Integrating Geopolymer Pervious Concrete Pavement for Sustainable Stormwater Management: A Case Study in the UAE

Changes in ocean chlorophyll-a (Chl-a) concentration are related to ecosystem balance. Here, we present high-quality gap-filled Chl-a data in open oceans, reflecting the distribution and changes in global Chl-a concentration. Our findings highlight the efficacy of reconstructing missing satellite observations using convolutional neural networks. This dataset and model are valuable for research in ocean color remote sensing, offering data support and methodological references for related studies.

This study blends advantages of altimetry backscattering coefficients and waveforms to estimate ice thickness for lakes without in situ data and provides an improved water level estimation for ice-covered lakes by jointly using different threshold retracking methods. Our results show that a logarithmic regression model is more adaptive in converting altimetry backscattering coefficients into ice thickness, and lake surface snow has differential impacts on different threshold retracking methods.

This study evaluated the accuracy of satellite precipitation estimates across different seasons, rainfall intensities, topographical features, and hydrological regions over the arid country of Saudi Arabia. Results confirmed that the performance of calibrated satellite products surpassed the near-real-time products in terms of consistency and estimated errors. This evaluation could help developers in improving satellite product calibration to achieve better detection accuracy over arid regions.