无人机在生物多样性遥感监测中的应用现状与展望
郭庆华, 吴芳芳, 胡天宇, 陈琳海, 刘瑾, 赵晓倩, 高上, 庞树鑫

Perspectives and prospects of unmanned aerial vehicle in remote sensing monitoring of biodiversity
Qinghua Guo,Fangfang Wu,Tianyu Hu,Linhai Chen,Jin Liu,Xiaoqian Zhao,Shang Gao,Shuxin Pang
表3 不同传感器的应用案例和优劣势对比
Table 3 Advantages and limitation of different sensors and the application
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