Examining the Impact of Spatial Accessibility to Rehabilitation Facilities on the Degree of Disability: A Heterogeneity Perspective

The positive effect of healthcare facilities on residents’ health has been extensively studied. However, few studies have focused on the role of rehabilitation services as unique healthcare services for persons with disabilities. This study aimed to examine the relationship between the spatial accessibility of rehabilitation facilities and the degree of disability. To this end, an approach of measuring the spatial accessibility of rehabilitation facilities to persons with disabilities was proposed. This approach integrates multiple key elements including the characteristics of facilities (i.e., the capacity, frequency of use and service radius), characteristics of the mobility of persons with disabilities (i.e., the mode of travel, escort support, transportation fee and barrier-free environment requirements) and travel time obtained from a routing application programme interface. The accessibility of rehabilitation facilities was calculated at the neighbourhood level within the Central Urban Area of Tianjin Municipality. The ordinal logistic regression analysis revealed that higher accessibility to rehabilitation facilities generally corresponded to lower severity of disability. However, the impact varied depending on the type of disability. Increased accessibility was associated with greater severity of intellectual disability, whereas it was linked to reduced severity of visual, hearing, limb, mental and speech disabilities. It is suggested to incorporate disability diversity and the accessibility of rehabilitation facilities into spatial planning and governance

Spatial disparity and structural inequality in disability patterns across Tianjin municipality: a multiple deprivation perspective

Reducing the spatial disparities and structural inequalities faced by disabled people is a global challenge in both developed and developing countries that requires an understanding of disability-driven deprivation. This study aims to develop and validate a conceptual framework for analysing the structural inequality and spatial disparity of disability-related deprivation. To achieve this goal, an Index of Disability-Related Multiple Deprivation (IDMD) based on six specific domains, including employment, education, marital status, health, services and barrier-free environments, is proposed. The IDMD was calculated at the sub-district level within the Tianjin municipality using aggregated registration information from the Tianjin Disability Database in 2020. Principal component analysis (PCA) was used to assign the weight of each indicator of IDMD. Moran I and LISA analysis were used to quantify the spatial disparity of IDMD across the municipality. Multi-Scale Geographically Weighted Regression (MGWR) was used to model the structural factors shaping the spatial disparity of disability-related deprivation in terms of gender, age, and disability types. Three key findings have been generated as follows. The spatial variability of IDMD revealed significant urban-rural disparity across the municipality, highlighting the difficulties faced by vulnerable and disadvantaged disabled people in rural areas. Men, working age groups and those with intellectual disability contributed most to the structural inequalities of IDMD. Thirdly, the location of greatest deprivation varied for different groups; working age groups faced the highest levels of deprivation in the urban centre, males faced the most deprivation in the urban fringe and those with intellectual, limb, visual, speech or mental disabilities were most deprived in rural areas. These findings reflect the complexity of structural factors affecting disability-related deprivation at the municipality scale. This study points to the need for informed, targeted welfare facilities planning and management strategies to improve spatial equity and social justice for disabled people

Observations and geophysical value-added datasets for cold high mountain and polar regions

Peer reviewe

Accessibility of Elderly Care Facilities Based on Social Stratification: A Case Study in Tianjin, China

With the increasingly prominent phenomenon of social stratification in urban development, it is of practical significance to study the accessibility of elderly care facilities for different social groups. The study improves the mathematical model of the two-step floating catchment area method (2SFCA) as regards three aspects: the accurate demand of elderly residents, the comprehensive supply capacity of elderly care facilities, and the precision of travel costs. Taking Tianjin as an example, the study measures the accessibility of elderly care facilities from the perspective of social stratification. The results show that: (1) The improved model is more practical in evaluating the accessibility of elderly care facilities. (2) The spatial distribution of social groups in Tianjin presents a concentric structure and the social stratification in the periphery area is more obvious. (3) The accessibility scores of elderly care facilities are higher in the city center, lower in the periphery area, higher in the south, and lower in the north. (4) High- and middle-income groups have better accessibility, while the elite and low-income groups have worse accessibility

Effect of vegetation index choice on soil moisture retrievals via the synergistic use of synthetic aperture radar and optical remote sensing

The recent launch of the Sentinel-1 A and Sentinel-1B synthetic aperture radar (SAR) satellite constellation has provided high-quality SAR data with fine spatial and temporal sampling characterizations (6˜12 revisit days at 10 m spatial resolution). When combined with high-resolution optical remote sensing, this data can potentially be used for high-resolution soil moisture retrieval over vegetated areas. However, the suitability of different vegetation index (VI) types for the parameterization of vegetation water content in SAR vegetation scattering models requires further investigation. In this study, the widely-used physical-based Advanced Integral Equation Model (AIEM) is coupled with the Water Cloud Model (WCM) for the retrieval of field-scale soil moisture. Three different VIs (NDVI, EVI, and LAI) produced by two different satellite sensors (Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat) are selected to examine their impact on the parameterization of vegetation water content, and subsequently, on soil moisture retrieval accuracy. Results indicate that, despite the different sensitivity of estimated surface roughness parameters to various VIs (i.e., this sensitivity is highest when utilizing MODIS EVI and lowest in the LAI-based model), the optimum roughness parameters derived from each VI exhibit no discernible difference. Consequently, the soil moisture retrieval accuracies show no noticeable sensitivity to the choice of a particular VI. Generally, meadow and grassland sites with small differences in VI-derived roughness parameters exhibit good performance in soil moisture estimation. With respect to the relative components in the coupled model, the vegetative contribution to the scattering signal exceeds that of soil at VI about 0.6∼0.8 [-] in NDVI-based models and 0.4∼0.6 [-] in EVI-based models. This study provides insight into the proper selection of vegetation indices during the use of SAR and optical imagery for the retrieval of high-resolution surface soil moisture.475711National Natural Science Foundation of China 5Natural Science Foundation of Guangdong Province, 557 ChinaFundamental Research Funds for 558 the Central Universitie

