全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...
-  2019 

USE OF CANOPY REFLECTANCE AT DIFFERENT GROWTH STAGE FOR ESTIMATION WHEAT YIELD

Full-Text   Cite this paper   Add to My Lib

Abstract:

It is difficult to predicting grain yield of wheat for a large area because the relationship may not be stable even if information on surface cover type is used. Remote sensing observations were found successful for reliable and quantitative estimates of canopy biophysical properties. Keeping this in view a study was planned in village Halali of district Raisen. The study area belongs to eastern part of the fertile Vindyanchal Plateau. This study has been done for the data collected during humid subtropical climate with cool, dry winter’s a hot summer and a humid monsoon season. The plant bio physical parameters were taken from LAI meter, Chlorophyll meter and Spectroradiometer. These parameters were taken as input parameters for PROSIAL model. The output of this model was recorded as simulated data. The simulated data & ground data were used to get R2 by linear correlation. Relationships between wave length and spectral response were drawn by relative spectral response (RSR) for 2nm intervals using Lagrange’s interpolation scheme. The empirical regression models were developed for the study area by using in situ field observation and LAI was calculated during growing to harvesting crop season 2015-2016. The spatial resolution of AWiFS (56m) was adequate enough to ensure relatively accurate retrials of LAI of wheat crop at regional scale. The AWiFS has a 5- days revisit period which may cause loss of data due to persistent cloud or fog and to assess. However, the Resoures at-2 increases the possibility to get clear sky data availability. The linear correlation between simulated and ground data during the wheat growing season gave high coefficient of determination (R2= 0.99) in SWIR band

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413