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Ein umfassendes Bewertungssystem für die Gesundheit des aquatischen Ökosystems basierend auf Fernerkundungstechnologie

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Water Science and Technology Institute, Beijing 100048, China

  • Email：tao_gf@mail.bnu.edu.cn
  • Introduction：陶果丰，研究方向为生态遥感和植被定量遥感。E-mail： tao_gf@mail.bnu.edu.cn
TAO Guofeng123,  
  • Affiliation：

    Beijing Water Science and Technology Institute, Beijing 100048, China

XUE Wanlai3,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

YUAN Bo12,  
  • Affiliation：

    Beijing Water Science and Technology Institute, Beijing 100048, China

LI Tianyu3,  
  • Affiliation：

    Beijing Water Science and Technology Institute, Beijing 100048, China

LI Wenzhong3,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

LI Jie12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

ZHAO Linlin12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

CUI Yuran12,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

XU Weiye12,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

WEI Xiangqin4,  
  • role： Corresponding author通信作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Advanced Interdisciplinary Institute of Satellite Applications, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

    Beijing Engineering Research Center for Global Land Remote Sensing Products, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China

  • Email：jiakun@bnu.edu.cn
  • Introduction：贾坤，研究方向为生态遥感和植被定量遥感。E-mail： jiakun@bnu.edu.cn
JIA Kun12*

Resümee

Eine wissenschaftliche und vernünftige Bewertung des Gesundheitszustands des aquatischen Ökosystems ist von großer Bedeutung für den Schutz der Kernstruktur und Dienstleistungsfunktionen des aquatischen Ökosystems. Derzeit gibt es nur wenige umfassende Studien zur Bewertung des regionalen aquatischen Ökosystems, und das Bewertungssystem weist Probleme wie eine einzige Art von Bewertungsindikatoren und Einschränkungen durch bodengestützte Beobachtungen auf. Aus diesem Grund konstruierte diese Studie unter Verwendung eines Fernerkundungsansatzes ein umfassendes Bewertungssystem für die Gesundheit des aquatischen Ökosystems in Peking, das die physikalische Struktur des Ökosystems, hydrologische und wasserqualitätsbezogene Elemente sowie landseitige Vegetationselemente umfasst. Gleichzeitig wurde die AHP (Analytic Hierarchy Process) -Methode mit der Entropie-Gewichtungsmethode kombiniert, um die Bewertungsindikatoren rationale zu gewichten und ein fernerkundungsgestütztes Bewertungssystem für die Gesundheit des aquatischen Ökosystems zu entwickeln. Basierend auf dem Gesamtindikatorwert für die Bewertung wurden die aquatischen Ökosysteme in die Kategorien Gesundheit, gut, durchschnittlich und schlecht unterteilt. Anhand von 10 typischen Gewässern in Peking wie dem Yongding-Fluss, dem Chaobai-Fluss, dem Kunming-See und dem Miyun-Stausee wurde eine umfassende Bewertung der Gesundheit des aquatischen Ökosystems durchgeführt. Die Ergebnisse zeigen: (1) Das Bewertungssystem kann den Zustand der Gesundheit des aquatischen Ökosystems vernünftig bewerten. Die hydrologischen und wasserqualitätsbezogenen Elemente haben den größten Einfluss auf die Gesundheit des aquatischen Ökosystems, gefolgt von den landseitigen Vegetationselementen und der geringsten Auswirkung der physikalischen Struktur des Ökosystems; (2) Unter den 10 typischen Gewässern in Peking wird der Yongding-Fluss und der Yuanmingyuan-See als gut bewertet, während die restlichen Gewässer als gesund eingestuft werden. Es wird empfohlen, gezielte ökologische Sanierungen für den Yongding-Fluss und den Yuanmingyuan-See durchzuführen.

Schlüsselwort

Fernerkundung; aquatisches Ökosystem; Gesundheitsbewertung; Bewertungssystem; rationalisierte Bewertung; Peking; Peking 2; Konstruktion des Gesamtindikatorwerts

