gmane.comp.gis.grass.user

Re: Natural breaks classification

Luigi Ponti — 2012-05-16T20:04:54

I am replying to myself as I may have omitted part of the answer -- my 
apologies. Start the same way:

     DTM.df <- as.data.frame(DTM)

then get variable names:

     names(deltaYieldVector.df)

then use the variable of interest (altitude, I guess):

     DTM_class <- classIntervals(DTM.df$varOfInterest, n=5, style="fisher")

This should work; we were feeding a data.frame as input to 
classIntervals, whereas a variable is needed (e.g. one of the variables 
in the data.frame).

Let me know how it goes.

Kind regards,

Luigi

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Re: Natural breaks classification

Luigi Ponti — 2012-05-16T19:10:26

I do not recall exactly, but it may be that classIntervals does not have 
a method for spatial data frames (i.e. the output of readRAST6). One 
thing I would try to get the breaks anyway, is a regular R data.frame, 
for example:

DTM.df <- as.data.frame(DTM)
DTM_class <- classIntervals(DTM.df, n=5, style="fisher")

Hope this helps,

Luigi
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Re: Natural breaks classification

Salvatore Mellino — 2012-05-16T18:55:08

Thanks,

I'm trying but I receive an error. 

1. In R I started the libraries spgarass6 and classInt 
2. I imported the DTM in R using           DTM <- readRAST6("DTM< at >mapset", ignore.stderr=TRUE)
3. I used the command                DTM_class <- classIntervals(DTM, n=5, style="fisher")             and I received the error

Error in classIntervals(DTM, n = 5, style = "fisher") : 
  var is not numeric


Any suggestion?

Salvatore


Il giorno 16/mag/2012, alle ore 17:58, Luigi Ponti ha scritto:


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Re: High-resolution agricultural land cover fromsatellite imagery

Luigi Ponti — 2012-05-16T16:59:28

Dear Markus

On 16/05/2012 14:19, Markus Neteler wrote:

Right. Sometimes I forget the secret weapon...


I had a feeling I was missing something important.

In the description of the two add-on modules, I found reference to two 
very interesting papers that triggered some more search. In particular, 
this conference paper by Stabile et al. (2009) on Fusion of 
High-resolution Aerial Orthophoto with LandSat TM Image for Improved 
Object-based Land-use Classification, uses the same data layers I may 
access (orthophoto + Landsat TM):
http://www.a-a-r-s.org/acrs/proceeding/ACRS2009/Papers/Oral%20Presentation/TS12-05.pdf

based on which, I wonder if it would make any sense to perform i.fusion e.g.

i.fusion.brovey -l ms1=lsat7_2002_20 ms2=lsat7_2002_40 \
                    ms3=lsat7_2002_50 pan=ortho_photo_rgb_composite \
                    outputprefix=brovey

and then use i.smap after i.gensigset (the use of group= and subgroup= 
parameters in both modules is a bit unclear to me) to classify the map 
using

Re: Natural breaks classification

Luigi Ponti — 2012-05-16T15:58:02

Hi Salvatore,

On 16/05/2012 17:38, Salvatore Mellino wrote:

I usually do that via the R package classInt
http://cran.r-project.org/web/packages/classInt/index.html

which requires using the GRASS-R interface. For a general overview of 
the integration, see
http://grass.osgeo.org/wiki/R_statistics

Kind regards,

Luigi
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Natural breaks classification

Salvatore Mellino — 2012-05-16T15:38:35

Hi,

I have a DTM raster map and I want to classify it in 5 classes by means of natural break method (http://en.wikipedia.org/wiki/Jenks_natural_breaks_optimization). Is it possible with GRASS.

Thanks,

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v.type

Patrick S. — 2012-05-16T14:36:08

Dear list,

first a feedback to the developers : Seems there has been a change to 
v.type?
"from_type" and "to_type" is now required, but the example still shows 
"type=from,to" as use case.

2.) using from_type=centroid and to_type=point does not create a point 
only layer, but still include boundaries. Any idea why?

patrick
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Re: High-resolution agricultural land cover fromsatellite imagery

Markus Neteler — 2012-05-16T12:19:15

...

You may use neural networks in R (using the GRASS-R interface).
For a general overview of the integration, see
http://grass.osgeo.org/wiki/R_statistics

...

As my master thesis, I wrote these two modules:

i.spec.sam: Spectral Angle mapping
http://grass.osgeo.org/wiki/Addons#i.spec.sam

i.spec.unmix: Spectral unmixing
http://grass.osgeo.org/wiki/Addons#i.spec.unmix

The latter needs proper update to GRASS 6 but that should not be too hard.

Markus
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Re: High-resolution agricultural land cover fromsatellite imagery

YAMADA,Yasuharu — 2012-05-16T09:01:39

Thank you for your reply.

And your quoted research paper(by Dr.Tatem,etc.) is very informative on me.
I can find "Superresolution Mapping Using a Hopfield Neural Network
With Fused Images" by Minh Q. Nguyen, Peter M. Atkinson, and Hugh G. Lewis,
IEEE Transaction on Geoscience and Remote Sensing, vol.44, No.3, pp736-749
(2006).


But I have never done neural network analysis on remote sensing visible
band data.  And I can find the function or tool of neural network analysis
only in the ENVI/IDL software package in my laboratory.


And I cannot find any tool or module on neural network analysis
in the GRASS software.


