SIZE ESTIMATION OF ANT NESTS IN INDUSTRIAL FOREST BY P-BAND SAR TOMOGRAPHY

被引：0
|
作者：
Ore, Gian [1 ]
Santos, Alexandre [2 ]
Ukan, Daniele [3 ]
Zanetti, Ronald [4 ]
Camargo, Mariane [5 ]
Oliveira, Luciano P. [6 ]
Hernandez-Figueroa, Hugo E.
机构：
[1] Univ Estadual Campinas, Sch Elect & Comp Engn, UNICAMP, Campinas, Brazil
[2] Fed Inst Mato Grosso, Dept Forest Engn, IFMT, Campus Caceres, Caceres, MT, Brazil
[3] UNICENTRO, Dept Forest Engn, Irati, PR, Brazil
[4] Univ Fed Lavras, Dept Entomol, UFLA, DEN, Lavras, MG, Brazil
[5] Klabin SA, Telemaco Borba, PR, Brazil
[6] Technol Innovat Inst, Directed Energy Res Ctr, Abu Dhabi, U Arab Emirates
来源：
IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2023年
基金：
巴西圣保罗研究基金会;
关键词：
Ant nests size estimation; SAR imaging; industrial forest;
D O I：
10.1109/IGARSS52108.2023.10282064
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Defoliation by leaf-cutting ants in commercial forest plantations is one of the leading causes of biomass and productivity losses affecting all of Brazilian industrial forest. Thus, the development of monitoring tools that allow extracting the information below the surface in large areas, such as synthetic aperture radar (SAR) systems, is crucial. This work presents a method for ant nest size estimation in industrial forest based on SAR images. A field study is carried out using a drone-borne SAR system to survey a commercial eucalyptus forest by using a helical flight pattern and P band transmitting frequency and finally generating a ground tomography. A convolutional neural network (CNN) is employed for the ant nests size estimation from the tomograms. A mean error of 5 % and 21 % was achieved for a training a validation dataset, respectively.
引用
收藏
页码：6592 / 6595
页数：4
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