Burned area determination using Sentinel-2 satellite images and the impact of fire on the availability of soil nutrients in Syria

被引:2
|
作者
Al-hasn, Rukea [1 ]
Almuhammad, Raed [1 ]
机构
[1] Gen Commiss Sci Agr Res GCSAR, Damascus, Syria
关键词
burned forest; NBR; dNBR; BAIS2; NDVI; FOREST-FIRE; VEGETATION RECOVERY; SPECTRAL INDEXES; SEVERITY; PATTERNS; WILDFIRES; LANDSAT;
D O I
10.17221/122/2021-JFS
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The objective of this research is the identification of burned forest areas that occurred in Syria from September 2nd to October 15th, 2020. Forest fire risk classes were determined using Sentinel-2 images. Normalized Burn Ratio (NBR), Differenced Normalized Burn Ratio (dNBR), and Burned Area Index for Sentinel-2 (BAIS2), and Normalized Difference Vegetation Index (NDVI) were used for the identification how much the forests have been destroyed and to establish fire risk classes. According to the study results, the size of the vegetation area that was destroyed due to fire was determined, and the probability of the forest fire exposure of these areas was established. The fires also altered some chemical properties in the soil during the combustion process. Thus, this study was focused on the impact of fire on the availability of soil nutrients. Soil samples were collected from three depths (0-10 cm, 10-20 cm and 20-30 cm) under the forest land a month after the fire in three locations: Al-Fazeen, Sawda and Gard Al-rihan. Pine (Pinus brutia) trees cover these areas. The results of this study indicated that the fire increased pH, EC and sand, the fire also led to an increase in the solubility of the available major soil elements N, P and K. There was an increase in the solubility of the soil microelements Zn, Cu, Mn and Fe while the content of organic material and silt and day ratio decreased at the three sites in comparison with unburned soil.
引用
收藏
页码:96 / 106
页数:11
相关论文
共 50 条
  • [1] An Unsupervised Burned Area Mapping Approach Using Sentinel-2 Images
    Sismanis, Michail
    Chadoulis, Rizos-Theodoros
    Manakos, Ioannis
    Drosou, Anastasios
    LAND, 2023, 12 (02)
  • [2] Agreement Index for Burned Area Mapping: Integration of Multiple Spectral Indices Using Sentinel-2 Satellite Images
    Smiraglia, Daniela
    Filipponi, Federico
    Mandrone, Stefania
    Tornato, Antonella
    Taramelli, Andrea
    REMOTE SENSING, 2020, 12 (11)
  • [3] Burned area detection and mapping using time series Sentinel-2 multispectral images
    Liu, Peng
    Liu, Yongxue
    Guo, Xiaoxiao
    Zhao, Wanjing
    Wu, Huansha
    Xu, Wenxuan
    REMOTE SENSING OF ENVIRONMENT, 2023, 296
  • [4] Assessment of Burned Areas during the Pantanal Fire Crisis in 2020 Using Sentinel-2 Images
    Shimabukuro, Yosio Edemir
    de Oliveira, Gabriel
    Pereira, Gabriel
    Arai, Egidio
    Cardozo, Francielle
    Dutra, Andeise Cerqueira
    Mataveli, Guilherme
    FIRE-SWITZERLAND, 2023, 6 (07):
  • [5] SEMANTIC SEGMENTATION OF BURNED AREAS IN SENTINEL-2 SATELLITE IMAGES USING DEEP LEARNING MODELS
    Ouadou, Anes
    Huangal, David
    Hurt, J. Alex
    Scott, Grant J.
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 6366 - 6369
  • [6] Burned Area Estimation Using a New Accuracy Verification Method Based on Sentinel-2 Images
    Chen, Yunping
    Lu, Chuangjiang
    Huang, Xuan
    Xie, Siyuan
    Sun, Yuan
    IEEE GEOSCIENCE AND REMOTE SENSING LETTERS, 2023, 20
  • [7] Burned Area Classification Based on Extreme Learning Machine and Sentinel-2 Images
    Gajardo, John
    Mora, Marco
    Valdes-Nicolao, Guillermo
    Carrasco-Benavides, Marcos
    APPLIED SCIENCES-BASEL, 2022, 12 (01):
  • [8] The Study of DMZ Wildfire Damage Area Detection Method Using Sentinel-2 Satellite Images
    Lee, Seulki
    Song, Jong-Sung
    Lee, Chang-Wook
    Ko, Bokyun
    KOREAN JOURNAL OF REMOTE SENSING, 2022, 38 (05) : 545 - 557
  • [9] Agricultural burned area detection using an integrated approach utilizing multi spectral instrument based fire and vegetation indices from Sentinel-2 satellite
    Deshpande, Monish Vijay
    Pillai, Dhanyalekshmi
    Jain, Meha
    METHODSX, 2022, 9
  • [10] QUANTITATIVE ASSESSMENT OF FOREST DEGRADATION AFTER FIRE USING ORTOGONALIZED SATELLITE IMAGES FROM SENTINEL-2
    Nedkov, Roumen
    COMPTES RENDUS DE L ACADEMIE BULGARE DES SCIENCES, 2018, 71 (01): : 83 - 86