Biodiversity Science ›› 2018, Vol. 26 ›› Issue (8): 807-818.doi: 10.17520/biods.2018079

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Applications of satellite and air-borne remote sensing in biodiversity research and conservation

Zhiyao Tang1, 2, *(), Minwei Jiang2, Jian Zhang3, Xinyue Zhang2   

  1. 1 Institute of Ecology, Peking University, Beijing 100871
    2 College of Urban and Environmental Sciences, Peking University, Beijing 100871
    3 College of Ecology and Environmental Sciences, East China Normal University, Shanghai 200241
  • Received:2018-07-19 Accepted:2018-08-28 Online:2018-09-27
  • Tang Zhiyao
  • About author:# Co-first authors

Human activities has increasingly threatened the biodiversity of the world. Biodiversity science is a discipline that depends on scale, and research questions are often affected by the ecological process of multi-temporal scales. The traditional survey methods of biodiversity are often limited by human and material resources. It is therefore urgent to integrate different data sources in the biodiversity sciences. The remote sensing technique has developed from optical remote sensing to the multi-source remote sensing including different platforms combined with various sensors, and further to integrate the hyperspectral and hyper spatial resolution and light detection and ranging (LiDAR). The large coverage, the accessibility to remote areas, and the long-term repeatability of the remote sensing technique provide new and better solutions for studying ecological and scientific issues at different temporal and spatial scales. In this paper, we review the opportunity and challenges in the application of remote sensing in biodiversity sciences and conservation practices. Specifically, we focus on the applications of remote sensing in the issues related to the population dynamics, species interaction and community diversity, functional traits and functional diversity and biodiversity management. We suggest that the satellite and airborne remotes that employed multi-band or hyperspectral, high spatial resolution and LiDAR provide biodiversity information from different scopes, and will play essential roles in the investigation of biodiversity in large-scale and remote areas. In the near future, species discrimination technique based on spectral characteristics and structure detection based on LiDAR will improve our understanding of the biodiversity sciences and management. We suggest to strengthen the communication between remote-sensing scientists and biodiversity researchers to promote the application of remote sensing technologies in biodiversity research and at different temporal and spatial scales.

Key words: remote sensing application, population dynamics, biodiversity, functional trait diversity, conservation

[1] Amano T, Székely T, Sandel B, Nagy S, Mundkur T, Langendoen T, Blanco D, Soykan CU, Sutherland WJ (2018) Successful conservation of global waterbird populations depends on effective governance. Nature, 553, 199-202.
[2] Andam KS, Ferraro PJ, Pfaff A (2008) Measuring the effectiveness of protected area networks in reducing deforestation. Proceedings of the National Academy of Sciences,USA, 105, 16089-16094.
[3] Andrew ME, Ustin SL (2006) Spectral and physiological uniqueness of perennial pepperweed (Lepidium latifolium). Weed Science, 54, 1051-1062.
[4] Asner GP, Knapp DE, Anderson CB, Martin RE, Vaughn N (2016) Large-scale climatic and geophysical controls on the leaf economics spectrum. Proceedings of the National Academy of Sciences,USA, 113, E4043-4051.
[5] Asner GP, Martin RE (2009) Airborne spectranomics: Mapping canopy chemical and taxonomic diversity in tropical forests. Frontiers in Ecology and the Environment, 7, 269-276.
[6] Asner GP, Martin RE, Anderson CB, Knapp DE (2015) Quantifying forest canopy traits: Imaging spectroscopy versus field survey. Remote Sensing of Environment, 158, 15-27.
[7] Asner GP, Martin RE, Knapp DE, Tupayachi R, Anderson CB, Sinca F, Vaughn NR, Llactayo W (2017) Airborne laser-guided imaging spectroscopy to map forest trait diversity and guide conservation. Science, 355, 385-389.
[8] Asner GP, Vitousek PM (2005) Remote analysis of biological invasion and biogeochemical change. Proceedings of the National Academy of Sciences,USA, 102, 4383-4386.
