Crop Growth Monitoring with Drone-Borne DInSAR

Gian Oré,Juliana A Góes,Valquíria Castro,Jhonnatan Yepes,Dieter Luebeck,Felicio Castro,Lucas H Gabrielli,Laila F Moreira,Hugo E Hernandez-Figueroa,Marlon S Alcântara,Luciano P Oliveira,Leonardo S Bins,Bárbara Teruel

doi:10.3390/rs12040615

Abstract

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.

Highlights

Agriculture has a vital role in the economic stability and social development of a country
Each image depicts an area of 300 m × 300 m, with 30 cm sampling in both directions
This work proposes a novel method for estimating the growth of different crops by executing circular flight paths with a drone-borne differential synthetic aperture radar interferometry (DInSAR) operating in the L-band with HH polarization

Summary

Introduction

Agriculture has a vital role in the economic stability and social development of a country. Effective agricultural management is essential to reduce costs and increase production. The monitoring of crop growth shall be done continuously for accurate support of decision-making [1]. Remote sensing has been an important tool for soil and crop monitoring. Optical remote sensing is widely used; synthetic aperture radar (SAR) remote sensing does not depend on weather conditions or sunlight. The radar wavelength is approximately one million times greater than the wavelength of optical systems and provides complementary information about the agriculture parameters

Methods

Results

Conclusion