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2019 , Vol. 39 >Issue 4: 604 - 615

DOI: https://doi.org/10.13284/j.cnki.rddl.003154

专刊：无人机在生态学和地理学中的应用

生态遥感新锐——轻小型无人机的应用

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  • （1. 中国科学院植物研究所 植被与环境变化国家重点实验室，北京 100093；2. 中国科学院大学，北京 100049；3. 成都理工大学 地质灾害防治与地质环境保护国家重点实验室，成都 610059；4. 东北林业大学 林学院，哈尔滨 150040；5. 内蒙古大学 生态与环境学院，呼和浩特 010000）
张菁（1995—），女，甘肃人，硕士研究生，主要从事城市生态学研究，（E-mail）eve.zhangj@gmail.com；627517643@qq.com；

网络出版日期: 2019-07-10

基金资助

“十三五”森林质量精准提升工程监测研究（0011107）

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New Technology for Ecological Remote Sensing: Light, Small Unmanned Aerial Vehicles (UAV)

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  • (1. State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China; 3. Chengdu University of Technology, State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu 610059, China; 4. Northeast Forestry University, School of Forestry, Harbin 150040, China; 5. School of Ecology and Environment, Inner Mongolia University, Hohhot 010000, China)

Online published: 2019-07-10

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摘要

基于研究对象视角梳理轻小型无人机遥感手段在生态学研究中的应用现状，重点分析了无人机在不同生态对象应用的优势和局限：优势主要在于其能够高灵活性、高分辨率地获取各生态对象的数据，为较大规模的生态研究提供了便利。在农田生态系统应用中主要关注农田信息检测、自动化农作等方面，但在这方面的应用还比较单一，缺乏更深层更全面的系统化应用；在森林草地中主要关注植被结构参数提取、生物量反演等，在数据采集过程中应注意设备的稳定性避免对数据准确性造成影响；城市生态系统主要集中在城市环境监测和测绘方面，同时城市方面飞控政策尚待完善；水生生态系统主要关注水生动植物监测和潮间带观测等，大规模监测也对设备续航和数据标准化处理提出了要求；动物研究应用中主要关注动物迁徙规律、物种分布等方面，在监测过程中需注意不要对动物栖息造成干扰。总的来说，无人机应用局限主要在于其获取的数据处理尚未标准化，飞控政策尚未成熟和硬件续航等方面。在此基础上探讨了未来无人机遥感在生态学研究的应用趋势：随着无人机智能化的软硬件发展和云端生态大数据的建立，无人机数据的获取和处理将更加智慧化，多源的无人机遥感数据将会更好地服务于生态学研究。

关键词： 无人机; 生态系统; 生态大数据; 激光雷达

本文引用格式

张菁，孙千惠，叶震，杨默含，赵晓霞，巨袁臻，胡天宇，郭庆华 . 生态遥感新锐——轻小型无人机的应用[J]. 热带地理, 2019 , 39(4) : 604 -615 . DOI: 10.13284/j.cnki.rddl.003154

Abstract

The foundation of ecological civilization construction is the acquisition of ecological remote sensing data. Traditional ecological data obtained on the basis of ground surveys are time-consuming, laborious, and cannot meet the requirements of large-scale data. However, satellite remote sensing data is inconvenient in obtaining ecological data in real time due to resolution and cycle problems. In recent years, light, small Unmanned Aerial Vehicles (UAV), offering advantages of high flexibility and high resolution, have played an important role in the fields of agriculture, environment ecology, and remote sensing, subsequently becoming the backbone of ecological research. This paper summarizes the application potential of UAV remote sensing in ecological research from the aspects of research object, research scale, and ecological trend, both analyzing the advantages and limitations of different ecosystem applications and discussing the application trend of UAV remote sensing in ecological research in the future. As a result of software and hardware problems such as data standardization and endurance, UAV applications still have some limitations. With the trends of intelligent software and hardware for UAV and the background of ecological big data, the acquisition and processing of UAV data will become more comprehensive, flexible, rapid, and intelligent in the future; as a result, the emerging UAV remote sensing data will be able to better serve ecological research. The application trend of UAV remote sensing in ecological big data can be summarized in three aspects: scaling, sampling, and synergy. The use of UAV has not been able to achieve scale due to its hardware limitations; therefore, expanding its scope of operation is both a great challenge and an important application direction. Sampling can help researchers obtain information from a small sample square and estimate the corresponding regional information by referring to the sample square. Synergies, including cloud storage, multi-source data fusion, scientific data classification, and data standardization processing can help researchers use data effectively. With the wide applications of multi-source data fusion, UAV data will also be widely used in ecological remote sensing surveying, providing important data support for ecosystem status, ecological stability, biodiversity assessment, ecosystem monitoring, ecosystem management, as well as other related aspects in the future. At the same time, as the new data brought by the UAV has a specific resolution and scale, the traditional data indicators are no longer applicable. In order to make better use of UAV data, the establishment of new indicators of UAV data is also an urgently pending task. The 21st century is the era of information and big data; with the development of science, technology, and society, new technologies emerge in an endless stream. Through research of cutting-edge theories such as artificial intelligence ecology, ecological big data, ecological prediction, as well as the establishment of new indices of UAV data, new technologies will be able to better serve ecology.

Key words： Unmanned Aerial Vehicle; ecosystems; ecological big data; lidar

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