Difference between revisions of "Pforzheim, Germany"

From Geohashing
imported>Ekorren
(Tempted to delete the Land usage data. The whole concept is entirely broken, sorry.)
imported>Koepfel
(done that)
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''most recent first''
 
''most recent first''
 
*[[2009-09-08 48 8|2009-09-08]]: [[User:Ekorren|Ekorren]] considers to go to Dornstetten, depending on weather and actual motivation.
 
*[[2009-09-08 48 8|2009-09-08]]: [[User:Ekorren|Ekorren]] considers to go to Dornstetten, depending on weather and actual motivation.
*[[2009-09-05 48 8|2009-09-05]]: [[User:Koepfel|Koepfel]] will try to reach the Hashpoint near Mühlacker, ETA ~11:30 (and then continue to 48 7)..
+
*[[2009-09-05 48 8|2009-09-05]]: [[User:Koepfel|Koepfel]] biked from Mühlacker to the hashpoint in a nearby forest.
 
*[[2009-08-22 48 8|2009-08-22]]: [[User:Ekorren|Ekorren]] found beautiful lakes and lots of trees in another Black Forest valley.
 
*[[2009-08-22 48 8|2009-08-22]]: [[User:Ekorren|Ekorren]] found beautiful lakes and lots of trees in another Black Forest valley.
 
*[[2009-08-11 48 8|2009-08-11]]: [[User:Koepfel|Koepfel]] found the Hashpoint on a path near Spielberg, about 4 kilometers away from the previous one.
 
*[[2009-08-11 48 8|2009-08-11]]: [[User:Koepfel|Koepfel]] found the Hashpoint on a path near Spielberg, about 4 kilometers away from the previous one.

Revision as of 23:27, 6 September 2009

Kaiserslautern Mannheim Würzburg
Strasbourg, France Pforzheim Stuttgart
Basel, Switzerland Zürich, Switzerland Sankt Gallen, Switzerland

Today's location: geohashing.info google osm bing/os kml crox

Today's Location: [Pforzheim, Germany]

About

The Pforzheim, Germany graticule contains Karlsruhe (South), Pforzheim and Villingen-Schwenningen as the biggest cities and the northern and middle parts of the Black Forest as dominant landscape feature.

Hashing in this graticule can get challenging for high elevation differences and steep slopes, but if you bring a bike or like a long walk, there aren't many places you can't reach.

According to Land usage, the chance for your hash to fall into one of the following areas is:

58.28%	"Natural reserves" (mostly mountain forests, and not quite really reserves)
20.93%	Fields
13.31%	Forests
3.97%	Near roads
1.79%	Near highways
1.54%	Settlements
0.19%	Water

According to reality, it's totally different than that, because the Land Usage script is based on data which is entirely unsuited for this purpose.

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