Fine-Grained Socioeconomic Prediction from Satellite Images with Distributional Adjustment

While measuring socioeconomic indicators is critical for local governments to make informed policy decisions, such measurements are often unavailable at fine-grained levels like municipality. This study employs deep learning-based predictions from satellite images to close the gap. We propose a method that assigns a socioeconomic score to each satellite image by capturing the distributional behavior observed in larger areas based on the ground truth. We train an ordinal regression scoring model and adjust the scores to follow the common power law within and across regions. Evaluation based on official statistics in South Korea shows that our method outperforms previous models in predicting population and employment size at both the municipality and grid levels. Our method also demonstrates robust performance in districts with uneven development, suggesting its potential use in developing countries where reliable, fine-grained data is scarce

Analyzing Asymmetric Volatility and Multifractal Behavior in Cryptocurrencies Using Capital Asset Pricing Model Filter

This research analyzes asymmetric volatility and multifractality in four representative cryptocurrencies using index-based asymmetric multifractal detrended fluctuation analysis. We suggest investigating an idiosyncratic risk premium, which can be obtained by removing the market influence in the cryptocurrency return series. We call the process a capital asset pricing model filter. The analyses on the original return series showed no significant sign of asymmetric volatility. However, the filter revealed a distinct asymmetric volatility, distinguishing the uptrend and downtrend fluctuations. Furthermore, the analyses on the idiosyncratic risk premium detected some cases of asymmetry in the degree and source of multifractality, whereas that on the original return series failed to detect the asymmetry. In conclusion, in a highly volatile market, the capital asset pricing model filter can improve an investigation of the asymmetric multifractality in cryptocurrencies

Assessing the Potential of Agricultural Reservoirs as the Source of Environmental Flow

Excessive nutrient loadings from drainage areas and resulting water quality degradation in rivers are the major environmental issues around the world. The water quality further deteriorates for the large seasonal variation of precipitation and water flow. Environmental decision makers have been exploring affordable and effective ways of securing environmental flow (EF) to improve the water quality, especially in dry seasons, and agricultural reservoirs have attracted the attention of policymakers as an alternative source of EF. This study proposed an analysis framework for assessing the EF supply potential of agricultural reservoirs as alternative sources of EF. A reservoir water balance model was prepared to mathematically represent the reservoir water balance and quantify temporal variations of the amount of water available for the EF supply. The simulation model was designed to explicitly consider inflow from the upstream drainage areas, irrigation water requirement, and hydrological processes happening in the reservoirs. The proposed framework was applied to four agricultural reservoirs located in South Korea to evaluate its efficiency. Results showed that the additional storage capacity added by the dam reinforcement enabled the study reservoirs to satisfy both needs, EF and irrigation water supply. The surplus capacity turned out to be enough to satisfy various EF supply scenarios at the annual time scale. However, the current operation plans do not consider the seasonal variations of reservoir hydrology and thus cannot supply EF without violating the original operational goal, irrigation water, especially in dry months. The results demonstrate that it is necessary to consider the temporal variations of EF when developing reservoir operation rules and plans to secure EF. This study also highlights the unconventional roles of agricultural reservoirs as resources for improved environmental quality. The methods presented in this study are expected to be a useful tool for the assessment of agricultural reservoirs’ EF supply potential