Concepedia

Geospatial Feature Importance

Geospatial Feature Importance is a methodological construct in geospatial data science that quantifies the relative contribution of individual spatial or spatiotemporal features to the predictive performance or explanatory power of a geospatial machine learning model.

43

Publications

1.7K

Citations

196

Authors

94

Institutions

Publications per year

2017–2026

38

Parents

Publications

43

Predicting Heavy Metal Adsorption on Soil with Machine Learning and Mapping Global Distribution of Soil Adsorption Capacities

Hongrui Yang, Kuan Huang, Kai Zhang et al. · Environmental Science & Technology · 2021 · 273 citations

, , +17

Interpretable Deep Learning for Spatial Analysis of Severe Hailstorms

David John Gagne, Sue Ellen Haupt, Douglas Nychka et al. · Monthly Weather Review · 2019 · 221 citations · Full text

, , +17

Feature importance: Opening a soil-transmitted helminth machine learning model via SHAP

Carlos Matías Scavuzzo, Juan M. Scavuzzo, Micaela Natalia Campero et al. · Infectious Disease Modelling · 2022 · 93 citations · Full text

, , +16

Comparing geospatial techniques to predict SOC stocks

Yaolin Liu, Long Guo, Qinghu Jiang et al. · Soil and Tillage Research · 2014 · 86 citations

, , +14

A comparison of machine learning approaches for identifying high-poverty counties: robust features of DMSP/OLS night-time light imagery

Guie Li, Zhongliang Cai, Xiaojian Liu et al. · International Journal of Remote Sensing · 2019 · 54 citations

, , +17

1–5 of 43

Authors

196

  1. XH
    Xiaoran Huang

    Swinburne University of Technology, Australia

    3 publications · 57 citations

    3

    h-index

  2. PL
    Paula Litkey

    Finnish Geospatial Research Institute, Finland

    2 publications · 35 citations

    2

    h-index

  3. LM
    Leena Matikainen

    Finnish Geospatial Research Institute, Finland

    2 publications · 35 citations

    2

    h-index

  4. BZ
    Bo Zhang

    South China Normal University, China

    2 publications · 42 citations

    2

    h-index

  5. JH
    Juha Hyyppä

    Finnish Geospatial Research Institute, Finland

    2 publications · 35 citations

    2

    h-index

1–5 of 196

Institutions

94

  1. Chinese Academy of Sciences

    Beijing, China

    4 h-index

    17 publications

    522 citations

  2. Swinburne University of Technology

    Melbourne, Australia

    3 h-index

    5 publications

    99 citations

  3. University of Twente

    Enschede, The Netherlands

    3 h-index

    10 publications

    292 citations

  4. North China University of Technology

    Beijing, China

    3 h-index

    11 publications

    201 citations

  5. University of Chinese Academy of Sciences

    Beijing, China

    3 h-index

    7 publications

    208 citations

  6. Chengdu University of Technology

    Chengdu, China

    2 h-index

    3 publications

    80 citations

  7. Nanjing University

    Nanjing, China

    2 h-index

    7 publications

    230 citations

  8. Institute of Geographic Sciences and Natural Resources Research

    Beijing, China

    2 h-index

    7 publications

    285 citations

1–8 of 94

Venues

  1. Remote Sensing

    7 publications · 214 citations

    7

    h-index

  2. Scientific Reports

    3 publications · 57 citations

    3

    h-index

  3. 2

    h-index

  4. International Journal of Health Geographics

    1 publications · 45 citations

    1

    h-index

  5. 1

    h-index

1–5