IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v13y2024i9p1527-d1482140.html
   My bibliography  Save this article

Wetlands Mapping and Monitoring with Long-Term Time Series Satellite Data Based on Google Earth Engine, Random Forest, and Feature Optimization: A Case Study in Gansu Province, China

Author

Listed:
  • Jian Zhang

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

  • Xiaoqian Liu

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

  • Yao Qin

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

  • Yaoyuan Fan

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

  • Shuqian Cheng

    (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China)

Abstract

Given global climate change and rapid land cover changes due to human activities, accurately identifying, extracting, and monitoring the long-term evolution of wetland resources is profoundly significant, particularly in areas with fragile ecological conditions. Gansu Province, located in northwest China, contains all wetland types except coastal wetlands. The complexity of its wetland types has resulted in a lack of accurate and comprehensive information on wetland changes. Using Gansu Province as a case study, we employed the GEE platform and Landsat time-series satellite data, combining high-quality sample datasets with feature-optimized multi-source feature sets. The random forest algorithm was utilized to create wetland classification maps for Gansu Province across eight periods from 1987 to 2020 at a 30 m resolution and to quantify changes in wetland area and type. The results showed that the wetland mapping method achieved robust classification results, with an average overall accuracy (OA) of 96.0% and a kappa coefficient of 0.954 across all years. The marsh type exhibited the highest average user accuracy (UA) and producer accuracy (PA), at 96.4% and 95.2%, respectively. Multi-source feature aggregation and feature optimization effectively improve classification accuracy. Topographic and seasonal features were identified as the most important for wetland extraction, while textural features were the least important. By 2020, the total wetland area in Gansu Province was 10,575.49 km 2 , a decrease of 4536.86 km 2 compared to 1987. The area of marshes decreased the most, primarily converting into grasslands and forests. River, lake, and constructed wetland types generally exhibited an increasing trend with fluctuations. This study provides technical support for wetland ecological protection in Gansu Province and offers a reference for wetland mapping, monitoring, and sustainable development in arid and semi-arid regions.

