抄録
The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.
| 元の言語 | English |
|---|---|
| ホスト出版物のタイトル | Information Modelling and Knowledge Bases XXIX |
| 編集者 | Naofumi Yoshida, Chawan Koopipat, Yasushi Kiyoki, Petchporn Chawakitchareon, Aran Hansuebsai, Virach Sornlertlamvanich, Bernhard Thalheim, Hannu Jaakkola |
| 出版者 | IOS Press |
| ページ | 176-187 |
| ページ数 | 12 |
| ISBN（電子版） | 9781614998334 |
| DOI | |
| 出版物ステータス | Published - 2018 1 1 |
| イベント | 27th International Conference on Information Modelling and Knowledge Bases, EJC 2017 - Krabi, Thailand 継続期間: 2017 6 5 → 2017 6 9 |
出版物シリーズ
| 名前 | Frontiers in Artificial Intelligence and Applications |
|---|---|
| 巻 | 301 |
| ISSN（印刷物） | 0922-6389 |
Conference
| Conference | 27th International Conference on Information Modelling and Knowledge Bases, EJC 2017 |
|---|---|
| 国 | Thailand |
| 市 | Krabi |
| 期間 | 17/6/5 → 17/6/9 |
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ASJC Scopus subject areas
- Artificial Intelligence
これを引用
An application of multispectral semantic-image space for global farming analysis and crop condition comparisons. / Wijitdechakul, Jinmika; Kiyoki, Yasushi; Sasaki, Shiori.
Information Modelling and Knowledge Bases XXIX. 版 / Naofumi Yoshida; Chawan Koopipat; Yasushi Kiyoki; Petchporn Chawakitchareon; Aran Hansuebsai; Virach Sornlertlamvanich; Bernhard Thalheim; Hannu Jaakkola. IOS Press, 2018. p. 176-187 (Frontiers in Artificial Intelligence and Applications; 巻 301).研究成果: Conference contribution
}
TY - GEN
T1 - An application of multispectral semantic-image space for global farming analysis and crop condition comparisons
AU - Wijitdechakul, Jinmika
AU - Kiyoki, Yasushi
AU - Sasaki, Shiori
PY - 2018/1/1
Y1 - 2018/1/1
N2 - The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.
AB - The global environmental analysis system is a new platform to analyze environmental multimedia data that acquired from nature resources. This system aims to realize and interpret environmental phenomena and changes occurring that happening in world wide scope. Semantic computing is important and promising approach to multispectral semantic-image analysis for various environmental aspects and contexts in physical world. In the previous study, we proposed a new system of agricultural monitoring and analysis based on semantic computing concept that it realizes the interpretation of agricultural health condition as human-level interpretation. In this paper, we propose a new analytical method for agriculture global comparisons to realize and recognize crop condition with several places in global scale. Multispectral semantic-image space for agricultural analysis can be utilized for global crop health monitoring by comparing crop conditions among different places. Our method applies semantic distance calculation to measure similarity among multispectral image data to realize the crop health condition as a ranking. According to our new proposed analytical method, we demonstrate a prototype implementation in the case of rye farm in Latvia and Finland. This prototype implementation shows an analysis in the case that image data have same crop type and conditions.
KW - Agricultural monitoring
KW - Global farming analysis
KW - Semantic computing
KW - UAV-multispectral sensor
UR - http://www.scopus.com/inward/record.url?scp=85063365128&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85063365128&partnerID=8YFLogxK
U2 - 10.3233/978-1-61499-834-1-176
DO - 10.3233/978-1-61499-834-1-176
M3 - Conference contribution
AN - SCOPUS:85063365128
T3 - Frontiers in Artificial Intelligence and Applications
SP - 176
EP - 187
BT - Information Modelling and Knowledge Bases XXIX
A2 - Yoshida, Naofumi
A2 - Koopipat, Chawan
A2 - Kiyoki, Yasushi
A2 - Chawakitchareon, Petchporn
A2 - Hansuebsai, Aran
A2 - Sornlertlamvanich, Virach
A2 - Thalheim, Bernhard
A2 - Jaakkola, Hannu
PB - IOS Press
ER -