Land cover change assessment using random forest and CA markov from remote sensing images in the protected forest of South Malang, Indonesia

被引:5
|
作者
Purwanto [1 ]
Latifah, Siti [2 ]
Yonariza [3 ]
Akhsani, Farid [1 ]
Sofiana, Eva Indra [1 ]
Ferdiansah, Mohammad Riski [1 ]
机构
[1] Univ Negeri Malang, Malang, Indonesia
[2] Univ Sumatera Utara, Medan, Indonesia
[3] Univ Andalas, Padang, Indonesia
关键词
Protected forest; Land cover change; Random forest; CA markov; REGION;
D O I
10.1016/j.rsase.2023.101061
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Protected forest has important roles in protecting life support systems through water manage-ment, maintain micro climate stability, flood prevention, erosion control, prevention of seawater intrusion and maintenance of soil fertility. Deforestation in protected forest areas will reduce the roles, however, deforestation appeared to occur in forested areas of Bantur Regency. Infrastruc-ture development which is growing rapidly and the compleexity of economic activities is driving deforestation in this region. The deforestation caused water supply problems, landslide and de-creased endemic bird population ("rangkong") in study areas. Therefore it is necessary to identify deforestation through land cover change assessment. This study aims at (1) quantifying the forest land cover changes in protected forest areas of Bantur and Donomulyo Regency, (2) identifying environmental condition in protected forest areas of Bantur and Donomulyo Regency. Landsat TM, ETM+ and 8 were used together with Random Forest classification for mapping the forest areas. Carbon Monoxide (CO) and temperature were used as biophysical factors in the model. The results of this study suggested the continuing deforestation with the existence of roads, economic activity, and tourism development triggered the deforestation pattern. Role of community was also found to affect the nature of deforestation.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] A Random Forest-Based CA-Markov Model to Examine the Dynamics of Land Use/Cover Change Aided with Remote Sensing and GIS
    Zhang, Zhenyu
    Hoermann, Georg
    Huang, Jinliang
    Fohrer, Nicola
    [J]. REMOTE SENSING, 2023, 15 (08)
  • [2] Extracting the Forest Type From Remote Sensing Images by Random Forest
    Li Linhui
    Jing Weipeng
    Wang Huihui
    [J]. IEEE SENSORS JOURNAL, 2021, 21 (16) : 17447 - 17454
  • [3] Modelling of land use and land cover changes and prediction using CA-Markov and Random Forest
    Asif, Muhammad
    Kazmi, Jamil Hasan
    Tariq, Aqil
    Zhao, Na
    Guluzade, Rufat
    Soufan, Walid
    Almutairi, Khalid F.
    Sabagh, Ayman El
    Aslam, Muhammad
    [J]. GEOCARTO INTERNATIONAL, 2023, 38 (01)
  • [4] Assessment of Carbon Stocks in the Topsoil Using Random Forest and Remote Sensing Images
    Kim, Jongsung
    Grunwald, Sabine
    [J]. JOURNAL OF ENVIRONMENTAL QUALITY, 2016, 45 (06) : 1910 - 1918
  • [5] Temporal Forest Change Detection and Forest Health Assessment using Remote Sensing
    Ya'acob, Norsuzila
    Azize, Aziean Binti Mohd
    Mahmon, Nur Anis
    Yusof, Azita Laily
    Azmi, Nor Farhana
    Mustafa, Norfazira
    [J]. 2013 INTERNATIONAL CONFERENCES ON GEOLOGICAL, GEOGRAPHICAL, AEROSPACE AND EARTH SCIENCES (AEROEARTH 2013), 2014, 19
  • [6] Simulation and prediction of land use and land cover change using GIS, remote sensing and CA-Markov model
    Khawaldah, H. A.
    Farhan, I.
    Alzboun, N. M.
    [J]. GLOBAL JOURNAL OF ENVIRONMENTAL SCIENCE AND MANAGEMENT-GJESM, 2020, 6 (02): : 215 - 232
  • [7] Rapid assessment remote sensing of forest cover change to inform forest management: Case of the Monarch reserve
    Mishkin, Miramanni
    Pacheco, Jose Antonio Navarrete
    [J]. ECOLOGICAL INDICATORS, 2022, 137
  • [8] Forest Cover Estimation in Ireland Using Radar Remote Sensing: A Comparative Analysis of Forest Cover Assessment Methodologies
    Devaney, John
    Barrett, Brian
    Barrett, Frank
    Redmond, John
    O'Halloran, John
    [J]. PLOS ONE, 2015, 10 (08):
  • [9] Validation of Random Forest Algorithm to Monitor Land Cover Classification and Change Detection using Remote Sensing Data in Google Earth Engine
    Mangkhaseum, Sackdavong
    Hanazawa, Akitoshi
    [J]. INTERNATIONAL WORKSHOP ON ADVANCED IMAGING TECHNOLOGY (IWAIT) 2022, 2022, 12177
  • [10] Assessment of land use and land cover change detection and prediction using remote sensing and CA Markov in the northern coastal districts of Tamil Nadu, India
    Devanantham Abijith
    Subbarayan Saravanan
    [J]. Environmental Science and Pollution Research, 2022, 29 : 86055 - 86067