[en] It is challenging to generate a time series of vegetation indices from moderate spatial resolution Landsat Thematic Mapper images (Landsat 8)for crop yield forecasting. In addition, crop yields are correlated with phenology information, especially the fruit filling days. The objectives of this study were to identify the phenology time for making a reliable jujube yield prediction, more importantly, explore an approach that used the length of phenology growth period to improve remotely sensed estimates of inter-annual variability for yields. The best time for making jujube yield prediction was found to be during the fruit filling period, showing higher correlation coefficient (r)between vegetation indices and yields. The average NDVI for 14th and 15th half-months represented a better performance for yield prediction, with a highest r value of 0.87 for NDVI, 0.82 for SAVI, 0.73 for NDWI and 0.73 for EVI, respectively. The potential of using Landsat-NDVI for jujube yield estimation, combined with the phenological length, was preliminarily proved based on 200 observations of individual jujube orchards, showing a validated R2 of 0.85, 0.80 and 0.67, RMSE of 0.61, 0.78 and 0.85 t ha−1 for 2013, 2014 and 2016, respectively. Furthermore, the phenological adjusted model was further evaluated by inter-annual official statistic data, with R2 and RMSE values ranging from 0.38 to 0.53, and 0.31 to 0.47 t ha−1, respectively. The proposed method showed better performance between years when the fruit filling days differed greatly than the leave-one-year-out method, which was verified to well fit to jujube yield monitoring and mapping two months before harvest.
Disciplines :
Computer science Agriculture & agronomy
Author, co-author :
Bai, Tiecheng; TERRA Teaching and Research Centre, Gembloux Agro-Bio Tech, Liège University, Belgium ; Southern Xinjiang Research Center for Information Technology in Agriculture, College of Information Engineering, Tarim University, Alaer, China
Zhang, Nannan; Southern Xinjiang Research Center for Information Technology in Agriculture, College of Information Engineering, Tarim University, Alaer, China
Mercatoris, Benoît ; Université de Liège - ULiège > Ingénierie des biosystèmes (Biose) > Biosystems Dynamics and Exchanges (BIODYNE)
Chen, Youqi; Institute of Agricultural Resources and Regional Planning of CAAS, Beijing, China
Language :
English
Title :
Jujube yield prediction method combining Landsat 8 Vegetation Index and the phenological length
NSCF - National Natural Science Foundation of China [CN]
Funding text :
This research was funded by National Natural Science Foundation of China ( 41561088 and 61501314 ) and Science & Technology Nova Program of Xinjiang Production and Construction Corps ( 2018CB020 ).
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