Predicting Wheat Harvest Time Using Satellite Images and Regression Models

被引：0

作者：

Taghizade, Sepideh ^{[1
]}

Navid, Hossain ^{[2
]}

Maghsodi, Yasser ^{[1
]}

Vahed, Mohammad Moghadam ^{[1
]}

Fellegarii, Reza ^{[1
]}

机构：

[1] Univ Tabriz, Dept Biosyst Engn, Tabriz, Iran

[2] KN Toosi Univ Technol, Dept Photogrammetry & Remote Sensing, Tehran, Iran

来源：

AMA-AGRICULTURAL MECHANIZATION IN ASIA AFRICA AND LATIN AMERICA | 2019年 / 50卷 / 03期

关键词：

Harvesting time; Satellite imagery; Stepwise regression model; Wheat farming; VEGETATION PHENOLOGY; WINTER-WHEAT; MODIS; NETWORK; INDEXES; MAIZE; YIELD;

D O I：

暂无

中图分类号：

S2 [农业工程];

学科分类号：

0828 ;

摘要：

Cereals have an important role in human food security. Therefore, accurate estimation of harvesting time is necessary to minimize the loss in wheat farming. The objective of this study was to determine wheat harvest time using satellite images accurately. Field data was sampled from the farms in Meiham region of Kordestan province in west of Iran. Also, satellite remote sensing technique was applied during wheat growing season in 2016 using Landsat 8 images. The vegetation indexes were used as input in prediction model in this study. The results illustrated that satellite imaging has enough potential to predict the harvesting time of wheat accurately. R-squared and RMSE values of the best structured stepwise regression model in this study were 0.785 as well, and 1.13 respectively. This method can beneficially be employed by farm managers to have an accurate estimation of the most appropriate harvesting time and be able to manage the process which is an important challenge for them.

引用

页码：28 / 33

页数：6

共 31 条

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