Climate change is expected to intensify and increase extreme events in the weather cycle. Since this has a significant impact on various sectors of our life, recent works are concerned …
For Landsat land cover classification, the time series observations are typically irregular in the number of observations in a period (eg, a year) and acquisition dates due to cloud cover …
Y Xing, X Lin, N Suh, Q Song, G Cheng - arXiv preprint arXiv:2402.00743, 2024 - arxiv.org
In practice, it is observed that transformer-based models can learn concepts in context in the inference stage. While existing literature, eg,\citet {zhang2023trained, huang2023context} …
Earth observation (EO) satellite missions have been providing detailed images about the state of Earth and its land cover for over 50 years. Long-term missions, such as those of …
Accurate early-season crop type classification is crucial for the crop production estimation and monitoring of agricultural parcels. However, the complexity of the plant growth patterns …
Abstract The Harmonized Landsat Sentinel-2 (HLS) data, harmonizing Landsat-8/9 and Sentinel-2 imagery, offers frequent 30 m resolution multispectral observations but is often …
Machine learning, satellites or local sensors are key factors for a sustainable and resource- saving optimisation of agriculture and proved its values for the management of agricultural …
Abstract Changes in policy and new plans can significantly influence land use and trigger land use change in the long term. The data for pre-and post-policy implementation is …
Weather extremes affect crop production. Remote sensing can help to detect crop damage and estimate lost yield due to weather extremes over large spatial extents. We propose a …