Integrated method for rice cultivation monitoring using Sentinel-2 data and Leaf Area Index

Egyptian Journal of Remote Sensing and Space Sciences

Mohamed Abouelghar¹  Anton Poddubskiy²  Igor Savin³  Abdelraouf M. Ali⁴  Khaled Abutaleb⁴  Nasser Saleh⁴  Mohammed El-Shirbeny⁵  Peter Dokukin⁵ 

[1] Agrarian-Technological Institute of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, Moscow.;;Corresponding author at: National Authority for Remote Sensing and Space Sciences (NARSS) &National Authority for Remote Sensing and Space Sciences, 23 Joseph Tito, El-Nozha Elgedidah, Cairo, Egypt;Agrarian-Technological Institute of the Peoples’ Friendship University of Russia, ul. Miklukho-Maklaya 6, Moscow 117198 Russia;National Authority for Remote Sensing and Space Sciences, 23 Joseph Tito, El-Nozha Elgedidah, Cairo, Egypt;

关键词: Sentinel-2;    NDVI;    LAI;    Rice;    Yield;   

DOI  :  

来源: DOAJ

【 摘 要 】

it is necessary to apply a remote sensing-based system for rice cultivation assessment parallel with the field measurements of the crop biophysical parameters. This study aims to map the rice cultivated areas and give an estimate for the expected yield (ton/ha) using Sentinel-2 satellite data. The study was carried out in an experimental site in the Kafr El-Sheikh governorate with a total area of 3240 ha. The multi-temporal Normalized Difference Vegetation Index (NDVI) extracted from nine Sentinel-2 imagery cover the whole summer season. The supervised nearest neighborhood object-based classification method was employed, resulting in a classification map with an overall accuracy of 95% and a kappa coefficient of 0.93. Yield prediction was carried out by using an empirical yield prediction model using the NDVI and the Leaf Area Index (LAI). The LAI was calculated using the Surface Energy Balance Algorithm for Land (SEBAL) model and then validated against the measured LAI. the Mean Absolute Percentage Error (MPAE) was calculated to estimate the error between the measured and predicted LAI and yield. The MPAE was found to be ±6.76% (i.e. ±0.28 m2/m2) with a high correlation between the measured and the calculated LAI with a coefficient of determination (R2 = 0.94). While for the yield, the MPAE was found to be ±6.53% (i.e. ±0.66 ton/ha) and R2 of 0.95. This method is applicable to estimate area and yield of rice in the northern Nile delta in adequate time before harvest.

【 授权许可】

Unknown