Mapping Homogeneous Response Areas for Forest Fuel Management Using Geospatial Data, K-Means, and Random Forest Classification

被引：0
|
作者：
Centro Universitario de la Costa Sur, Universidad de Guadalajara, Avenida Independencia Nacional 151, Jalisco, Autlán de Navarro [1 ]
48900, Mexico
不详 [2 ]
28801, Spain
不详 [3 ]
45110, Mexico
机构：
来源：
Forests | 1600年 / 12卷
关键词：
Average annual precipitation - Fire management - Forest fuel - Fuels management - Geo-spatial data - Homogeneous response area - K-means - Machine-learning - P-values - Random forest classification;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
94
引用
收藏
相关论文
共 50 条
  • [1] Mapping Homogeneous Response Areas for Forest Fuel Management Using Geospatial Data, K-Means, and Random Forest Classification
    Agustin Chavez-Duran, Alvaro
    Olvera-Vargas, Miguel
    Figueroa-Rangel, Blanca
    Garcia, Mariano
    Aguado, Inmaculada
    Ariel Ruiz-Corral, Jose
    FORESTS, 2022, 13 (12):
  • [2] detection of response shift using a mixed approach combining: k-means and random forest methods
    Boucekine, Mohamed
    Baumstarck, Karine
    Michel, Pierre
    Boyer, Laurent
    Loundou, Anderson
    Ghattas, Badih
    Auquier, Pascal
    QUALITY OF LIFE RESEARCH, 2015, 24 : 135 - 136
  • [3] The k-means forest classifier for high dimensional data
    Chen, Zizhong
    Ding, Xin
    Xia, Shuyin
    Chen, Baiyun
    2018 9TH IEEE INTERNATIONAL CONFERENCE ON BIG KNOWLEDGE (ICBK), 2018, : 322 - 327
  • [4] Traffic Accidents Analytics in UK Urban Areas using k-means Clustering for Geospatial Mapping
    Sinclair, Christopher
    Das, Saptarshi
    2021 INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY AND FUTURE ELECTRIC TRANSPORTATION (SEFET), 2021,
  • [5] A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm
    Bhattacharjee, Ananya
    Murugan, R.
    Goel, Tripti
    HEALTH AND TECHNOLOGY, 2022, 12 (04) : 787 - 800
  • [6] A hybrid approach for lung cancer diagnosis using optimized random forest classification and K-means visualization algorithm
    Ananya Bhattacharjee
    R. Murugan
    Tripti Goel
    Health and Technology, 2022, 12 : 787 - 800
  • [7] K-Random Forests: a K-means style algorithm for Random Forest clustering
    Bicego, Manuele
    2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), 2019,
  • [8] Fuzzy k-means classification of topo-climatic data as an aid to forest mapping in the Greater Yellowstone Area, USA
    Burrough, PA
    Wilson, JP
    van Gaans, PFM
    Hansen, AJ
    LANDSCAPE ECOLOGY, 2001, 16 (06) : 523 - 546
  • [9] Digital mapping of zinc in urban topsoil using multisource geospatial data and random forest
    Shi, Tiezhu
    Hu, Xianjun
    Guo, Long
    Su, Fenzheng
    Tu, Wei
    Hu, Zhongwen
    Liu, Huizeng
    Yang, Chao
    Wang, Jingzhe
    Zhang, Jie
    Wu, Guofeng
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 792
  • [10] Fuzzy k-means classification of topo-climatic data as an aid to forest mapping in the Greater Yellowstone Area, USA
    Peter A. Burrough
    John P. Wilson
    Pauline F.M. van Gaans
    Andrew J. Hansen
    Landscape Ecology, 2001, 16 : 523 - 546
12345