IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v10y2021i3p262-d510954.html
   My bibliography  Save this article

Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach

Author

Listed:
  • Qianning Zhang

    (Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China)

  • Zhu Xu

    (Faculty of Geosciences and Environmental Engineering, Southwest Jiaotong University, Chengdu 611756, China
    State-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Southwest Jiaotong University, Chengdu 611756, China
    National Collaborative Innovation Center for Rail Transport Safety, Southwest Jiaotong University, Chengdu 611756, China)

Abstract

Scale effects are inherent in spatial analysis. Quantitative knowledge about them is necessary for properly interpreting and scaling analysis results. The objective of this study was to systematically model patch area scaling and the associated uncertainty. A hybrid approach was taken to tackle the difficulty involved. Recognizing that patch’s size and shape play the key role in shaping its scaling behavior, a function model of patch area scaling based on patch morphology was first conceptually formulated. It was then substantiated by sampling and interpolating in the scale-integrated domain of patch morphology, which is characterized by a one-dimensional size index, namely the relative support range (RSR), and a compactness index, namely filling . The area scaling model obtained unveils a simple consistent scaling pattern of all patches and an overall fading range between 0.12 and 3.16 in terms of RSR. The uncertainty model built exhibits a filling -dependent pattern of the variance of patch area, which can be as large as 0.67 (i.e., 67%) in terms of standard deviation. The models were validated by using them to predict patch and class area scaling of the test patches and landscapes. This study demonstrated the basic feasibility of analytically modeling scaling behavior. It also revealed the uncertainty of scale effects is very significant due to the inevitable randomness in rasterization.

Suggested Citation

  • Qianning Zhang & Zhu Xu, 2021. "Fully Portraying Patch Area Scaling with Resolution: An Analytics and Descriptive Statistics-Combined Approach," Land, MDPI, vol. 10(3), pages 1-21, March.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:3:p:262-:d:510954
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/10/3/262/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/10/3/262/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lausch, Angela & Salbach, Christoph & Schmidt, Andreas & Doktor, Daniel & Merbach, Ines & Pause, Marion, 2015. "Deriving phenology of barley with imaging hyperspectral remote sensing," Ecological Modelling, Elsevier, vol. 295(C), pages 123-135.
    2. Chen Jun & Yifang Ban & Songnian Li, 2014. "Open access to Earth land-cover map," Nature, Nature, vol. 514(7523), pages 434-434, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Menelio Bardales & Catherine Bukowski & Valentín Molina-Moreno & Francisco Jesús Gálvez-Sánchez & Ángel Fermín Ramos-Ridao, 2022. "A Tool for the Assessment of Forest Biomass as a Source of Rural Sustainable Energy in Natural Areas in Honduras," Sustainability, MDPI, vol. 14(18), pages 1-15, September.

