The “dry gets drier, wet gets wetter” (DGDWGW) paradigm is widely accepted in global moisture change. However, Greve et al.¹ have declared that this paradigm has been overestimated. This controversy leaves a large gap in the understanding of the evolution of water-related processes. Here, we examine the global moisture trends using satellite soil moisture for the past 35 years (1979–2013). Our results support those of Greve et al., although there are quantitative differences. Generally, approximately 30% of global land has experienced robust moisture trends (22.16% have become drier and 7.14% have become wetter). Only 15.12% of the land areas have followed the DGDWGW paradigm, whereas 7.77% have experienced the opposite trend. A new finding is that there is a significant “drier in dry, wetter in wet” (DIDWIW) trend paradigm; 52.69% of the drying trend occurred in arid regions and 48.34% of the wetter trend occurred in the humid regions. Overall, 51.63% of the trends followed the DIDWIW paradigm and 26.93% followed the opposite trend. We also identified the DGDWGW and DIDWIW paradigms in low precipitation-induced arid regions in which the dry soil led to an increasing sensible heat flux and temperature and subsequently potential evapotranspiration.

Under rapid urbanization, many cities in China suffer from serious fine particulate matter (PM_2.5) pollution. As the emission sources or adsorption sinks, land use and the corresponding landscape pattern unavoidably affect the concentration. However, the correlation varies with different regions and scales, leaving a significant gap for urban planning. This study clarifies the correlation with the aid of in situ and satellite-based spatial datasets over six urban agglomerations in China. Two coverage and four landscape indices are adopted to represent land use and landscape pattern. Specifically, the coverage indices include the area ratios of forest (F_PLAND) and built-up areas (C_PLAND). The landscape indices refer to the perimeter-area fractal dimension index (PAFRAC), interspersion and juxtaposition index (IJI), aggregation index (AI), Shannon’s diversity index (SHDI). Then, the correlation between PM_2.5 concentration with the selected indices are evaluated from supporting the potential urban planning. Results show that the correlations are weak with the in situ PM_2.5 concentration, which are significant with the regional value. It means that land use coverage and landscape pattern affect PM_2.5 at a relatively large scale. Furthermore, regional PM_2.5 concentration negatively correlate to F_PLAND and positively to C_PLAND (significance at p < 0.05), indicating that forest helps to improve air quality, while built-up areas worsen the pollution. Finally, the heterogeneous landscape presents positive correlation to the regional PM_2.5 concentration in most regions, except for the urban agglomeration with highly-developed urban (i.e., the Jing-Jin-Ji and Chengdu-Chongqing urban agglomerations). It suggests that centralized urbanization would be helpful for PM_2.5 pollution controlling by reducing the emission sources in most regions. Based on the results, the potential urban planning is proposed for controlling PM_2.5 pollution for each urban agglomeration.

Satellite video (SV) can acquire rich spatiotemporal information on the earth. Single object tracking (SOT) in SVs enables the continuous acquisition of the position and range of a specific object, expanding the field of remote-sensing applications. In SVs, objects are small with limited features and vulnerable to tracking drift. In this article, a correlation filter based dual-flow (DF) tracker is proposed to explore how the hybridization of spatial–spectral feature fusion and motion model can boost tracking. To represent small objects, the DF adaptively fuses complementary features using a state-aware indicator in feature flow. In motion flow, the indicator perceives the confidence of the feature flow. A dual-mode prediction model is then constructed to simulate the object's motion pattern and cooperate linear and nonlinear motion patterns to implement SOT in SVs. The ablation experiments demonstrate that the DF contributes to tracking. Experimental comparisons on 14 real SVs captured by the Jilin-1 satellite constellation show that DF achieves optimal performance with an area under the curve of 0.912 in the precision plot, 0.700 in the success plot, and a speed of 155.2 frames per second. This work would encourage the development of remote-sensing ground surveillance.