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Objectives: To assess the feasibility of estimating an EQ-5D-5L value set using a small study design in cancer patients and to compare the EQ-5D-5L values based on the preferences of cancer patients with those of the general public. Methods: Patients with clinically diagnosed cancers were recruited from two hospitals in Shanghai, China. In face-to-face interviews using the EQ-PVT survey, health states were valued by cancer patients using both cTTO and DCE methods. cTTO data was modelled alone or jointly with DCE data. Forty-eight models using different model specifications (cross-attribute level effect [CALE] and additive models), random/fixed effects model assumptions, data heteroscedasticity and censoring were estimated. The best performed model was identified in terms of monotonicity of estimated model coefficients and out-of-sample prediction accuracy. Results: Data collected from 221 cancer patients who participated in the study were included. The hybrid CALE model using both TTO and DCE data performed best in terms of prediction accuracy (Lin's concordance coefficient = 0.989; root mean squared error = 0.058) and suggested that pain/discomfort and anxiety/depression were the most undesirable health problems. Compared to values based on general Chinese public's health preferences, the values based on cancer patients' preferences were much higher and lower for health states characterized by extreme mobility problems and severe/extreme pain or discomfort, respectively. Conclusion: This study demonstrated the feasibility of using a small design to develop EQ-5D-5L value sets based on cancer patients' health preferences. Since there were signs of differences between preferences of patients and general population, it may be valuable to develop patient-specific value sets and use them in clinical decision making and economic evaluations. [ABSTRACT FROM AUTHOR]

Building height serves as an essential feature of urban morphology that provides valuable insights into human socio-cultural behaviors and their impact on the environment in an urban milieu. However, openly accessible building height information at the individual building level is still lacking and remains sorely limited. Previous studies have shown that the ICESat-2′s ATL03/08 products are of good accuracy for urban building heights retrieval, however, these studies are limited to areas with available data coverage. To this end, we propose a method for extracting urban building height by using ICESat-2 ATL03 photons and high-resolution remote sensing images. We first extracted the information of building roof to footprint offsets and building shadows from high resolution imagery using multitasking CNN frameworks. Using the building height samples calculated from ICESat-2 ATL03 photons, we developed a building height estimation method that combines building offset and shadow length information. We assessed the efficacy of the proposed method in the Wujiaochang area of Shanghai city, China. The results indicated that the proposed method is able to extract building height with a MAE of 4.7 m, and outperforms the traditional shadow-based and offset-based method. We believe that the proposed method is a good candidate for accurately retrieving building heights on a city-wide scale. [ABSTRACT FROM AUTHOR]

Automatic building rooftop extraction is of great importance to many applications including building reconstruction, solar energy supply, and disaster management. This study proposes a building rooftop extraction method using DSM data generated from aerial stereo images and vegetation cover vector data. The method consists of five steps: noise filtering, dilation reconstruction, vegetation and terrain region removal, region growing and merging, and post-processing. We applied the proposed method to the centre of Shanghai, China, a typical urban area. Experimental results show that the proposed method can successfully extract building rooftops, with an approximately 82.6% quality percentage and 96.2% matched overlay. [ABSTRACT FROM AUTHOR]

The brightness of nighttime lights (NTL) has been proven to be strongly related to population density and thus has been widely used for population estimation from national to county levels. However, the limited availability of fine-grained census data makes an accurate assessment of the pixel-level relationship between NTL intensity and population a challenge. Consequently, pixel-level population estimation bias based on NTL intensity has been rarely investigated. Using fine-grained census data, we quantitively evaluated the correlation between urban population and NTL intensity over the core areas in Shanghai city, China. We also proposed a simple index called building volume adjusted nighttime light index (BVANI) for better characterizition of the relationship between urban population and NTL intensity. Our results found that pixel-level NTL intensity has a minimal correlation with population and the exclusive use of NTL intensity will not improve our ability to model population. While the assessment of BVANI shows that BVANI has an inverse relationship with pupation and the relationship between BVANI and population follows a power-law distribution. The relationship strength with population can be significantly improved by using BVANI with a correlation coefficient of 0.60. We believe that BVANI can be used as an important modeling factor for mapping fine-scale urban populations. • NTL intensity has a minimal correlation with population at pixel level. • An index called building volume adjusted nighttime light index (BVANI) was proposed. • The relationship between BVANI and population follows a power-law distribution. • BVANI reduces pixel-level population estimation biases significantly. [ABSTRACT FROM AUTHOR]

Vegetation provides many environmental benefits to the city, and daily access to vegetation contributes to the well-being and psychological status of urban residents. Understanding and measuring urban dwellers’ view-based exposure to greenery has become an important and much needed task for assessing the quality of urban life. This paper presents a new quantitative and objective indicator, the Floor Green View Index (FGVI). It is defined as the area of visible urban vegetation on a particular floor of a city building. The method for estimating FGVI consists of three steps: creating observation points and setting observation platform for each detected floor, conducting viewshed analysis and extracting visible urban green space, and computing the Floor Green View Index. The method is proposed and tested through a case study of the Lujiazui region, Shanghai, China, using airborne Light Detection and Ranging (LiDAR) data and aerial photographs. The new indicator and methods can be used as powerful quantitative tools for urban design, landscape architecture, urban green planning and management. [ABSTRACT FROM AUTHOR]

• A grid scheme with buffer was proposed to estimate solar radiance at building-scale. • A four-quadrant based segmentation method was designed to distinguish rooftop type. • Two scenarios were set up to assess rooftop's solar energy utilization potential. • A successful application in Shanghai revealed the details of solar energy potential. The assessment of potential and utilization of solar energy for each building has become an essential precondition of urban sustainable development. Currently, there are two challenges, namely high computation cost for an assessment within a large city and missing rooftop information for each building. In this study, by taking the downtown area in Shanghai as sample, a grid scheme with buffer was proposed to alleviate the computational burden and successfully estimate solar radiation with an accuracy of 0.91. Also, a quadrant-based segmentation method was developed to classify rooftop types with an overall accuracy of 83.63%, which helps better calculate solar energy utilization cost. Finally, we assumed PhotoVoltaic conversion (PV) systems or Domestic Solar Water Heater (DSWH) systems are installed on all suitable rooftops and analyzed their utilization cost, as well as economic and ecological benefits. The results show that 165,529 and 52,131 buildings are suitable for PV and DSWH systems, respectively. PV system's average payback time is about five years with reducing standard coal consumption of 1.85 × 1011kg. The DSWH system requires three more years to balance the cost and benefits. The criteria of further solar energy planning are also concluded from three perspectives: building height and density, and rooftop structure. [ABSTRACT FROM AUTHOR]

Background To evaluate the cost-effectiveness of adding 23-valent pneumococcal polysaccharide vaccine (PPSV23) to the immunization schedule for the elderly population (age > 60 years) in Shanghai, China. Methods A decision-tree model, with data and assumptions adapted from the societal perspective of Shanghai City, was developed to project the health outcomes of PPSV23 vaccination (compared with no vaccination) over a lifetime course. Sensitivity analysis was used to test the model’s robustness. The clinical data, utility and treatment costs related to pneumococcal diseases were either cited from the literature or calculated from local sources. Results The incremental cost-effectiveness ratio of PPSV23 vaccination compared with no vaccination was $16,699/quality-adjusted life years gained, which was lower than the per capita GDP of Shanghai ($16,840). Sensitivity analyses showed that the model’s outcome is robust. Conclusions Routine vaccination of the elderly population with PPSV23 is cost-effective in Shanghai, China. [ABSTRACT FROM AUTHOR]