CIG based Stress Identification Method for Maize Crop using UAV based Remote Sensing

被引：2

作者：

Kumar, Ajay ^{[1
]}

Taparia, Mahesh ^{[1
]}

Rajalakshmi, P. ^{[1
]}

Guo, Wei ^{[2
]}

Naik, Balaji B. ^{[3
]}

Marathi, Balram ^{[3
]}

Desai, U. B. ^{[1
]}

机构：

[1] Indian Inst Technol Hyderabad, Dept Elect Engn, Hyderabad, India

[2] Univ Tokyo, Inst Sustainable Agroecosyst Serv, Int Field Phen Res Lab, Grad Sch Agr & Life Sci, Tokyo, Japan

[3] Prof Jayashankar Telangana State Agr Univ PJTSAU, Hyderabad, Telangana, India

来源：

2020 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS 2020) | 2020年

关键词：

Multispectral images; computer vision; UAV based remote sensing; high throughput plant phenotyping; crop monitoring; SMART IRRIGATION; USE EFFICIENCY; WATER; PERFORMANCE; CANOPY; IMAGES; SYSTEM; PLANTS;

D O I：

10.1109/sas48726.2020.9220016

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

The health and yield of crops depend on the use of water, nutrients, and fertilizers. Due to climatic changes and reduction in rainfall, farmers are relying on groundwater for irrigation, which should be used optimally. The use of water and other agronomic inputs can be optimized by monitoring the health of crops and soil. Usually, it is done by manual observation, which is labor-intensive and time-consuming. In this paper, we propose Chlorophyll Index Green (CIG) vegetative index-based method for monitoring the crop health using near-infrared, green, and red band images acquired using a multispectral camera mounted on Unmanned Ariel Vehicle (UAV). The proposed method clearly classifies the water-stressed area of the field and helps in optimizing the irrigation process and monitoring the crop-health.

引用

页数：6

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