Remotely sensed (RS) imagery is increasingly being adopted in investigations and applications outside of traditional land-use land-cover change (LUCC) studies. This is due to the increased awareness by governments, NG...Remotely sensed (RS) imagery is increasingly being adopted in investigations and applications outside of traditional land-use land-cover change (LUCC) studies. This is due to the increased awareness by governments, NGOs and Industry that earth observation data provide important and useful spatial and temporal information that can be used to make better decisions, design policies and address problems that range in scale from local to global. Additionally, citizens are increasingly adopting spatial analysis into their work as they utilize a suite of readily available geospatial tools. This paper examines some of the ways remotely sensed images and derived maps are being extended beyond LUCC to areas such as fire modeling, coastal and marine applications, infrastructure and urbanization, archeology, and to ecological, or infrastructure footprint analysis. Given the interdisciplinary approach of such work, this paper organizes selected studies into broad categories identified above. Findings demonstrate that RS data and technologies are being widely used in many fields, ranging from fishing to war fighting. As technology improves, costs go down, quality increases and data become increasingly available, greater numbers of organizations and local citizens will be using RS in important everyday applications.展开更多
文摘国家森林资源(连续)清查[national (continuous) forest inventory, NFI/NCFI,文中统称NFI]是森林资源监测体系的重要组成部分,可为制定国家林业发展战略和调整林业方针政策提供及时有效的科学依据。遥感在推动NFI技术进步方面发挥了重要作用,已成为支撑NFI运行不可或缺的技术手段。在将遥感数据作为辅助数据用于提高NFI总体参数估测精度和效率方面,国内外学者已开展了大量估计模型和方法研究,可概括为4类:设计推断法(design-based inference method)、模型辅助法(design-based and model-assisted method)、模型法(model-dependent method)和混合法(design and model hybrid method)。笔者针对这4类估测方法,总结了国内外研究现状,分析了国内相关研究存在的问题,并就未来重点研发方向和内容提出了建议。在设计推断法方面,国内外技术水平没有太大差距;国外开展了大量模型辅助法研究并已应用于NFI业务,但国内相关研究较少,且业务应用仅体现在面积成数估计,今后应加强该方法的应用示范和推广工作。关于模型法在NFI中的应用国外对多源数据协同应用中的不确定性度量方法进行了深入研究;国内对模型法的研究也很多,但对科学评价模型的拟合效果、度量模型估测结果的不确定性等缺乏系统研究,应作为后续研究重点;国外已针对NFI应用开发了3类混合法,国内对第1类混合法研究较少,对第2类混合法的研究还仅局限于用双重回归抽样法估计地类面积,而对第3类汇合法尚未采用“数据同化”思路开展相关应用研究。建议未来加强这3类混合法在国内NFI中的深入研究和应用示范。
文摘Remotely sensed (RS) imagery is increasingly being adopted in investigations and applications outside of traditional land-use land-cover change (LUCC) studies. This is due to the increased awareness by governments, NGOs and Industry that earth observation data provide important and useful spatial and temporal information that can be used to make better decisions, design policies and address problems that range in scale from local to global. Additionally, citizens are increasingly adopting spatial analysis into their work as they utilize a suite of readily available geospatial tools. This paper examines some of the ways remotely sensed images and derived maps are being extended beyond LUCC to areas such as fire modeling, coastal and marine applications, infrastructure and urbanization, archeology, and to ecological, or infrastructure footprint analysis. Given the interdisciplinary approach of such work, this paper organizes selected studies into broad categories identified above. Findings demonstrate that RS data and technologies are being widely used in many fields, ranging from fishing to war fighting. As technology improves, costs go down, quality increases and data become increasingly available, greater numbers of organizations and local citizens will be using RS in important everyday applications.