Suggested Citation

  • Jian Zhang & Xiaoqian Liu & Yao Qin & Yaoyuan Fan & Shuqian Cheng, 2024. "Wetlands Mapping and Monitoring with Long-Term Time Series Satellite Data Based on Google Earth Engine, Random Forest, and Feature Optimization: A Case Study in Gansu Province, China," Land, MDPI, vol. 13(9), pages 1-25, September.
    • Handle: RePEc:gam:jlands:v:13:y:2024:i:9:p:1527-:d:1482140
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/13/9/1527/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/13/9/1527/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jean-François Pekel & Andrew Cottam & Noel Gorelick & Alan S. Belward, 2016. "High-resolution mapping of global surface water and its long-term changes," Nature, Nature, vol. 540(7633), pages 418-422, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Giacomo Falchetta & Nicolò Stevanato & Magda Moner-Girona & Davide Mazzoni & Emanuela Colombo & Manfred Hafner, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," Working Papers 2020.09, Fondazione Eni Enrico Mattei.
    2. Berggreen, Steve & Mattisson, Linn, 2023. "The Curse of Bad Geography: Stagnant Water, Diseases, and Children’s Human Capital," Working Papers 2023:11, Lund University, Department of Economics.
    3. Nicolás Ruiz, Néstor & Suárez Alonso, María Luisa & Vidal-Abarca, María Rosario, 2021. "Contributions of dry rivers to human well-being: A global review for future research," Ecosystem Services, Elsevier, vol. 50(C).
    4. Jinlong Li & Genxu Wang & Chunlin Song & Shouqin Sun & Jiapei Ma & Ying Wang & Linmao Guo & Dongfeng Li, 2024. "Recent intensified erosion and massive sediment deposition in Tibetan Plateau rivers," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    5. Mohammad Zeynoddin & Hossein Bonakdari & Silvio José Gumiere & Alain N. Rousseau, 2023. "Multi-Tempo Forecasting of Soil Temperature Data; Application over Quebec, Canada," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    6. Romy Hulskamp & Arjen Luijendijk & Bas Maren & Antonio Moreno-Rodenas & Floris Calkoen & Etiënne Kras & Stef Lhermitte & Stefan Aarninkhof, 2023. "Global distribution and dynamics of muddy coasts," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    7. Vinícius B. P. Chagas & Pedro L. B. Chaffe & Günter Blöschl, 2022. "Climate and land management accelerate the Brazilian water cycle," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    8. Zhang, Yuliang & Wu, Zhiyong & Singh, Vijay P. & Lin, Qingxia & Ning, Shaowei & Zhou, Yuliang & Jin, Juliang & Zhou, Rongxing & Ma, Qiang, 2023. "Agricultural drought characteristics in a typical plain region considering irrigation, crop growth, and water demand impacts," Agricultural Water Management, Elsevier, vol. 282(C).
    9. Paulilo Brasil & Pedro Medeiros, 2020. "NeStRes – Model for Operation of Non-Strategic Reservoirs for Irrigation in Drylands: Model Description and Application to a Semiarid Basin," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(1), pages 195-210, January.
    10. Donghui Xu & Gautam Bisht & Zeli Tan & Eva Sinha & Alan V. Vittorio & Tian Zhou & Valeriy Y. Ivanov & L. Ruby Leung, 2024. "Climate change will reduce North American inland wetland areas and disrupt their seasonal regimes," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    11. Qianhan Wu & Linghong Ke & Jida Wang & Tamlin M. Pavelsky & George H. Allen & Yongwei Sheng & Xuejun Duan & Yunqiang Zhu & Jin Wu & Lei Wang & Kai Liu & Tan Chen & Wensong Zhang & Chenyu Fan & Bin Yon, 2023. "Satellites reveal hotspots of global river extent change," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    12. Alexey Victorov & Veronika Kapralova & Timofey Orlov & Olga Trapeznikova & Maria Arkhipova, 2022. "Research into Cryolithozone Spatial Pattern Changes Based on the Mathematical Morphology of Landscapes," Energies, MDPI, vol. 15(3), pages 1-19, February.
    13. Renlu Qiao & Shuo Gao & Xiaochang Liu & Li Xia & Guobin Zhang & Xi Meng & Zhiyu Liu & Mo Wang & Shiqi Zhou & Zhiqiang Wu, 2024. "Understanding the global subnational migration patterns driven by hydrological intrusion exposure," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    14. Eleni S. Bekri & Ioannis P. Kokkoris & Charalambos S. Christodoulou & Antonia Sophocleous-Lemonari & Panayotis Dimopoulos, 2023. "Management Implications at a Protected, Peri-Urban, Salt Lake Ecosystem: The Case of Larnaca’s Salt Lakes (Cyprus)," Land, MDPI, vol. 12(9), pages 1-18, September.
    15. Margaret Kalacska & Oliver Lucanus & Leandro Sousa & J. Pablo Arroyo-Mora, 2020. "High-Resolution Surface Water Classifications of the Xingu River, Brazil, Pre and Post Operationalization of the Belo Monte Hydropower Complex," Data, MDPI, vol. 5(3), pages 1-12, August.
    16. Abbasi, H.N. & Zeeshan, Muhammad, 2023. "An integrated Geographic Information System and Analytical Hierarchy process based approach for site suitability analysis of on-grid hybrid concentrated solar-biomass powerplant," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    17. Quezada Lambertin, Carlos Eduardo & Nina Vargas, Marco Leandro & Flores Quizbert, Ruben, 2023. "Estimación del indicador 6.6.1: Proporción de cuencas hidrográficas de municipios y territorios indígenas de Bolivia que experimentan grandes cambios en la extensión de sus aguas superficiales," Documentos de trabajo 2/2023, Instituto de Investigaciones Socio-Económicas (IISEC), Universidad Católica Boliviana.
    18. Yi Xi & Shushi Peng & Gang Liu & Agnès Ducharne & Philippe Ciais & Catherine Prigent & Xinyu Li & Xutao Tang, 2022. "Trade-off between tree planting and wetland conservation in China," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    19. Falchetta, Giacomo & Stevanato, Nicolò & Moner-Girona, Magda & Mazzoni, Davide & Colombo, Emanuela & Hafner, Manfred, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," FEP: Future Energy Program 305213, Fondazione Eni Enrico Mattei (FEEM) > FEP: Future Energy Program.
    20. Conghong Huang & Yan Tang & Yiyang Wu & Yu Tao & Muwu Xu & Nan Xu & Mingze Li & Xiaodan Liu & Henghui Xi & Weixin Ou, 2024. "Assessing Long-Term Thermal Environment Change with Landsat Time-Series Data in a Rapidly Urbanizing City in China," Land, MDPI, vol. 13(2), pages 1-15, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jlands:v:13:y:2024:i:9:p:1527-:d:1482140. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.