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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier6qtX3pFwXQZeBBx/wmapc
Repositorysid.inpe.br/banon/2002/12.03.10.31
Last Update2002:11.28.02.00.00 (UTC) administrator
Metadata Repositorysid.inpe.br/banon/2002/12.03.10.31.19
Metadata Last Update2022:06.14.00.12.27 (UTC) administrator
DOI10.1109/SIBGRAPI.2001.963061
Citation KeyPugsleyCruvCara:2001:NeAgDi
TitleNew agroclimatic digital images classification system and risk zone mapping
Year2001
Access Date2024, May 02
Number of Files1
Size770 KiB
2. Context
Author1 Pugsley, Luciano
2 Cruvinel, Paulo Estevão
3 Caramori, Paulo Henrique
EditorBorges, Leandro Díbio
Wu, Shin-Ting
Conference NameBrazilian Symposium on Computer Graphics and Image Processing, 14 (SIBGRAPI)
Conference LocationFlorianópolis, SC, Brazil
Date15-18 Oct. 2001
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Pages237-244
Book TitleProceedings
Tertiary TypeFull Paper
OrganizationSBC - Brazilian Computer Society
History (UTC)2008-07-17 14:10:54 :: administrator -> banon ::
2008-08-26 15:22:03 :: banon -> administrator ::
2009-08-13 20:37:15 :: administrator -> banon ::
2010-08-28 20:00:13 :: banon -> administrator ::
2022-06-14 00:12:27 :: administrator -> :: 2001
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsimage processing
classification
segmentation
AbstractThis paper presents a methodology to support farm decision-making by characterizing regional potential and climatic risks involved during agricultural crop cycles. It introduces agricultural zoning based on a system that classifies digital images of agroclimatic indices. The methodology uses as a first step analyses and processing of climatic data from weather stations through GIS tools. These results are interpolated to generate images of several limiting parameters of agricultural crops. In the second step, these images are segmented using techniques, such as regional growing segmentation by pixel aggregation and regional split/merging segmentation. By using the resulting description of characteristics, the system allows linking the region to recorded geodesic data, generating geo-referenced maps for data storage, information overjay, derivative maps, generation, and vector analyses of risk factors necessary in each image. Through arithmetic operations of digital images and risk analyses with parameter vector, the system generates a matrix of results corresponding to a single image of pseudoregions. These regions are merged into larger similar regions, following theoretical decision methods such as that for optimal statistical classification. As result, the system makes it possible to generate maps containing homogeneous zones with optimized planting dates.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2001 > New agroclimatic digital...
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/6qtX3pFwXQZeBBx/wmapc
zipped data URLhttp://urlib.net/zip/6qtX3pFwXQZeBBx/wmapc
Languageen
Target File237-244.pdf
User Groupadministrator
Visibilityshown
5. Allied materials
Next Higher Units8JMKD3MGPEW34M/46Q6TJ5
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2022/04.29.19.35 9
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
NotesThe conference was held in Florianópolis, SC, Brazil, from October 15 to 18.
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