LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Moharana, S.; Dutta, S. (2014)
Languages: English
Types: Article
Subjects:
Rice Agriculture, mainly cultivated in South Asia regions, is being monitored for extracting crop parameter, crop area, crop growth profile, crop yield using both optical and microwave remote sensing. Hyperspectral data provide more detailed information of rice agriculture. The present study was carried out at the experimental station of the Regional Rainfed Low land Rice Research Station, Assam, India (26.1400° N, 91.7700° E) and the overall climate of the study area comes under Lower Brahmaputra Valley (LBV) Agro Climatic Zones. The hyperspectral measurements were made in the year 2009 from 72 plots that include eight rice varieties along with three different level of nitrogen treatments (50, 100, 150 kg/ha) covering rice transplanting to the crop harvesting period. With an emphasis to varieties, hyperspectral measurements were taken in the year 2014 from 24 plots having 24 rice genotypes with different crop developmental ages. All the measurements were performed using a spectroradiometer with a spectral range of 350–1050 nm under direct sunlight of a cloud free sky and stable condition of the atmosphere covering more than 95 % canopy. In this study, reflectance collected from canopy of rice were expressed in terms of waveforms. Furthermore, generated waveforms were analysed for all combinations of nitrogen applications and varieties. A hierarchical clustering technique was employed to classify these waveforms into different groups. By help of agglomerative clustering algorithm a few number of clusters were finalized for different rice varieties along with nitrogen treatments. By this clustering approach, observational error in spectroradiometer reflectance was also nullified. From this hierarchical clustering, appropriate spectral signature for rice canopy were identified and will help to create rice crop classification accurately and therefore have a prospect to make improved information on rice agriculture at both local and regional scales. From this hierarchical clustering, spectral signature library for rice canopy were identified which will help to create rice crop classification maps and critical wave bands like green (519,559 nm), red (649 nm), red edge (729 nm) and NIR region (779,819 nm) were marked sensitive to nitrogen which will further help in nitrogen mapping of paddy agriculture over therefore have the prospect to make improved informed decisions.
  • No references.
  • No related research data.
  • No similar publications.

Share - Bookmark

Cite this article

Collected from