Editorial for Special Issue “Advances in SAR: Sensors, Methodologies, and Applications”

Balz, Timo; Soergel, Uwe; Crespi, Mattia; Osmanoǧlu, Batuhan

doi:10.3390/rs10081233

Remote Sensing

2018

DOI: 10.3390/rs10081233

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Editorial for Special Issue “Advances in SAR: Sensors, Methodologies, and Applications”

Timo Balz

Uwe Soergel

Mattia Crespi

et al.

Abstract: n/a

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Cited by 2 publications

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Rice Crop Monitoring Using Sentinel-1 SAR Data: A Case Study in Saku, Japan

Kobayashi

Ide²

2022

Remote Sensing

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Global warming affects rice crop production, causing deterioration of rice grain quality. This study used C-band microwave images taken by the Sentinel-1 satellites to monitor rice crop growth with the aim to understand microwave backscatter behavior, focusing on decreases in panicle water contents with ripening, which affect C-band backscatter. Time-series changes illustrated a similar tendency across all four analysis years, showing that VV/VH ratio at an incidence angle of 45–46° stopped decreasing to be stable over the reproductive and ripening periods due to reductions in the panicle water content that allowed for greater microwave penetration into the canopy, thereby increasing panicle-related backscatter. Furthermore, multivariate regression analysis combined with field observations showed that VV and VH with the shallow incidence angles were significantly negatively correlated with panicle water content, which well demonstrated backscatter increases with plant senescence. Furthermore, it was observed that backscatter behaviors were highly consistent with changes in crop phenology and surface condition. Accordingly, Sentinel-1 images with shallow incidence angles and high revisit observation capabilities offer a strong potential for estimating panicle water content. Therefore, it seems reasonable to conclude that C-band SAR data is capable of retrieving grain filling conditions to estimate proper harvesting time.

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Rice Crop Monitoring Using Sentinel-1 SAR Data: A Case Study in Saku, Japan

Kobayashi

Ide²

2022

Remote Sensing

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Potential of ALOS2 Polarimetric Imagery to Support Management of Poplar Plantations in Northern Italy

Laurin

Mattioli²,

Innocenti³

et al. 2022

Remote Sensing

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Poplar is one of the most widespread fast-growing forest species. In Northern Italy, plantations are characterized by large interannual fluctuations, requiring frequent monitoring to inform on wood supply and to manage the stands. The use of radar satellite data is proving useful for forest monitoring, being weather independent and sensitive to the changes in forest canopy structure, but it has been scarcely tested in the case of poplar. Here, L-band ALOS2 (Advanced Land Observing Satellite-2) dual-pol data were tested to detect clear-cut plantations in consecutive years. ALOS2 quad-pol data were used to discriminate among different age classes, a much complex task than detecting poplar plantations extent. Results from different machine learning algorithms indicate that with dual-pol data, poplar forest can be discriminated from clear-cut areas with 80% overall accuracy, similar to what is usually obtained with optical data. With quad-pol data, four age classes were classified with moderate overall accuracy (73%) based on polarimetric decompositions, three 3 age classes with higher accuracy (87%) based on HV band. Sources of error are represented by poplar areas of intermediate age when stems, branches and leaves were not developed enough to detect by scattering mechanisms. This study demonstrates the feasibility of monitoring poplar plantations with satellite radar, which represents a growing source of information thanks to already-planned future satellite missions.

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Editorial for Special Issue “Advances in SAR: Sensors, Methodologies, and Applications”

Abstract: n/a

Cited by 2 publications

References 26 publications

Rice Crop Monitoring Using Sentinel-1 SAR Data: A Case Study in Saku, Japan

Rice Crop Monitoring Using Sentinel-1 SAR Data: A Case Study in Saku, Japan

Potential of ALOS2 Polarimetric Imagery to Support Management of Poplar Plantations in Northern Italy

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