Submit or Track your Manuscript LOG-IN

Real Time Estimation of Wheat Chlorophyll Content Retrieve from Landsat 8 Imagery Under Rainfed Condition

Real Time Estimation of Wheat Chlorophyll Content Retrieve from Landsat 8 Imagery Under Rainfed Condition

Syed Shah Mohioudin Gillani1, Muhammad Naveed Tahir1, Adeel Anwar1*, Syed Ijaz Ul Haq2, Muhammad Awais3, Mujahid Iqbal4, Javed Iqbal5, Hina Ahmed Malik3, Syed Muhammad Zaigham Abbas Naqvi6, Raza Ullah7 and Muhammad Abdullah Khan1

1Department of Agronomy, PMAS-Arid Agriculture University, Rawalpindi, 46300, Pakistan; 2School of Agriculture Engineering and Food Sciences, Shandong University of Technology, Zibo, China, 255000; 3Institute of Soil and Environmental Sciences University of Agriculture, Faisalabad, PAkistan; 4Agriculture Research Institute Sariab Quetta, Pakistan; 5Department of Agricultural Engineering, Khwaja Fareed University of Engineering and Information Technology, Rahim Yar Khan, Pakistan; 6Department of Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China; 7Agronomy College, Jilin Agriculture University, Changchun, China.

*Correspondence | Adeel Anwar, Department of Agronomy, PMAS-Arid Agriculture University, Rawalpindi, 46300, Pakistan; Email:


Monitoring crop bio-physical characteristics through non-destructive methods enable us to understand the different environmental impacts and help to respond to them precisely and rapidly. Chlorophyll pigmentation in plants is a supreme factor to assess the health of plants and ultimately leads to crop yield estimation. The present experiment evaluated the capacity of high-resolution satellite imagery to estimate wheat chlorophyll content coupled with ground-based information for accurately monitoring crop chlorophyll status under rainfed conditions. Images with zero clouds from LANDSAT 8 and ground data collection were carried out in a simultaneous time frame. Vegetation indices (VI) comprised of normalized difference vegetation index (NDVI), green normalized difference vegetation index (GNDVI), chlorophyll absorbed ratio index (CARI), modified chlorophyll absorbed ratio index (MCARI), and transformed chlorophyll absorbed ratio index (TCARI) were derived by LANDSAT 8 imagery for chlorophyll determination. Validation of the chlorophyll contents was performed (43 locations under rainfed conditions) nondestructively using a chlorophyll meter (SPAD-502 Minolta) along with GPS positions during Mid-March, 2017 for the wheat crop. Regressional models were plotted amongst the ground-truthed statistics and the VIs originated from satellite images to assess the accuracy. High sensitivity for chlorophyll determination was reported for NDVI and MCARI with R2 values of 0.81 and 0.80 respectively. Results proposed the real-time application of satellite imagery with high spatial resolution at wider regions. This will help the scientists to monitor and manage the nutrient requirements of plants as well as will enable them to accurately and rapidly respond to plant health by determining chlorophyll contents in plants.

To share on other social networks, click on any share button. What are these?

Sarhad Journal of Agriculture


Vol.39, Iss. 1, Pages 1-297


Click here for more

Subscribe Today

Receive free updates on new articles, opportunities and benefits

Subscribe Unsubscribe