A Geospatial Application, which I'm still working on

• So, you interested in building a mapping application ?
• Yes
• Okay, I'm gonna take you through each and every step. All you need to do is to follow me.
• You ready ?
• Definitely

I'm going to use Fedora Linux for implementing this whole process.

For database implementation I'll use PostgreSQL.

 postgres (PostgreSQL) 10.7

GeoSpatial Data to be stored and processed using PostGIS.

 Name         : postgis
 Version      : 2.4.3

A lot of Python scripts are going to be used for automating tile generation and database population procedure.

Python 3.7.3

NPM used for installing different JavaScript dependencies.

 >> npm --version
 6.4.1

Express app to be written for implementing Tile Map Server.

 >> node --version
 v10.15.0
 >> npm info express
 express@4.16.4

Mapnik used for rendering map tiles.

>> mapnik --version
 3.0.20

Well that's it 😄.

First thing first, you need world map data ( here we'll be using shapefiles ) to build a map of world. We'll use GADM as map data source. Here is the data, which we'll require.

So I've written small bash script for you to download and unzip that data. Well you're free to do that on your own too.

#!/usr/bin/bash
# script downloads shape files from GADM, make sure you're connected to internet
wget https://biogeo.ucdavis.edu/data/gadm3.6/gadm36_levels_shp.zip
# unzips downloaded zip into multiple layered shape files, which will be later on used for inflating features into database
unzip gadm36_levels_shp.zip

Now let's setup a PostgreSQL database with postgis extension enabled. Make sure you've installed PostgreSQL database properly on your system. I found it helpful.

Login to PostgreSQL.

 >> psql --username=your-user-name-for-postgresql # which is generally postgres

Create a database named world_features.

 >> create database world_features;

Now simply quit i.e. logout from psql prompt.

 >> \q

Relogin to use newly created database.

 >> psql --username=your-user-name-for-postgresql --dbname=world_features

Let's enable postgis extension for this database. Make sure you've installed postgis first.

 >> create extension postgis;

And initial setup is done. Now we gonna automate things 😉.

That shapefile we downloaded, has 6 layers. So we'll be creating 6 different tables, where we're going to store that huge map data.

😟

Hey wait, we're going to automate that whole thing. Now happy ???

☺️

Alright so let's automate. And don't forget to grab a cup of ☕, cause this gonna be a bit longer.

See we're going to process almost few hundreds of thousands features ( mostly polygon / multipolygon geometry ), using geo.Open('/path-to-gadm36_0.shp').GetLayer(0).GetFeature(j).GetGeometryRef().ExportToWkt(), where j is feature count. So of course this gonna be time consuming.

 def app(path='/path-to-file/gadm36_{}.shp', file_id=[0, 1, 2, 3, 4, 5]):
     # path, path to gadm shapefiles
     # gadm has 6 layers, shape files hold corresponding layer number too
     print('[+]Now grab a cup of coffee, cause this gonna be a little longer ...\n')
     for i in file_id:
         print('[+]Working on `{}`'.format(path.format(i)))
         datasource = geo.Open(path.format(i))  # datasource opened
         # layer fetched, only a single layer present in a shape file
         layer = datasource.GetLayer(0)
         tmp = []
         for j in range(layer.GetFeatureCount()):
             feature = layer.GetFeature(j)  # gets feature by id
             gid = 'NA'
             name = 'NA'
             # there might be some fields present in shapefile, which is None
             if(feature.items().get('GID_{}'.format(i)) is not None):
                 # To handle so, I'm adding these two checks, otherwise those might be causing problem during database population
                 gid = feature.items().get('GID_{}'.format(i))
             if(feature.items().get('NAME_{}'.format(i)) is not None):
                 name = feature.items().get('NAME_{}'.format(i))
             tmp.append([gid, name,
                     feature.GetGeometryRef().ExportToWkt()])
             # holds data in temp variable
             # data format -- [feature_id, feature_name, outline]
         if(inflate_into_db('world_features', 'username', 'password', {i: tmp})):
             # finally inflate into database
             print('[+]Success')
 return

Don't forget to change username and password, required for database login, before running this script.

 if(inflate_into_db('world_features', 'username', 'password', {i: tmp})):
        # finally inflate into database
        print('[+]Success')

Simply run this script and it'll be done.

 >>  python3 fetch_and_push.py 

And it's done. Wanna check ?

Login to postgresql.

 >> psql --username=your-user-name-for-postgresql --dbname=world_features

Type in psql prompt.

 >> select feature_id, feature_name from world_features_level_0 where feature_id = 'IND';
 feature_id | feature_name 
 ------------+--------------
 IND        | India
 (1 row)

And this is the structure of table, which the script built for us. All 6 tables has same structure.

 >> \d world_features_level_0;
                Table "public.world_features_level_0"
     Column    |       Type        | Collation | Nullable | Default 
 --------------+-------------------+-----------+----------+---------
 feature_id   | character varying |           | not null | 
 feature_name | character varying |           | not null | 
 outline      | geography         |           |          | 
 Indexes:
     "world_features_level_0_pkey" PRIMARY KEY, btree (feature_id)
     "world_features_level_0_index" gist (outline)

// TODO