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Estimation of Net Rice Production by Remote Sensing and Multi Source Datasets

Estimation of Net Rice Production by Remote Sensing and Multi Source Datasets

Syed Muhammad Hassan Raza1*, Syed Amer Mahmood1, Syeeda Areeba Gillani1, Syed Shehzad Hassan1, Muneeb Aamir1, Muhammad Saifullah1, Mubashar Basheer1, Atif Ahmad1, Saif-ul-Rehman2 and Tariq Ali1 

1RS/GIS group, Space Science Department, Punjab University Lahore, Pakistan; 2Department of Geography Government College University Lahore.

smhn72@gmail.com  

Figure 1

 Map of Punjab province in Pakistan.

Figure 2

Flow of methodology 

Figure 3

A composite containing 15 bands. 

Figure 4

Linear regression applied to NDVI values and the CRS reported yield. 

Figure 5

Linear regression applied to RVI values and the CRS reported yield. 

Figure 6

Relationship between NDVI and RVI based yield values. 

Figure 7

Spatio-temporal extent of rice cultivation from 2008-2016. 

Figure 8

A comparison of rice areas. 

Figure 9

Linear regression applied to satellite verses CRS reported rice areas. 

Figure 10

Variations in NDVI throughout the rice growth period including pre-plantationflooding,_vegetative stage, reproductive stage and the ripening stage. 

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Sarhad Journal of Agriculture

September

Vol.40, Iss. 3, Pages 680-1101

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