无人机在生物多样性遥感监测中的应用现状与展望

doi:10.17520/biods.2016105

摘要/Abstract

摘要：

近十年, 无人机平台由于其灵活机动、成本低等优势在植被生态调查、资源环境监测、生物多样性保护等领域逐渐兴起。本文从生物多样性遥感监测应用角度首先介绍了无人机分类系统, 为具体工作开展过程中如何选择合适的载体和传感器提供了参考; 继而总结了不同类型无人机的适用性及其可搭载传感器的用途与区别。在此基础上, 针对无人机平台的高精度遥感信息具体应用案例, 就反映生物多样性变化并揭示其驱动机制方面的无人机遥感直接和间接指标的相关研究进展展开阐述。最后, 就目前无人机遥感技术在生物多样性监测领域的应用中存在的限制, 如软硬件结合匹配程度不够、部分设备过于昂贵、法律法规不完善、与传统生物多样性监测手段结合较弱等问题进行探讨。我们认为: 无人机遥感技术可以很好地弥补地面监测与航天、卫星遥感之间的尺度空缺, 更好地将监测点上的结果以准确、可靠的推绎方法扩展到区域尺度供决策分析使用。今后迫切需要进一步加大生物多样性近地面遥感监测项目建设的实施力度, 从整体上提高生物多样性热点区域应对变化的分析预警能力。

关键词: 无人机, 遥感, 传感器, 激光雷达, 多源数据

Abstract

During the past decade, unmanned aerial vehicle (UAV) based remote sensing has been increasingly used in the fields of vegetation inventory, natural resource management, and biodiversity conservation, due to its low cost and high flexibility. In this study, we present a reference for the selection of UAV platforms and remote sensing sensors, by introducing a UAV classification system and summarizing applicability in biodiversity monitoring using remote sensing techniques. For each UAV platform category, we also introduce the characteristics and capabilities of different remote sensing sensors that can be supported. Moreover, through the combination of a case study which collected high-fidelity UAV-based remotely sensed data, we discuss current research progress using UAV-borne remote sensing data to derive direct and indirect biodiversity parameters. Finally, we discuss the current limitations of UAV-based remote sensing platforms for biodiversity monitoring, such as the existing gap between hardware and software, the high cost of certain components (e.g. the initial measurement unit), incomplete laws and regulations, and the disconnect with traditional biodiversity monitoring methods. In summary, we believe that UAV-based remote sensing platforms can greatly help to fill the gaps between terrestrial measurements and aerial/spaceborne measurements, and can increase the accuracy and reliability of upscaling point-based terrestrial measurements to the regional scale. There is a need to launch more projects that address building a UAV-based biodiversity monitoring network, and therefore improve our capability to analyze and forecast biodiversity changes in hotspots.

Key words: UAV, remote sensing, sensors, LiDAR, multi-source data

郭庆华, 吴芳芳, 胡天宇, 陈琳海, 刘瑾, 赵晓倩, 高上, 庞树鑫 (2016) 无人机在生物多样性遥感监测中的应用现状与展望. 生物多样性, 24, 1267-1278. DOI: 10.17520/biods.2016105.

Qinghua Guo, Fangfang Wu, Tianyu Hu, Linhai Chen, Jin Liu, Xiaoqian Zhao, Shang Gao, Shuxin Pang (2016) Perspectives and prospects of unmanned aerial vehicle in remote sensing monitoring of biodiversity. Biodiversity Science, 24, 1267-1278. DOI: 10.17520/biods.2016105.

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链接本文: https://www.biodiversity-science.net/CN/10.17520/biods.2016105

https://www.biodiversity-science.net/CN/Y2016/V24/I11/1267

图/表 7

参考文献 53

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	微型无人机 Mini UAV	轻型无人机 Light UAV	小型无人机 Small UAV	大型无人机 Large UAV
空机重量 Weight (kg)	< 7	7-116	≤ 5,700	> 5,700
载荷大小 Payload (kg)	< 5	5-30	≤ 50	200-900
续航时间 Flying time (h)	< 1	< 2	< 10	< 48
最大飞行高度 Max ?ying height (km)	< 0.25	< 1	< 4	3-20

	微型无人机 Mini UAV	轻型无人机 Light UAV	小型无人机 Small UAV	大型无人机 Large UAV
空机重量 Weight (kg)	< 7	7-116	≤ 5,700	> 5,700
载荷大小 Payload (kg)	< 5	5-30	≤ 50	200-900
续航时间 Flying time (h)	< 1	< 2	< 10	< 48
最大飞行高度 Max ?ying height (km)	< 0.25	< 1	< 4	3-20

