Sentinel-2 Poplar Index for Operational Mapping of Poplar Plantations over Large Areas

Abstract

Poplar (Populus spp.) is a fast-growing tree planted to meet the growing global demand for wood products. In France, the country with the largest area planted with poplar in Europe, accurate and up-to-date maps of its spatial distribution are not available at the national scale. This makes it difficult to estimate the extent and location of the poplar resource and calls for the development of a robust and timely stable approach for mapping large areas in order to ensure efficient monitoring. In this study, we investigate the potential of the Sentinel-2 time series to map the diversity of poplar plantations at the French countrywide scale. By comparing multiple configurations of spectral features based on spectral bands and indices over two years (2017 and 2018), we identify the optimal spectral regions with their respective time periods to distinguish poplar plantations from other deciduous species. We also define a novel poplar detection index (PI) with four variants that combine the best discriminative spectral bands. The results highlight the relevance of SWIR followed by red edge regions, mainly in the growing season, to accurately detect poplar plantations, reflecting the sensitivity of poplar trees to water content throughout their phenological cycle. The best performances with stable results were obtained with the PI2 poplar index combining the B5, B11, and B12 spectral bands. The PI2 index was validated over two years with an average producer’s accuracy of 92% in 2017 and 95% in 2018. This new index was used to produce the national map of poplar plantations in 2018. This study provides an operational approach for monitoring the poplar resource over large areas for forest managers.

Monitoring Forest Diversity under Moso Bamboo Invasion: A Random Forest Approach

“…Theoretically, the reflectance in the short-wave infrared bands (B11, B12) is predominantly affected by leaf water content [15,29], and around 1450 nm and 1950 nm are most pronounced [53]. According to previous studies, these absorption bands saturate at higher water contents, and the intermediate absorption region around 1650 nm and 2200 nm is sensitive to differences in leaf water content [54,55]. This coincides with the B11 and B12 bands.…”

Estimation of Wheat Kernel Moisture Content in-Field Based on Planetscope and Sentinel-2 Satellite Images

“…Therefore, B5 in PS and B4 in S2 are sensitive parameters for wheat KMC, and other bands and indices related to chlorophyll have a certain impact on wheat KMC estimation. Similarly, SWIR bands like B11 and B12 in S2 located within the water absorption spectrum range (Hamrouni et al, 2022) are also strong indicators of changes in wheat KMC. In terms of vegetation indices, PSRI maximizes sensitivity between carotenoids to chlorophylls ratio, and it can indicate an increase in canopy stress, which effectively characterizes plant fruit maturity, so it also shows strong sensitivity to changes in wheat KMC.…”

Remote Sensing Applications in Monitoring Poplars: A Review

“…This is important as it helps in meeting supply demands. In mountainous regions, poplar was quantified using leaf area index (LAI) as an important agent for canopy structure, as well as biomass, carbon, and energy exchange estimation indices [53], while in urban landscapes, it was mostly studied to quantitatively relate leaf chlorophyll content (LCC) with other vegetation indices [54,55]. The reason for the low number of studies in the mountainous landscape could be due to the nature of mountains coupled with inconsistent seasonal species changes, which affect the efficacy of some remote sensing sensors to accurately detect and discriminate floral species [56].…”