geospatial-data

See below; version 2.4.2 from the ubuntugis ppa.

Expected output is just the version information, no crash.

$ gdal2tiles.py --version
GDAL 2.4.2, released 2019/06/28
Traceback (most recent call last):
  File "/usr/bin/gdal2tiles.py", line 2927, in <module>
    main()
  File "/usr/bin/gdal2tiles.py", line 2917, in main
    input_file, output_folder, options = process_args(argv[1:])

Is there a way to know when the imagery was collected? I assume sometime in the daylight hours, and probably recently(?) but I have no way of knowing by looking at the output and the associated image.

Can that output be put in the CLI output or some other metadata file that gets associated with the LC####### directory?

A small thing, and not very important, but it seems redundant to end every episodes title with "in R" since the name of the lesson is "Introduction to Geospatial Raster and Vector Data with R" and all the episodes use R. Furthermore, there are three episodes that don't say "in R" that do in fact use R....

Expected behavior and actual behavior

Cropping any raster with any GeoVector should work. Instead, if the GeoVector is bigger than the world, an error is raised.

simple_world.geojson.zip

Steps to reproduce the probl

Investigate how to build a .deb installer.

In previous experience teaching dplyr I have found that using Hadley Wickham's split-apply-combine language has helped students understand the power of dplyr, and might make some of the later exercises (and diagrams) easier to understand.

It would be very useful to create a template for the schedule of a geospatial workshop to be used in the workshop website. This schedule should be added to this file: https://github.com/carpentries/workshop-template/blob/gh-pages/_includes/dc/schedule.html

Aug	SEP	Oct
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2019	2020	2021

geospatial-data

Here are 149 public repositories matching this topic...

OSGeo / gdal

plant99 / felicette

geoman-io / leaflet-geoman

ResidentMario / geoplot

locationtech / geowave

acgeospatial / awesome-earthobservation-code

jorisvandenbossche / geopandas-tutorial

Unidata / thredds

Azure / pixel_level_land_classification

osmlab / atlas

rh389 / dynamodb-geo.js

opengeospatial / ogcapi-features

linwoodc3 / gdeltPyR

corteva / rioxarray

koordinates / sno

datacarpentry / r-raster-vector-geospatial

halestudio / hale

unicef / magicbox

sevar83 / android-spatialite

satellogic / telluric

Expected behavior and actual behavior

Steps to reproduce the probl

carpentrieslab / python-aos-lesson

nasa-jpl-memex / GeoParser

creare-com / podpac

TrainingByPackt / Data-Visualization-with-Python

datadesk / census-map-consolidator

TerraME / terrame

datacarpentry / r-intro-geospatial

datacarpentry / geospatial-workshop

agrc / forklift

unicef / magicbox-open-api

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