Study on probabilistic neural network for extracting remote sensing information of rice planting area
In order to improve the extraction precision of rice planting area, multitemporary remote sensing images chosen based on the growth stages of rice were performed atmospheric correction and geometric rectification. The fusion algorithms which are used to select the optimal bands combination include s...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2007-11-01
|
| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/1008-9209.2007.06.0691 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849247479515578368 |
|---|---|
| author | YANG Xiao-hua HUANG Jing-feng |
| author_facet | YANG Xiao-hua HUANG Jing-feng |
| author_sort | YANG Xiao-hua |
| collection | DOAJ |
| description | In order to improve the extraction precision of rice planting area, multitemporary remote sensing images chosen based on the growth stages of rice were performed atmospheric correction and geometric rectification. The fusion algorithms which are used to select the optimal bands combination include single band statistic, principal component transformation and ratio transformation. The basic algorithm and theory of the PNN (probabilistic neural network) were analyzed, and it was applied to classify the image of the optimal bands combination. The classified result was compared with those of BP (back propagation) neural network and minimum-distance method. Results show that the classification precision of PNN is higher than that of minimum-distance by 6 percentage points, and BP by 13 percentage points. As for the precision of rice planting area extraction, the PNN's extraction precision is higher than that of minimum-distance by 15 percent points. Therefore, PNN is an effective method for classification of remote sensing images, and it plays a unique role in extracting the crops planting area. |
| format | Article |
| id | doaj-art-6b01738378dc47d29ccabf95417d45a2 |
| institution | Kabale University |
| issn | 1008-9209 2097-5155 |
| language | English |
| publishDate | 2007-11-01 |
| publisher | Zhejiang University Press |
| record_format | Article |
| series | 浙江大学学报. 农业与生命科学版 |
| spelling | doaj-art-6b01738378dc47d29ccabf95417d45a22025-08-20T03:58:11ZengZhejiang University Press浙江大学学报. 农业与生命科学版1008-92092097-51552007-11-013369169810.3785/1008-9209.2007.06.069110089209Study on probabilistic neural network for extracting remote sensing information of rice planting areaYANG Xiao-huaHUANG Jing-fengIn order to improve the extraction precision of rice planting area, multitemporary remote sensing images chosen based on the growth stages of rice were performed atmospheric correction and geometric rectification. The fusion algorithms which are used to select the optimal bands combination include single band statistic, principal component transformation and ratio transformation. The basic algorithm and theory of the PNN (probabilistic neural network) were analyzed, and it was applied to classify the image of the optimal bands combination. The classified result was compared with those of BP (back propagation) neural network and minimum-distance method. Results show that the classification precision of PNN is higher than that of minimum-distance by 6 percentage points, and BP by 13 percentage points. As for the precision of rice planting area extraction, the PNN's extraction precision is higher than that of minimum-distance by 15 percent points. Therefore, PNN is an effective method for classification of remote sensing images, and it plays a unique role in extracting the crops planting area.https://www.academax.com/doi/10.3785/1008-9209.2007.06.0691probabilistic neural networkremote sensingimage classification |
| spellingShingle | YANG Xiao-hua HUANG Jing-feng Study on probabilistic neural network for extracting remote sensing information of rice planting area 浙江大学学报. 农业与生命科学版 probabilistic neural network remote sensing image classification |
| title | Study on probabilistic neural network for extracting remote sensing information of rice planting area |
| title_full | Study on probabilistic neural network for extracting remote sensing information of rice planting area |
| title_fullStr | Study on probabilistic neural network for extracting remote sensing information of rice planting area |
| title_full_unstemmed | Study on probabilistic neural network for extracting remote sensing information of rice planting area |
| title_short | Study on probabilistic neural network for extracting remote sensing information of rice planting area |
| title_sort | study on probabilistic neural network for extracting remote sensing information of rice planting area |
| topic | probabilistic neural network remote sensing image classification |
| url | https://www.academax.com/doi/10.3785/1008-9209.2007.06.0691 |
| work_keys_str_mv | AT yangxiaohua studyonprobabilisticneuralnetworkforextractingremotesensinginformationofriceplantingarea AT huangjingfeng studyonprobabilisticneuralnetworkforextractingremotesensinginformationofriceplantingarea |