关于卫星图像在农业中的使用的文献计量学和社会网络分析：基于熵的方法
Bibliometric and social network analysis on the use of satellite imagery in agriculture: an entropy-based approach
摘要：
卫星图像作为减少对自然资源的影响和增加农民利润的宝贵工具越来越受欢迎。这项研究的目的是双重的：挖掘科学文献，揭示这一研究领域的结构，并调查在何种程度上科学成果可以达到更广泛的公众受众。为了满足这两个目标，Web的科学和Twitter数据集检索和分析，分别。对于学术文献，观察到不同国家的不同表现：美国和中国在发表的论文和雇用的研究人员方面都是领先者。在分类关键词中，使用最多的是“分辨率”、“大地卫星”、“产量”、“小麦”和“多光谱”。然后，通过对各类文摘中所用词汇的语义网络进行分析，发现了卫星遥感研究的不同方面。这些分析表明，通过遥感反演气象参数和广泛使用植被指数十分重要。作为新出现的专题，土地使用评估和作物识别的分类任务与高光谱传感器的使用一样突出。关于学术界与公众的互动，分析表明，Twitter上几乎没有这种互动：其中大部分活动来自私营公司宣传其业务。这表明，学术界与其他社会部门的行为者之间仍然存在沟通差距。
英文摘要：
Satellite imagery is gaining popularity as a valuable tool to lower the impact on natural resources and increase profits for farmers. The purpose of this study is twofold: to mine the scientific literature to reveal the structure of this research domain, and to investigate to what extent scientific results can reach a wider public audience. To meet these two objectives, a Web of Science and a Twitter dataset were retrieved and analysed, respectively. For the academic literature, different performances of various countries were observed: the USA and China resulted as the leading actors, both in terms of published papers and employed researchers. Among the categorised keywords, "resolution", "Landsat", "yield", "wheat" and "multispectral" are the most used. Then, analysing the semantic network of the words used in the various abstracts, the different facets of the research in satellite remote sensing were detected. The importance of retrieving meteorological parameters through remote sensing and the broad use of vegetation indexes emerged from these analyses. As emerging topics, classification tasks for land use assessment and crop recognition stand out, alongside the use of hyperspectral sensors. Regarding the interaction of academia with the public, the analysis showed that it is practically absent on Twitter: most of the activity therein stems from private companies advertising their business. This shows that there is still a communication gap between academia and actors from other societal sectors.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
