GEO SPATIAL TECHNOLOGIES FOR CROP IDENTIFICATION

We have taken up the challenge of crop identification and to analyze the difference between paddy and sugarcane. So as to get accurate and faster estimation of crop area which is very essential for area-based subsidies and helps in deciding agriculture policies .The outcomes of the analysis made the team understand various parameters to identify crop.

The android application “kriti demo” is given to us. which collects the GPS coordinates of specific field crop.LANDSAT-8(OLI) image of Anakapalli (March, April, and May 2018) is taken.

NDVI & MSAVI – indexes indicating vegetation with in a threshold values using raster calculater.

                                        

                                                                                             

We apply threshold value to identify the chlorophyll content. For example , the ndvi vale is 0.09479 to 0.32475 then the range given to apply threshold is >0.18.It converts in to binary as 0 and 1.

0 = black (condition unsatisfied); 1 = white(condition satisfied).

The graph showing the variations in range of MSAVI and NDVI for paddy along three months march, April and May.The paddy is cultivated in Rabi and Kharif seasons. Rabi  crop is harvested  in march-may and sowed in Oct-nov. Kharif crop is harvested in sept-oct and sowed in june-july.According to the graph,the values of Msavi and NDVI are maximum in march and april decrease in may.It shows that as the paddy ripening the chlorophyll content decreases.

The graph showing the variations in range of MSAVI and NDVI for sugarcane along three months march,april and may. Sugarcane is a commercial crop.Sugarcane Seed is grown from march/april/may/june to December.According to the graph the values of MSAVI and NDVI are minimum in march and gradually increase towards may.It shows that the chlorophyll content increase.

CONCLUSION:

This analysis is useful to get accurate and faster estimation of crop area which is very essential for area-based subsidies and helps in deciding agriculture policies. This can be useful to agricultural department.

komali

Komali Avirneni

Being a girl born from an agricultural family I am interested in agriculture related problems.So I have chosen to use spatial data for crop identification to improve accuracy and speed in estimation of crop area  which is very essential for area-based subsidies in India.

Godi Sai Kiran

Working with kaiinos was a good opportunity for me.This analysis gave me the exposure how to use open data and open source softwares for solving the problems in agricultural sector. As a student this exercise helped me to gain knowledge on data driven analysis.

Krishna Cheekatla

In agriculture, farmers cultivate various crops according to rainfall and soil type in that area.Machine learning can be used to estimate acreage of crops in large areas.We used open data from NASA for our work where we tried to differentiate paddy with sugar cane.
Crop Classification
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