The implementation of the United Nations (UN) 2030 Agenda for Sustainable Development (2030 Agenda), with its 17 sustainable development goals (SDGs), faces challenges such as insufficient data, limited research methodologies, and uneven progress across regions. Earth observation (EO), particularly scientific satellites, offers unique advantages in supporting global sustainable development by providing objective, dynamic, and large-scale datasets for SDG evaluations and policymaking, as well as by facilitating the study of Earth’s environmental systems and their interactions with human activity. Sustainable Development Science Satellite 1 (SDGSAT-1), the world’s first scientific satellite dedicated to supporting the 2030 Agenda, was designed and developed by the International Research Center of Big Data for Sustainable Development Goals (CBAS). Its three advanced EO sensors, i.e., Thermal Infrared Spectrometer (TIS), Glimmer Imager (GLI), and Multispectral Imager (MSI), furnish high-quality data, enabling continuous monitoring of human activity and environmental changes to bolster SDG-related research and global sustainability initiatives. As of November 2025, SDGSAT-1 has collected over 480 000 global terrain coverage images since its launch in November 2021. All its datasets have been shared free of charge with the Global Scientific Community through the SDGSAT-1 Open Science Program initiated in September 2022. The datasets have enabled researchers from more than 110 countries, 10 UN agencies, and various international organizations to publish over 180 scientific articles, 17 UN reports, and numerous public data products. These have demonstrated applications in urban development, disaster response, environmental monitoring, agriculture, and marine conservation. This article reviews the technical innovations and mission specifications of the SDGSAT-1 satellite, demonstrates its contribution in leveraging space technology for SDG monitoring and evaluation, and discusses the future evolution of development of EO systems, specifically the planned Sustainable Development Satellite Constellation, for supporting the global achievement of SDGs.

The Ejin Banner, as an essential and vulnerable oasis area, locates in arid and semi-arid region, northwestern China. To assess the water and vegetation variation from 2000 to 2015, this study selected the Modified Normalized Difference Water Index (MNDWI) and the Modified Soil Adjusted Vegetation Index (MSAVI) as indicators to interpret the Landsat TM/OLI images. The results indicate that the water have witnessed a significant increase from 0 to 70.7283 km2during this period. Meanwhile, the area of vegetation had a growth of 92.8%, rising from 137.3508 km2in 2000 to 264.7539 km2in 2015. In addition, the meteorological statistics test suggested that the warmer and wetter climate promoted the vegetation and water resources recover. Important as the oases are, results suggest that the oases reversion can effectively suppress the expansion of the Badain Jaran Desert, emphasizing the value of the oases protection for preventing the eco-environment deterioration and desertification.

This study presents new results for geological mapping in arid and semi-arid regions using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data. ASTER multispectral thermal-infrared (TIR) data have been processed for mapping soil desertification and salinization at the Taklimakan Desert and its surrounding areas, west China. The mineralogical indices such as Desertification Index (DI) and Salinity Index (SI) were proposed to estimate and monitor the silicate and soluble salt minerals which related with desertification and salinization in the arid and semi-arid environments. These mineralogical indices were verified by field observation and measurement data. It is concluded that the proposed methods have great potential for desertification and salinization mapping in arid and semi arid regions. Thus, it can provide an effective technology for the long-term monitoring and assessment of the eco-environment change in the dry lands on local, regional and global scales.

Ecosystem services are the important link between the ecological system and human welfare. Quantifying and predicting the changes of ecosystem service value (ESV) is an important tool to seek choices to manage natural and human-made capital more effectively and sustainably. This study aims to model and predict the impacts of future Land Use/Land Cover(LULC) changes on ESV in a coastal area suffering rapid process of urbanization of China, Qingdao. Based on Landsat images and random forest algorithm, LULC in 1990, 1995, 2000, 2005, 2010, and 2015 were mapped and classified. A cellular automaton (CA)-Markov model was used to simulate future LULC changes in 2025. ESVs was quantified and predicted based LULC data and a modified coefficient method. The total ESV of Qingdao decreased from 172.72 billion yuan in 1990 to 164.17 billion yuan in 2025, mainly due to the loss of farmland and grassland. The built-up land should be controlled to the occupation of farmland and grassland. The management of LULC should follow ecological protection rules to protect environment and achieve sustainable and balanced development.

An improved method for measuring and potentially monitoring surface particle size using satellite multispectral VNIR-SWIR-TIR ASTER TIR imagery was successfully tested for the Mu Us Desert to Loess Plateau region of China. The remote sensing results were validated against field sample data and published work. This work has implications for establishing a new mineral-based Earth Observation indicator for quantitative monitoring process of desertification.

The development of methods for mapping lithology and structure has been the main goals of geological remote sensing research. With the successful development of mineralogic indices, e.g., Quartz Index (QI), Carbonate Index (CI), Mafic Index (MI) based on the ASTER multispectral thermal infrared (TIR) data, which have demonstrated the usefulness and effectiveness of ASTER TIR data on lithologic mapping, we have produced the regional mosaic mapping of the indices covering wide area in the semi-arid to arid regions across the globe. Here in this paper, we show the method of making the regional lithological mapping with the indices defined for ASTER data, present example results of mapping covering a part of the Tibetan Plateau and surrounding area, and then make some geological discussions on the results.

Bashibulake, located in the southwestern Tian Shan, is a sandstone-type uranium deposit that is typically related to hydrocarbons. Based on the analysis of the mineral characteristic and spectral features related to uranium mineralization, the spatial distribution of alteration was extracted from multispectral remote sensing data, and combined with the surface and underground tectonic interpretation from the remote sensing data and seismic reflection profiles, the ore-controlling role of the structure-alteration zone was analyzed.