盘点论文里10种常用的研究区图
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2023年05月26日 10:19:44
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论文研究区图很简单,大家记住以下三点: 一是地图要素不能漏 二是颜值配色要注意 三是该标注的就标注 总之,   人靠衣装,论文靠图装,好看就行~ 不多说,将各种研究区图分类展示

论文研究区图很简单,大家记住以下三点:

总之,   人靠衣装,论文靠图装,好看就行~

不多说,将各种研究区图分类展示

图1( 黑白基础款

配料:行政边界



 图2(彩色基础款)

配料:行政边界、Arcgis在线地图



 图3(彩色基础款)

配料:行政边界、Arcgis在线地图



 图4(DEM款)

配料:行政边界、DEM



 图5(卫片款)

配料:行政边界、 Arcgis在线卫片



 图6(夹带“私货”款)

配料:行政边界、研究数据(路网、共享单车)



 图7(夹带“私货”款)

配料:行政边界、研究数据(路网、共享单车)



 图8(夹带“私货”款)

配料:行政边界、在线卫片、研究数据(建筑、宜出行数据)



 图9(轻奢款)

配料: 行政边界、Arcgis在线地图、鹰眼图(左下角)、不同透明度的掩膜



图10(高定款)

配料:DEM、鹰眼图、在线卫片、带透明度的图例背景、 阴影的 行政边界、自己DIY的高程图例


以上各图均经过审稿检验,起码不出错,足矣,供大家参考~

     

参考文献
图1:Cui X, Li S*, Gao F. Examining spatial carbon metabolism: Features, future simulation, and land-based mitigation, Ecological Modelling,438,2020,109325,
图2:Gao F, Li S*, Tan Z, Wu Z, Zhang X, Huang  G, Huang Z. (2021) Understanding the modifiable areal unit problem in dockless bike sharing usage and exploring the interactive effects of built environment factors, International Journal of Geographical Information Science, 35:9, 1905-1925
图3:Deng X, Gao F*, Liao S, Li S. Unraveling the association between the built environment and air pollution from a geospatial perspective,Journal of Cleaner Production,386,2023,135768
图4:Deng X, Liu Y, Gao F*, Liao S, Zhou F, Cai G. Spatial Distribution and Mechanism of Urban Occupation Mixture in Guangzhou: An Optimized GeoDetector-Based Index to Compare Individual and Interactive Effects. ISPRS International Journal of Geo-Information. 2021; 10(10):659.
图5:Gao, F., Li, S*, Tan, Z. et al. Visualizing the Spatiotemporal Characteristics of Dockless Bike Sharing Usage in Shenzhen, China. J geovis spat anal 6, 12 (2022).
图6:高枫,李少英*,吴志峰,吕帝江,黄冠平 & 刘小平.(2019).广州市主城区共享单车骑行目的地时空特征与影响因素. 地理研究(12),2859-2872.
图7: Gao F, Li S*, Tan Z, Zhang X, Lai Z, Tan Z. How Is Urban Greenness Spatially Associated with Dockless Bike Sharing Usage on Weekdays, Weekends, and Holidays?     ISPRS  International Journal of Geo-Information   . 2021; 10(4):238.
图8: Gao F, Huang G, Li S*, Huang Z, Chai L. Integrating the Eigendecomposition Approach and k-Means Clustering for Inferring Building Functions with Location-Based Social Media Data.  ISPRS  International Journal of Geo-Information . 2021; 10(12):834.
图9: Gao, F., Wu, J*., Xiao, J., Li, X., Liao, S., Chen, W. (2023). Spatially explicit carbon emissions by remote sensing and social sensing. Environmental Research,221,115257.
图10:Deng, X., Gao, F*., Liao, S*., Liu, Y., Chen, W. (2022). Spatiotemporal evolution patterns of urban heat island and its relationship with urbanization in Guangdong-Hong Kong-Macao greater bay area of China from 2000 to 2020. Ecological Indicators,146,109817.

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