[9] Avery MI, Haines-Young RH (1990) Population estimates for the dunlin Calidris alpina derived from remotely sensed satellite imagery of the Flow Country of northern Scotland. Nature, 344, 860-862.
[10] Balzotti CS, Asner GP (2017) Episodic canopy structural transformations and biological invasion in a Hawaiian forest. Frontiers in Plant Science, 8, 1256.
[11] Barbeitoa I, Dassot M, Bayer D, Collet C, Drössler L, Löf M, Del Rio M, Ruiz-Peinado R, Forrester DI, Bravo-Oviedo A (2017) Terrestrial laser scanning reveals differences in crown structure of Fagus sylvatica in mixed vs. pure European forests. Forest Ecology and Management, 405, 381-390.
[12] Bradley BA (2014) Remote detection of invasive plants: A review of spectral, textural and phenological approaches. Biological Invasions, 16, 1411-1425.
[13] Bradley BA, Mustard JF (2006) Characterizing the landscape dynamics of an invasive plant and risk of invasion using remote sensing. Ecological Applications, 16, 1132-1147.
[14] Brook BW, Ellis EC, Perring MP, Mackay AW, Blomqvist L (2013) Does the terrestrial biosphere have planetary tipping points? Trends in Ecology and Evolution, 28, 396-401.
[15] Bruner AG, Gullison RE, Rice RE (2001) Effectiveness of parks in protecting tropical biodiversity. Science, 291, 125-128.
[16] Buermann W, Saatchi S, Smith TB, Zutta BR, Chaves JA, Milá B, Graham CH (2008) Predicting species distributions across the Amazonian and Andean regions using remote sensing data. Journal of Biogeography, 35, 1160-1176.
[17] Burley HM, Mokany K, Ferrier S, Laffan FW, Williams KJ, Harwood TD (2016) Primary productivity is weakly related to floristic alpha and beta diversity across Australia. Global Ecology and Biogeography, 25, 1294-1307.
[18] Cheatheam LK (1977) Density and distribution of the black- tailed prairie dog in Texas. The Texas Journal of Science, 29, 33-40.
[19] Cho MZ, Mathieu R, Asner GP, Naidoo L, van Aardt J, Ramoelo A, Debba P, Wessels K, Main R, Smit IPJ (2012) Mapping tree species composition in South African savannas using an integrated airborne spectral and LiDAR system. Remote Sensing of Environment, 125, 214-226.
[20] Clark ML, Roberts DA, Clark DB (2005) Hyperspectral discrimination of tropical rain forest tree species at leaf to crown scales. Remote Sensing of Environment, 96, 375-398.
[21] Cord A, Rodder D (2011) Inclusion of habitat availability in species distribution models through multi-temporal remote- sensing data? Ecological Applications, 21, 3285-3298.
[22] Cord AF, Klein D, Gernandt DS, de la Rosa JAP, Dech S (2014) Remote sensing data can improve predictions of species richness by stacked species distribution models: A case study for Mexican pines. Journal of Biogeography, 41, 736-748.
[23] Cowley MJR, Wilson RJ, Leon-Cortes JL, Gutierrez D, Bulman CR, Thomas CD (2000) Habitat-based statistical models for predicting the spatial distribution of butterflies and day-flying moths in a fragmented landscape. Journal of Applied Ecology, 37, 60-72.
[24] Curran PJ (1989) Remote sensing of foliar chemistry. Remote Sensing of Environment, 30, 271-278.
[25] Dalsted KJ, Sather-Blair S, Worcester BK, Klukas R (1981) Application of remote sensing to prairie dog management. Journal of Range Management, 34, 218-223.
[26] Davies AB, Asner GP (2014) Advances in animal ecology from 3D-LiDAR ecosystem mapping. Trends in Ecology and Evolution, 29, 681-691.
