Linking Earth Observation and taxonomic, structural and functional biodiversity: Local to ecosystem perspectives

被引：135

作者：

Lausch, A. ^{[1
]}

Bannehr, L. ^{[2
]}

Beckmann, M. ^{[1
]}

Boehm, C. ^{[3
]}

Feilhauer, H. ^{[4
]}

Hacker, J. M. ^{[5
]}

Heurichr, M. ^{[6
]}

Jung, A. ^{[7
,8
]}

Klenke, R. ^{[9
]}

Neumann, C. ^{[10
]}

Pause, M. ^{[11
]}

Rocchini, D. ^{[12
]}

Schaepman, M. E. ^{[13
]}

Schmidtlein, S. ^{[14
]}

Schulz, K. ^{[15
]}

Selsam, P. ^{[3
]}

Settele, J. ^{[16
,17
]}

Skidmore, A. K. ^{[18
]}

Cord, A. F. ^{[1
]}

机构：

[1] UFZ Helmholtz Ctr Environm Res, Dept Computat Landscape Ecol, Permoserstr 15, D-04318 Leipzig, Germany

[2] Inst Geoinformat & Surveying, Facil Management & Geoinformat, Dept Architecture, Bauhausstr 8, D-06846 Dessau, Germany

[3] Friedrich Schiller Univ Jena, Dept Geog, Loebdergraben 32, D-07743 Jena, Germany

[4] FAU Erlangen Nurnberg, Inst Geog, Wetterkreuz 15, D-91058 Erlangen, Germany

[5] Flinders Univ S Australia, Airborne Res Australia Salisbury South, Sch Environm, Salisbury South, SA 5106, Australia

[6] Bavarian Forest Natl Pk, D-94481 Grafenau, Germany

[7] Szent Istvan Univ, MTA SZIE Plant Ecol Res Grp, Pater Karoly U1, H-2100 Godollo, Hungary

[8] Szent Istvan Univ, Tech Dept, Villanyi Ut 29-43, H-1118 Budapest, Hungary

[9] UFZ Helmholtz Ctr Environm Res, Dept Conservat Biol, Permoserstr 15, D-04318 Leipzig, Germany

[10] German Res Ctr Geosci GFZ, Helmholtz Ctr Potsdam, Dept Geodesy & Remote Sensing, D-14473 Potsdam, Germany

[11] UFZ Helmholtz Ctr Environm Res, Dept Monitoring & Explorat Technol, Permoserstr 15, D-14473 Potsdam, Germany

[12] Fdn Edmund Mach, Res & Innovat Ctr, Dept Biodivers & Mol Ecol, GIS & EO Unit, Via E Mach 1, I-38010 San Michele All Adige, TN, Italy

[13] Univ Zurich Irchel, Dept Geog, Winterthurerstr 190, CH-8057 Zurich, Switzerland

[14] KIT Karlsruhe, Inst Geog & Geoecol, Kaiserstr 12, D-76131 Karlsruhe, Germany

[15] Univ Nat Resources & Life Sci, Inst Water Management Hydrol & Hydraul Engn, Muthgasse 18, A-1190 Vienna, Austria

[16] UFZ Helmholtz Ctr Environm Res, Dept Community Ecol, Theodor Lieser Str 4, D-06120 Halle, Germany

[17] German Ctr Integrat Biodivers Res iDiv, iDiv, Deutsch Pl 5e, D-04103 Leipzig, Germany

[18] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, POB 217, NL-7500 AE Enschede, Netherlands

来源：

ECOLOGICAL INDICATORS | 2016年 / 70卷

关键词：

Remote sensing; Biodiversity; Spectral traits; Spectral trait variations; Spectral biodiversity; OBJECT-BASED APPROACH; INDUCED CHLOROPHYLL FLUORESCENCE; MODELING SPECIES DISTRIBUTIONS; LAND-COVER CLASSIFICATION; NATURA; 2000; HABITATS; LASER-SCANNING DATA; IMAGING SPECTROSCOPY; CONTINUOUS FIELDS; AFRICAN SAVANNAS; SIMULATED SENTINEL-2;

D O I：

10.1016/j.ecolind.2016.06.022

中图分类号：

X176 [生物多样性保护];

学科分类号：

090705 ;

摘要：

Impacts of human civilization on ecosystems threaten global biodiversity. In a changing environment, traditional in situ approaches to biodiversity monitoring have made significant steps forward to quantify and evaluate BD at many scales but still, these methods are limited to comparatively small areas. Earth observation (EO) techniques may provide a solution to overcome this shortcoming by measuring entities of interest at different spatial and temporal scales. This paper provides a comprehensive overview of the role of EO to detect, describe, explain, predict and assess biodiversity. Here, we focus on three main aspects related to biodiversity taxonomic diversity, functional diversity and structural diversity, which integrate different levels of organization molecular, genetic, individual, species, populations, communities, biomes, ecosystems and landscapes. In particular, we discuss the recording of taxonomic elements of biodiversity through the identification of animal and plant species. We highlight the importance of the spectral traits (ST) and spectral trait variations (STV) concept for EO-based biodiversity research. Furthermore we provide examples of spectral traits/spectral trait variations used in EO applications for quantifying taxonomic diversity, functional diversity and structural diversity. We discuss the use of EO to monitor biodiversity and habitat quality using different remote-sensing techniques. Finally, we suggest specifically important steps for a better integration of EO in biodiversity research. EO methods represent an affordable, repeatable and comparable method for measuring, describing, explaining and modelling taxonomic, functional and structural diversity. Upcoming sensor developments will provide opportunities to quantify spectral traits, currently not detectable with EO, and will surely help to describe biodiversity in more detail. Therefore, new concepts are needed to tightly integrate EO sensor networks with the identification of biodiversity. This will mean taking completely new directions in the future to link complex, large data, different approaches and models. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：317 / 339

页数：23

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