Wheat Yield Calculation Based on Remote Sensing in Saharsa (Bihar) - 2022

Yield calculation of the crop is very important for assessing the production and it depends on many variables like soil, weather, agricultural practices (date of planting, amount of irrigation and fertilizer use), seeds, pests, weeds and biotic stress.

Remote sensing provides an effective and efficient way to forecast yield. Remote sensing has been widely used by many institutions across world to calculate area and yield of a crop.

In this paper, we focus on forecasting yield of wheat based on data from Sentinel-2 satellite data. The study area was wheat crop in Saharsa (Bihar). The crop is in advanced stage and has vegetated fully and harvest is expected in next 20-30 days.

Methodology:

Data from Sentinel-2 was used and random fields were selected from the mapped area and yield was calculated using NDVI (Normalized Difference Vegetation Index) and LAI (Leaf Area Index).

Farmonaut platform was used to map fields to create bounded regions (fields) as shown in Figure-1. On the dates of observations the sample fields were free from clouds and normal data was observed. Crop classification was done manually by ground truthing to ascertain the crop is standing in the field.

Figure-1              Comparison of peak NDVI in 2022 Vs 2021 wheat crop

Maximum NDVI was used to calculate yields for the given fields which means peak vegetative growth rate. Peak vegetative growth helps to forecast yields more accurately.

Below are the observations of NDVI of the various fields. The maximum NDVI was reached on 8-March-2022 compared to 21 Feb 2021 which was used to calculate yield. From the maximum NDVI, LAI was calculated which was subsequently used to calculate yield. This approach is being used after going through a lot of available texts and final model was considered.

In this procedure the estimated LAI was used with WTGROWS model for yield mapping. This model suggests direct correlation between grain yields and LAI. This relationship was applied to all the fields to calculate yields.

NDVI started to rise after planting of crop in November continued to rise until 08-March-2022 making the data as best date for calculating yield. The NDVI started falling after 08-March-2022 and will fall until harvest. Best results of yield is obtained when the NDVI is maximum.  

NDVI and LAI showed the best correlation for the estimated yields. The yields ranged from 2.87 Tons/ha to 2.98 Tons/ha compared to 3.5 Tons/ha to 3.7 Tons/ha last year (2021).  

 

Figure-2

 

Area (sq. m.)

26-Feb-22

03-Mar-22

08-Mar-22

13-Mar-22

Maximum LAI

Estimated Yield  Kg/ha

Field 1

3600

0.4

0.5

0.5

0.44

1.827376043

2981

Field 2

7700

0.4

0.5

0.5

0.43

1.827376043

2981

Field 3

1500

0.4

0.48

0.5

0.45

1.827376043

2981

Field 4

3100

0.4

0.49

0.5

0.43

1.827376043

2981

Field 5

6600

0.4

0.44

0.49

0.4

1.785290384

2944

Field 6

2700

0.39

0.43

0.47

0.4

1.704004521

2871

Field 7

2000

0.4

0.48

0.49

0.42

1.785290384

2944

Field 8

4300

0.4

0.44

0.48

0.41

1.744173984

2908

Field 9

1700

0.4

0.46

0.5

0.44

1.827376043

2981

Field 10

3700

0.4

0.49

0.5

0.48

1.827376043

2981

 

Figure-3

Observations

The delay in Max NDVI occurred due to late planting of wheat crop as rains in during the planting due to cyclones led to delay in planting. Moreover, rains in vegetative stage of crop led to worsening of condition of the crop.

Also, the average max temperature in the crop season was below corresponding period last year and humidity and cloud cover was significantly higher in 2021-22 leading to less sunlight on the crop thereby affecting the quality of crop and lower yields. Higher humidity leads to frost and less sunlight in winter. Also, more cloud cover leads to lower temperature and less sunlight which directly affects the crop. Even wind speed was higher in the season.

In the Figure 1, there is comparison of peak NDVI of 2021-22 wheat crop vs 2020-21 white crop showing that last year wheat crop was in much better condition that current year and the average yield was 3.7 Tonnes/Hectare in the above plot while this year the average yield in the above 10 fields are 3.0 Tonnes/Hectare which is approximately 20% below last year. The data was corroborated with discussion with Krishi Vigyan Kendra- Saharsa which said the peak crop yield will fall from 4.5 Tonnes/Hectare to 3.7 Tonnes/Hectare which is approximately 20% lower than last year. Late planting, rains before planting, after planting, higher cloud cover, lower temperature, higher humidity and higher wind speed led to lower yield in current year. The crop will be ready to harvest by mid-April-2022 compared to start of April last year.

 

Date

Min. Temp (C)

Max. Temp (C)

Humidity (%)

Pressure (hPa)

Cloud Cover (%)

Wind Speed (m/s)

21-02-2021

21

27

27

1018

0

4.43

08-03-2021

21

31

39

1010

0

4.08

13-03-2021

23

32

49

1013

68

4.22

 

 

 

 

 

 

 

21-02-2022

17

24

38

1012

1

2.68

08-03-2022

18

33

32

1009

0

2.64

13-03-2022

23

28

26

1009

0

2.86

 

 

 

 

 

 

 

2020-21 (1 Dec-Mar 10)

18.80

22.98

41.99

1014.00

7.68

2.39

2021-22(1 Dec-Mar 10)

18.02

20.87

50.95

1014.54

25.88

2.85

 

 

 

 

 

 

 

2021 (1 Feb-10 March)

20.41

25.00

37.38

1013.03

6.14

2.47

2022 (1 Feb-10 March)

18.06

21.43

48.83

1012.43

16.86

3.14

 

 

 

 

 

 

 

2021 (Jan)

16.93

21.14

47.79

1014.21

14.00

2.58

2022 (Jan)

16.41

18.68

57.09

1015.64

31.41

2.76

Figure-4                                Weather parameters responsible for lower yield

 

 

Results:

Data from our observation show that the average yield is 3.0 Tonnes/Hectare compared to 3.7 Tonnes/Hectare in the same fields last year. The yield range from 2.87 Tonnes/Hectare to 2.94 Tonnes/Hectare compared to 3.49 Tonnes/Hectare to 3.71 Tonnes/Hectare.

The above mentioned forecasted yields can vary depending upon weather and other unavoidable factors before harvest. If normal condition prevail then the above yields can be achieved subject to error of 10%.

The researches done in the area of yield forecasting of field crops by remote sensing has demonstrated good results. With the help of new sensors and indexes, researchers can calculate yields with less errors in future.

We will keep posting about any such informative information on to our blogs, to help as many people as possible. Farmonaut is built upon a vision to bridge the technological gap between farmers and strives to bring state-of-the-art technologies in the hands of each and every farmer. For any queries/suggestions, please contact us at support@farmonaut.com.

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