[27] Davies AB, Marneweck DG, Druce DJ, Asner GP (2016a) Den site selection, pack composition, and reproductive success in endangered African wild dogs. Behavioral Ecology, 27, 1869-1879.
[28] Davies AB, Tambling CJ, Kerley GIH, Asner GP (2016b) Effects of vegetation structure on the location of lion kill sites in African thicket. PLoS ONE, 11, e0149098.
[29] De Wulf RR, Goossens RE, McKinnon JR, Cai WS (1988) Remote sensing for wildlife management: Giant panda habitat mapping from Landsat MSS images. Geocarto International, 1, 41-50.
[30] Elith J, Leathwick JR (2009) Species distribution models: Ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution,and Systematics, 40, 677-697.
[31] Everitt JH, DeLoach CJ (1990) Remote sensing of Chinese tamarisk (Tamarix chinensis) and associated vegetation. Weed Science, 38, 273-278.
[32] Fagan ME, DeFries RS, Sesnie SE, Arroyo-Mora JP, Soto C, Singh A, Townsend PA, Chazdon RL (2015) Mapping species composition of forests and tree plantations in northeastern Costa Rica with an integration of hyperspectral and multitemporal Landsat imagery. Remote Sensing, 7, 5660-5696.
[33] Feret JB, Asner GP (2014) Mapping tropical forest canopy diversity using high-fidelity imaging spectroscopy. Ecological Applications, 24, 1289-1296.
[34] Fjeldsaê J, Ehrlich D, Lambin E, Prins E (1997) Are biodiversity “hotspots” correlated with current ecoclimatic stability? A pilot study using the NOAA-AVHRR remote sensing data. Biodiversity and Conservation, 6, 401-422.
[35] Fretwell PT, LaRue MA, Morin P, Kooyman GL, Wienecke B, Ratcliffe N, Fox AJ, Fleming AH, Porter C, Trathan PN (2012) An emperor penguin population estimate: The first global, synoptic survey of a species from space. PLoS ONE, 7, e33751.
[36] Funk JL, Larson JE, Ames GM, Butterfield BJ, Cavender-Bares J, Firn J, Laughlin DC, Sutton-Grier AE, Williams L, Wright J (2017) Revisiting the Holy Grail: Using plant functional traits to understand ecological processes. Biological Review, 92, 1156-1173.
[37] Ge S, Carruthers R, Gong P, Herrera A (2006) Texture analysis for mapping Tamarix parviflora using aerial photographs along Cache Creek, California. Environmental Monitoring and Assessment, 114, 65-83.
[38] Ghulam A, Porton I, Freeman K (2014) Detecting subcanopy invasive plant species in tropical rainforest by integrating optical and microwave (InSAR/PolInSAR) remote sensing data, and a decision tree algorithm. ISPRS Journal of Photogrammetry and Remote Sensing, 88, 174-192.
[39] Goetz S, Steinberg D, Dubayah R, Blair B (2007) Laser remote sensing of canopy habitat heterogeneity as a predictor of bird species richness in an eastern temperate forest, USA. Remote Sensing of Environment, 108, 254-263.
[40] Gómez-Rodríguez C, Bustamante J, Koponen S, Díaz-Paniagua C (2008) High-resolution remote-sensing data in amphibian studies: Identification of breeding sites and contribution to habitat models. Herpetological Journal, 18, 103-113.
[41] Guo QH, Liu J, Li YM, Zhai QP, Wang YC, Wu FF, Hu TY, Wan HW, Liu HM, Shen WM (2016) A near-surface remote sensing platform for biodiversity monitoring: Perspectives and prospects. Biodiversity Science, 24, 1249-1266. (in Chinese with English abstract)
[郭庆华, 刘瑾, 李玉美, 翟秋萍, 王永财, 吴芳芳, 胡天宇, 万华伟, 刘慧明, 申文明 (2016) 生物多样性近地面遥感监测: 应用现状与前景展望. 生物多样性, 24, 1249-1266.]
