Geospatial assessment of forest fire impacts utilizing high-resolution KazEOSat-1 satellite data

被引:0
|
作者
Babu, K. V. Suresh [1 ]
Singh, Swati [2 ]
Kabdulova, G. [1 ]
Gulnara, Kabzhanova [1 ]
Baktybekov, G. [1 ]
机构
[1] Kazakhstan Natl Co, Astana, Kazakhstan
[2] CSIR Natl Bot Res Inst, Lucknow, India
关键词
burned area; KazEOSat-1; satellite; GEMI; AVI; BAI; QUANTIFYING BURN SEVERITY; SPECTRAL INDEXES; VEGETATION; MODIS; MOUNTAINS; BIOMASS;
D O I
10.3389/ffgc.2024.1296100
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Forest fires or wildfires frequently occur in Kazakhstan, especially in the months from June to September, damaging the forest resources. Burnt area mapping is important for fire managers to take appropriate mitigation steps and carry out restoration activities after the fire event. In this study, KazEOSat-1 high-resolution satellite datasets are used to map the burnt area in the regions of Kazakhstan. KazEOSat-1 satellite is in a Sun-synchronous orbit, consisting of four bands, namely blue, green, red, and NIR multispectral bands, in 4 m spatial resolution, while panchromatic data are in 1 m spatial resolution. This study examined three spectral indices, namely AVI, BAI, and GEMI, for mapping the burnt area based on the four spectral bands NIR, blue, red, and green of the KazEOSat-1 satellite datasets. The DN values for each band are used to determine TOA reflectance, which is then used as a basis for deriving the aforementioned spectral indices. The results of spectral indices, AVI, BAI, and GEMI are compared based on a discriminative index (M) for quantifying the effectiveness of each index based on burned area derived from KazEOSat-1 datasets. The spectral index BAI shows higher M values than other indices; therefore, the index BAI has the higher capability to extract the burned area as compared with AVI and GEMI. Accuracy was calculated based on the number of forest fire incidents that fell in burned and unburned areas, and the results indicate that BAI shows the highest accuracy, whereas AVI shows the lowest accuracy among them. Therefore, the BAI has the highest ability for extracting the burned area using the KazEOSat-1 satellite datasets. As the revisit time period of KazEOSat is 3 days, this study will be useful to map the burnt area and fire progression in Kazakhstan.
引用
收藏
页数:7
相关论文
共 50 条
  • [41] Climate change impacts assessment on Bangladesh Mangrove Forest using high-resolution datasets and Google Earth Engine
    Halder, Bijay
    Pereira, Paulo
    JOURNAL OF COASTAL CONSERVATION, 2024, 28 (01)
  • [42] Fire Danger Assessment Using Moderate-Spatial Resolution Satellite Data
    Kussul, Nataliia
    Fedorov, Oleh
    Yailymov, Bohdan
    Pidgorodetska, Liudmyla
    Kolos, Liudmyla
    Yailymova, Hanna
    Shelestov, Andrii
    FIRE-SWITZERLAND, 2023, 6 (02):
  • [43] Monitoring of land/forest fires with high-resolution data at CRISP
    Lim, OK
    Liew, SC
    Kwoh, LK
    Lim, H
    EURO-ASIAN SPACE WEEK - CO-OPERATION IN SPACE: WHERE EAST & WEST FINALLY MEET, 1999, 430 : 305 - 307
  • [44] Forest habitat mapping by means of high-resolution airborne data
    Holopainen, M
    27TH INTERNATIONAL SYMPOSIUM ON REMOTE SENSING OF ENVIRONMENT, PROCEEDINGS: INFORMATION FOR SUSTAINABILITY, 1998, : 403 - 406
  • [45] Detection of storm losses in Alpine forest areas by different methodical approaches using high-resolution satellite data
    Schwarz, M
    Steinmeier, C
    Waser, L
    OBSERVING OUR ENVIRONMENT FOR SPACE: NEW SOLUTIONS FOR A NEW MILLENNIUM, 2002, : 251 - 257
  • [46] A Comparative Approach of Identification and Segmentation of Forest Fire Region in High Resolution Satellite Images
    Ganesan, P.
    Sathish, B. S.
    Sajiv, G.
    2016 WORLD CONFERENCE ON FUTURISTIC TRENDS IN RESEARCH AND INNOVATION FOR SOCIAL WELFARE (STARTUP CONCLAVE), 2016,
  • [47] MTF Compensation Method Utilizing the Curved Edge for High-resolution Satellite Image Recovery
    Luo, Qiuhua
    Wang, Lin
    Yang, Hong
    Zhang, Shaohui
    Shao, Xiaopeng
    SATELLITE DATA COMPRESSION, COMMUNICATIONS, AND PROCESSING X, 2014, 9124
  • [48] Application of high-resolution satellite images to detailed landslide hazard assessment
    Nichol, Janet
    Wong, Man Sing
    Shaker, Ahmed
    2009 JOINT URBAN REMOTE SENSING EVENT, VOLS 1-3, 2009, : 1591 - +
  • [49] Characterizing fire effects on conifers at tree level from airborne laser scanning and high-resolution, multispectral satellite data
    Klauberg, Carine
    Hudak, Andrew T.
    Silva, Carlos Alberto
    Lewis, Sarah A.
    Robichaud, Peter R.
    Jain, Terrie B.
    ECOLOGICAL MODELLING, 2019, 412
  • [50] Bridge monitoring and assessment by high-resolution satellite remote sensing technologies
    Gagliardi, Valerio
    Ciampoli, Luca Bianchini
    D'Amico, Fabrizio
    Alani, Amir M.
    Tosti, Fabio
    Battagliere, Maria Libera
    Benedetto, Andrea
    SPIE FUTURE SENSING TECHNOLOGIES (2020), 2020, 11525