A Method for Reforestation Monitoring Based on Joint Analysis of Optical–Microwave Data on the NDVI–RVI Plane

This paper proposes a method for comprehensive assessing of the state and dynamics of young forest growth through joint analysis of multispectral optical images and satellite radar data. Previous research showed that separate analysis of vegetation (using the NDVI index) and radar (using the RVI index) data produced significantly different forecasts of reforestation levels after a fire. Therefore, we propose evaluating the temporal dynamics of reforestation through the NDVI–RVI plane, comparing against control areas of coniferous and mixed forests and also a treeless area. We demonstrate that these areas create a movable triangular zone, where changes in vegetation indices indicate an increase in forest projective cover, aboveground biomass growth, and replacement/restoration of species. To describe such dynamics, we introduce two quantitative indices: the degree of reforestation index (DRI) and the ratio of species index (RSI). To process the data and scale the results, we used the modern functionality of the Google Earth Engine (GEE) cloud platform. We obtained NDVI values from Landsat-5 and -8 data during the 2007–2020 winter (snow) period, minimizing the influence of soil and grass on assessing deciduous and evergreen coniferous plantations’ crown dynamics. Additionally, we obtained the radar vegetation index RVI from synthetic aperture satellite radar (SAR) data of ALOS‑1 PALSAR‑1 (2006–2010) and ALOS‑2 PALSAR‑2 (2016–2020) with the help of the GEE cloud platform to study forest vegetation biomass changes.