[42] Hakkenberg CR, Peet RK, Urban DL, Song C (2018) Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing. Ecological Applications, 28, 177-190.
[43] He KS, Bradley BA, Cord AF, Rocchini D, Tuanmu MN, Schmidtlein S, Turner W, Wegmann M, Pettorelli N (2015) Will remote sensing shape the next generation of species distribution models? Remote Sensing in Ecology and Conservation, 1, 4-8.
[44] Heitkonig IMA, Ringrose S, Epema GF, Bonyongo C, Veenendaal E, Stein A, Breeuwer A, van Hasselt M, Klop E, van Goethem J, Slot M (2003) Watching wildlife from space. In: International Wetlands Conference (eds Bernard T, Mosepele K, Ramberg L), Botswana.
[45] Hong SK, Kim S, Cho KH, Kim JE, Kang S, Lee D (2004) Ecotope mapping for landscape ecological assessment of habitat and ecosystem. Ecological Research, 19, 131-139.
[46] Jackson RD (1986) Remote sensing of biotic and abiotic plant stress. Annual Review of Phytopathology, 24, 265-287.
[47] Jetz W, Cavender-Bares J, Pavlick R, Schimel D, Davis FW, Asner GP, Guralnick R, Kattge J, Latimer AM, Moorcroft P (2016) Monitoring plant functional diversity from space. Nature Plants, 2, 1-4.
[48] Jones C, Song C, Moody A (2015) Where’s woolly? An integrative use of remote sensing to improve predictions of the spatial distribution of an invasive forest pest the Hemlock Woolly Adelgid. Forest Ecology and Management, 358, 222-229.
[49] Joppa LN, Loarie SR, Pimm SL (2008) On the protection of “protected areas”. Proceedings of the National Academy of Sciences,USA, 105, 6673-6678.
[50] Juchheim J, Annighofer P, Ammer C, Calders K, Raumonen P, Seidel D (2017) How management intensity and neighborhood composition affect the structure of beech (Fagus sylvatica L.) trees. Trees, 31, 1723-1735.
[51] Kalluri S, Gilruth P, Rogers D, Szczur M (2007) Surveillance of arthropod vector-borne infectious diseases using remote sensing techniques: A review. PLoS Pathogens, 3, e116.
[52] Kerr JT, Ostrovsky M (2003) From space to species: Ecological applications for remote sensing. Trends in Ecology and Evolution, 18, 299-305.
[53] Kerr JT, Southwood TRE, Cihlar J (2001) Remotely sensed habitat diversity predicts butterfly species richness and community similarity in Canada. Proceedings of the National Academy of Sciences,USA, 98, 11365-11370.
[54] Knipling EB (1970) Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Remote Sensing of Environment, 1, 155-159.
[55] Koh LP, Wich SA (2012) Dawn of drone ecology: Low-cost autonomous aerial vehicles for conservation. Tropical Conservation Science, 5, 121-132.
[56] Kuenze C, Ottinger M, Wegmann M, Guo H, Wang C, Zhang J, Dech S, Wikelski M (2014) Earth observation satellite sensors for biodiversity monitoring: Potentials and bottlenecks. International Journal of Remote Sensing, 35, 6599-6647.
[57] Lausch A, Bannehr L, Beckmann M, Boehm C, Feilhauer H, Hacker JM, Heurich M, Jung A, Klenke R, Neumann C (2016) Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives. Ecological Indicators, 70, 317-339.
[58] Levanoni O, Levin N, Peer G, Turbe A, Kar S (2011) Can we predict butterfly diversity along an elevation gradient from space? Ecography, 34, 372-383.
[59] Levick SR, Setterfield SA, Rossiter-Rachor NA, Hutley LB, McMaster D, Hacker JM (2015) Monitoring the distribution and dynamics of an invasive grass in tropical savanna using airborne LiDAR. Remote Sensing, 7, 5117-5132.
