Remote Sensing of Photosynthesis, Vegetation Productivity and Climate Variability in Bangladesh

Abstract

Monitoring vegetation productivity and photosynthetic activity is significant for a better understanding of plant response to climatic variability on the Earth. This study focused on remote sensing-based seasonal vegetation productivity and photosynthetic activity, employing a satellite-retrieved solar-induced chlorophyll fluorescence (SIF) observation of Bangladesh. However, SIF may be able to provide terrestrial photosynthesis anomaly and understanding of phenological status, thus depending on the energy efficiency of photosynthetically active radiation (PAR) and its association with vegetation productivity. This study used recent GOSIF satellite-provided SIF to explore photosynthesis function, and to show variation in photosynthesis over Bangladesh from 2005 to 2018, with a parallel comparison of satellite-obtained vegetation greenness, using additional satellite measurement of variability in Gross Primary Production (GPP), Vegetation Indices (VIs), and Land Surface Temperature (LST). GPP reflects vegetation productivity, whereas the Normalized Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) datasets were used to measure the vegetative greenness. MODIS-based LST measurement were also used for accessing climatic response. Largely similar spatial and seasonal trends from 2005 to 2018 were found among vegetation greenness, photosynthesis anomaly, vegetation productivity and climatic response, where SIF, VIs, GPP, and temperature variability were all strongly positive correlations. Strong significant correlations were obtained between SIF and GPP (r = +0.91), SIF and EVI (r = +0.77), SIF and NDVI (r = +0.71) and SIF and LST (r = +0.58), reflecting the dependency between vegetation productivity and photosynthetic activity. This research could present better results and would be more useful for future phenological research.