The carbon release and transport in rivers are expected to increase in a warming climate with enhanced melting. We present a continuous dataset of DOC in the river, precipitation, and groundwater, including air temperature, discharge, and precipitation in the source region of the Yangtze River (SRYR). Our study shows that the average concentrations of DOC in the three end-members are characterized as the sequence of groundwater > precipitation > river, which is related to the water volume, cycle period, and river flow speed. The seasonality of DOC in the river is observed as the obvious bimodal structure at Tuotuohe (TTH) and Zhimenda (ZMD) gauging stations. The highest concentration appears in July (2.4 mg L⁻¹ at TTH and 2.1 mg L⁻¹ at ZMD) and the secondary high value (2.2 mg L⁻¹ at TTH 1.9 mg L⁻¹ at ZMD) emerges from August to September. It is estimated that 459 and 6751 tons of DOC are transported by the river at TTH and ZMD, respectively. Although the wet deposition flux of DOC is nearly ten times higher than the river flux, riverine DOC still primarily originates from soil erosion of the basin rather than precipitation settlement. Riverine DOC fluxes are positively correlated with discharge, suggesting DOC fluxes are likely to increase in the future. Our findings highlight that permafrost degradation and glacier retreat have a great effect on DOC concentration in rivers and may become increasingly important for regional biogeochemical cycles.

Urban villages represent informal residential areas emerging since China’s rapid urbanization process. Scientific map generalization of urban villages with scientific maps aids readers in discerning their distribution and making informed decisions concerning them. However, there is still a scarcity of research on the automatic extraction and generalization of urban villages from vector data, which needs to be studied to further improve the expression of maps. To address this problem, this paper presents a methodology for the extraction and generalization of urban villages from Digital Line Graphics. Firstly, a heuristic approach is employed to analyze the atypical morphological characteristics of urban villages. Then, indices based on computational geometry and the modified Hausdorff distance are utilized to quantify these traits. Lastly, an automatic generalization principle for urban villages is offered. The approach was tested in experimental blocks and proved to be effective. It offers a novel method for the automatic extraction and cartography of urban villages.

Quantitative relations between topological similarity degree and map scale change of multi-scale contour clusters are vital to the automation of map generalization. However, no method has been proposed to calculate the relations. This paper aims at filling the gap by proposing a new approach. It firstly constructed a directed contour tree by pre-processing of unclosed contours, and then developed a quantitative expression of topological relations of contour cluster based on directed contour tree. After this, it employed 108 groups of multi-scale contour clusters with different geomorphological types to explore the changing regularity of topological indices with map scale. Last, it used 416 points to calculate the quantitative relations between topological similarity degree and map scale change by curve fitting method. The results show that the quantitative expression of multi-scale topological indexes is closely related to the contour interval change, and power function is the best fit among the candidate functions.

This paper aims to propose a new approach to calculate the quantitative relations between morphostructural similarity degree and map scale change in multi-scale contour clusters for automatic contour generalization. Terrain lines were extracted by pre-processing of unclosed contour lines, and an indirect quantitative expression method of morphostructural similarity relation was proposed based on terrain line hierarchical trees. Thirteen groups of multi-scale contour clusters with different drainage areas of loess geomorphy were employed to explore the changing regularity of morphostructural similarity indices with map scale. Finally, the quantitative relations between morphostructural similarity degree and map scale change were calculated using 52 groups of points. The results show that power function is the best fit among the candidate functions, and the quantitative relations between the morphostructural similarity degree and map scale change can be expressed using the same power function, which facilitates the automation of contour generalization.