[60] Lewis E, MacSharry B, Juffe-Bignoli D, Harris N, Burrows G, Kingston N, Burgess ND (2018) Dynamics in the global protected-area estate since 2004. Conservation Biology. (accessed on 2017-11-23)
[61] Li Y, Härdtle W, Bruilheide H, Nadrowski K, Scholten T, von Wehrden H, von Oheimb G (2014a) Site and neighborhood effects on growth of tree saplings in subtropical plantations (China). Forest Ecology and Management, 327, 118-127.
[62] Li Y, Hess C, von Wehrden H, Härdtle W, von Oheimb G (2014b) Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning. Annals of Forest Science, 71, 453-462.
[63] Lim K, Treitz P, Wulder M, St-Onge B, Flood M (2003) LiDAR remote sensing of forest structure. Progress in Physical Geography, 27, 88-106.
[64] Liu J, Linderman M, Ouyang Z, An L, Yang J, Zhang H (2001) Ecological degradation in protected areas: The case of Wolong Nature Reserve for giant pandas. Science, 292, 98-101.
[65] Liu L, Coops NC, Aven NW, Pang Y (2017) Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data. Remote Sensing of Environment, 200, 170-182.
[66] Liu XJ, Ma KP (2015) Plant functional traits—concepts, applications and future directions. Scientia Sinica Vitae, 45, 325-339. (in Chinese with English abstract)
[刘晓娟, 马克平 (2015) 植物功能性状研究进展. 中国科学: 生命科学, 45, 325-339.]
[67] Loarie SR, Tambling CG, Asner GP (2013) Lion hunting behaviour and vegetation structure in an African savanna. Animal Behavior, 85, 899-906.
[68] Loffler E, Margules C (1980) Wombats detected from space. Remote Sensing of Environment, 9, 47-56.
[69] Lucas KL, Carter GA (2008) The use of hyperspectral remote sensing to assess vascular plant species richness on Horn Island, Mississippi. Remote Sensing of Environment, 112, 3908-3915.
[70] Luoto M, Kuussaari M, Toivonen T (2002) Modelling butterfly distribution based on remote sensing data. Journal of Biogeography, 29, 1027-1037.
[71] Lynch HJ, Schwaller MR (2014) Mapping the abundance and distribution of Adelie penguins using Landsat-7: First steps towards an integrated multi-sensor pipeline for tracking populations at the continental scale. PLoS ONE, 9, e113301.
[72] Ma KP (2016) Hot topics for biodiversity science. Biodiversity Science, 24, 1-2. (in Chinese)
[马克平 (2016) 生物多样性科学的热点问题. 生物多样性, 24, 1-2.]
[73] Malahlela OE, Cho MA, Mutanga O (2015) Mapping the occurrence of Chromolaena odorata (L.) in subtropical forest gaps using environmental and remote sensing data. Biological Invasion, 17, 2027-2042.
[74] McGraw JB, Warner TA, Key TL, Lamar WR (1998) High spatial resolution remote sensing of forest trees. Trends in Ecology and Evolution, 13, 300-301.
[75] McMahon CR, Howe H, van den Hoff J, Alderman R, Brolsma H, Hindell MA (2014) Satellites, the all-seeing eyes in the sky: Counting elephant seals from space. PLoS ONE, 9, e92613.
[76] Metz J, Seidel D, Schall P, Scheffer D, Schulze ED, Ammer C (2013) Crown modeling by terrestrial laser scanning as an approach to assess the effect of aboveground intra- and interspecific competition on tree growth. Forest Ecology and Management, 310, 275-288.
[77] Mitchell JJ, Glenn NF (2009) Subpixel abundance estimates in mixture-turned matched filtering classifications of leafy spurge (Euphorbia esuls L.). International Journal of Remote Sensing, 30, 6099-6119.
[78] Mumby PJ, Green EP, Edwards AJ, Clark CD (1997) Coral reef habitat mapping: How much detail can remote sensing provide? Marine Biology, 130, 193-202.