References

  1. 1.
    Bai Y, Li S G, Liu M H and Guo Q. 2022. Assessment of vegetation change on the Mongolian Plateau over three decades using different remote sensing products. Journal of Environmental Management, 317: 115509
  2. 2.
    Bo L M, Wei W, Yin L, Zhao L and Xia J N. 2023a. Evolution characteristics and influencing factors of hydro-ecological space pattern in the Yangtze River Economic Belt from 2000 to 2020. China Environmental Science, 43(2): 874-885
  3. 3.
    Bo L M, Wei W, Zhao L, Yin L and Xia J N. 2023b. Spatial and temporal evolution characteristics and the driving mechanism of water eco-space in the Tibetan Plateau. Advances in Earth Science, 38(4): 401-413
  4. 4.
    Chawla I, Karthikeyan L and Mishra A K. 2020. A review of remote sensing applications for water security: quantity, quality, and extremes. Journal of Hydrology, 585: 124826
  5. 5.
    Cramer W, Kicklighter D W, Bondeau A, Moore III B, Churkina G, Nemry B, Ruimy A, Schloss A L and ThE. Participants OF. ThE. Potsdam NpP. Model Intercomparison. 1999. Comparing global models of terrestrial net primary productivity (NPP): overview and key results. Global Change Biology, 5(S1): 1-15
  6. 6.
    Deng W, Yan D H, He Y and Zhang G X. 2004. Study on ecological storeroom of water in the watershed. Advances in Water Science, 15(3): 341-345
  7. 7.
    Dogliotti A I, Ruddick K G, Nechad B, Doxaran D and Knaeps E. 2015. A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters. Remote Sensing of Environment, 156: 157-168
  8. 8.
    Duarte G, Segurado P, Haidvogl G, Pont D, Ferreira M T and Branco P. 2021. Damn those damn dams: fluvial longitudinal connectivity impairment for European diadromous fish throughout the 20th century. Science of the Total Environment, 761: 143293
  9. 9.
    Feng Q, Cheng X J, Shen X, Xiao X, Wang L H and Zhang W. 2017. Inland riverine turbidity estimation for Hanjiang river with Landsat-8 OLI imager. Geomatics and Information Science of Wuhan University, 42(5): 643-647
  10. 10.
    Frothingham K M, Rhoads B L and Herricks E E. 2001. Stream geomorphology and fish community structure in channelized and meandering reaches of an agricultural stream//Dorava J M, Montgomery D R, Palcsak B B and Fitzpatrick F A, eds. Geomorphic Processes and Riverine Habitat. Washington: American Geophysical Union: 105-117
  11. 11.
    Gao Y T. 2014. Typical River Characterization Index Analysis and Health Assessment in Beijing. Beijing: Beijing Forestry University
  12. 12.
    Gharibi H, Mahvi A H, Nabizadeh R, Arabalibeik H, Yunesian M and Sowlat M H. 2012. A novel approach in water quality assessment based on fuzzy logic. Journal of Environmental Management, 112: 87-95
  13. 13.
    Gu L, Gao J R, Liu Y, Gao Y T, Qian B T and Wang Y. 2012. Assessment of river naturalness in Beijing suburb-taking Tanghe river as an example. Bulletin of Soil and Water Conservation, 32(1): 165-170
  14. 14.
    Jia K, Liang S L, Gu X F, Baret F, Wei X Q, Wang X X, Yao Y J, Yang L Q and Li Y W. 2016. Fractional vegetation cover estimation algorithm for Chinese GF-1 wide field view data. Remote Sensing of Environment, 177: 184-191
  15. 15.
    Jiang H Y，Jia K，Zhao X，Wei X Q，Wang B，Yao Y J，Zhang X T and Jiang B. 2020. Review on the theory， method， and research progress of leaf area index estimation in mountainous areas. Journal of Remote Sensing (in Chinese), 24(12): 1433-1449
  16. 16.
    Kelly E R, Cronk R, Kumpel E, Howard G and Bartram J. 2020. How we assess water safety: a critical review of sanitary inspection and water quality analysis. Science of the Total Environment, 718: 137237
  17. 17.
    Kumar M, Kalra N, Singh H, Sharma S, Rawat P S, Singh R K, Gupta A K, Kumar P and Ravindranath N H. 2021. Indicator-based vulnerability assessment of forest ecosystem in the Indian Western Himalayas: an analytical hierarchy process integrated approach. Ecological Indicators, 125: 107568
  18. 18.
    Li G C, Zhao H M, Wu Y, Yang B, Li L H, Zhang H, Yang Q G and Chen W. 2021. Spatiotemporal changes of key ecological and environmental parameters of Fangcheng Golden Camellia Nature Reserve in Guangxi from 2000 to 2016. Bulletin of Surveying and Mapping, (2): 13-17
  19. 19.
    Li R Y, Xin C L, Chen N, Xiao K W and Xin S J. 2022. Evaluation and prediction of water ecological security in Daxia River Basin on the perspective of Production-Living-Ecological Space. Water Resources and Hydropower Engineering, 53(7): 82-93
  20. 20.
