Early Career Participants Support for Geocomputation 2015

该奖项将支持将来自世界各地的地理空间学者聚集在一起参加在德克萨斯州理查森的德克萨斯大学达拉斯分校举行的2015年地理计算会议的努力。国家科学基金会的支持将促进多达50名学者和研究生的参与。这个现在每两年举行一次的会议通常在欧洲举行，这是它第三次在美国举行。地球计算2015将推动空间研究，促进教学和学习，并加强美国和国际空间科学家之间现有的网络。会议将提供机会，分享涉及地球计算问题的一系列社会科学和环境科学研究中的关键元主题的最新研究和发展知识。它还将促进年轻、代表性不足的国际研究人员之间的科学合作，这些人通常可能没有这样的网络机会。在地理计算领域，与许多其他科学领域一样，研究和教育的进步越来越依赖于国际合作的发展，这些合作将来自许多不同国家的有技能的学者和教育工作者聚集在一起。地球计算会议是一个特别重要的论坛，它汇聚了一批高素质的地球空间科学家，从事计算科学和方法方面的创新和变革性工作。会议将涵盖的关键主题包括可视化和虚拟现实、跨时空范围操作的优化、数据挖掘和知识发现。它们的实际应用将在广泛的自然科学、社会科学、环境和工程科学领域以及更广泛的现实世界领域找到。

This award will support efforts to bring together geospatial scholars from around the world for the Geocomputation 2015 conference at the University of Texas-Dallas in Richardson, Texas. NSF support will facilitate the participation of up to 50 scholars and graduate students. This now-biennial conference usually is held in Europe, with this event being only the third time it has been held in the U.S. Geocomputation 2015 will advance the spatial research, promote teaching and learning, and enhance existing networks among U.S. and international spatial scientists. The conference will provide opportunities to share latest research and advance knowledge about critical meta-topics in a wide range of social and environmental science research involving geocomputational issues. It also will facilitate scientific collaboration among young, underrepresented, and international researchers who may not ordinarily have such networking opportunities.In geocomputation as in many other scientific fields, advances in research and education increasingly rely on the development of international collaborations that bring together skilled scholars and educators from many different nations. The Geocomputation conference is an especially important forum that brings together a high caliber of geospatial scientists performing innovative and transformative work in computational science and methods. Examples of critical topics that the conference will cover are visualization and virtual reality, optimization of operating across a range of spatio-temporal scales, data mining, and knowledge discovery. Their practical applications will be found in a broad spectrum of natural science, social science, environmental, and engineering scientific fields as well as in a broader range of real-world domains.