	固定翼 Fixed-wing	多旋翼 Rotating-wing
优势 Advantage	飞行速度快、航程远、航时长、载荷大、空中最大飞行高度更高 Faster in flying speed, longer in flying time and distance, larger in payload, and higher in max ?ying height	起飞环境要求低, 不受场地限制; 能悬停, 可长时间观测某个静止目标; 操作简单、维护方便 Less requirements in takeoff and landing place, hover in place and observe, and easy to operate and maintain.
局限性 Limitation	操作相对困难, 受场地限制较多 More difficult in operation, and more requirements in takeoff and landing place	载荷小、续航时间短 Lower in payload and shorter in flying time

	固定翼 Fixed-wing	多旋翼 Rotating-wing
优势 Advantage	飞行速度快、航程远、航时长、载荷大、空中最大飞行高度更高 Faster in flying speed, longer in flying time and distance, larger in payload, and higher in max ?ying height	起飞环境要求低, 不受场地限制; 能悬停, 可长时间观测某个静止目标; 操作简单、维护方便 Less requirements in takeoff and landing place, hover in place and observe, and easy to operate and maintain.
局限性 Limitation	操作相对困难, 受场地限制较多 More difficult in operation, and more requirements in takeoff and landing place	载荷小、续航时间短 Lower in payload and shorter in flying time

传感器 Sensor	原始数据 Raw data	应用案例 Application	优势 Advantage	局限性 Limitation
高分相机 High-resolution camera	二维图像, 包含颜色信息 2D image, RGB bands	草地监测(Bareth et al, 2015)、林火监测(Merino et al, 2012)、野生动物研究(Jones et al, 2006)、地形产品生成(Mancini et al, 2013) Grassland monitoring (Bareth et al, 2015), wildfire detection (Merino et al, 2012), wildlife research (Jones et al, 2006), and terrain products generation (Mancini et al, 2013)	价格便宜、数据处理技术相对成熟 Cheap in hardware and mature in data post-processing	成像质量受天气条件影响; 光谱信息有限 The imaging quality is affected by the weather condition, and limited in spectral information
多光谱成像仪 Multi spectrum sensor	二维图像, 包含几个离散波段的光谱信息 2D image, several spectral bands	冠层截获的光合有效辐射研究(Guillen-Climent et al, 2012); 精准农业(De Biasio et al, 2011) Photosynthetically available radiation interception in canopy (Guillen-Climent et al, 2012). Precision agriculture (De Biasio et al, 2011)	能够获取光谱信息, 反演常用植被指数 Easy to retrieval vegetation index	同物异谱、同谱异物现象造成数据解译困难 Difficult in classification due to synonyms spectrum phenomenon and same spectrum different object phenomenon
高光谱成像仪 Hyperspectral sensor	二维图像, 能够获取近百个波段的光谱信息 2D image, hundred spectral bands	病虫害监测(Näsi et al, 2015) 冠层生化参数反演(Zarco-Tejada et al, 2013) Pest monitoring (Näsi et al, 2015) Deriving canopy biochemical parameter	光谱分辨率高, 有利于精确反演各种生化参数 Higher in spectral resolution, easier to the precise derive biochemical parameters	数据量大, 数据处理分析难度大 Large in data size and difficult in data processes and analysis
热红外相机 Thermal infrared sensor	二维图像, 包含温度信息 2D image, contains temperature information	干旱胁迫响应研究(Bendig et al, 2012)、冠层水分胁迫研究(Bellvert et al, 2013)、动物监测(Israel , 2011) Plant response to drought (Bendig et al, 2012), water deficiency in canopy (Bellvert et al, 2013), and animal monitoring (Israel, 2011)	能够获取温度信息, 可以识别部分动物 Obtain temperature information and detect some animals	温度变化易受周围环境影响 Affected by the environment temperature
激光雷达扫描仪 LiDAR sensor	点云数据, 包含三维地理坐标 Point cloud, with 3D geographic coordinates	森林参数提取(许子乾等, 2015)、变化监测(Wallace et al, 2012a) Forest parameters extraction (Xu et al, 2015), and change detection (Wallace et al, 2012a)	高精度, 受外界环境因素影响小; 可反演植被三维形态结构参数。 High precision, rarely influenced by the external environment; able to retrieve three dimensional shape and structure parameters of vegetation	无法获取纹理、光谱信息 Unable to obtain texture and spectral information