轻小型无人机低空遥感及其在生态学中的应用进展

doi:10.13287/j.1001-9332.201702.030

应用生态学报 ›› 2017, Vol. 28 ›› Issue (2): 528-536.doi: 10.13287/j.1001-9332.201702.030

• 中国生态学学会2016年学术年会会议专栏 • 上一篇下一篇

轻小型无人机低空遥感及其在生态学中的应用进展

孙中宇^{1, 2}, 陈燕乔¹, 杨龙^1*, 唐光良¹, 袁少雄¹, 林志文¹

¹广东省地理空间信息技术与应用公共实验室/广州地理研究所, 广州 510070;
²华南师范大学, 广州 510631

收稿日期:2016-07-11 出版日期:2017-02-18 发布日期:2017-02-18
通讯作者: * E-mail: yanglong@gdas.ac.cn
作者简介:孙中宇, 男, 1986年生, 博士, 助理研究员. 主要从事森林生态学研究. E-mail: sunzhyu_lzu@126.com
基金资助:
本文由国家自然科学基金项目(31400380)、广东省自然科学基金项目(2014A030310225)、广东省科技计划项目(2015B070701020)和广东省科学院平台环境与能力建设专项资金项目(2016GDASPT-0301)资助

Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.

SUN Zhong-yu^{1, 2}, CHEN Yan-qiao¹, YANG Long^1*, TANG Guang-liang¹, YUAN Shao-xiong¹, LIN Zhi-wen¹

¹Guangdong Open Laboratory of Geospatial Information Technology and Application/Guangzhou Institute of Geography, Guangzhou 510070, China;
²South China Normal University, Guangzhou 510631, China.

Received:2016-07-11 Online:2017-02-18 Published:2017-02-18
Contact: * E-mail: yanglong@gdas.ac.cn
Supported by:
This work was supported by the Natural Science Foundation of China(31400380), the Natural Science Foundation of Guangdong (2014A030310225), the Science and Technology Plan Project of Guangdong (2015B070701020) and the Platform Environment and Ability Construction Project of Guangdong Academy of Sciences (2016GDASPT-0301).

摘要/Abstract

摘要： 无人机低空遥感系统弥补了航天和航空遥感在影像分辨率、重访周期、云层影响以及高成本等方面的不足,为中观尺度的生态学研究提供了新方法.本文介绍了轻小型无人机低空遥感系统的组成,从物种、种群、群落和生态系统尺度综述了其在生态学中的应用现状,并指出目前存在的不足和未来的发展方向,以期为无人机生态学的后续研究提供参考.无人机生态学当前面临的挑战和未来发展的方向主要有物种形态和光谱特征库的建立、物种自动识别、光谱数据与植物生理生态过程之间关系的进一步挖掘、生态系统三维立体监测、多来源多尺度遥感数据融合等.随着无人机平台技术、传感器技术以及数据传输处理技术的成熟,以无人机低空遥感技术为基础的无人机生态学将迎来发展的机遇和曙光.

Abstract: Low-altitude unmanned aerial vehicles (UAV) remote sensing system overcomes the deficiencies of space and aerial remote sensing system in resolution, revisit period, cloud cover and cost, which provides a novel method for ecological research on mesoscale. This study introduced the composition of UAV remote sensing system, reviewed its applications in species, population, community and ecosystem ecology research. Challenges and opportunities of UAV ecology were identified to direct future research. The promising research area of UAV ecology includes the establishment of species morphology and spectral characteristic data base, species automatic identification, the revelation of relationship between spectral index and plant physiological processes, three-dimension monitoring of ecosystem, and the integration of remote sensing data from multi resources and multi scales. With the development of UAV platform, data transformation and sensors, UAV remote sensing technology will have wide application in ecology research.

孙中宇, 陈燕乔, 杨龙, 唐光良, 袁少雄, 林志文. 轻小型无人机低空遥感及其在生态学中的应用进展[J]. 应用生态学报, 2017, 28(2): 528-536.