[79] Myers BJ, Benson ML (1981) Rainforest species on large-scale colour photos. Photogrammetric Engineering and Remote Sensing, 47, 505-513.
[80] Olsson PO, Jönsson AM, Eklundh L (2012) A new invasive insect in Sweden Physokermes inopinatus: Tracing forest damage with satellite based remote sensing. Forest Ecology and Management, 285, 29-37.
[81] Palminteri S, Powell GVN, Asner GP, Peres CA (2012) LiDAR measurements of canopy structure predict spatial distribution of a tropical mature forest primate. Remote Sensing of Environment, 127, 98-105.
[82] Pau S, Gillespie TW, Wolkovich EM (2012) Dissecting NDVI-species richness relationships in Hawaiian dry forests. Journal of Biogeography, 39, 1678-1686.
[83] Pausas JG, Ribeiro E (2017) Fire and plant diversity at the global scale. Global Ecology and Biogeography, 26, 889-897.
[84] Pereira HM, Ferrier S, Walters M, Geller GN, Jongman RHG, Scholes RJ, Bruford MW, Brummitt N, Butchart SHM, Cardoso AC (2013) Essential biodiversity variables. Science, 339, 277-278.
[85] Peterson EB (2005) Estimating cover of an invasive grass (Bromus tectorum) using tobit regression and phenology derived from two dates of Landsat ETM+ data. International Journal of Remote Sensing, 12, 2491-2507.
[86] Pettorelli N, Owen HJF, Duncan C (2016) How do we want satellite remote sensing to support biodiversity conservation globally? Methods in Ecology and Evolution, 5, 656-665.
[87] Resasco J, Hale AN, Henry MC, Gorchov DL (2007) Detecting an invasive shrub in a deciduous forest understory using late-fall Landsat sensor imagery. International Journal of Remote Sensing, 28, 3739-3745.
[88] Rocchini D, Balkenhol N, Carter GA, Foody GM, Gillespie TW, He KS, Kark S, Levin N, Lucas K, Luoto M (2010) Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges. Ecological Informatics, 5, 318-329.
[89] Rocchini D, Luque S, Pettorelli N, Bastin L, Doktor D, Faedi N, Feilhauer H, Feret JB, Foody GM, Gavish Y (2018) Measuring β-diversity by remote sensing: A challenge for biodiversity monitoring. Methods in Ecology and Evolution, 9, 1787-1798.
[90] Sandino J, Wooler A, Gonzalez F (2017) Towards the automatic detection of pre-existing termite mounds through UAS and hyperspectral imagery. Sensors, 17, 2196.
[91] Schneider FD, Morsdorf F, Schmid B, Petchey OL, Hueni A, Schimel DS, Schaepman ME (2017) Mapping functional diversity from remotely sensed morphological and physiological forest traits. Nature Communications, 8, 1441.
[92] Schwaller MR, Southwell CJ, Emmerson LM (2013) Continental-scale mapping of Adelie penguin colonies from Landsat imagery. Remote Sensing of Environment, 139, 353-364.
[93] Seidel D, Hoffmann N, Ehbrecht M, Juchheim J, Ammer C (2015) How neighborhood affects tree diameter increment— New insights from terrestrial laser scanning and some methodical considerations. Forest Ecology and Management, 336, 119-128.
[94] Sidle JG, Johnson DH, Euliss BR, Tooze M (2002) Monitoring black-tailed prairie dog colonies with high-resolution satellite imagery. Wildlife Society Bulletin, 30, 405-411.
[95] Skidmore AK, Pettorelli N, Coops NC, Geller GN, Hansen M, Lucas R, Mücher CA, O’Connor B, Paganini M, Henrique MP, Schaepman ME, Turner W, Wang T, Wegmann M (2015) Agree on biodiversity metrics to track from space. Nature, 523, 403-405.
