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Open AccessArticle

Crop Growth Monitoring with Drone-Borne DInSAR

1
School of Electrical and Computer Engineering, University of Campinas - UNICAMP, Campinas 13083-852, Brazil
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School of Agricultural Engineering, University of Campinas - UNICAMP, Campinas 13083-875, Brazil
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National Institute for Space Research - INPE, São José dos Campos 12227-010, Brazil
4
Radaz Indústria e Comércio de Produtos Eletrônicos Ltda., São José dos Campos, Brazil
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(4), 615; https://doi.org/10.3390/rs12040615 (registering DOI)
Received: 31 December 2019 / Revised: 30 January 2020 / Accepted: 3 February 2020 / Published: 12 February 2020
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 centimeters height. This work shows that the drone-borne DInSAR has potential as a complementary tool for precision agriculture.
Keywords: differential interferometry; DInSAR; precision agriculture; drone-borne radar; crop growth deficit map differential interferometry; DInSAR; precision agriculture; drone-borne radar; crop growth deficit map
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MDPI and ACS Style

Oré, G.; Alcântara, M.S.; Góes, J.A.; Oliveira, L.P.; Yepes, J.; Teruel, B.; Castro, V.; Bins, L.S.; Castro, F.; Luebeck, D.; Moreira, L.F.; Gabrielli, L.H.; Hernandez-Figueroa, H.E. Crop Growth Monitoring with Drone-Borne DInSAR. Remote Sens. 2020, 12, 615.

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