SUN Zhong-yu, CHEN Yan-qiao, YANG Long, TANG Guang-liang, YUAN Shao-xiong, LIN Zhi-wen. Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.[J]. Chinese Journal of Applied Ecology, 2017, 28(2): 528-536.

参考文献

[1] Liao X-H (廖小罕), Zhou C-H (周成虎). The Deve-lopment Report of Light-weight UAV Remote Sensing. Beijing: Science Press, 2016 (in Chinese)
[2] Floreano D, Wood RJK. Science, technology and the future of small autonomous drones. Nature, 2015, 521: 460-466
[3] Marris E. Drones in science: Fly, and bring me data. Nature, 2013, 498: 156-158
[4] Cui S-Z (崔书珍), Zhou J-G (周金国). Application of UAV aerial system on surveying and mapping of topographic map at scale 1∶1000. Surveying and Mapping of Geology and Mineral Resources (地矿测绘), 2014, 30(4): 29-31 (in Chinese)
[5] Tang L, Shao G. Drone remote sensing for forestry research and practices. Journal of Forestry Research, 2015, 26: 791-797
[6] Zhang C, Kovacs JM. The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture, 2012, 13: 693-712
[7] Lei T-J (雷添杰), Gong A-D (宫阿都), Li C-C (李长春), et al. Application of UAV remote sensing system monitoring in the low-temperature and frozen ice-snow disaster. Journal of Anhui Agricultural Sciences (安徽农业科学), 2011, 39(4): 2417-2419 (in Chinese)
[8] Dulava S, Bean WT, Richmond OMW. Environmental reviews and case studies: Applications of unmanned aircraft systems (UAS) for waterbird surveys. Environmental Practice, 2015, 17: 201-210
[9] Zang K (臧克), Sun Y-H (孙永华), Li J (李京), et al. Application of miniature unmanned aerial vehicle remote sensing system to Wenchuan earthquake. Journal of Natural Disasters (自然灾害学报), 2010, 19(3): 162-166 (in Chinese)
[10] Morgan JL, Gergel SE, Coops NC. Aerial photography: A rapidly evolving tool for ecological management. BioScience, 2010, 60: 47-59
[11] Anderson K, Gaston KJ. Lightweight unmanned aerial vehicles will revolutionize spatial ecology. Frontiers in Ecology & the Environment, 2013, 11: 138-146
[12] Chrétien LP, Théau J, Ménard P. Wildlife multispecies remote sensing using visible and thermal infrared imagery acquired from an unmanned aerial vehicle (UAV). International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, 40: 241-248
[13] Pérez-Ortiz M, Peña JM, Gutiérrez PA, et al. A semi-supervised system for weed mapping in sunflower crops using unmanned aerial vehicles and a crop row detection method. Applied Soft Computing, 2015, 37: 533-544
[14] Gini R, Passoni D, Pinto L, et al. Use of unmanned aerial systems for multispectral survey and tree classification: A test in a park area of northern Italy. European Journal of Remote Sensing, 2014, 57: 251-269
[15] Mora C, Vieira G, Pina P, et al. Land cover classification using high-resolution aerial photography in Adventdalen, Svalbard. Geografiska Annaler, 2015, 97: 473-488
[16] Zweig CL, Burgess MA, Percival HF, et al. Use of unmanned aircraft systems to delineate fine-scale wetland vegetation communities. Wetlands, 2015, 35: 303-309
[17] Ishihama F, Watabe Y, Oguma H. Validation of a high-resolution, remotely operated aerial remote-sensing system for the identification of herbaceous plant species. Applied Vegetation Science, 2012, 15: 383-389
[18] Fletcher AT, Erskine PD. Mapping of a rare plant species (Boronia deanei) using hyper-resolution remote sensing and concurrent ground observation. Ecological Management & Restoration, 2012, 13: 195-198
