N达勒姆.H.—The lakes of 新汉普郡 are popular destinations for both residents and visitors to the Granite State, 提供多种娱乐选择，如游泳, 划船和钓鱼. 由于气候变化影响了陆地和水域的温度, 这也会增加有毒的蓝绿藻的繁殖, 被称为蓝藻, 这可能会给成年人带来潜在的健康风险, 儿童与宠物. Testing each suspicious body of water can be expensive and time-consuming but researchers 在 University of 新汉普郡 have developed a promising alternative by using unmanned aerial systems (UAS), 或无人机, equipped with special sensors to help identify the harmful blooms faster and more efficiently.

“这是第一次在新罕布什尔州的湖泊上进行此类研究, which is surprising because cyanobacteria blooms are becoming an increasing public and ecological issue all across New England,拉塞尔·康高尔顿说, 自然资源与环境学教授，美国国家自然研究所的科学家.H. 农业实验站. “该地区有这么多水体, 测试水样可能会很昂贵，但无人机的速度更快, 更简单、更安全的选择, 进行测试的人很少接触到毒素.”

在他们的 研究, 发表在遥感杂志上, the researchers outlined how they used UAS equipped with a multispectral sensor to capture imagery in various wavelengths of the electromagnetic spectrum (blue, 绿色红色, 红边和近红外)，允许准确的检测, 水生生态系统某些部分的鉴定和定量, 比如蓝藻和绿藻. 

They flew the drone over six bodies of water in southern 新汉普郡: Silver Lake and French, 格林伍德, 大尺度, 休厄尔和塔克池塘. The drone collected images of the lake in a lateral grid pattern that enabled researchers to accurately analyze and determine cyanobacteria concentrations. Water samples were also collected by a researcher who would canoe to selected locations in the lake. These samples were then analyzed in a water quality lab and used to determine the accuracy of the results of the image analysis.

The team conducted their water surveys from May 2022 to September 2022 and collected samples from each of the six bodies of water. They analyzed and processed over 180 water samples for chlorophyll-a—each sample taking over two days to analyze. Comparatively, the collection and processing of the UAS imagery took significantly less time—about 4.比传统的水采样方法快5倍.

“用无人机, a small lake might take as little as 10 to 15 minutes to fly over and less than an hour to do everything including set up, flying and packing away the equipment—and an entire lake’s worth of imagery could be processed within just two hours,克里斯汀·邦宁说, 他是联合国大学研究生研究员，也是该研究的主要作者. "The traditional method of testing for cyanobacteria took so much longer because each sample had to be collected and processed individually. 最终, the ability to use this technology streamlined the entire process and eliminated significant time spent in the lab.”

The 研究 also revealed a correlation between cyanobacteria cell concentration and concentrations of chlorophyll-a and phycocyanin—the latter being a pigment responsible for the blue-green algae's color. 这种相关性允许使用光谱图像来识别蓝藻, 水中叶绿素-a和藻蓝蛋白的浓度, 帮助确定潜在的危害程度.

其他合著者包括阿曼达·麦奎德, UNH推广专家和Benjamin Fraser, 博士后研究员.

这项研究是由美国农业部国家粮食和农业研究所资助的.H. 农业实验站和新罕布什尔州.

成立于1887年 NH农业试验站 在 UNH生命科学与农业学院 is UNH’s first research center and an elemental component of 新汉普郡's land-grant university heritage and mission.

永利app新版本官网地址 激励创新，改变我们国家、民族和世界的生活. 超过16个,000 students from 49 states and 82 countries engage with an award-winning faculty in top-ranked programs in business, 工程, 法律, 卫生和公共服务, 文科和理科横跨200多个学习项目. 卡内基R1分类机构, 联合国大学与美国宇航局合作, 美国国家海洋和大气管理局, NSF, 和国家卫生研究院, and received over $210 million in competitive external funding in FY23 to further explore and define the frontiers of land, 海洋与太空.

照片和图像供下载

http://colsa.主要研究.edu/file/45687
Researcher Christine Bunyon collects a cyanobacteria sample from 大尺度 Pond in Henniker, 新汉普郡. 
图片提供:Christine Bunyon / UNH

http://colsa.主要研究.edu/file/45690
无人驾驶航空系统(UAS)照片, 大疆矩阵300 RTK模型, 用于捕捉新罕布什尔州蓝藻华的图像数据. 
图片提供:Christine Bunyon / UNH

http://colsa.主要研究.edu/file/45688
凯泽湖的地图, showing locations of sampling (blue points) and transect lines (yellow) th在 UAS followed for capturing overhead aerials. 
由Christine Bunyon / UNH提供

http://colsa.主要研究.edu/file/45689
A pie chart providing an approximate comparison of the amount of time each task took to complete. Blue sections represent those associated with the collection and processing of water quality parameters. Grayscale sections represent those associated with the collection and processing of UAS parameters. Traditional water quality tasks took roughly 310 hours to complete while UAS tasks took roughly 65 hours to complete. 
图片提供:Christine Bunyon / UNH