We conducted a standardized spatial thinking ability test (STAT) to examine the spatial thinking abilities of a group of Chinese undergraduates with a focus on their spatial reasoning, which is a very important component of critical spatial thinking. The college subject of human geography in China is often geared toward the preparation of students for government consultancy and policy-making tasks, known as the “tasks leading disciplines” (renwu dai xueke), where the pedagogies are problem-solving based and sustainability centered. Geographic Information Systems (GIS) has become the universal tool for problem solving in geography and other areas, thus human geography in this situation gives us a context to test and investigate whether and to what extent GIS implementation is able to improve undergraduate spatial thinking levels. Our comparative analysis reported the marginally significant difference of STAT test scores between GIS application (geoinformation group) and its control group (geography group without GIS training). It was also found that the Chinese students performed the spatial reasoning better in this test than American participants as reported in prior study, displaying their higher spatial cognition in terms of problem solving and Boolean logics. Futhermore, a strong negative correlation was reported between STAT test scores and final exam rank. It is possible that the higher geography education in a context of China may not fully embrace the spatial thinking capacity as the strategic goal. The results can help us to better understand the Oriental and Western gaps in higher geography education. Policy suggestions are given in the conclusion.
This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km2 Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).
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