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pcplantdb - Re: [pcplantdb] Re: openGIS / locales

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  • From: Richard Morris <webmaster@pfaf.org>
  • To: Permaculture Plant Database <pcplantdb@lists.ibiblio.org>
  • Subject: Re: [pcplantdb] Re: openGIS / locales
  • Date: Mon, 28 Mar 2005 11:30:16 +0100

Sean Maley wrote:
Zip codes come with latitude and longitude, but many
international postal codes don't. However, the
formula calculating distance is fairly simple. Even
better is if we can get GPS savvy users. The GPS not
only gives better accuracy to lat/long than postal
codes, but also includes altitude. Throw in some
weather gadgets and an accurate micro-climate picture
can be developed over time for any given locality. On
the exreme end of sensor automation, we get pretty far
out of scope for PIW, which I'm still not sure where
the real scope ends anyway.

I've been mulling this over a bit and heres a few ideas about how
i'd do it. Assumes superb data resources, infinite coding time etc.

First we need to seperate positions from properties. We really have two things:
1) physical locations:
lat-long coordinates,
post code/zipcode regions
names of states, countries regions
bio regions
native ranges of a particular plant
2) Properties about these regions:
max/min temp
altitude
plants who's native habitat is in specific place
properties of a plant in that region (ie when it typically
flowers)

Physical locations have two different types
spot coordinates, define a single location (lat/long).
regions, define an area.

Spot coordinates are easy to represent, just use two
coordinates, latitude and longitude seem obvious.

Regions can be represented as a closed polygon whos boundary
is the boundary of the region

* --------------*
| \
| \
| *
* /
\ /
* ------------*

the corners (or verticies) of the polygon are just spot coordinates.

Hopefully we can get data from the web for most of the regions
we're interested in (countries, postcodes).

There is a lot of fun stuff we can do with this data
find which regions are inside which other region
find overlapping regions
find which regions contain a particular spot
cordinate
theres some well know algorithms for doing the above.

In terms of searching a user could
input the name of a particular region
find all the regions which are contained
within that region
find all the plants in the region
or
input a particular spot coordinate
find regions containing that coordinate
find plants which could grow in that position

Once we have regions sorted is then working out the types of relationships we might have with the regions. Trickiest
is features which depend on both the plant and the region
i.e. max height of plant in that position.

The above does make mean that we need to find a lot of data giving the boundaries of regions, but it seems like there is some open content data on this about.

Reactions?

Rich





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