Application of remote sensing data for monitoring of forest vegetation on the territory of Nature Park "Blue Stones", Bulgaria

被引:2
|
作者
Stoyanov, Andrey [1 ]
Georgiev, Nikolay [1 ]
Gigova, Iliyana [1 ]
Borisova, Denitsa [1 ]
机构
[1] Bulgarian Acad Sci, Space Res & Technol Inst, Acad G Bonchev Str Bl 1, Sofia 1113, Bulgaria
关键词
Tasseled Cap Transformation; NDVI; greenness; forest vegetation; NDGI; SAR;
D O I
10.1117/12.2538115
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The aim of the study is to give assessment of and monitor the vegetation's condition of the forest areas in which territories the predominantly forest species of the plantations is Eastern Mysian beech (Fagus orientalis), by combinative approach of Remote Sensing's methods and generation of different vegetation indices (NDVI, NDGI). SAR and optical data of the Sentinel when the phenophase of the forest vegetation is the most active, from April to July, respectively, for the years of the selected period were chosen. Tasseled Cap Orthogonal Transformation is applied to the selected images, resulting in three components - TCT component of the "brightness", TCT component of the "wetness" and the TCT component of the "greenness". In the present research, the TCT component of the "greenness" was used, which is giving more accurate and precise data on the current state of the forest vegetation. A comparative analysis of the processed data obtained from the applied different methods and vegetation indices has been made, in order to select the higher quality and more precise results with purpose the analysis and assessment of the state of forest vegetation on the territory of the Natural Park.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Using Temperature Vegetation Drought Index for Monitoring Drought Based on Remote Sensing Data
    Huang, Linsheng
    Guan, Qingsong
    Dong, Yansheng
    Zhang, Dongyan
    Huang, Wenjiang
    Liang, Dong
    PROGRESS IN ENVIRONMENTAL SCIENCE AND ENGINEERING (ICEESD2011), PTS 1-5, 2012, 356-360 : 2854 - +
  • [42] APPLICATION RESEARCH OF BIG DATA TECHNOLOGY IN COTTON REMOTE SENSING MONITORING
    Liu, Changzheng
    Song, Yaping
    Zhang, Ronghua
    Qian, Lipeng
    Yi, Jiaxin
    FRESENIUS ENVIRONMENTAL BULLETIN, 2020, 29 (7A): : 5885 - 5891
  • [43] Application of Remote Sensing Data in Large-Scale Monitoring of Wetlands
    Shinkarenko, S. S.
    Bartalev, S. A.
    COSMIC RESEARCH, 2024, 62 (SUPPL1) : S100 - S114
  • [44] Application of Principal Component Analysis to Remote Sensing Data for Deforestation Monitoring
    Sule, Suki Dauda
    Wood, Aidan
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XXII, 2020, 11528
  • [45] The application of remote-sensing data to monitoring and modelling of soil erosion
    King, C
    Baghdadi, N
    Lecomte, V
    Cerdan, O
    CATENA, 2005, 62 (2-3) : 79 - 93
  • [46] Application of remote sensing data for monitoring eutrophication of floodplain water bodies
    Fedonenko, E., V
    Kunakh, O. M.
    Chubchenko, Y. A.
    Zhukov, O., V
    BIOSYSTEMS DIVERSITY, 2022, 30 (02) : 179 - 190
  • [47] Technology and Application Demonstration of Remote Sensing Monitoring and Early Warning for Forest and Grassland Fires
    He, Binbin
    Chen, Rui
    Quan, Xingwen
    Yao, Jinsong
    Yin, Changming
    Wang, Zili
    Zhang, Qiming
    Yang, Shuai
    Dianzi Keji Daxue Xuebao/Journal of the University of Electronic Science and Technology of China, 2024, 53 (05): : 698 - 705
  • [48] Forest fire monitoring using airborne optical full spectrum remote sensing data
    Pang Y.
    Jia W.
    Qin X.
    Si L.
    Liang X.
    Lin X.
    Li Z.
    1600, Science Press (24): : 1280 - 1292
  • [49] Monitoring Approach for Tropical Coniferous Forest Degradation Using Remote Sensing and Field Data
    Duarte, Efrain
    Barrera, Juan A.
    Dube, Francis
    Casco, Fabio
    Hernandez, Alexander J.
    Zagal, Erick
    REMOTE SENSING, 2020, 12 (16)
  • [50] Monitoring the Ecological Drought Condition of Vegetation during Meteorological Drought Using Remote Sensing Data
    Won, Jeongeun
    Jung, Haeun
    Kang, Shinuk
    Kim, Sangdan
    KOREAN JOURNAL OF REMOTE SENSING, 2022, -38 (05) : 887 - 899