[96] Skowronek S, Ewald M, Isermann M, Van De Kerchove R, Lenoir J, Aerts R, Warrie J, Hattab T, Honnay O, Schmidtlein S (2017) Mapping an invasive bryophyte species using hyperspectral remote sensing data. Biological Invasions, 19, 239-254.
[97] Stevens N, Lehmann CER, Murphy BP, Durigan G (2017) Savanna woody encroachment is widespread across three continents. Global Change Biology, 23, 235-244.
[98] Tang ZY, Fang JY, Sun JY, Gaston KJ (2011) Effectiveness of protected areas in maintaining plant production. PLoS ONE, 6, e19116.
[99] Tao SL, Guo QH, Li C, Wang ZH, Fang JY (2016) Global patterns and determinants of forest canopy height. Ecology, 97, 3265-3270.
[100] Tesfamichael SG, Newete SW, Adam E, Dubula B (2017) Field spectroradiometer and simulated multispectral bands for discriminating invasive species from morphologically similar cohabitant plants. GIScience & Remote Sensing, 55, 417-436.
[101] Townsend PA, Eshleman KN, Welcker C (2004) Remote sensing of gypsy moth defoliation to assess variations in stream nitrogen concentrations. Ecological Applications, 14, 504-516.
[102] Tucker CJ, Hielkema JU, Roffey J (1985) The potential of satellite remote sensing of ecological conditions for survey and forecasting desert-locust activity. International Journal of Remote Sensing, 6, 127-138.
[103] Turner W (2014) Sensing biodiversity. Science, 346, 301-302.
[104] Turner W, Rondinini C, Pettorelli N, Mora B, Leidner AK, Szantoi Z, Buchanan G, Dech S, Dwyer J, Herold M (2015) Free and open-access satellite data are key to biodiversity conservation. Biological Conservation, 182, 173-176.
[105] Turner W, Spector S, Gardiner N, Fladeland M, Sterling E, Steininger M (2003) Remote sensing for biodiversity science and conservation. Trends in Ecology and Evolution, 18, 306-314.
[106] Tweheyo M, Lye KA, Weladji RB (2004) Chimpanzee diet and habitat selection in the Budongo Forest Reserve, Uganda. Forest Ecology and Management, 188, 267-278.
[107] Underwood E, Ustin S, DiPietro D (2003) Mapping nonnative plants using hyperspectral imagery. Remote Sensing of Environment, 86, 150-161.
[108] Ustin SL, Gamon JA (2010) Remote sensing of plant functional types. New Phytologist, 186, 795-816.
[109] Watson RM, Turner MIM (1965) A count of the large mammals of the Lake Manyara National Park: Results and discussion. African Journal of Ecology, 3, 95-98.
[110] Wiens J, Sutter R, Anderson M, Blanchar J, Barnett A, Aguilar-Amuchastegui N, Avery C, Laine S (2009) Selecting and conserving lands for biodiversity: The role of remote sensing. Remote Sensing of Environment, 113, 1370-1381.
[111] Wu B, Zhu CQ, Li DQ, Dong K, Wang XL, Shi PL (2006) Setting biodiversity conservation priorities in the Forests of the Upper Yangtze Ecoregion based on ecoregion conservation methodology. Biodiversity Science, 14, 87-97. (in Chinese with English abstract)
[吴波, 朱春全, 李迪强, 董珂, 王秀磊, 石培礼 (2006) 长江上游森林生态区生物多样性保护优先区确定——基于生态区保护方法. 生物多样性, 14, 87-97.]
[112] Xiao Y, Ouyang ZY, Zhu CQ, Zhao JZ, He GJ, Wang XK (2004) An assessment of giant panda habitat in Minshan, Sichuan, China. Acta Ecologica Sinica, 24, 1373-1379. (in Chinese with English abstract)
[肖燚, 欧阳志云, 朱春全, 赵景柱, 何国金, 王效科 (2004) 岷山地区大熊猫生境评价与保护对策研究. 生态学报, 24, 1373-1379.]
