With the development of satellite and remote sensing techniques, more and more image data from airborne/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of “algorithm fusion” methods; (3) Establishment of an automatic quality assessment scheme.

The air quality in China, particularly the PM_2.5 (particles less than 2.5 μm in aerodynamic diameter) level, has become an increasing public concern because of its relation to health risks. The distribution of PM_2.5 concentrations has a close relationship with multiple geographic and socioeconomic factors, but the lack of reliable data has been the main obstacle to studying this topic. Based on the newly published Annual Average PM_2.5 gridded data, together with land use data, gridded population data and Gross Domestic Product (GDP) data, this paper explored the spatial-temporal characteristics of PM_2.5 concentrations and the factors impacting those concentrations in China for the years of 2001–2010. The contributions of urban areas, high population and economic development to PM_2.5 concentrations were analyzed using the Geographically Weighted Regression (GWR) model. The results indicated that the spatial pattern of PM_2.5 concentrations in China remained stable during the period 2001–2010; high concentrations of PM_2.5 are mostly found in regions with high populations and rapid urban expansion, including the Beijing-Tianjin-Hebei region in North China, East China (including the Shandong, Anhui and Jiangsu provinces) and Henan province. Increasing populations, local economic growth and urban expansion are the three main driving forces impacting PM_2.5 concentrations.

The purpose of this study was to assess soil heavy metal contamination and the potential risk for local residents in Suxian county of Hunan Province, southern China. Soil, rice and vegetable samples from the areas near the mining industrial districts were sampled and analyzed. The results indicate that the anthropogenic mining activities have caused local agricultural soil contamination with As, Pb, Cu and Cd in the ranges of 8.47–341.33 mg/kg, 19.91–837.52 mg/kg, 8.41–148.73 mg/kg and 0.35–6.47 mg/kg, respectively. GIS-based mapping shows that soil heavy metal concentrations abruptly diminish with increasing distance from the polluting source. The concentrations of As, Pb, Cu and Cd found in rice were in the ranges of 0.02–1.48 mg/kg, 0.66–5.78 mg/kg, 0.09–6.75 mg/kg, and up to 1.39 mg/kg, respectively. Most of these concentrations exceed their maximum permissible levels for contaminants in foods in China. Heavy metals accumulate to significantly different levels between leafy vegetables and non-leafy vegetables. Food consumption and soil ingestion exposure are the two routes that contribute to the average daily intake dose of heavy metals for local adults. Moreover, the total hazard indices of As, Pb and Cd are greater than or close to the safety threshold of 1. Long-term As, Pb and Cd exposure through the regular consumption of the soil, rice and vegetables in the investigated area poses potential health problems to residents in the vicinity of the mining industry.

The 18th National Congress of the Communist Party of China put forward the optimization of territorial space development patterns as the primary measure of ecological civilization construction, and put forward the goal of “promoting intensive and efficient production space, livable and moderate living space, and beautiful (picturesque scenery) ecological space”. Through literature research and summing induction, this paper combs the research progress of the overall optimization of “Production–Living–Ecological” space (PLES) systematically. It is found that the existing work mainly focuses on the overall optimization of PLES from the perspectives of land-use quality, land-use suitability evaluation, resource and environmental carrying capacity, and comparative advantages. However, due to the lack of understanding of the scientific connotation of PLES, and the imperfect construction of quantitative identification methods and classification system, there are many problems in the technical approaches of the overall optimization of PLES, which remain to be clarified. In the future, the technological approach to the overall optimization of PLES should be guided by the vision of building a beautiful China, with the theory of a human–Earth coupling system as the core, and systematically build a theoretical system and technical framework to identify and optimize territorial space.