problem | where | z level(s) | sktich |
---|---|---|---|
label cut off, bufferSize/metatile | germnay | 5 | n |
orphan/ambiguous dots | errywhere | 4 | dots |
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
import psycopg2 | |
con = psycopg2.connect("dbname=nyc3 user=postgres") # CONnect to a database | |
cur = con.cursor() | |
cur.execute('''select ctidfp00 from tracts;''') | |
results = cur.fetchall() |
PROJCS["NAD_1983_StatePlane_New_York_Long_Island_FIPS_3104_Feet",GEOGCS["GCS_North_American_1983",DATUM["D_North_American_1983",SPHEROID["GRS_1980",6378137.0,298.257222101]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Lambert_Conformal_Conic"],PARAMETER["False_Easting",984250.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",-74.0],PARAMETER["Standard_Parallel_1",40.66666666666666],PARAMETER["Standard_Parallel_2",41.03333333333333],PARAMETER["Latitude_Of_Origin",40.16666666666666],UNIT["Foot_US",0.3048006096012192]] |
select | |
id, | |
sum(st_area((gval).geom) | |
/ 10000) as total_area_ha, | |
round( min((gval).val)) as min_slope, | |
round( sum((gval).val * st_area((gval).geom)) | |
/ st_area(st_collect((gval).geom)) | |
) as avg_slope_sqm, | |
round( max((gval).val)) as max_slope | |
from ( |
#countries { | |
line-color: #6e7a6e; | |
line-width: .9; | |
line-join: round; | |
} | |
#admin1landline[ADM0 = 'Brazil']{ | |
line-width:.75; | |
line-color:#6e7a6e; | |
line-dasharray:5,10; |
Drop view slope_area3; | |
create or replace view slope_area3 as | |
select gid::integer, new_geom, area_hectare from | |
(select generate_series(1, ST_NumGeometries(mymulti)) as gid, | |
ST_GeometryN(mymulti, generate_series(1, ST_NumGeometries(mymulti))) as new_geom, | |
st_area(ST_GeometryN(mymulti, generate_series(1, ST_NumGeometries(mymulti)))) | |
/10000 AS area_hectare | |
from (select max(gid) as gid, st_memunion(the_geom) as mymulti | |
from | |
(select * from parcel_stats |
We're excited to announce that official Transport for London and National Rail icons will now be featured on Mapbox Streets at rail stations throughout Great Britain.
New icons make neighborhoods more immediately familiar on the already data rich maps, but simplifying the rich OpenStreetMap data required a concerted effort from both our data team and cartographers. In many cases stations are represented as buildings, and other times as a single point. In yet other instances, one station will have multiple points, with each representing a platform or entrance. If two rail networks service the same station, that station might have on point for each rail service.
Many nodes for just two stations - King's Cross and St. Pancras
Estamos animados de liberar un conjunto de datos de todas las carreteras en el estado Mexicano de Jalisco, listo para contribuirlos con el editor popular JOSM. Mira el repositorio osm-jalisco para bajar los datos y aprender como empezar.
Una prestación estilizada en TileMIll
Estamos animados de liberar un conjunto de datos de todas las carreteras en el estado mexicano de Jalisco, asi que se lo puede contribuir en el editor popular JOSM. Vista nuestra repositorio osm-jalisco para bajar los datos y aprender como empezar.
Una prestación estilizada en TileMIll
##An Open Mapping Tool Chain
The process of adding data to OpenStreetMap to styling and publishing your maps online is not obvious at first. I'll walk though the open source tool chain we use to contribute to OSM, and how to use TileMill to leverage OSM data to build custom maps. Specifically I will share some of our recent experience over the past several weeks of tracing in Brazil and publishing maps online. I will share specifics on how to get started tracing roads and buildings from satellite imagery in a few minutes to how we actively engage local communities and working with local governments to open large datasets and import them to OpenStreetMap. Finally I will end showing how how to turn an OSM export into a map and publish it on your web site.