Water resources are a key factor for regional sustainable development. However, the published water resource data in China is based on a large geographical scale, such as watershed units, and the data cannot reflect subtle differences in water resource distribution. The paper aimed to distribute water resources of the third-order basin of China into grid-cells of 1 km × 1 km. First, we used Moran's I index to analyze the spatial pattern of water resources of the third-order basin. Second, we constructed a spatial autocorrelation model between water resources of third-order basins and the associated factors. Third, we applied the model to simulate the gridded water resource distribution and evaluated the simulation accuracy. The results indicated that significant spatial autocorrelation existed among the water resources of third-order basins. Northern China was the low-value clustering area of water resources and Southeast China was the high-value clustering area of water resources. Slope and precipitation were the main factors that influenced the amount of water resources. The simulating accuracy of water resource distribution was very high, apart from some extremely arid regions (Gurbantunggut Desert, Kumtag Desert, and Hexi Desert). On the whole, the gridded water resource distribution map was valid and was helpful for regional water resource management.

Identifying urban built-up area boundaries is critical to urban data statistics, size measurement, and spatial control. However, previous methods of extracting urban built-up area boundaries based on low-resolution remote-sensing data are frequently constrained by data accuracy. In this paper, a new method for extracting urban built-up area boundaries using high-resolution remote sensing images based on scale effects is proposed. Firstly, we generate a number of different levels of edge-multiplied hexagonal vector grids. Secondly, the impervious surface densities are calculated based on the hexagonal vector grids with the longest edge. Then, the hexagonal grids with higher impervious surface densities are extracted as the built-up area of the first level. Thirdly, we gradually reduce the spatial scale of the hexagonal vector grid and repeat the extraction process based on the extracted built-up area in the previous step. Eventually, we obtain the urban built-up area boundary at the smallest scale. Plausibility checks indicate that the suggested method not only guarantees the spatial continuity of the resultant urban built-up area boundary, but also highlights the prevailing orientation of urban expansion. The extracted Beijing built-up area boundary can serve as a reference in decision-making for space planning and land-use control.