[19] Husson E, Hagner O, Ecke F. Unmanned aircraft systems help to map aquatic vegetation. Applied Vegetation Science, 2013, 17: 567-577
[20] Trichon V. Crown typology and the identification of rain forest trees on large-scale aerial photographs. Plant Eco-logy, 2001, 153: 301-312
[21] Calderón R, Navas-Cortés JA, Lucena C, et al. High-resolution airborne hyperspectral and thermal imagery for early detection of Verticillium wilt of olive using fluorescence, temperature and narrow-band spectral indices. Remote Sensing of Environment, 2013, 139: 231-245
[22] Zarco-Tejada PJ, González-Dugo V, Berni JAJ. Fluorescence, temperature and narrow-band indices acquired from a UAV platform for water stress detection using a micro-hyperspectral imager and a thermal camera. Remote Sensing of Environment, 2011, 117: 322-337
[23] Baluja J, Diago MP, Balda P, et al. Assessment of vineyard water status variability by thermal and multispectral imagery using an unmanned aerial vehicle (UAV). Irrigation Science, 2012, 30: 511-522
[24] Bellvert J, Zarco-Tejada PJ, Girona J, et al. Mapping crop water stress index in a ‘pinotnoir’ vineyard: Comparing ground measurements with thermal remote sensing imagery from an unmanned aerial vehicle. Precision Agriculture, 2014, 15: 361-376
[25] Flynn KF, Chapra SC. Remote sensing of submerged aquatic vegetation in a shallow non-turbid river using an unmanned aerial vehicle. Remote Sensing, 2014, 6: 12815-12836
[26] Kalacska M, Arroyomora JP, Gea JD, et al. Videogra-phic analysis of Eriophorum vaginatum spatial coverage in an ombotrophic bog. Remote Sensing, 2013, 5: 6501-6512
[27] He KS, Rocchini D, Neteler M, et al. Benefits of hyperspectral remote sensing for tracking plant invasions. Diversity & Distributions, 2011, 17: 381-392
[28] Chabot D, Bird DM. Wildlife research and management methods in the 21st century: Where do unmanned aircraft fit in? Journal of Unmanned Vehicle Systems, 2015, 3: 137-155
[29] Koski W, Allen T, Ireland D, et al. Evaluation of an unmanned airborne system for monitoring marine mammals. Aquatic Mammals, 2009, 35: 347-357
[30] Koski WR, Abgrall P, Yazvenko SB. An inventory and evaluation of unmanned aerial systems for offshore surveys of marine mammals. Journal of Cetacean Research & Management, 2010, 11: 239-247
[31] Koski WR, Gamage G, Davis AR, et al. Evaluation of UAS for photographic re-identification of bowhead whales, Balaena mysticetus. Journal of Unmanned Vehicle Systems, 2015, 3: 22-29
[32] Koski WR, Thomas TA, Funk DW, et al. Marine mammal sightings by analysts of digital imagery versus aerial surveyors: A preliminary comparison. Journal of Unmanned Vehicle Systems, 2013, 1: 25-40
[33] Hodgson A, Kelly N, Peel D. Unmanned aerial vehicles (UAVs) for surveying marine fauna: A dugong case study. PLoS One, 2013, 8(11): e79556
[34] Maire F, Mejias L, Hodgson A, et al. Detection of dugongs from unmanned aerial vehicles. 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems, Chicago, USA, 2013: 234-245
[35] Watts AC, Perry JH, Smith SE, et al. Small unmanned aircraft systems for low-altitude aerial surveys. Journal of Wildlife Management, 2010, 74: 1614-1619
[36] Mulero-Pázmány M, Barasona JÁ, Acevedo P, et al. Unmanned aircraft systems complement biologging in spatial ecology studies. Ecology & Evolution, 2015, 5: 4808-4818
[37] Barasona JA, Mulero-Pázmány M, Acevedo P, et al. Unmanned aircraft systems for studying spatial abundance of ungulates: Relevance to spatial epidemiology. PLoS One, 2014, 9(12): e115608