[113] Xin LJ, Jin YC, Zhu YP, Luo JW, Wang L, Chen B, Wang W (2015) Development of effectiveness assessment indicators of desert nature reserves in China: A case study of the Anxi National Nature Reserve. Journal of Desert Research, 35, 1693-1699. (in Chinese with English abstract)
[辛利娟, 靳勇超, 朱彦鹏, 罗建武, 王亮, 陈冰, 王伟 (2015) 中国荒漠类自然保护区保护成效评估指标及其应用. 中国沙漠, 35, 1693-1699.]
[114] Xin LJ, Wang W, Jin YC, Diao ZY, Li JS (2014) Indices of ecological effects of grassland nature reserves in China. Pratacultural Science, 31, 75-82. (in Chinese with English abstract)
[辛利娟, 王伟, 靳勇超, 刁兆岩, 李俊生 (2014) 全国草地类自然保护区的成效评估指标. 草业科学, 31, 75-82.]
[115] Xu C, Holmgren M, Van Nes EH, Maestre FT, Soliveres S, Berdugo M, Kefi S, Marquet PA, Abades S, Scheffer M. (2015) Can we infer plant facilitation from remote sensing? a test across global drylands. Ecological Applications, 25, 1456-1462Yan YY, Deng J, Zhang ZQ, Zhou XY, Yang DD (2014) Research progress in the protection efficacy evaluation of wildlife nature reserves. Chinese Journal of Ecology, 33, 1128-1134. (in Chinese with English abstract)
[晏玉莹, 邓娇, 张志强, 周先雁, 杨道德 (2014) 野生动物类型自然保护区保护成效评估研究进展. 生态学杂志, 33, 1128-1134.]
[116] Zellweger F, Baltensweiler A, Ginzler C, Roth T, Braunisch V, Bugmann H, Bollmann K (2016) Environmental predictors of species richness in forest landscapes: Abiotic factors versus vegetation structure. Journal of Biogeography, 43, 1080-1090.
[117] Zhang J, Hu J, Lian J, Fan Z, Ouyang X, Ye W (2016a) Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring. Biological Conservation, 198, 60-69.
[118] Zhang J, Nielsen SE, Mao LF, Chen SB, Svenning JC (2016b) Regional and historical factors supplement current climate in shaping global forest canopy height. Journal of Ecology, 104, 469-478.
[119] Zhang J, Rivard B, Sanchez-Azofeifa A, Castro-Esau K (2006) Intra- and inter-class spectral variability of tropical tree species at La Selva, Costa Rica: Implications for species identification using HYDICE imagery. Remote Sensing of Environment, 105, 129-141.
[120] Zhang YJ, Fan CK, Huang K, Liu YJ, Zu JX, Zhu JT (2017) Opportunities and challenges in remote sensing applications to ecosystem ecology. Chinese Journal of Ecology, 36, 809-823. (in Chinese with English abstract)
[张扬建, 范春捆, 黄珂, 刘瑶杰, 俎佳星, 朱军涛 (2017) 遥感在生态系统生态学上应用的机遇与挑战. 生态学杂志, 36, 809-823.]
[121] Zheng YM, Zhang HY, Niu ZG, Gong P (2012) Protection efficacy of national wetland reserves in China. Chinese Science Bulletin, 57, 207-230. (in Chinese)
[郑姚闽, 张海英, 牛振国, 宫鹏 (2012) 中国国家级湿地自然保护区保护成效初步评估. 科学通报, 57, 207-230.]
[122] Zimmermann NE, Edwards TC, Moisen GG, Frescino TS, Blackard JA (2007) Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah. Journal of Applied Ecology, 44, 1057-1067.
[123] Zou L, Miller SN, Schmidtmann ET (2006) Mosquito larval habitat mapping using remote sensing and GIS: Implications of coalbed methane development and West Nile Virus. Journal of Medical Entomology, 43, 1034-1041.
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