One paper was accepted by Environmental and Sustainability Indicators 

It is titled “Global Disparities in CO2 Emissions from Mobility Sectors of Diverse Economies: A Macroscopic Exploration Across 188 Countries/Regions”. 

One paper has been accepted by JAG! It's about "A Novel Geospatial Machine Learning Approach to Quantify Non-Linear Effects of Land Use/Land Cover Changes on Carbon Dynamics". 

People have an insufficient understanding of in-depth process behind the satellite images. Different disciplines are essential to drive the development of remote sensing application technology. Only with better understanding can interpret the valuable information and geo-processes into effective datasets or physical models. Flood forecasting models, for example, require a lot of expertise in the field of hydrology. Many research fields require knowledge of remote sensing, while there is insufficient support for them in selecting appropriate data or integrations of expertise knowledge. Some emerging technologies, such as Deep Learning and AI, have been applied in remote sensing, especially for state-of-the-art performance in object identification; however, remote sensing sensors have multiple bands and multispectral features, and these technologies have not yet been fully explored. With the rapid development of remote sensing and accumulations of massive datasets, cloud computing (i.e., Google Earth Engine) and various platforms have been developed...