[38] van Gemert JC, Verschoor CR, Mettes P, et al. Nature conservation drones for automatic localization and coun-ting of animals. European Conference on Computer Vision, Zurich, Switzerland, 2014: 255-270
[39] Whitehead K, Hugenholtzchris H. Remote sensing of the environment with small unmanned aircraft systems (UASs). Ⅰ. A review of progress and challenges. Journal of Unmanned Vehicle Systems, 2014, 2: 69-85
[40] Potapov ER, Utekhina IG, Rimlinger D. Usage of UAV for surveying steller’s sea eagle nests. Raptors Conservation, 2013, 27: 253-260
[41] Goebel ME, Perryman WL, Hinke JT, et al. A small unmanned aerial system for estimating abundance and size of antarctic predators. Polar Biology, 2015, 38: 1-12
[42] Chabot D, Bird DM. Evaluation of an off-the-shelf unmanned aircraft system for surveying flocks of geese. Waterbirds, 2012, 35: 170-174
[43] Weissensteiner MH, Poelstra JW, Wolf JBW. Low-budget ready-to-fly unmanned aerial vehicles: An effective tool for evaluating the nesting status of canopy-breeding bird species. Journal of Avian Biology, 2015, 46: 425-430
[44] Sardà-Palomera F, Bota G, Viñolo C, et al. Fine-scale bird monitoring from light unmanned aircraft systems. Ibis, 2012, 154: 177-183
[45] Husson E, Lindgren F, Ecke F. Assessing biomass and metal contents in riparian vegetation along a pollution gradient using an unmanned aircraft system. Water, Air & Soil Pollution, 2014, 225: 1-14
[46] Feng J-L (冯家莉), Liu K (刘凯), Zhu Y-H (朱远辉), et al. Application of unmanned aerial vehicles to mangrove resources monitoring. Tropical Geography (热带地理), 2015, 35(1): 35-42 (in Chinese)
[47] Xie C-X (谢彩香), Chen S-L (陈士林), Lin Z-J (林宗坚), et al. Investigation on the application of remote sensing technology in medical plant resources. Mordern Chinese Medicine (中国现代中药), 2007, 9(6): 4-6 (in Chinese)
[48] Moser D, Zechmeister HG, Plutzar C, et al. Landscape patch shape complexity as an effective measure for plant species richness in rural landscapes. Landscape Ecology, 2002, 17: 657-669
[49] Getzin S, Wiegand K, Schöning I. Assessing biodiversity in forests using very high-resolution images and unmanned aerial vehicles. Methods in Ecology & Evolution, 2012, 3: 397-404
[50] Man Q, Dong P, Guo H, et al. Light detection and ranging and hyperspectral data for estimation of forest biomass: A review. Journal of Applied Remote Sensing, 2014, 8: 81598
[51] Zahawi RA, Dandois JP, Holl KD, et al. Using lightweight unmanned aerial vehicles to monitor tropical fo-rest recovery. Biological Conservation, 2015, 186: 287-295
[52] Chen D (陈荻), Li W-Z (李卫正), Kong W-L (孔文丽), et al. On the method of three-dimensional green volume calculation based on low-altitude high-definition images: Case study of the Nanjing Forestry University Campus. Chinese Garden (中国园林), 2015, 31(9): 22-26 (in Chinese)
[53] Hunt ER, Daughtry CST, Mirsky SB, et al. Remote sensing with simulated unmanned aircraft imagery for precision agriculture applications. IEEE Journal of Selected Topics in Applied Earth Observations & Remote Sensing, 2014, 7: 4566-4571
[54] Lassau SA, Cassis G, Flemons PKJ, et al. Using high-resolution multi-spectral imagery to estimate habitat complexity in open-canopy forests: Can we predict ant community patterns? Ecography, 2005, 28: 495-504
