Assessment of forest vegetation state through remote sensing in response to fire impact

Roumen Nedkov; Emiliya Velizarova; Daniela Avetisyan; Nikolay Georgiev

doi:10.1117/12.2570808

26 August 2020 Assessment of forest vegetation state through remote sensing in response to fire impact

Roumen Nedkov, Emiliya Velizarova, Daniela Avetisyan, Nikolay Georgiev

Proceedings Volume 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020); 115240Q (2020) https://doi.org/10.1117/12.2570808
Event: Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 2020, Paphos, Cyprus

Abstract

Forests ecosystems are extremely vulnerable to the changes of climatic parameters such as quantity and seasonal distribution of precipitations, temperature variation, heat transfer, soil moisture content and others. The consequences of forest vegetation alterations include growth and productivity failures, insect outbreaks, biodiversity changes, and increase in the incidence of forest fires and floods. Remote sensing has been identified as an effective tool for better understanding how forest ecosystems respond to dynamics of climatic parameters and their impact to forest vegetation state in terms of the occurrence of hazard events. In the present study spectral indices like Normalized difference greenness indices (NDGI), Normalized Difference Vegetation Index (NDVI), Improved Modified Chlorophyll Adsorption Ratio Index (MCARI₂), Moisture Stress Index (MSI), and Normalized Difference Water Index (NDWI), derived trough remote sensing methods have been applied for monitoring of the forest state before and after fire event occurred on 29 July 2016. Using a model based on the three major Tasseled Cap components, a Disturbance Index (DI) for the affected forest ecosystem was quantified. The study area is situated in southeastern Bulgaria – a region, highly vulnerable to forest disturbances due to climate changes. The results obtained after the application of the suggested indices show that changes observed in the forest ecosystem state could be assessed with a high accuracy. These results were confirmed with statistical analyses with high correlation coefficients for greenness component and Normalized Difference Vegetation Index (NDVI).

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Roumen Nedkov, Emiliya Velizarova, Daniela Avetisyan, and Nikolay Georgiev "Assessment of forest vegetation state through remote sensing in response to fire impact", Proc. SPIE 11524, Eighth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2020), 115240Q (26 August 2020); https://doi.org/10.1117/12.2570808

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KEYWORDS

Vegetation

Multispectral imaging

Remote sensing

Climatology

Ecosystems

Climate change

Statistical analysis

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