline: pipeline }));
            console.log(exec('pdal pipeline ' + f, {
                encoding: 'utf8'
            }));
            ++t;
        }
    }
});