Estimation of Postfire Reforestation with SAR Polarimetry and NDVI Time Series

Abstract

This communication is devoted to the methodology of remote complex analysis of forest restoration after strong wildfires. It is proposed to quantify the projective leaf/needles area index by multispectral optical images. The increase in dimensions of trunks and branches commensurate with a radar wavelength of 24 cm is estimated using radar polarimetric data. It is shown that the growth’s potential of aboveground biomass in different spots of test site ranges from 35 to 70% in the case under consideration. Such a new approach will make it possible to further consider more accurately the role of boreal forests as one of the largest carbon stocks.

Development of Methodology for Monitoring and Assessing the National Greening Program Using Optical and Sar Data

“…Thus, NDVI offers information on vegetation status by measuring the difference between these two spectral bands (Pettorelli et al, 2005). A number of reforestation initiatives were evaluated for their effectiveness using the NDVI (Bondur et al, 2022;Gore et al, 2023;Lin et al, 2020).…”

“…The RVI and RFDI are indicators of vegetation density and degradation, respectively (Çolak et al, 2021). Several works used these indices to monitor changes in vegetation cover (Bondur et al, 2022;Çolak et al, 2021).…”

A Novel Method of Boreal Zone Reforestation/Afforestation Estimation Using PALSAR-1,2 and Landsat-5,8 Data

“…At the same time, remote forest monitoring systems are being developed based on the processing of Big SAR data [13][14][15][16]. The main advantage of radar data is the high penetrating power of radio waves.…”

Monitoring of post-fire reforestation based on vegetation indices of optical and radio bands

“…One of the urgent tasks of modern research on the state of the underlying land cover is to develop an integrated approach to the use of satellite data from various sensors to provide a comprehensive study of the state and dynamics of objects, improve the quality of classification and interpretation of processing results [1][2][3][4]. In particular, comprehensive studies of forests based on remote data of optical, thermal and radio ranges seem promising, allowing to identify various aspects of this complex multilevel and multicomponent ecological systemfrom photosynthesis, thermal and water balance to the determination of various parameters of the forest environment, such as the volume and density of aboveground biomass, etc.…”

“…In particular, comprehensive studies of forests based on remote data of optical, thermal and radio ranges seem promising, allowing to identify various aspects of this complex multilevel and multicomponent ecological systemfrom photosynthesis, thermal and water balance to the determination of various parameters of the forest environment, such as the volume and density of aboveground biomass, etc. For example, methods of combining optical and radar remote sensing data for the processes of afforestation of agricultural fields and reforestation after logging and fires have shown high efficiency [1,4,5]. In this paper, the possibility of monitoring and assessing the degree of post-fire forest restoration based on a combination of long-term changes in the vegetation indices of the optical and radio ranges is investigated.…”