Habitat quality (HQ) is of great significance to regional sustainable development, which is a key link for regional ecological security and human welfare. Assessing the temporal and spatial evolution of HQ caused by land-use change could provide a scientific basis for regional ecological protection and land management. Here, based on the ArcGIS platform and the InVEST model, this study quantified the spatial and temporal evolutions of land use, landscape patterns, and HQ from 1985 to 2015, in Taihu Lake Basin (TLB). Hotspot analysis tools were used to identify the spatial agglomeration and evolution characteristics of HQ in TLB. The results showed that, (1) the land use and landscape pattern in TLB experienced dramatic change process during 1985–2015, with the dominating conversion being from farmland to construction land, which led to an increase in landscape heterogeneity and fragmentation. (2) The HQ was generally reduced in the past 30 years. In particular, the decline of HQ was extremely severe in the peripheral area of cities and roads, due to urban sprawl. (3) Regarding the spatial distribution of HQ, the northern and eastern areas were generally higher, while the western and southern areas were generally lower. The hotspots areas were mainly located in the southwestern mountain area and west-central lake area, while the cold spots areas were mainly located in urban areas in the north and the east. (4) The area and degree of habitat degradation were both increased significantly due to land-use change, and the degradation of the Taihu Lake was highlighted. Strengthening the ecological environment management and reducing the threat of urban expansion to the HQ is urgently required. This study could help understand HQ of the TLB and provide a scientific basis for decision-makers.

The concept of local climate zone (LCZ) has standardized the calculation of urban heat island (UHI) intensity (UHII) and established the connection among urban morphology, surface property, and UHI. In addition, LCZ has provided a new insight into the studies on urban thermal environment. This study selected Nanjing, China, as the study area and utilized a combined method that comprised remote sensing based and geographic information system based methods based on random forest classifier for LCZ classification. Overall accuracy reached 92%, and kappa coefficient was 0.911. In addition, the seasonal and diurnal differences of land surface temperature (LST) were analyzed via LST retrieval from Landsat data and computational fluid dynamics model simulation, respectively. Results confirmed the warmest and coldest zones in four seasons. The LST distribution characteristics of land cover and built types were basically the same during the four seasons. Moreover, the UHII difference of an LCZ class in various seasons and the UHII difference of a season in various LCZs were investigated. The daily LSTs of the simulated LCZs (1 to 6) within 24 h showed the same variation law but different variation extents in a day. The LST variations of built types were related to building elements, such as building height, building density, building layout, and green ratio. This study identified an existing relation between LST and LCZ and analyzed LST on the basis of LCZs from seasonal and diurnal scales, which provides guidance for future researchers.

Urban floods are linked to patterns of land use, specifically urban sprawl. Since the 1980s, government-led new districts are sweeping across China, which account for many of the floods events. Focuses of urbanization impact on floods are extending gradually from hydraulic channels, to imperviousness ratio, to imperviousness pattern in urban areas or urbanized basins. Thus, the paper aims to explore how urban land pattern can affect floods in urban areas to provide decision makers with guidance on land use and stormwater management. Imperviousness was generally correlated with spatial variations in land use, with lower imperviousness in less dense, new districts, and higher imperviousness in more dense, uniform/clustered development in local areas adjacent to hot nodes. The way imperviousness and channel are organized, and the location of imperviousness within a catchment, can influence floods. Local government’s approach to new district planning, in terms of zoning provisions, has only considered some development aspects and has not adequately integrated flood management. A key issue for the planning should been done to adequately cater for flooding, particularly considering the benefits of keeping natural conveyance systems (rivers) and their floodplains to manage flood waters.

Residential thermal environment affects the life of residents in terms of their physical and mental health. Many studies have shown that building design elements affect the urban thermal environment. In this study, Nanjing City was used as the study area. A three-dimensional microclimate model was used to simulate and analyze the effects of four main factors, namely, building height, density, layout and green ratio, on thermal environment in residential areas. Results showed that 25% building density obtained a low average air temperature (ATa) and average predicted mean vote (APMV) during 24 h. Thus, a higher building height indicates a lower ATa and APMV and better outdoor comfort level. In addition, peripheral layout had the lowest ATa and APMV, followed by the determinant and point group layouts. The green ratio increased from 0% to 50% with a 10% step and the ATa and APMV decreased gradually. However, when the green ratio increased from 30% to 40%, ATa and APMV decreased most. The effects of building height, density and green ratio on the thermal environment in residential areas were interactive. The effects of building density, green ratio and layout on hourly air temperature and hourly predicted mean vote in daytime varied from these indicators during night time. How the four building design elements interact with thermal environment were probed from two aspects of air temperature and thermal comfort based on the validated ENVI-met, which is the element of novelty in this study. However, thermal comfort has rarely been considered in the past studies about urban outdoor thermal environment.

Understanding the link between greenspace patterns and land surface temperature is very important for mitigating the urban heat island (UHI) effect and is also useful for planners and decision-makers for providing a sustainable design for urban greenspace. Although coupling remote sensing data with a computational fluid dynamics (CFD) model has widely been used to examine interactions between UHI and greenspace patterns, the paper aims to examine the impact of five theoretical models of greenspace patterns on land surface temperature based on the improvement of the accuracy of CFD modeling by the combination of LiDAR data with remote sensing images to build a 3D urban model. The simulated results demonstrated that the zonal pattern always had the obvious cooling effects when there are no large buildings or terrain obstacles. For ambient environments, the building or terrain obstacles and the type of greenspace have the hugest influence on mitigating the UHI, but the greenspace area behaves as having the least cooling effect. A dotted greenspace pattern shows the best cooling effect in the central area or residential district within a city, while a radial and a wedge pattern may result in a “cold source” for the urban thermal environment.