Efficient climate change monitoring and modeling rely on high-quality geospatial and environmental datasets. Due to limitations in technical capabilities or resources, the acquisition of high-quality data for many environmental disciplines is costly. Digital Elevation Model (DEM) datasets are such examples whereas their low-resolution versions are widely available, high-resolution ones are scarce. In an effort to rectify this problem, we propose and assess an EfficientNetV2 based model. The proposed model increases the spatial resolution of DEMs up to 16times without additional information.
翻译:有效的气候变化监测和建模依靠高质量的地理空间和环境数据集。由于技术能力或资源有限,获取许多环境学科的高质量数据成本很高。数字升降模型(DEM)数据集就是这样的例子,尽管其低分辨率版本广泛提供,但高分辨率数据集却很少。为了纠正这一问题,我们建议和评估一个高效的NetV2模型。拟议的模型在没有更多信息的情况下将德国马克的空间分辨率提高到16倍。