ANT NESTS DETECTION IN INDUSTRIAL FORESTS BY SAR P-BAND TOMOGRAPHY

被引：1

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. ^{[1
]}

机构：

[1] Univ Estadual Campinas, UNICAMP, Sch Elect & Comp Engn, Campinas, Brazil

[2] Fed Inst Mato Grosso, IFMT, Dept Forest Engn, Campus Caceres, Cuiaba, MT, Brazil

[3] UNICENTRO, Dept Forest Engn, Irati, PR, Brazil

[4] Univ Fed Lavras, DEN UFLA, Entomol Dept, 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：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

基金：

巴西圣保罗研究基金会;

关键词：

Electromagnetic simulation; ant nests detection; SAR imaging; Industrial Forest;

D O I：

10.1109/IGARSS46834.2022.9884086

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The presence of leaf-cutting ants in commercial forest plantations is one of the main causes of the loss of biomass and productivity that affect the large pulp producers in Brazil. Thus, the development of monitoring tools that allow the extraction of information below the surface in large areas, such as SAR systems, is of crucial importance. This work presents a set of unprecedented electromagnetic simulations for the detection of leaf-cutting ant nests with 6 up to 385 chambers in industrial forests. The different tests range from the one-signal case to a tomographic processing based on SAR imaging, obtaining promising results that can be used in subsequent tests with real data based on SAR mapping.

引用

页码：4791 / 4794

页数：4

共 8 条

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