The evaluation of building damage is of great significance for flood management. Chinese floodplains usually contain small- and medium-sized towns with many other scattered buildings. Detailed building information is usually scarce, making it difficult to evaluate flood damage. We developed an evaluation method for building damage by using airborne LiDAR data to obtain large-area, high-precision building information and digital elevation models (DEMs) for potentially affected areas. These data were then used to develop a two-dimensional (2-D) flood routing model. Next, flood loss rate curves were generated by fitting historical damage data to allow rapid evaluation of single-building losses. Finally, we conducted an empirical study based on the Gongshuangcha detention basin in China’s Dongting Lake region. The results showed that the use of airborne LiDAR data for flood-related building damage evaluation can improve the assessment accuracy and efficiency; this approach is especially suitable for rural areas where building information is scarce.
The survival and distribution of animals cannot be separated from a certain environment. How patterns in mammalian species depend on the environment remain unclear. This study incorporating spatial data on climate, precipitation, topography, and vegetation quantitatively analyzed the influence of specific geographical factors on the spatial distribution of terrestrial mammalian richness using the Geodetector model. We used the spatial analysis method of geographical information systems (GIS), separating the mammalian distribution of 621 species into 10 by 10 km grids to measure spatial richness. Our results showed that there were significant spatial differences in terrestrial mammalian richness in China. There was a low richness in the east and west, but high richness in the south. Individual factor detection results showed that annual precipitation (AP) and the minimum temperature of the coldest month (MTCM) were the dominant factors affecting the spatial pattern of mammal richness in China. Patterns in the distribution of species richness had distinct characteristics for different mammalian orders and were influenced by different environmental factors. The richness distribution of most orders was mainly affected by MTCM and AP. Interactive detection results showed that interacting factors in pairs play much bigger roles in the spatial distribution of species richness than individual factors. The synergistic effect of elevation with AP and MTCM best explained the distribution differences of species richness. We found that the Geodetector model is a valuable tool, hoping to be more widely used in biogeography.
We describe large-scale patterns of terrestrial mammal distribution in China by using geographical information system (GIS) spatial analysis. Mammal taxa, examined by species, family, and order, were binned into 10 km × 10 km grids to explore the relationship between their spatial distribution and geographical factors potentially affecting the same. The spatial pattern of species richness revealed four agglomerations: high richness in the south, low in north, and two low richness areas in eastern and western China. Species richness patterns in Carnivora was the most similar to overall terrestrial mammals’ richness; however, species richness in different orders exhibited distributions distinct from the overall pattern. We found a negative relationship between richness and latitude gradient. Species richness was most strongly correlated with forested ecosystems, and was found to be higher at an elevation of 2000~2200 m, with greater altitudinal variation indicative of higher species richness.
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