I will introduce some research paper for solving mixel problem as follows.
-------------------------------------------------------------------------------------
1.   Yoshiki Yamagata and Yoshifumi Yasuoka (1996) “Unmixing wetland vegetation types by subspace method using hyperspectral CASI image”, Int. Archives of Photogrammetry and remote
Sensing, 31(７), pp.781-787

2. The VSW index meth

Re: Calculate stream order from digitized hydrologynetwork

Filipe Silva Dias — 2012-05-15T21:19:31

Done

http://trac.osgeo.org/grass/ticket/1657

On Tue, May 15, 2012 at 10:15 PM, Markus Neteler <neteler< at >osgeo.org> wrote:

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Re: Calculate stream order from digitized hydrologynetwork

Markus Neteler — 2012-05-15T21:15:15

I have now added a new "Addons" component in trac.

Markus
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Re: Calculate stream order from digitized hydrologynetwork

Margherita Di Leo — 2012-05-15T12:55:37

It's the same bug tracker of main code: http://trac.osgeo.org/grass/
You can just indicate the keyword "add-ons".
Thank you for collaboration.

madi

On Tue, May 15, 2012 at 1:14 PM, Filipe Silva Dias <filipesdias< at >gmail.com>wrote:

Re: Calculate stream order from digitized hydrologynetwork

Filipe Silva Dias — 2012-05-15T12:11:04

Thanks Daniel
Easy and simple and it worked perfectly =)
Best

On Tue, May 15, 2012 at 12:36 PM, Daniel Victoria <daniel.victoria< at >gmail.com

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Re: Calculate stream order from digitized hydrologynetwork

Daniel Victoria — 2012-05-15T11:36:45

There is a software from the people at Rio de Janeiro State University
that should do what you want. It's called HydroFlow

http://www.fgel.uerj.br/labgis/hydroflow/en/index_ingles.htm

I used it once and it's quite simple to run. Results are also very
good but you can't have loops in your drainadge.

Better yet, it's open source :)

Cheers
Daniel

On Tue, May 15, 2012 at 8:14 AM, Filipe Silva Dias
<filipesdias< at >gmail.com> wrote:
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Re: Calculate stream order from digitized hydrologynetwork

Filipe Silva Dias — 2012-05-15T11:14:24

Sure, is there a bug tracker for grass gis extensions...?

On Tue, May 15, 2012 at 11:39 AM, Margherita Di Leo <diregola< at >gmail.com>wrote:

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Re: Calculate stream order from digitized hydrologynetwork

Margherita Di Leo — 2012-05-15T10:39:21

Hi Filipe,

could you fill a bug report reporting this? Thanks

Best,
madi

On Mon, May 14, 2012 at 3:53 PM, Filipe Silva Dias <filipesdias< at >gmail.com>wrote:

Re: Calculate stream order from digitized hydrologynetwork

Filipe Silva Dias — 2012-05-15T09:41:56

I found a similar question here:

http://gis.stackexchange.com/questions/22735/how-to-calculate-stream-order-for-vector-data-without-a-dem



On Mon, May 14, 2012 at 2:53 PM, Filipe Silva Dias <filipesdias< at >gmail.com>wrote:

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Re: High-resolution agricultural land cover fromsatellite imagery

Luigi Ponti — 2012-05-15T08:20:40

Dear 山田 康晴,

Thanks for your kind reply.

On 15/05/2012 03:18, 山田 康晴 wrote:
The reason is that I found that paper I cited in my previous email
(Tatem et al. 2003;
<http://eprints.soton.ac.uk/260104/1/tatem_tgis.pdf>), which described a
way to increase resolution of land cover. I thought higher resolution
would be a good thing because of the highly fragmented agricultural
landscape I was targeting (the paper by Tatem and colleagues also
analyzes an area with small-scale agriculture in Greece).
I have accessed the grass-user mailing list seeking for a possible
GRASS-based approach to the task. Hence, I would be very glad if you
could point to a couple of the research papers you refer to.
Yes, I am based in Italy and my background is mostly in applied ecology.
Of course people at ESA are expert in the field. My goal when accessing
this mailing list was to see if more GRASS-related info on the topic
would emerge that may benefit me and other GRASS users.

Kind regards and thank you,

Luigi


____

Re: High-resolution agricultural land cover fromsatellite imagery

山田康晴 — 2012-05-15T01:18:52

I wonder why you want to use the Landsat TM data for the analysis of
the high resolusion agricultural land cover.


The Landsat TM, not ETM, has very long histry and is not the High-resolution
 data as for both spatial and frequential points of view.
There are so many research papers for the analysis on agricultural
land cover.

The "esa" or Italy scientists must have much information for your interest.
Are you a scientist in Italy?




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Re: [GRASS-user] Re: XYZ Data (UTM32N) workflow to DEM and reprojection to Gauß Krüger 3

Hamish — 2012-05-14T21:32:22

Hi,

just to add to what others have already said; it is better to
reproject to your target projection _before_ doing the
rasterization step, that way you avoid the generational loss
from r.proj. Try to import them directly as points into your
target location.

So methods could be:

xyz.txt -> v.in.ascii -> v.proj -> v.surf.rst
 (for many millions of input points use the v.in.ascii -zbt flags)

or

xyz.txt -> m.proj (or cs2cs) -> r.in.xyz -> r.surf.nnbathy (addon)


r.in.xyz is very good at creating DEM cells at points with known
data, but it does not do any interpolation, you need the
r.surf.nnbathy module (or another r.surf.* or v.surf.* module)
to fill in the gaps.


good luck,
Hamish
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Re: From GRASS to postgis - srid 900914 using v.out.ogr

Markus Neteler — 2012-05-14T19:21:10

While I would not expect that/if so consider it to be a bug, could you try to
enable debug output?

g.gisenv set=DEBUG=3

The output may give ideas.

Use
g.gisenv set=DEBUG=0
to disable then debug output.

Markus


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