Several Asian countries are undergoing rapid economic development driven by diverse factors. This development is leading to continuous land use changes, including deforestation, urbanization, and agricultural conversion. Such transformations threaten essential ecosystem functions and services, like food provision, climate regulation, and cultural benefits. Land-use changes, influenced by economic activities and policies, carry extensive consequences, impacting ecosystem productivity, water resources, and climate stability. Remote sensing technology significantly aids in monitoring and quantifying these changes, offering valuable insights for land management and policy decisions. The NASA Land-Cover and Land-Use Change (LCLUC) Program within NASA’s Earth Science Division program aims to establish global assessments of land changes using space-based methods (https://lcluc.umd.edu/). The South/Southeast Asia Research Initiative (SARI), funded by NASA LCLUC, focuses on advancing LCLUC science in the region and fostering collaborations between US and Asian researchers. Utilizing geospatial data from remote sensing and models, SARI employs a comprehensive approach, considering biophysical and socioeconomic aspects of land systems and their interactions. SARI has been enhancing LCLUC science through science projects, partnerships, training, workshops, and capacity building exchanges since 2015. This Special Issue, stemming from SARI meetings in the Philippines and Malaysia in 2018 and 2019, gathers articles focusing on LCLUC, degradation, and ecosystem services in Asia. Of over 90 submissions, 30 have been accepted, providing insights into these issues and their regional impacts. The articles are summarized into various sub-themes below.

Although water availability strongly controls gross primary production (GPP), the impact of soil moisture content (wilting point) is poorly quantified on regional and global scales. In this study, we used 10-year observations of solar-induced chlorophyll fluorescence (SIF) from the GOSAT satellite to estimate the wilting point of a semiarid grassland on the Mongolian Plateau. Radiative-transfer model inversion and soil-vegetation-atmosphere transfer simulation were jointly conducted to distinguish the drought impacts on physiology from changes in leaf-canopy optical properties. We modified an existing inversion algorithm and the widely used SCOPE model to adequately evaluate dryland features, e.g., sparse canopy and strong convection. The modified model with retrieved parameters and calibrated to GOSAT SIF predicts realistic GPP values. We found that (1) the SIF yield estimated from GOSAT shows a clear sigmoidal pattern in relation to drought, and the estimated wilting point matches ground-based observations within ~0.01 m3 m-3 for the soil moisture content, (2) tuning the maximum carboxylation rate improves SIF prediction after considering changes in leaf-canopy optical properties, implying that GOSAT detected drought stress in leaf-level photosynthesis, and (3) the surface energy balance has significant impacts on the grassland’s SIF; the modified model reproduces observed SIF radiance well (mean bias = 0.004 mW m-2 nm-1 sr-1 in summer), whereas the original model predicts substantially low values under weak horizontal wind (unstable) conditions. Some model-observation mismatches in the SIF suggest that more research is needed for fluorescence parametrization (e.g., photoinhibition) and additional observation constraints.