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Lake Water storage can be estimated based on Lake Boundary and lakebed terrain. The boundary of a lake can be extracted from the remote sensing satellite image or the Unmanned Aerial Vehicle (UAV) orthophoto, but the information of the lake and its surroundings, which is supposed to be three-dimensional, is recorded in two dimensions in this way. When the tall and dense vegetation are projected on the lake, the extracted lake boundary from orthophoto would be smaller than reality, which results in lower value of the lake water storage. UAV oblique photogrammetry can solve this problem by recording multi-angle images of the lake and its surroundings. Based on aerial photogrammetry theory, a real 3D model of the lake can be constructed by combing UAV oblique photogrammetric images. The model can accurately present the actual scene of the lake, and the extracted lake boundary can be very close to reality. In this study, UAV and Unmanned Surface Boats (USB) have been employed to collect UAV oblique photogrammetric images and lakebed terrain data, respectively. The lake boundary has been extracted based on the UAV real 3D model. The Digital Elevation Model (DEM) of lakebed terrain has been built based on lakebed terrain data collected by USB. Finally, the water storage of the lake is estimated based on the boundary and DEM. Experiments show that a real 3D model based on UAV data can depict lake boundaries accurately, which could eliminate the impact of vegetation shied around the lake. Utilizing the UAV and USB can be a standard method for estimating the water storages of small lakes.

It is essential to understand how urban plans affect urban growth patterns in order to improve current urban planning and management systems. Few studies have been conducted to analyse urban growth patterns of Shenzhen, an international megacity located in southern China, but none of them revealed the relationships between urban planning and urban growth patterns. This study explores the effects of urban master plans on urban growth patterns in different plan periods in Shenzhen. We first quantified the urban growth patterns comparing pixel- and patch-based methods. Three methods resulted in different quantities and spatial characteristics of urban growth. We then explored the relationships between urban growth patterns and urban planning in Shenzhen through multinomial logistic regression models. Across two planning periods, the master plans together with other socio-economic, physical, proximity, accessibility and neighbourhood factors shaped the urban growth patterns of Shenzhen. Out of the master plan elements, planned main roads in the Master Plan of Shenzhen 1996–2010 and the planned built-up zone in the Master Plan of Shenzhen 2010–2020 ha d stronger effects on urban growth patterns but contributed less than most other factors, e.g. distance to ocean. The importance of the other influence factors also varied over time. This changing effect suggests that we need to consider carefully whether driving factors might change in their importance over time when investigating future scenarios of urban land use change. Overall, this approach could also be applied to monitor progress in the paradigm shift towards an integrated urban-rural development in China.