It is concluded that analyzing spatial neighborhoods is especially useful for making up for missing future data in crop-mapping models under early-season data constraints, meaning architectures and imputation strategies must be evaluated as a combined framework.
Early-season crop yield prediction is critical for food security assessment and timely agricultural decision-making, yet large-scale remote-sensing applications are often constrained by a mismatch between pixel-level observations and county-level yield labels. This mismatch limits the use of fine-grained spatial hetero...
Mei-Qi Zeng, Wenxi Wu, Ran Yang et al.· Remote Sensing· 0 citations
Rice cropping-intensity products indicate the number of rice-growing seasons within a year but cannot reveal the seasonal compositions that define rice cropping systems. This limitation constrains detailed characterization of regional rice production patterns. To address this gap, this study developed a framework for r...
Reliable and up-to-date information on crop distribution is essential for ensuring food security in the face of rapid population growth and climate change, and with recent advancements in remote sensing and artificial intelligence, large-scale analyses of agricultural landscapes can now be performed more quickly and ac...
Yacine Ait Ali Yahia, K. Amrouche, Abir Safta· INGENIERÍA INVESTIGA· 0 citations
The increasing availability of agricultural timeseries data enabled more accurate and data-driven crop yield prediction. However, raw meteorological, soil, and vegetation datasets often fail to capture complex temporal dependencies essential for robust forecasting. This study proposes a structured feature engineering...
K. Lata, A. Kumar, P. Sharma et al.· BIO Web of Conferences· 0 citations
Reliable pre-season yield forecasting remains a persistent challenge in avocado (Persea americana Mill.) production, due to strong year-to-year variation and alternate bearing. This study developed an early-season, block-level yield forecasting framework combining multi-temporal Sentinel-2 optical indices, Sentinel-1 S...
Muhammad Moshiur Rahman, A. Robson, Phillip West et al.· Remote Sensing· 0 citations
Satellite image time series (SITS) from Sentinel-2 provide valuable temporal information for crop-type mapping. However, most existing approaches model crop phenology at a single temporal scale and may miss complementary short-term, seasonal, and annual dynamics. To address this limitation, this letter proposes a multi...
