Editorial for the Special Issue: “Human-Environment Interactions Research Using Remote Sensing”

[...]human activities such as urbanization, industrialization, and river diversion continue to alter the landscape, affecting the biodiversity and ecosystem services of the natural environment [3]. [...]understanding the interactions between human and natural systems is crucial to predict potential social-environmental transformations and inform governments and residents to plan early. Relationships between the decrease and recovery in NTL radiance and social-environmental characteristics, i.e., Twitter activities, damaged housing units, and land use and land cover types, were further examined. [...]the study tested three algorithms in land loss modeling, including logistic regression, random forest, and extreme gradient boosting (XGBoost) to delineate the land loss mechanisms. [...]the study projected future land loss patterns and found that a total area of 180 km2 of land has an over 50% probability of turning to water from 2016 to 2031.