SAR-Based Monitoring of Maize Phenology in the High-Yielding Mpumalanga Province of South Africa
Maize is one of the most important crops in South Africa, making timely information on its growth and phenological development essential for effective production management and yield forecasting. This study investigated the potential of Sentinel-1 SAR to characterize maize phenological periods in Mpumalanga Province, one of South Africa’s highest-yielding maize-producing regions, during the 2018–2019, 2019–2020, and 2020–2021 cropping seasons. Sentinel-1 vertical transmit-horizontal receive (VH) polarization and vertical transmit-vertical receive (VV) polarization gamma naught backscatter coefficients and the VH:VV cross-polarization ratio were analyzed together with the Sentinel-2 Normalized Difference Vegetation Index (NDVI) and field survey data. Unsupervised classification was used to assist in identifying candidate maize fields, and the seasonal variations in SAR indices showed patterns similar to those previously observed in North West Province. The increase in the VH:VV cross-polarization ratio was associated with the expected emergence period, and NDVI-derived emergence dates generally fell within the emergence periods indicated by SAR. The peak of VH gamma naught occurred several days after or coincided with the NDVI peak, suggesting its potential as an indicator of the expected heading period, whereas the peak of the VH:VV cross-polarization ratio was consistent with the expected mature period, as was the second peak of VH gamma naught. Peak VH gamma naught exhibited a significant negative relationship with maize yield (R2 = 0.79, p < 0.01). Compared with North West Province, Mpumalanga showed lower peak VH gamma naught values despite substantially higher yields, suggesting that differences in planting density and canopy structure reduced the contribution of volume scattering within the maize canopy. These results suggest that Sentinel-1 SAR has potential for providing phenological indicators of maize in both semi-arid and high-yield production environments.
Authors
- Zaid A. Bello (ORCID: https://orcid.org/0000-0002-8897-1834)
- Mokhele Edmond Moeletsi (ORCID: https://orcid.org/0000-0003-3932-5569)
- Mitsuru Tsubo (ORCID: https://orcid.org/0000-0002-8729-2215)
- Masao Moriyama
- Reiji Kimura
Institutions
- Agricultural Research Council of South Africa (ZA)
- Tottori University (JP)
- University of Limpopo (ZA)
Publication Details
- Journal
- Remote Sensing
- Published
- 2026-09-20
- DOI
- https://doi.org/10.3390/rs18183231
- Primary Topic
- Remote Sensing in Agriculture
- Type
- article
- Field-Weighted Citation Impact
- 0.00