Accurately estimating gross primary productivity (GPP), the largest carbon flux in terrestrial
ecosystems, is crucial for advancing our understanding of global carbon cycle and …

Gross primary production (GPP) models driven by fine resolution remote sensing data
characterize the spatial and temporal heterogeneities in plant photosynthesis, which is …

Accurate estimation of mountain vegetation gross primary productivity (GPP) at fine spatial
resolutions offers opportunities to better understand mountain ecosystems' feedback to the …

Functional diversity is a critical component driving ecosystem functioning. Spatially explicit
data of plant functional traits and diversity are essential for understanding biodiversity effects …

Ecosystem services (ES) are directly affected by land use and land cover changes (LUCC);
however, the impacts of extended period LUCC on ES are poorly explored. Here, we …

Accurate simulations of the spatial and temporal changes in vegetation gross primary
production (GPP) play an important role in ecological studies. Previous studies highlighted …

ABSTRACT High spatial resolution Gross Primary Productivity (GPP) estimation makes it
feasible to better understand the spatial heterogeneity of mountain vegetation …

Attributions and predictions of gross primary productivity (GPP) under climate change is of
great significance for facilitating a deeper understanding of the global and regional …

Restricted by the design of satellite sensors, the existing satellite-based normalized
difference vegetation index (NDVI) cannot simultaneously have a high temporal resolution …

Northern forest ecosystems make up an important part of the global carbon cycle. Hence,
monitoring local-scale gross primary production (GPP) of northern forest is essential for …