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Modeling of forest ecosystems recovery after fire based on orthogonalization of multispectral satellite data

The aim of this study is to monitor the post-fire recovery of forest ecosystems on the basis of remote aerospace methods and data. To achieve this goal, a hybrid model for styding the dynamics of recovery processes of forest ecosystems after fire was developed. Based on the Greenness Tasseled cap component, Normalized Differential Greenness Index (NDGI) was obtained and used as input data in combination with vegetation indices (NDVI, MCARI2). NDGI is an index for vegetation dynamic assessment based on orthogonal transformation of satellite images from Sentinel-2. NDGI shows the vegetation dynamic change depending on temporal periods. The values of this index range from +1 to -1. Using NDGI assessment can be made of negative and positive changes of the vegetation. This study uses a new approach for forest ecosystems assessment, based on this index using the Greenness component obtained from orthogonalization of satellite images in combination with generated vegetation indices (NDVI and MCARI2). Optimization of model performance and automatization of Sentinel-2 MSI data processing were conducted. Sentinel-2 MSI model for orthogonalization of multispectral data was used for Tasseled cap transformation. Results obtained by implementation of the proposed approach show that the integrated composite images of NDGI, NDVI and MCARI2 represent the condition of forest ecosystems.