## 4 Discussion
The pattern is consistent with the findings of [PERSON] et al., [43] who found a significant correlation (R\({}^{2}\) = 0.82) and suggested that the underestimation by MOD 17 product was due to the influence of the leaf area index. Similarly, a comparison of cropland flux towers--NPP to MODIS-NPP in China by [44], showed that MODIS has considerably undervalued a cropland NPP, which may partially explain the lower NPP recorded from paddy-fields-dominated areas in this study. Using MOD17A3 HGFv006 which is an improved version to obtain similar trends consistent with previous works,suggests that MODIS products tend to be biome sensitive hence can be influenced by their composition. The use of NDVI in the past decades to quantify vegetation biophysical properties like the net primary productivity is still prevalent. However, it is more reliable to estimate the above-ground biomass from EVI than from NDVI because it is capable of moderating atmospheric and canopy-related effects. This study has shown a strong correlation between EVI and CASA estimated NPP. This trend is consistent with the results of [PERSON] et al. [45], who found a substantial correlation (R\({}^{2}\) = 0.90) between EVI and CASA NPP and attributed the low EVI counts to the function of human interference with natural vegetation. In this work, an effort was made to confirm the interference of landuse that might have influenced the EVI by comparing it with FLUXNET NPP, since tower footprints are relatively less prone to vegetation disturbances due to agricultural and urban development activities. The analysis demonstrated a good relationship between EVI and FLUXNET NPP, a low EVI was observed relative to the FLUXNET NPP, which suggests that urbanization, seasonal agriculture, deforestation, and related land-use systems may be responsible for NPP fluctuations across Songkhla province. Generally, it is assumed that the prevailing climate and vegetation determine the distribution of NPP within a region, NPP trends are well-ordered by a blend of rapidly warming temperatures and EVI patterns over the same period [46]. Naturally, when one moves to warmer and wetter areas that promote respiration, the percentage of gross productivity used up in respiration rises, consequently, tropical rainforests have very high respiration rates hence huge variation between gross and net primary productivity values are obtained. Songkhla province has conventionally been a hub of rubber industry development and innovation for some decades now; this study found that para rubber plantations occupy 389,562.1 hectares (52.7%) of the total land across the entire province. The para rubber abundance trend in this area could presumably be linked to a suitable humid tropical climate and edaphic factors, whereas its district-wise distribution largely depends on the land availability and prevailing land-use type. Other considerations may include labor supply and proximity to the market because many farmers live far away from the market, making it difficult to access rubber development information [47]. The present study revealed that para rubber AGB summed up to 31.9 million tonnes C ha\({}^{-1}\) across Songkhla province. The trend showed heterogeneity within locations, spatial variation in carbon stock aboveground is dependent on a variety of factors, including stand structure and composition, topography, altitude, and disturbance. As a result, it can be hypothesized that the density and structural complexity of certain forest types can have a significant effect on its AGB potential. Similar spatial variability in AGB has been reported by [PERSON] et al. [48], at the landscape scale assessment of Khao Yai National Park in central Thailand. They discovered a high degree of spatial variability in AGB, with a noticeable bias in favor of low AGB values, attributing this to human activity in this region prior to the park's creation.