Vector-to-raster conversion is a process accompanied with errors.The errors are classified into predicted errors before rasterization and actual errors after that.Accurate prediction of the errors is beneficial to developing reasonable rasterization technical schemes and to making products of high quality.Analyzing and establishing a quantitative relationship between the error and its affecting factors is the key to error prediction.In this study,land cover data of China at a scale of 1:250 000 were taken as an example for analyzing the relationship between rasterization errors and the density of arc length(DA),the density of polygon(DP) and the size of grid cells(SG).Significant correlations were found between the errors and DA,DP and SG.The correlation coefficient(R2) of a model established based on samples collected in a small region(Beijing) reaches 0.95,and the value of R2 is equal to 0.91 while the model was validated with samples from the whole nation.On the other hand,the R2 of a model established based on nationwide samples reaches 0.96,and R2 is equal to 0.91 while it was validated with the samples in Beijing.These models depict well the relationships between rasterization errors and their affecting factors(DA,DP and SG).The analyzing method established in this study can be applied to effectively predicting rasterization errors in other cases as well. 相似文献
Managing nonpoint-source (NPS) pollution of groundwater systems is a significant challenge because of the heterogeneous nature of the subsurface, high costs of data collection, and the multitude of scales involved. In this study, we assessed a particularly complex NPS groundwater pollution problem in Michigan, namely, the salinization of shallow aquifer systems due to natural upwelling of deep brines. We applied a system-based approach to characterize, across multiple scales, the integrated groundwater quantity–quality dynamics associated with the brine upwelling process, assimilating a variety of modeling tools and data—including statewide water well datasets scarcely used for larger scientific analysis. Specifically, we combined (1) data-driven modeling of massive amounts of groundwater/geologic information across multiple spatial scales with (2) detailed analysis of groundwater salinity dynamics and process-based flow modeling at local scales. Statewide “hotspots” were delineated and county-level severity rankings were developed based on dissolved chloride (Cl−) concentration percentiles. Within local hotspots, the relative impact of upwelling was determined to be controlled by: (1) streams—which act as “natural pumps” that bring deeper (more mineralized) groundwater to the surface; (2) the occurrence of nearly impervious geologic material at the surface—which restricts fresh water dilution of deeper, saline groundwater; and (3) the space–time evolution of water well withdrawals—which induces slow migration of saline groundwater from its natural course. This multiscale, data-intensive approach significantly improved our understanding of the brine upwelling processes in Michigan, and has applicability elsewhere given the growing availability of statewide water well databases. 相似文献
China has experienced unprecedented urbanization in the past decades, resulting in dramatic changes in the physical, limnological, and hydrological characteristics of lakes in urban landscapes. However, the spatiotemporal dynamics in distribution and abundance of urban lakes in China remain poorly understood. Here, we characterized the spatiotemporal change patterns of urban lakes in China’s major cities between 1990 and 2015 using remote-sensing data and landscape metrics. The results showed that the urban lake landscape patterns have experienced drastic changes over the past 25 years. The total surface area of the urban lakes has decreased by 17,620.02?ha, a decrease of 24.22%, with a significant increase in the landscape fragmentation and a reduction in shape complexity. We defined three lake-shrinkage types and found that vanishment was the most common lake-shrinkage pattern, followed by edge-shrinkage and tunneling in terms of lake area. Moreover, we also found that urban sprawl was the dominant driver of the lake shrinkage, accounting for 67.89% of the total area loss, and the transition from lakes to cropland was also an important factor (19.86%). This study has potential for providing critical baseline information for government decision-making in lake resources management and urban landscape design. 相似文献
Do collective behaviors of the daily routine of a city's inhabitants form the periodical cycling of human activity at the city level (here termed the “city's diurnal rhythm”)? If the answer is yes, do there exist geographical patterns in the city's diurnal rhythm? Using a nationwide dataset of observed uses of location‐aware services in the largest Chinese social media platform, we first confirm the significant periodicity in city‐level human activity from the perspective of the aggregate degree of social media uses over a day. We then investigate geographical changes in the diurnal rhythm of human activity and its local variations in different parts of the city, and between weekdays and weekend days, over 340 Chinese cities. Our results show that a city's diurnal rhythm across the whole country exhibits both regular, nationally conspicuous shifts along geographical gradients and locally distinct spatiotemporal changes within the city. Our findings could provide insights into the characterization of the daily routine of city‐level human activity and its geographical patterns, and have potential for several issues in terms of planning, management, and decision‐making related to human population dynamics. 相似文献
With the depletion of mineral resources on land, seafloor massive sulfide deposits have the potential to become as important for exploration, development and mining as those on land. However, it is difficult to investigate the ocean environment where seafloor massive sulfide deposits are located. Thus, improving prospecting efficiency by reducing the exploration search space through mineral prospectivity mapping (MPM) is desirable. MPM has been used in the exploration for seafloor deposits on regional scales, e.g., the Mid-Atlantic Ridge and Arctic Ridge. However, studies of MPM on ultraslow-spreading ridges on segment scales to aid exploration for seafloor massive sulfide have not been carried out to date. Here, data of water depth, geology and hydrothermal plume anomalies were analyzed and the weights-of-evidence method was used to study the metallogenic regularity and to predict the potential area for seafloor massive sulfide exploration in 48.7°–50.5° E segments on the ultraslow spreading Southwest Indian Ridge. Based on spatial analysis, 11 predictive maps were selected to establish a mineral potential model. Weight values indicate that the location of seafloor massive sulfide deposits is correlated mainly with mode-E faults and oceanic crust thickness in the study area, which correspond with documented ore-controlling factors on other studied ultraslow-spreading ridges. In addition, the detachment fault and ridge axis, which reflect the deep hydrothermal circulation channel and magmatic activities, also play an important role. Based on the posterior probability values, 3 level A, 2 level B and 2 level C areas were identified as targets for further study. The MPM results were helpful for narrowing the search space and have implications for investigating and evaluating seafloor massive sulfide resources in the study area and on other ultraslow-spreading ridges.