[55] Pasher J, King DJ. Multivariate forest structure modelling and mapping using high resolution airborne imagery and topographic information. Remote Sensing of Environment, 2010, 114: 1718-1732
[56] Hunt ER, Hively WD, Fujikawa SJ, et al. Acquisition of NIR-green-blue digital photographs from unmanned aircraft for crop monitoring. Remote Sensing, 2010, 2: 290-305
[57] Primicerio J, Gennaro SFD, Fiorillo E, et al. A flexible unmanned aerial vehicle for precision agriculture. Precision Agriculture, 2012, 13: 517-523
[58] Zarco-Tejada PJ, Guillén-Climent ML, Hernández-Clemente R, et al. Estimating leaf carotenoid content in vineyards using high resolution hyperspectral imagery acquired from an unmanned aerial vehicle (UAV). Agricultural and Forest Meteorology, 2013, 171-172: 281-294
[59] Lucieer A, Malenovský Z, Veness T, et al. Hyperua-simaging spectroscopy from a multirotor unmanned aircraft system. Journal of Field Robotics, 2014, 31: 571-590
[60] Näsi R, Honkavaara E, Lyytikäinensaarenmaa P, et al. Using UAV-based photogrammetry and hyperspectral imaging for mapping bark beetle damage at tree-level. Remote Sensing, 2015, 7: 15467-15493
[61] Wulder MA, White JC, Nelson R, et al. Lidar sampling for large-area forest characterization: A review. Remote Sensing of Environment, 2012, 121: 196-209
[62] Jaakkola A, Hyyppä J, Kukko A, et al. A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements. ISPRS Journal of Photogrammetry & Remote Sensing, 2010, 65: 514-522
[63] Lin Y, Hyyppa J, Jaakkola A. Mini-uav-borne lidar for fine-scale mapping. IEEE Geoscience & Remote Sensing Letters, 2011, 8: 426-430
[64] Wallace L, Lucieer A, Watson C, et al. Development of a UAV-lidar system with application to forest inventory. Remote Sensing, 2012, 4: 1519-1543
[65] Hugenholtz CH, Whitehead K, Brown OW, et al. Geomorphological mapping with a small unmanned aircraft system (suas): Feature detection and accuracy assessment of a photogrammetrically-derived digital terrain model. Geomorphology, 2013, 194: 16-24
[66] Zhang Q-Y (张启元). The application of UAV aerial technology in basic farmland mapping at alpine region. Journal of Qinghai University (Natural Science) (青海大学学报: 自然科学版), 2014, 32(2): 55-59 (in Chinese)
[67] Zhao Y-G (赵永刚). Application of UAV aerial in the mine surveying. China High-tech Enterprises (中国高新技术企业), 2015(7): 63-64 (in Chinese)
[68] Wen D-P (文道平), Wu J (吴杰). Application of UAV low altitude photogrammetry in the terrain measurement of wind field in Yunnan Plateau Mountain Area. Technology Innovation and Application (科技创新与应用), 2015(4): 32-33 (in Chinese)
[69] Wang X-C (王晓臣), Zhu J-H (朱京海), Liang T (梁婷), et al. Study on application of unmanned ae-rial vehicle remote sensing technology in eco-environmental impact assessment. Environmental Impact Assessment (环境影响评价), 2015, 37(2): 70-73 (in Chinese)
[70] Mancini F, Dubbini M, Gattelli M, et al. Using unmanned aerial vehicles (UAV) for high-resolution reconstruction of topography: The structure from motion approach on coastal environments. Remote Sensing, 2013, 5: 6880-6898
[71] Gonçalves J, Henriques R, Alves P, et al. Evaluating an unmanned aerial vehicle-based approach for assessing habitat extent and condition in fine-scale early successional mountain mosaics. Applied Vegetation Science, 2016, 19: 132-146
[72] Lian PK, Wich SA. Dawn of drone ecology: Low-cost autonomous aerial vehicles for conservation. Tropical Conservation Science, 2012, 5: 121-132
