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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Crop Growth Monitoring with Drone-Borne DInSAR

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Ore, Gian [1] ; Alcantara, Marlon S. [1] ; Goes, Juliana A. [1] ; Oliveira, Luciano P. [1] ; Yepes, Jhonnatan [2] ; Teruel, Barbara [2] ; Castro, Valquiria [1] ; Bins, Leonardo S. [3] ; Castro, Felicio [1] ; Luebeck, Dieter [4] ; Moreira, Laila F. [4] ; Gabrielli, Lucas H. [1] ; Hernandez-Figueroa, Hugo E. [1]
Total Authors: 13
[1] Univ Estadual Campinas, UNICAMP, Sch Elect & Comp Engn, BR-13083852 Campinas - Brazil
[2] Univ Estadual Campinas, UNICAMP, Sch Agr Engn, BR-13083875 Campinas - Brazil
[3] Natl Inst Space Res INPE, BR-12227010 Sao Jose Dos Campos - Brazil
[4] Radaz Ind Comercio Prod Eletron Ltda, BR-12244000 Sao Jose Dos Campos - Brazil
Total Affiliations: 4
Document type: Journal article
Source: REMOTE SENSING; v. 12, n. 4 FEB 2020.
Web of Science Citations: 0

Accurate, high-resolution maps of for crop growth monitoring are strongly needed by precision agriculture. The information source for such maps has been supplied by satellite-borne radars and optical sensors, and airborne and drone-borne optical sensors. This article presents a novel methodology for obtaining growth deficit maps with an accuracy down to 5 cm and a spatial resolution of 1 m, using differential synthetic aperture radar interferometry (DInSAR). Results are presented with measurements of a drone-borne DInSAR operating in three bands-P, L and C. The decorrelation time of L-band for coffee, sugar cane and corn, and the feasibility for growth deficit maps generation are discussed. A model is presented for evaluating the growth deficit of a corn crop in L-band, starting with 50 cm height. This work shows that the drone-borne DInSAR has potential as a complementary tool for precision agriculture. (AU)

FAPESP's process: 17/19416-3 - Drone-borne radar for sugar cane precision agriculture
Grantee:Hugo Enrique Hernández Figueroa
Support type: Research Grants - Research Partnership for Technological Innovation - PITE
FAPESP's process: 18/00601-8 - Remote sensing radar carried by drone
Grantee:Dieter Lubeck
Support type: Research Grants - Innovative Research in Small Business - PIPE