MRI: Acquisition of a small Unmanned Aircraft System (UAS) for natural and urban ecosystem studies and risk disaster management

该合同允许纽约州立大学奥尔巴尼分校购买无人驾驶飞机系统。由Alexander Buyantuev博士领导的研究人员将使用该系统进行一项多学科研究，重点是监测快速的生态和地球物理过程，并将对单个树木尺度上的环境变化的理解推进到整个景观。利用尖端无人机技术和地面测量实现的近地表遥感的几个项目将审查气候变暖和当地人为影响，如土壤酸化、风力发电和城市化对植被生长的影响。深入了解这些影响对于更准确地预测未来生态系统的状况和制定合理的缓解战略是非常重要的。研究人员还将致力于密切研究该技术在确定最佳做法和为风暴后地区分析和今后的应急管理应用制定协议方面的使用情况。总体而言，这些研究预计将使大量学生和公众受益，无论是他们直接参与工作，还是通过在课堂上或公开演讲时接触到研究。Buyantuev和他的同事将使用专业级无人机系统(UAS)，配备视觉、多(高)光谱、热和激光传感器，在林地和发达地区附近收集地理空间数据。这种非常高分辨率的数据将弥补地面采样与机载和星载遥感之间缺少的一环，主要是来自广泛使用的陆地卫星和MODIS卫星的数据。这将使研究人员能够评估气候变暖和相关的树木生长时间变化如何影响云杉中非结构性碳的动态，并更好地了解土壤酸化和变暖对美国纽约州北部糖枫林生长季到来和生长季长度的影响。该小组还特别感兴趣的是，风力涡轮机是替代能源和环境友好型电力生产的来源，以及以扩大建设用地为特征的城市化进程如何改变当地气候和植被/作物生长。这些影响将通过量化现有风电场附近和郊区土地开发梯度上的年际生长季节和生物量变化来研究。这项研究将产生有价值的数据集和方法，将高分辨率图像处理成重要的科学信息。

This award permits University at Albany, SUNY, to purchase an unmanned aircraft system. Researchers led by Dr. Alexander Buyantuev will use the system to conduct a multidisciplinary study focused on monitoring fast ecological and geophysical processes and advance the understanding of environmental changes at scales of individual trees to whole landscapes. Several projects that utilize near surface remote sensing made possible by the cutting edge drone technology and ground measurements will examine effects of climate warming and local anthropogenic impacts, such as soil acidification, wind power generation, and urbanization, on vegetation growth. Gaining insight into these effects is of great importance to predict more accurately the state of ecosystems in the future and to develop sound mitigation strategies. Researchers will also be committed to look closely into the use of the technology in identifying best practices and developing protocols for post-storm area analysis and future emergency management applications. Overall, these studies are expected to benefit a large number of students and the public by either their direct involvement in the work or through exposure to research during classwork or public presentations.Dr. Buyantuev with colleagues will use a professional grade unmanned aircraft system (UAS) outfitted with visual, multi (hyper-) spectral, thermal, and laser sensors to collect geospatial data at forested field sites and near developed areas. Such very high resolution data will provide the missing link in scaling between ground sampling and airborne and spaceborne remote sensing, primarily data from widely used Landsat and MODIS satellites. It will allow researchers to assess how climate warming and associated changes in timing of tree growth affect the dynamics of nonstructural carbon in spruce trees and understand better the effects of soil acidification and warming on growing season arrival and length for sugar maple stands in Upstate New York, USA. The team is also particularly interested in how wind turbines, being the sources of alternative and environmentally friendly power production, and the process of urbanization characterized by the expansion of built-up land, modify local climates and vegetation/crop growth. These effects will be studied by quantifying inter-annual growing seasons and biomass changes in the vicinity of an existing wind farm and along the gradient of land development in a suburban site. The research will generate valuable datasets and methods for processing high resolution imagery into important scientific information.