Abstract
Biogenic Volatile Organic Compounds (BVOCs) emitted from the terrestrial ecosystem into the Earth's atmosphere are an important component of atmospheric chemistry. Due to the scarcity of measurement, a reliable enhancement of BVOCs emission maps can aid in providing denser data for atmospheric chemical, climate, and air quality models. In this work, we propose a strategy to super-resolve coarse BVOC emission maps by simultaneously exploiting the contributions of different compounds. To this purpose, we first accurately investigate the spatial inter-connections between several BVOC species. Then, we exploit the found similarities to build a Multi-Image Super-Resolution (MISR) system, in which a number of emission maps associated with diverse compounds are aggregated to boost Super-Resolution (SR) performance. We compare different configurations regarding the species and the number of joined BVOCs. Our experimental results show that incorporating BVOCs' relationship into the process can substantially improve the accuracy of the super-resolved maps. Interestingly, the best results are achieved when we aggregate the emission maps of strongly uncorrelated compounds. This peculiarity seems to confirm what was already guessed for other data-domains, i.e., joined uncorrelated information are more helpful than correlated ones to boost MISR performance. Nonetheless, the proposed work represents the first attempt in SR of BVOC emissions through the fusion of multiple different compounds.
Abstract (translated)
生物生成 Volatile有机化合物(BVOCs)从地面生态系统释放到地球大气中是大气化学的一个重要组成部分。由于测量资源的短缺，可靠的增强BVOCs排放图的能力可以帮助为大气化学、气候和空气质量模型提供更密集的数据。在本研究中，我们提出了一种策略，通过同时利用不同化合物的贡献来超级分辨率粗粒度的BVOC排放图。为此，我们首先准确地研究了几种BVOC物种的空间相互联系。然后，我们利用发现相似之处构建了一个多图像超级分辨率(MISR)系统，其中与多种化合物相关的排放图被聚合以增强超级分辨率(SR)性能。我们比较了不同物种和合并BVOC数量的Configurations。我们的实验结果表明，将BVOCs的关系融入过程中可以极大地改善超级分辨率地图的准确性。有趣的是，最好的结果是在聚合强烈无相关性的化合物的排放图时实现。这个特性似乎证实了对其他数据域的预测，即合并无相关性信息比相关信息以增强MISR性能更有效。然而， proposed 的研究代表了通过融合多个不同化合物的方式来实现BVOC排放超级分辨率的第一次尝试。
URL
https://arxiv.org/abs/2305.14180
