TOPSOIL MOISTURE ESTIMATION FOR PRECISION AGRICULTURE USING UNMMANED AERIAL VEHICLE MULTISPECTRAL IMAGERY

被引：28

作者：

Hassan-Esfahani, Leila ^{[1
]}

Torres-Rua, Alfonso ^{[1
]}

Ticlavilca, Andres M. ^{[1
]}

Jensen, Austin ^{[1
]}

McKee, Mac ^{[1
]}

机构：

[1] Utah State Univ, Utah Water Res Lab, Logan, UT 84322 USA

来源：

2014 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2014年

关键词：

Remote Sensing; High Resolution Imaging; AggieAir; Soil Moisture; Learning Machines;

D O I：

10.1109/IGARSS.2014.6947175

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：

There is an increasing trend in crop production management decisions in precision agriculture based on observation of high resolution aerial images from unmanned aerial vehicles (UAV). Nevertheless, there are still limitations in terms of relating the spectral imagery information to the agricultural targets. AggieAir (TM) is a small, autonomous unmanned aircraft which carries multispectral cameras to capture aerial imagery during pre-programmed flights. AggieAir enables users to gather imagery at greater spatial and temporal resolution than most manned aircraft and satellite sources. The platform has been successfully used in support of a wide variety of water and natural resources management areas. This paper presents results of an on-going research in the application of the imagery from AggieAir in the remote sensing of top soil moisture estimations for a large field served by a center pivot sprinkler irrigation system.

引用

页数：4

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