    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. Hao Wang & Huimin Yan & Yunfeng Hu & Yue Xi & Yichen Yang, 2022. "Consistency and Accuracy of Four High-Resolution LULC Datasets—Indochina Peninsula Case Study," Land, MDPI, vol. 11(5), pages 1-19, May.
    2. Jingyi Wang & Chen Weng & Zhen Wang & Chunming Li & Tingting Wang, 2022. "What Constitutes the High-Quality Soundscape in Human Habitats? Utilizing a Random Forest Model to Explore Soundscape and Its Geospatial Factors Behind," IJERPH, MDPI, vol. 19(21), pages 1-23, October.
    3. Qing Yang & Zhanqiang Chang & Chou Xie & Chaoyong Shen & Bangsen Tian & Haoran Fang & Yihong Guo & Yu Zhu & Daoqin Zhou & Xin Yao & Guanwen Chen & Tao Xie, 2023. "Combining Soil Moisture and MT-InSAR Data to Evaluate Regional Landslide Susceptibility in Weining, China," Land, MDPI, vol. 12(7), pages 1-34, July.
    4. Gang Lin & Dong Jiang & Xiang Li & Jingying Fu, 2022. "Accounting for Carbon Sink and Its Dominant Influencing Factors in Chinese Ecological Space," Land, MDPI, vol. 11(10), pages 1-19, October.
    5. Hao Wang & Yunfeng Hu, 2021. "Simulation of Biocapacity and Spatial-Temporal Evolution Analysis of Loess Plateau in Northern Shaanxi Based on the CA–Markov Model," Sustainability, MDPI, vol. 13(11), pages 1-17, May.
    6. Mu Li & Lingli Zhang & Yuanyuan Chen & Shuangliang Liu & Mingyao Cai & Qiangqiang Sun, 2024. "Construction of Landscape Ecological Risk Collaborative Management Network in Mountainous Cities—A Case Study of Zhangjiakou," Land, MDPI, vol. 13(10), pages 1-28, September.
    7. Yunchen Wang & Boyan Li, 2022. "The Spatial Disparities of Land-Use Efficiency in Mainland China from 2000 to 2015," IJERPH, MDPI, vol. 19(16), pages 1-20, August.
    8. Zhang, Shaoyao & Deng, Wei & Zhang, Hao & Wang, Zhanyun, 2023. "Identification and analysis of transitional zone patterns along urban-rural-natural landscape gradients: An application to China’s southwest mountains," Land Use Policy, Elsevier, vol. 129(C).
    9. Chaoqing Huang & Chao He & Qian Wu & MinhThu Nguyen & Song Hong, 2023. "Classification of the Land Cover of a Megacity in ASEAN Using Two Band Combinations and Three Machine Learning Algorithms: A Case Study in Ho Chi Minh City," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
    10. Wei Guo & Yongjia Teng & Yueguan Yan & Chuanwu Zhao & Wanqiu Zhang & Xianglin Ji, 2022. "Simulation of Land Use and Carbon Storage Evolution in Multi-Scenario: A Case Study in Beijing-Tianjin-Hebei Urban Agglomeration, China," Sustainability, MDPI, vol. 14(20), pages 1-19, October.
    11. Ziqian Kang & Shuo Wang & Ling Xu & Fenglin Yang & Shushen Zhang, 2021. "Suitability assessment of urban land use in Dalian, China using PNN and GIS," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 106(1), pages 913-936, March.
    12. Myroslava Lesiv & Anatoly Shvidenko & Dmitry Schepaschenko & Linda See & Steffen Fritz, 2019. "A spatial assessment of the forest carbon budget for Ukraine," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 24(6), pages 985-1006, August.
    13. Feng Zhang & Xiasong Hu & Jing Zhang & Chengyi Li & Yupeng Zhang & Xilai Li, 2022. "Change in Alpine Grassland NPP in Response to Climate Variation and Human Activities in the Yellow River Source Zone from 2000 to 2020," Sustainability, MDPI, vol. 14(14), pages 1-15, July.
    14. Baifei Ren & Keunhyun Park & Anil Shrestha & Jun Yang & Melissa McHale & Weilan Bai & Guangyu Wang, 2022. "Impact of Human Disturbances on the Spatial Heterogeneity of Landscape Fragmentation in Qilian Mountain National Park, China," Land, MDPI, vol. 11(11), pages 1-26, November.
    15. Dongchuan Wang & Hua Chai & Zhiheng Wang & Kangjian Wang & Hongyi Wang & Hui Long & Jianshe Gao & Aoze Wei & Sirun Wang, 2022. "Dynamic Monitoring and Ecological Risk Analysis of Lake Inundation Areas in Tibetan Plateau," Sustainability, MDPI, vol. 14(20), pages 1-20, October.
    16. Zhibo Lu & Qian Song & Jianyun Zhao, 2023. "Evolution of Landscape Ecological Risk and Identification of Critical Areas in the Yellow River Source Area Based on LUCC," Sustainability, MDPI, vol. 15(12), pages 1-16, June.
    17. Xuebin Zhang & Litang Yao & Jun Luo & Wenjuan Liang, 2022. "Exploring Changes in Land Use and Landscape Ecological Risk in Key Regions of the Belt and Road Initiative Countries," Land, MDPI, vol. 11(6), pages 1-22, June.
    18. Lei Wang & Aifeng Lv, 2022. "Identification and Diagnosis of Transboundary River Basin Water Management in China and Neighboring Countries," Sustainability, MDPI, vol. 14(19), pages 1-13, September.
    19. Yaoping Cui & Xinliang Xu & Jinwei Dong & Yaochen Qin, 2016. "Influence of Urbanization Factors on Surface Urban Heat Island Intensity: A Comparison of Countries at Different Developmental Phases," Sustainability, MDPI, vol. 8(8), pages 1-14, July.
    20. Chen, Zhe & Yang, Bisheng & Zhu, Rui & Dong, Zhen, 2024. "City-scale solar PV potential estimation on 3D buildings using multi-source RS data: A case study in Wuhan, China," Applied Energy, Elsevier, vol. 359(C).

    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:3:p:262-:d:510954. 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.