[GRASS-user] High-resolution agricultural land cover from satellite imagery

[YAMADA,Yasuharu]

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 method and its algorism by Yoshiki Yamagata, et al
    The Journal of the Remote Sensing Society of Japan (in Japanese), 17(4), pp.54-64(1997)

3. David A. Landgrebe (2003) "Signal Theory Methods in Multispectral Remote Sensing",
    Wiley Series in Remote Sensing book ISBN 0-471-42028-X
   There is some explanations for the hyper spectral remote sensing data analysis,
   such as the Spectral Angle Mapper(SAM). And this book is the manual of "MultiSpec",
   a kind of open source software.
   https://engineering.purdue.edu/~biehl/MultiSpec/
   When I sent my e-mail to the Purdue university developing team, Dr. David A.
  Landgrebe, professor emeritus of Purdue university, directly replied to my question.
-------------------------------------------------------------------------------------

 Thank you.


(2012/05/15 17:20), Luigi Ponti wrote:
> Dear 山田 康晴,
> 
> Thanks for your kind reply.
> 
> On 15/05/2012 03:18, 山田 康晴 wrote:
>> I wonder why you want to use the Landsat TM data for the analysis of
>> the high resolusion agricultural land cover.
> 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).
>>
>> 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.
> 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.
>>
>> The "esa" or Italy scientists must have much information for your interest.
>> Are you a scientist in Italy?
> 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
> 
>>
>>
>>> We are targeting an agricultural area in southern Italy (several
>>> thousands hectares) for which we have full orthophoto coverage (0.5
>>> meters resolution), and Landsat TM data can apparently be downloaded
>>> freely from<http://glcf.umd.edu/data/landsat/>. High-resolution
>>> agricultural land cover might seem overkill, but the area is highly
>>> fragmented and hence standard CORINE land cover data tend to classify
>>> most of the land as mixed types (not very helpful).
>>>
>>> I would like to ask a general recommendation on the best way to approach
>>> an agricultural land cover task such as the one outlined above, together
>>> with possible info on previous implementation of increasing spatial
>>> resolution of agricultural land cover maps in GRASS via neural networks
>>> or other approaches.
>>>
>>> Kind regards, thanks in advance and apologies for a long post,
>>>
>>> Luigi
>>> _______________________________________________
>>> grass-user mailing list
>>> grass-user at lists.osgeo.org
>>> http://lists.osgeo.org/mailman/listinfo/grass-user
>>
>>
>>
> 
> 
> 

-- 
-------------------------------------------
Yasuharu Yamada
Chief Researcher,
Research Project for Resources Information Technology,
NIRE, NARO Japan
yamaday at affrc.go.jp
http://nkk.naro.affrc.go.jp/
----------------------------------------------------------------------------------
This e-mail is intended only for the designated recipient(s) and may
contain confidential information. Please don't forward the message
to the other person(s) or place(s) without prior notice.