Investigating the Relationship between X-Band SAR Data from COSMO-SkyMed Satellite and NDVI for LAI Detection

Fulvio Capodici,Guido D'Urso,Antonino Maltese

doi:10.3390/rs5031389

Fulvio Capodici, Guido D'Urso + Show 1 more

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https://doi.org/10.3390/rs5031389

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Abstract

Monitoring spatial and temporal variability of vegetation is important to manage land and water resources, with significant impact on the sustainability of modern agriculture. Cloud cover noticeably reduces the temporal resolution of retrievals based on optical data. COSMO-SkyMed (the new Italian Synthetic Aperture RADAR-SAR) opened new opportunities to develop agro-hydrological applications. Indeed, it represents a valuable source of data for operational use, due to the high spatial and temporal resolutions. Although X-band is not the most suitable to model agricultural and hydrological processes, an assessment of vegetation development can be achieved combing optical vegetation indices (VIs) and SAR backscattering data. In this paper, a correlation analysis has been performed between the crossed horizontal-vertical (HV) backscattering (s°HV) and optical VIs (VIopt) on several plots. The correlation analysis was based on incidence angle, spatial resolution and polarization mode. Results have shown that temporal changes of s°HV (Δs°HV) acquired with high angles (off nadir angle; θ > 40°) best correlates with variations of VIopt (ΔVI). The correlation between ΔVI and Δs°HV has been shown to be temporally robust. Based on this experimental evidence, a model to infer a VI from s° (VISAR) at the time, ti + 1, once known, the VIopt at a reference time, ti, and Δs°HV between times, ti + 1 and ti, was implemented and verified. This approach has led to the development and validation of an algorithm for coupling a VIopt derived from DEIMOS-1 images and s°HV. The study was carried out over the Sele plain (Campania, Italy), which is mainly characterized by herbaceous crops. In situ measurements included leaf area index (LAI), which were collected weekly between August and September 2011 in 25 sites, simultaneously to COSMO-SkyMed (CSK) and DEIMOS-1 imaging. Results confirm that VISAR obtained using the combined model is able to increase the feasibility of operational satellite-based products for supporting agricultural practices. This study is carried out in the framework of the COSMOLAND project (Use of COSMO-SkyMed SAR data for LAND cover classification and surface parameters retrieval over agricultural sites) funded by the Italian Space Agency (ASI).

Highlights

Earth observation (EO) is more and more used to manage land and water resources for agricultural applications, such as leaf water potential [1,2], soil water content [3,4,5,6,7], irrigation water management [8,9,10] and flood prediction [11,12,13]
This paper explores the possibility of coupling SAR and optical images for assessing a new type of vegetation indices (VIs), as resulting from the project “Use of COSMO-SkyMed data for LANDcover classification and surface parameters retrieval over agricultural sites”
In scheme 1, best fitting (N = 10; r2 ~ 0.79, Figure 4(a)) resulted when considering leaf area index (LAI) for VI and dpr for CSK collected at high angles only, reducing the available dataset to five couples of DEIMOS-1 and CSK images

Summary

Introduction

Earth observation (EO) is more and more used to manage land and water resources for agricultural applications, such as leaf water potential [1,2], soil water content [3,4,5,6,7], irrigation water management [8,9,10] and flood prediction [11,12,13]. From optical imaging, the temporal resolution of observations from active sensors, such as SAR, is not limited by sky cloudiness; if carefully validated, it may be used in combination with thermal and optical imageries to provide a more continuous monitoring of land surfaces. (Germany); SeoSAR PAZ 1 and 2 (Spain); Sentinel 1 (European Space Agency); Radarsat RCM (Canada); Kompsat 5 (Korea). These new SAR missions (acquiring at X-, C- and L-bands) are characterized by dual polarization capability, a short revisit time (from 12 h to ~10 days) and high spatial resolution (

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