IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i11p1192-d672846.html
   My bibliography  Save this article

Prediction and Selection of Appropriate Landscape Metrics and Optimal Scale Ranges Based on Multi-Scale Interaction Analysis

Author

Listed:
  • Gang Fu

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    College of Water Sciences, Beijing Normal University, Beijing 100875, China
    State Environment Protection Key Laboratory of Regional Eco-Processand Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Wei Wang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    State Environment Protection Key Laboratory of Regional Eco-Processand Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Junsheng Li

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    College of Water Sciences, Beijing Normal University, Beijing 100875, China
    State Environment Protection Key Laboratory of Regional Eco-Processand Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Nengwen Xiao

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    State Environment Protection Key Laboratory of Regional Eco-Processand Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Yue Qi

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    State Environment Protection Key Laboratory of Regional Eco-Processand Function Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

Abstract

Landscape metrics are widely used in landscape planning and land use management. Understanding how landscape metrics respond with scales can provide more accurate prediction information; however, ignoring the interference of multi-scale interaction may lead to a severe systemic bias. In this study, we quantitatively analyzed the scaling sensitivity of metrics based on multi-scale interaction and predict their optimal scale ranges. Using a big data method, the multivariate adaptive regression splines model (MARS), and the partial dependence model (PHP), we studied the scaling relationships of metrics to changing scales. The results show that multi-scale interaction commonly exists in most landscape metric scaling responses, making a significant contribution. In general, the scaling effects of the three scales (i.e., spatial extent, spatial resolution, and classification of land use) are often in a different direction, and spatial resolution is the primary driving scale in isolation. The findings show that only a few metrics are highly sensitive to the three scales throughout the whole scale spectrum, while the other metrics are limited within a certain threshold range. This study confirms that the scaling-sensitive scalograms can be used as an application guideline for selecting appropriate landscape metrics and optimal scale ranges.

Suggested Citation

  • Gang Fu & Wei Wang & Junsheng Li & Nengwen Xiao & Yue Qi, 2021. "Prediction and Selection of Appropriate Landscape Metrics and Optimal Scale Ranges Based on Multi-Scale Interaction Analysis," Land, MDPI, vol. 10(11), pages 1-21, November.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:11:p:1192-:d:672846
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/11/1192/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/11/1192/
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lei Shi & Xu He & Bo Hu & Jiuwei Li & Lei Yu, 2024. "Evaluation of Rice–Crayfish Field Fragmentation Based on Landscape Indices: A Case Study of Qianjiang City, China," Land, MDPI, vol. 13(7), pages 1-17, July.
    2. Karolina Zięba-Kulawik & Piotr Wężyk, 2022. "Monitoring 3D Changes in Urban Forests Using Landscape Metrics Analyses Based on Multi-Temporal Remote Sensing Data," Land, MDPI, vol. 11(6), pages 1-19, June.
    3. Shangkun Yu & Yi Miao & Mengcheng Li & Xiaoming Ding & Chengxin Wang & Wangsheng Dou, 2022. "Theoretical Development Model for Rural Settlements against Rural Shrinkage: An Empirical Study on Pingyin County, China," Land, MDPI, vol. 11(8), pages 1-20, August.
    4. Hebing Zhang & Qingqing Yan & Fangfang Xie & Shouchen Ma, 2023. "Evaluation and Prediction of Landscape Ecological Security Based on a CA-Markov Model in Overlapped Area of Crop and Coal Production," Land, MDPI, vol. 12(1), pages 1-18, January.
    5. Sonali Sharma & Pawan Kumar Joshi & Christine Fürst, 2022. "Exploring Multiscale Influence of Urban Growth on Landscape Patterns of Two Emerging Urban Centers in the Western Himalaya," Land, MDPI, vol. 11(12), pages 1-23, December.

    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:10:y:2021:i:11:p:1192-:d:672846. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.