[73] D’Oleire-Oltmanns S, Marzolff I, Peter KD, et al. Unmanned aerial vehicle (UAV) for monitoring soil erosion in morocco. Remote Sensing, 2012, 4: 3390-3416
[74] Whitehead K, Moorman BJ, Hugenholtz CH. Brief communication: Low-cost, on-demand aerial photogrammetry for glaciological measurement. Cryosphere, 2013, 7: 1879-1884
[75] Klemas V. Using remote sensing to select and monitor wetland restoration sites: An overview. Journal of Coas-tal Research, 2013, 29: 958-970
[76] Vivoni ER, Rango A, Anderson CA, et al. Ecohydrology with unmanned aerial vehicles. Ecosphere, 2014, 5: art130
[77] Birdsong TW, Bean M, Grabowski TB, et al. Application and utility of a low-cost unmanned aerial system to manage and conserve aquatic resources in four texas rivers. Journal of Southeast Assocciation of Fish and Wildlife Agencies, 2015, 2: 80-85
[78] Puttock AK, Cunliffe AM, Anderson K, et al. Aerial photography collected with a multirotor drone reveals impact of Eurasian beaver reintroduction on ecosystem structure. Journal of Unmanned Vehicle Systems, 2015, 3: 123-130
[79] Liu B-T (刘斌涛), Tao H-P (陶和平), Liu S-Q (刘邵权), et al. Dynamics of regional ecological frangibility under natural hazard stress: A case study in Qingping Town of Sichuan Province, Southwest China. Chinese Journal of Applied Ecology (应用生态学报), 2012, 23(1): 584-585 (in Chinese)
[80] Homainejad N, Rizos C. Application of multiple categories of unmanned aircraft systems (UAS) in different airspaces for bushfire monitoring and response. ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, XL-1/W4: 55-60
[81] Merino L, Caballero F, Martínez-De-Dios JR, et al. An unmanned aircraft system for automatic forest fire monitoring and measurement. Journal of Intelligent & Robotic Systems, 2012, 65: 533-548
[82] Turner D, Lucieer A, Malenovský Z, et al. Spatial co-registration of ultra-high resolution visible, multispectral and thermal images acquired with a micro-UAV over antarctic moss beds. Remote Sensing, 2014, 6: 4003-4024
[83] Nishar A, Richards S, Dan B, et al. Thermal infrared imaging of geothermal environments and by an unmanned aerial vehicle (UAV): A case study of the Wairakei-Tauhara geothermal field, Taupo, New Zealand. Rene-wable Energy, 2016, 86: 1256-1264
[84] Amici S, Turci M, Giammanco S, et al. UAV thermal infrared remote sensing of an Italian mud volcano. Advances in Remote Sensing, 2013, 2: 358-364
[85] Dios JRM, Ollero A. Automatic detection of windows thermal heat losses in buildings using UAVs. 2006 World Automation Congress, Budapest, Hungary, 2006: 1-6
[86] Zhang J, Jung J, Sohn G, et al. Thermal infrared inspection of roof insulation using unmanned aerial vehicles. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2015, XL-1/W4: 381-386
[87] Hakala T, Suomalainen J, Peltoniemi JI. Acquisition of bidirectional reflectance factor dataset using a micro unmanned aerial vehicle and a consumer camera. Remote Sensing, 2010, 2: 819-832
[88] Lebourgeois V, Bégué A, Labbé S, et al. Can commercial digital cameras be used as multispectral sensors? A crop monitoring test. Sensors, 2008, 8: 7300-7322
[89] Hruska R, Mitchell J, Anderson M, et al. Radiometric and geometric analysis of hyperspectral imagery acquired from an unmanned aerial vehicle. Remote Sensing, 2012, 4: 2736-2752

轻小型无人机低空遥感及其在生态学中的应用进展

Small unmanned aerial vehicles for low-altitude remote sensing and its application progress in ecology.

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