Spatio-temporal prediction tasks play a crucial role in facilitating informed decision-making through anticipatory insights. By accurately predicting future outcomes, the ability to strategize, preemptively address risks, and minimize their potential impact is enhanced. The precision in forecasting spatial and temporal patterns holds significant potential for optimizing resource allocation, land utilization, and infrastructure development. While existing review and survey papers predominantly focus on specific forecasting domains such as intelligent transportation, urban planning, pandemics, disease prediction, climate and weather forecasting, environmental data prediction, and agricultural yield projection, limited attention has been devoted to comprehensive surveys encompassing multiple objects concurrently. This paper addresses this gap by comprehensively analyzing techniques employed in traffic, pandemics, disease forecasting, climate and weather prediction, agricultural yield estimation, and environmental data prediction. Furthermore, it elucidates challenges inherent in spatio-temporal forecasting and outlines potential avenues for future research exploration.

中文翻译：

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不同领域的时空预测建模技术：一项调查


时空预测任务在通过预期洞察促进明智决策方面发挥着至关重要的作用。通过准确预测未来结果，可以增强制定战略、先发制人地解决风险并最大限度地减少其潜在影响的能力。预测空间和时间模式的精度在优化资源分配、土地利用和基础设施开发方面具有巨大潜力。虽然现有的综述和调查论文主要关注特定的预测领域，如智能交通、城市规划、流行病、疾病预测、气候和天气预报、环境数据预测和农业产量预测，但对同时包含多个对象的综合调查的关注有限。本文通过全面分析交通、流行病、疾病预测、气候和天气预测、农业产量估算和环境数据预测中采用的技术来解决这一差距。此外，它阐明了时空预报中固有的挑战，并概述了未来研究探索的潜在途径。