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Wheat Yield Prediction through Spectral Indices, Using Agro-Meteorological Data
| Content Provider | Scilit |
|---|---|
| Author | Benipal, Amanpreet Kaur Sood, Anil |
| Copyright Year | 2021 |
| Description | Agro-meteorological parameters define the agricultural productivity of any region. The impact of agro-meteorological parameters on wheat production was studied using remote sensing and GIS for the Rabi season in drought and wet years in 2007–08 and 2010–11, respectively, in the Shaheed Bhagat Singh Nagar (SBS) district of Punjab, India. After classification of the images, pixels related to the wheat crop were grouped together to generate the wheat mask which was used to study the profile of crop growth and to generate the profile for spectral indices. The yields predicted with the spectral index models were close to the actual yield (% relative deviation, RD < 2.5%) for both years. The % RD was maximal in the case of Normalized Difference Vegetation Index (NDVI) for both years (−2.31% in 2007–08 and −2.14% in 2010–11), whereas the Infrared Percentage Vegetation Index (IPVI) predicted the yield with the lowest % RD for both years, namely 2007–08 (RD = −0.21%) and 2010–11 (RD = −0.59%), indicating that, of the spectral indices, IPVI is the best for yield prediction of wheat in the study area. Book Name: Re-envisioning Remote Sensing Applications |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2020-0-12750-8&isbn=9781003049210&doi=10.1201/9781003049210-3&format=pdf |
| Ending Page | 40 |
| Page Count | 24 |
| Starting Page | 17 |
| DOI | 10.1201/9781003049210-3 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2021-02-17 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Re-envisioning Remote Sensing Applications Remote Sensing Drought Spectral Indices Agro Meteorological Data Predicted the Yield |
| Content Type | Text |
| Resource Type | Chapter |
