Land cover classification and change detection analysis of Qaroun and Wadi El-Rayyan lakes using multi-temporal remotely sensed imagery

被引:26
|
作者
Mohamed, Soha A. [1 ]
El-Raey, Mohamed E. [2 ]
机构
[1] Egyptian Minist Higher Educ, High Inst Tourism Hotels & Comp, Cairo, Egypt
[2] Univ Alexandria, Alexandria, Egypt
关键词
Remote sensing; Image classification; GIS; Digital change detection; Simulation; Prediction; Markov chain model; CELLULAR-AUTOMATA MODELS; MARKOV-CHAIN; DESERT;
D O I
10.1007/s10661-019-7339-x
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Qaroun Lake, Wadi El-Rayyan, and Wadi El-Hitan are some of the most promising ecotourism destinations in Egypt due to their natural mineral resources, wildlife, and biodiversity in addition to their historic heritage that dates back to the age of The Pharos. These natural resources should be managed and maintained without affecting the needs of future generations. Land use/land cover change is the most important factor in causing biodiversity loss. Accordingly, the objectives of this study are to identify, quantify, and model future land cover changes using remote sensing and GIS techniques. To fulfill the objectives of the study, a hybrid image classification is employed using the combination of unsupervised and supervised classification methods to detect land cover types. Post-classification comparison is used to map changes in land cover between 2000 and 2017. Markov model is applied to analyze, predict, and simulate future land cover changes from 2017 to 2050. This is in order to safeguard against the adverse effects and negative consequences of land cover changes, preserve the natural resources, and consequently achieve goals of sustainable development. The outcome of this study can provide policy makers and urban planners with the required information regarding the status of the environment and subsequently reduce pressure on natural resources in order to facilitate conservation planning and sustainable development.
引用
收藏
页数:19
相关论文
共 50 条
  • [1] Land cover classification and change detection analysis of Qaroun and Wadi El-Rayyan lakes using multi-temporal remotely sensed imagery
    Soha A. Mohamed
    Mohamed E. El-Raey
    [J]. Environmental Monitoring and Assessment, 2019, 191
  • [2] Land Cover classification and change-detection analysis using multi-temporal remote sensed imagery and landscape metrics
    Fichera, Carmelo Riccardo
    Modica, Giuseppe
    Pollino, Maurizio
    [J]. EUROPEAN JOURNAL OF REMOTE SENSING, 2012, 45 (01): : 1 - 18
  • [3] Land use classification and change detection by using multi-temporal remotely sensed imagery: The case of Chunati wildlife sanctuary, Bangladesh
    Islam, Kamrul
    Jashimuddin, Mohammed
    Nath, Biswajit
    Nath, Tapan Kumar
    [J]. EGYPTIAN JOURNAL OF REMOTE SENSING AND SPACE SCIENCES, 2018, 21 (01): : 37 - 47
  • [4] Multi-temporal land use classification and change detection using remotely sensed imagery: The case of Hirpora Wildlife Sanctuary, Western Himalayas
    Bhat, Tariq Ahmad
    Bhat, Aadil Hussain
    Tanveer, Syed
    Ahmad, Khursheed
    [J]. JOURNAL OF EARTH SYSTEM SCIENCE, 2024, 133 (03)
  • [5] Inception time DCNN for land cover classification by analyzing multi-temporal remotely sensed images
    Kalita, Indrajit
    Roy, Moumita
    [J]. 2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 5736 - 5739
  • [6] Land cover classification from multi-temporal, multi-spectral remotely sensed imagery using patch-based recurrent neural networks
    Sharma, Atharva
    Liu, Xiuwen
    Yang, Xiaojun
    [J]. NEURAL NETWORKS, 2018, 105 : 346 - 355
  • [7] Review of Change Detection Methods Using Multi-Temporal Remotely Sensed Images
    Yin Shou-jing
    Wu Chuan-qing
    Wang Qiao
    Ma Wan-dong
    Zhu Li
    Yao Yan-juan
    Wang Xue-lei
    Wu Di
    [J]. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2013, 33 (12) : 3339 - 3342
  • [8] Characterizing spatiotemporal dynamics of land cover with multi-temporal remotely sensed imagery in Beijing during 1978–2010
    Jinling Zhao
    Wei Guo
    Wenjiang Huang
    Linsheng Huang
    Dongyan Zhang
    Hao Yang
    Lin Yuan
    [J]. Arabian Journal of Geosciences, 2014, 7 : 3945 - 3959
  • [9] Change detection from remotely sensed multi-temporal images using morphological operators
    LeQuere, P
    Maupin, P
    Desjardins, R
    Mouchot, MC
    StOnge, B
    Solaiman, B
    [J]. IGARSS '97 - 1997 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, PROCEEDINGS VOLS I-IV: REMOTE SENSING - A SCIENTIFIC VISION FOR SUSTAINABLE DEVELOPMENT, 1997, : 252 - 254
  • [10] Soil salinity and vegetation cover change detection from multi-temporal remotely sensed imagery in Al Hassa Oasis in Saudi Arabia
    Allbed, Amal
    Kumar, Lalit
    Sinha, Priyakant
    [J]. GEOCARTO INTERNATIONAL, 2018, 33 (08) : 830 - 846