Radar remote sensing reveals potential underestimation of rainfall erosivity at the global scale.

Rainfall kinetic energy (RKE) constitutes one of the most critical factors that drive rainfall erosivity on surface soil. Direct measurements of RKE are limited, relying instead on the empirical relations between kinetic energy and rainfall intensity (KE-I relation), which have not been well regionalized for data-scarce regions. Here, we present the first global rainfall microphysics-based RKE (RKEMPH) flux retrieved from radar reflectivity at different frequencies. The results suggest that RKEMPH flux outperforms the RKE estimates derived from a widely used empirical KE-I relation (RKEKE-I) validated using ground disdrometers. We found a potentially widespread underestimation of RKEKE-I, which is especially prominent in some low-income countries with ~20% underestimation of RKE and the resultant rainfall erosivity. Given the evidence that these countries are subject to greater rainfall-induced soil erosion, these underestimations would mislead conservation practices for sustainable development of terrestrial ecosystems.

Geographic modeling and simulation systems for geographic research in the new era: Some thoughts on their development and construction.

Regionality, comprehensiveness, and complexity are regarded as the basic characteristics of geography. The exploration of their core connotations is an essential way to achieve breakthroughs in geography in the new era. This paper focuses on the important method in geographic research: Geographic modeling and simulation. First, we clarify the research requirements of the said three characteristics of geography and its potential to address geo-problems in the new era. Then, the supporting capabilities of the existing geographic modeling and simulation systems for geographic research are summarized from three perspectives: Model resources, modeling processes, and operational architecture. Finally, we discern avenues for future research of geographic modeling and simulation systems for the study of regional, comprehensive and complex characteristics of geography. Based on these analyses, we propose implementation architecture of geographic modeling and simulation systems and discuss the module composition and functional realization, which could provide theoretical and technical support for geographic modeling and simulation systems to better serve the development of geography in the new era.

Taiwan has shifted to being a net CO2 exporter since the mid-1990s.

With the integration of the global economy and increased international trade, CO2 emissions embodied in trade have attracted broad attention. In this study, we examined Taiwan's CO2 emissions embodied in its imports and exports with its 167 trade partners from 1970 to 2015 using the emissions embodied in bilateral trade (EEBT) method. The results show that since the mid-1990s, Taiwan has shifted to being a net CO2 emissions exporter. The share of Taiwan's CO2 emissions exported to developed countries has decreased. However, the share exported to Mainland China, Hong Kong special administrative region and many developing countries in Southeast Asia has increased. The results of a structural decomposition analysis show that emissions intensity changes were the main driving force for Taiwan's exported CO2 emissions during 1970-1996, while increased export volumes were the largest driving force for Taiwan's exported CO2 emissions during 1996-2015. Emissions intensity changes and population growth are the main driving factors for Taiwan's CO2 emissions produced and consumed by itself increases. Based on the SDA results, environmentally friendly policies, such as energy efficiency and industrial structure optimization, are suggested to help Taiwan shift towards a sustainable economy.

Remote sensing estimation of chlorophyll-a concentration in Taihu Lake considering spatial and temporal variations.

The estimation of chlorophyll-a concentrations (Chla) in lakes using remote sensing is convenient, but its use remains challenging in large eutrophic water bodies due to the great spatial and temporal variations of its optical properties. Combining the sampling location and date information with Chla data, this study divided the lake water into three types, I, II and III, and then built an optimal Chla estimation model for each type based on 11 datasets collected from 2004 to 2012 in Taihu Lake, China. The resultant model expression is Chla = exp (ax2 + bx + c), where x is R701/R677, (1/R686-1/R695) × R710 and (R690/R550-R675/R700) / (R690/R550 + R675/R700). For the Chla ranging from 2 to 192 mg/m3, the root-mean-square error (RMSE) of the new model decreased up to 5.1 mg/m3 compared to that of previous band combination models, such as band ratio, three-band and four-band models when directly validated. The RMSE of the re-parametrization model (the lowest RMSE < 12 mg/m3) is also lower than for those models (the lowest RMSE > 16 mg/m3), indicating that the Chla estimation model that considers the spatial and temporal variations has a better performance and validation accuracy and therefore is more effective for remote sensing monitoring of water quality.

