cquest

Ingredients

• a decent DEM
• gdal
• some computer

compute grayscale hillshade using gdaldem

gdaldem hillshade -compute_edges your_dem_file hillshade.tif

color-ramp to compute transparency (alpha channel)

In another bowl, prepare the following shade.ramp file:

YKCzoli

Processing LiDAR to extract building heights

Walk through

Detailed walk through of building extraction using postgis

First lets pull a data layer from of openstreetmap. You can do this any which way you’d like, as there are a variety of methods for pulling openstreetmap data from their database. Check the [wiki] (http://wiki.openstreetmap.org/wiki/Downloading_data) for a comprehensive list. My favourite method thus far is pulling the data straight into QGIS using the open layers plugin. For those who may want to explore this method, check [this tutorial] (http://www.qgistutorials.com/en/docs/downloading_osm_data.html). For building extraction you only need building footprints, and include the building tags. Not all polygons are of type building in OSM, so we can download all the polygons, and then filter the layer for only polygons tagged as buildings.

LiDAR data was pulled from USGS via the Earth Explorer site. [Here] (http://earthobservatory.nasa.gov/blogs/ele

hogmoru

Technical details for https://stackoverflow.com/a/44169445/6730571

Details of investigation:

On a base system, /usr/bin/java is a symlink that points to /System/Library/Frameworks/JavaVM.framework/Versions/Current/Commands/java, which is an Apple wrapper tool that locates and executes the actual java.

(Do not touch anything in those 2 system directories. It should actually be impossible due to "System Integrity Protection" anyway.)

If you don't have Java installed, attempting to execute java will open a dialog that invites you to install it.

grischard

-- The following lines must be added to /usr/local/Cellar/osm2pgsql/HEAD/share/osm2pgsql/default.style
-- # Extras for create_osm_street_list.sql
-- way       postal_code       text       linear
-- way       alt_name          text       linear
-- way       name:lb           text       linear
-- way       alt_name:lb       text       linear
-- way       is_in:city        text       linear

DROP TABLE IF EXISTS road_names_osm;

lxe

Receive GOES-16 and GOES-17 Images with a Raspberry Pi and RTL-SDR dongle

Also see the original Pieter Noordhuis's guide

Hardware

You need:

1. Raspberry Pi Model B (or B+) with a MicroSD Card $35-40
2. An RTL-SDR dongle:

grischard

#!/usr/bin/env python
# -*- coding: utf-8 -*-

"""
Return GeoJSON centroids with population for each locality in Luxembourg.

BD-Adresses doesn't include communes, so we use the OpenStreetMap community's
csventrifuge output, which has been enriched. The output of this script is
© OpenStreetMap Contributors, see https://openstreetmap.org/copyright.

grischard

Firefishy

cd /path-to-dir/LUREF_NGL/; find . -type f -iname '*.tif' >input-files.txt
docker run -it --rm -v /path-to-dir/LUREF_NGL:/data osgeo/gdal:alpine-normal-v2.4.1 sh -l
(in docker) gdalbuildvrt -resolution highest -r nearest ANA_LUREF_NGL_DTM.vrt -input_file_list input-files.txt
# Rest not in docker...
gdaladdo -ro --config COMPRESS DEFLATE --config COMPRESS_OVERVIEW DEFLATE --config ZLEVEL 9 --config BIGTIFF_OVERVIEW IF_SAFER --config GDAL_TIFF_OVR_BLOCKSIZE 512 -r nearest ANA_LUREF_NGL_DTM.vrt 4 16 64 256 1024 4096
gdaldem hillshade ANA_LUREF_NGL_DTM.vrt lu_hillshade_2017.tif -co BIGTIFF=YES -co TILED=YES -co COMPRESS=DEFLATE -co GDAL_NUM_THREADS=ALL_CPUS -of GTiff -b 1 -z 1.0 -s 0.5 -az 315.0 -alt 45.0
gdaladdo -ro --config COMPRESS_OVERVIEW JPEG --config PHOTOMETRIC_OVERVIEW YCBCR --config INTERLEAVE_OVERVIEW PIXEL --config BIGTIFF_OVERVIEW IF_SAFER --config GDAL_TIFF_OVR_BLOCKSIZE 512 -r average lu_hillshade_2017.tif 4 16 64 256 1024 4096
gdalwarp -t_srs epsg:3857 -r lanczos -multi -wo NUM_THREADS=ALL_CPUS A

dannberg

---
created: <% tp.file.creation_date() %>
---
tags:: [[+Daily Notes]]

# <% moment(tp.file.title,'YYYY-MM-DD').format("dddd, MMMM DD, YYYY") %>

<< [[Timestamps/<% tp.date.now("YYYY", -1) %>/<% tp.date.now("MM-MMMM", -1) %>/<% tp.date.now("YYYY-MM-DD-dddd", -1) %>|Yesterday]] | [[Timestamps/<% tp.date.now("YYYY", 1) %>/<% tp.date.now("MM-MMMM", 1) %>/<% tp.date.now("YYYY-MM-DD-dddd", 1) %>|Tomorrow]] >>

---

aneesdev

<?php

trait EnhancedEnum
{
    /**
     * Get the enum value from the name. e.g case INVOICE = 'invoice'; will return 'invoice'
     *
     * @param  string  $name
     * @return static
     */