    Niu Z R and Jia L. 2023. Water ecological security evaluation and diagnosis of obstacles in the Yangtze River Basin of Gansu Province from the perspective of Ecology-Life-Production space. Journal of Hydroecology, 44(2): 19-25
  21. 21.
    Piao S L, Fang J Y and Guo Q H. 2001. Application of CASA model to the estimation of Chinese terrestrial net primary productivity. Acta Phytoecologica Sinica, 25(5): 603-608
  22. 22.
    Rathi B S, Kumar P S and Vo D V N. 2021. Critical review on hazardous pollutants in water environment: occurrence, monitoring, fate, removal technologies and risk assessment. Science of the Total Environment, 797: 149134
  23. 23.
    Rhoads B L, Schwartz J S and Porter S. 2003. Stream geomorphology, bank vegetation, and three-dimensional habitat hydraulics for fish in midwestern agricultural streams. Water Resources Research, 39(8): 1218
  24. 24.
    Santos J I, Vidal T, Gonçalves F J M, Castro B B and Pereira J L. 2021. Challenges to water quality assessment in Europe–is there scope for improvement of the current Water Framework Directive bioassessment scheme in rivers?. Ecological Indicators, 121: 107030
  25. 25.
    Sun R, Pan X Y, Wang J W, Ren Y, Du P, Ma Y and Xing Y. 2021. An analysis and evaluation of ecological water replenishment benefit of Yongding River (Beijing section). China Rural Water and Hydropower, (6): 19-24
  26. 26.
    Tang Y, Wang Z G, Wang W Q, Huang H J and Yuan Y. 2020. Multifunctional classification of aquatic habitats for remote sensing data. Progress in Geography, 39(3): 454-460
  27. 27.
    Wang Y S, Yu X X, He K N, Song S M, Jia G D and Huang Z Y. 2012. Ecosystem services value based on land use change in Huairou reservoir watershed. Transactions of the Chinese Society of Agricultural Engineering, 28(5): 246-251
  28. 28.
    Yan G J, Hu R H, Luo J H, Marie W, Jiang H L, Mu X H, Xie D H and Zhang W M. 2019. Review of indirect optical measurements of leaf area index: recent advances, challenges, and perspectives. Agricultural and Forest Meteorology, 265: 390-411
  29. 29.
    Yang Q, Wang X H, Zhang J Y and Zhao W. 2017. Planning based on spatial pattern of water ecology. China Water Resources, (3): 6-9
  30. 30.
    Yang Y P, Wang Q, Xiao Q and Wen J G. 2006. Quantitative remote sensing inversion methods of chlorophyll-a concentration in Taihu Lake based on TM data. Geography and Geo-Information Science, 22(2): 5-8
  31. 31.
    Yu K J. 2015. Aquatic ecological infrastructure of wild China: the theory and practice. Journal of Poyang Lake, (1): 5-18
  32. 32.
    Yu K J, Wang C L, Li D H, Yuan H, Li W H and Hong M. 2019. The concept, methodology and a case study in defining the ecological redline for the hydro-ecological space. Acta Ecologica Sinica, 39(16): 5911-5921
  33. 33.
    Zhang S W, Yang R, Hou W X, Wang L L, Liu S, Song H Y, Zhao W J and Li L J. 2023. Analysis of fractional vegetation cover changes and driving forces on both banks of Yongding River before and after ecological water replenishment. Ecology and Environmental Sciences, 32(2): 264-273
  34. 34.
    Zheng G Z and Li C Y. 2022. An empirical algorithm for retrieving chlorophyll-a concentration in the sea area near Palawan Island. Science of Surveying and Mapping, 47(5): 168-176
  35. 35.
    Zheng Z B，Zhang R F，Li J Z，Lin L and Yang H. 2022. Remote sensing retrieval of chlorophyll-a concentration in Dianchi lake based on orbita hyperspectral imagery. National Remote Sensing Bulletin， 26(11)：2162-2173
  36. 36.
    Zhou B T， Zhang Y Y and Shi K. 2022. Research progress on remote sensing assessment of lake nutrient status and retrieval algorithms of characteristic parameters. National Remote Sensing Bulletin， 26(1)：77-91
  37. 37.
    Zhou D J, Wang G Z, He G J, Yin R Y, Long T F, Zhang Z M, Chen S B and Luo B. 2021. A large-scale mapping scheme for urban building from Gaofen-2 images using deep learning and hierarchical approach. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14: 11530-11545
  38. 38.
    Zhou G J, Tong Y L, Wang L Q, Chi H L, Zhu X H and Liang T. 2022. Multi-dimensional identification technology and application of water ecological space and protection line in the territorial spatial planning. Journal of Natural Resources, 37(12): 3102-3117
  39. 39.
    Zuo Q T, Liu J and Dou M. 2016. Analysis of the impact of dam operations on the river water ecological environment. Advances in Water Science, 27(3): 439-447

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