Remote observation of water clarity patterns in Three Gorges Reservoir and Dongting Lake of China and their probable linkage to the Three Gorges Dam based on Landsat 8 imagery.

The Secchi disk depth (ZSD) plays a critical role in describing water clarity. Several studies have shown linkages between Three Gorges Dam (TGD) and the downstream lacustrine ecosystem in the middle and lower Yangtze River basin. However, the potential influence on the ZSD fluctuation in the entire anthropogenic reservoirs of Three Gorges (ER) and Dongting Lake (DTL) has not been reported, possibly due to technical obstacles in obtaining statistically significant spatial and temporal results. We addressed this challenge by using remote sensing technology: the Landsat 8 Operational Land Imager (OLI). We proposed a new, robust remote-sensing algorithm to estimate ZSD from OLI imagery using red and green band-ratio, leading to MAPE of 21.68% and RMSE of 0.076m for ZSD ranging from 0.1m to 1.05m. After satisfactory image-based validation, the algorithm was implemented on OLI data to derive ZSD patterns over ER and DTL from 2013 to 2017. Several crucial findings can be drawn: 1) Spatial-temporal patterns of ZSD exhibited notable fluctuations over both ER and DTL, and they also demonstrated a significant correlation with each other because of the opposite temporal cycle of ZSD fluctuations between ER and DTL; 2) Temporally, monthly fluctuations of ZSD between ER and DTL had opposite temporal cycles, which was mainly attributed to the surface runoff and sediment discharge driven by the outbound runoff variations of TGD. Spatially, the heterogeneity of the ZSD pattern in ER might have resulted from the different geographical regions being divided by large anthropologic hydrological facilities, such as TGD; 3) The relationship between ZSD and total suspended matter (TSM) showed a significant negative correlation, as did the relationship between ZSD and Kd(490). These findings demonstrate that TSM often plays a principal role in light attenuation of extremely turbid inland waters; 4) An inversed phenomenon of water clarity was observed at the intersection of DTL and the Yangtze River around Chenglingji site (YRAC), which was due to the opposite temporal cycle of ZSD fluctuations between DTL and ER after the impoundment of TGD; and 5) Owing to the analysis of noise-equivalent ZSD, OLI data can be used to derive ZSD, since the imagery uncertainty is 0.07m by means of our band-ratio algorithm, which demonstrates similar results to MODIS. The proposed ZSD-derived algorithm in this study could be suitable for other turbid lakes or reservoirs to formulate related strategies of water quality management in the middle and lower Yangtze River basin, and the unveiled findings here improve our understanding of ZSD spatiotemporal fluctuations in large river-connected lakes, such as Poyang Lake.

Spatio-Temporal Constrained Human Trajectory Generation from the PIR Motion Detector Sensor Network Data: A Geometric Algebra Approach.

Passive infrared (PIR) motion detectors, which can support long-term continuous observation, are widely used for human motion analysis. Extracting all possible trajectories from the PIR sensor networks is important. Because the PIR sensor does not log location and individual information, none of the existing methods can generate all possible human motion trajectories that satisfy various spatio-temporal constraints from the sensor activation log data. In this paper, a geometric algebra (GA)-based approach is developed to generate all possible human trajectories from the PIR sensor network data. Firstly, the representation of the geographical network, sensor activation response sequences and the human motion are represented as algebraic elements using GA. The human motion status of each sensor activation are labeled using the GA-based trajectory tracking. Then, a matrix multiplication approach is developed to dynamically generate the human trajectories according to the sensor activation log and the spatio-temporal constraints. The method is tested with the MERL motion database. Experiments show that our method can flexibly extract the major statistical pattern of the human motion. Compared with direct statistical analysis and tracklet graph method, our method can effectively extract all possible trajectories of the human motion, which makes it more accurate. Our method is also likely to provides a new way to filter other passive sensor log data in sensor networks.