Application of Geodesign Techniques for Ecological Engineered Landscaping of Urban River Wetlands: A Case Study of Yuhangtang River

Although geodesign techniques have been studied and developed worldwide, there is still a lack of in-depth application of geodesign workflows for redesigning urban river wetlands with characteristics of ecologically engineered landscaping (EEL). The study mainly aims at putting forward a proper approach in the methodological foundation for EEL practices in river wetlands. A typical EEL-oriented project of river restoration in Hangzhou, China, was conducted in this study. Based on in-situ geodata and tools within QGIS, individual geological factors analysis, with the hierarchical analysis method (AHP) and ecological vulnerability evaluation (EVE), was conducted by experts’ voting and the weighted linear combination (WLC) method. Analysis of hydrological-related factors proceeded. This GIS-based analysis with expert knowledge provided comprehensive redesign solutions for the redesign project, i.e., restoration of the riverbed, spatial restoration in the horizontal and vertical dimensions, and integration with the multifunctional design. Detailed three-dimensional models for design practices were developed to present redesigned topology and space accordingly. Terrain, inundation, and visibility analysis proceeded with parametric mapping programs within Grasshopper to check the feasibility. The adapted geodesign-based workflow in the study also applies to the site analysis, sustainable assessment and landscape planning for urban wetlands EEL projects

Application of Geodesign Techniques for Ecological Engineered Landscaping of Urban River Wetlands: A Case Study of Yuhangtang River

Although geodesign techniques have been studied and developed worldwide, there is still a lack of in-depth application of geodesign workflows for redesigning urban river wetlands with characteristics of ecologically engineered landscaping (EEL). The study mainly aims at putting forward a proper approach in the methodological foundation for EEL practices in river wetlands. A typical EEL-oriented project of river restoration in Hangzhou, China, was conducted in this study. Based on in-situ geodata and tools within QGIS, individual geological factors analysis, with the hierarchical analysis method (AHP) and ecological vulnerability evaluation (EVE), was conducted by experts’ voting and the weighted linear combination (WLC) method. Analysis of hydrological-related factors proceeded. This GIS-based analysis with expert knowledge provided comprehensive redesign solutions for the redesign project, i.e., restoration of the riverbed, spatial restoration in the horizontal and vertical dimensions, and integration with the multifunctional design. Detailed three-dimensional models for design practices were developed to present redesigned topology and space accordingly. Terrain, inundation, and visibility analysis proceeded with parametric mapping programs within Grasshopper to check the feasibility. The adapted geodesign-based workflow in the study also applies to the site analysis, sustainable assessment and landscape planning for urban wetlands EEL projects

Template-Mediated Synthesis of Hierarchically Porous Metal–Organic Frameworks for Efficient CO2/N2 Separation

Carbon dioxide (CO2) is generally unavoidable during the production of fuel gases such as hydrogen (H2) from steam reformation and syngas composed of carbon monoxide (CO) and hydrogen (H2). Efficient separation of CO2 from these gases is highly important to improve the energetic utilization efficiency and prevent poisoning during specific applications. Metal–organic frameworks (MOFs), featuring ordered porous frameworks, high surface areas and tunable pore structures, are emerging porous materials utilized as solid adsorbents for efficient CO2 capture and separation. Furthermore, the construction of hierarchical MOFs with micropores and mesopores could further promote the dynamic separation processes, accelerating the diffusion of gas flow and exposing more adsorptive pore surface. Herein, we report a simple, efficient, one-pot template-mediated strategy to fabricate a hierarchically porous CuBTC (CuBTC-Water, BTC = 1,3,5-benzenetricarboxylate) for CO2 separation, which demonstrates abundant mesopores and the superb dynamic separation ability of CO2/N2. Therefore, CuBTC-Water demonstrated a CO2 uptake of 180.529 cm3 g−1 at 273 K and 1 bar, and 94.147 cm3 g−1 at 298 K and 1 bar, with selectivity for CO2/N2 mixtures as high as 56.547 at 273 K, much higher than microporous CuBTC. This work opens up a novel avenue to facilely fabricate hierarchically porous MOFs through one-pot synthesis for efficient dynamic CO2 separation

Encapsulating Trogtalite CoSe2 Nanobuds into BCN Nanotubes as High Storage Capacity Sodium Ion Battery Anodes

Trogtalite CoSe2 nanobuds encapsulated into boron and nitrogen codoped graphene (BCN) nanotubes (CoSe2@BCN-750) are synthesized via a concurrent thermal decomposition and selenization processes. The CoSe2@BCN-750 nanotubes deliver an excellent storage capacity of 580 mA h g−1 at current density of 100 mA g-1 at 100th cycle, as the anode of a sodium ion battery. The CoSe2@BCN-750 nanotubes exhibit a significant rate capability (100-2000 mA g-1 current density) and high stability (almost 98% storage retention after 4000 cycles at large current density of 8000 mA g-1). The reasons for these excellent storage properties are illuminated by theoretical calculations of the relevant models, and various possible Na+ ion storage sites are identified through first-principles calculations. These results demonstrate that the insertion of heteroatoms, B-C, N-C as well as CoSe2, into BCN tubes, enables the observed excellent adsorption energy of Na+ ions in high energy storage devices, which supports the experimental results

Microwave-based vegetation descriptors in the parameterization of water cloud model at L-band for soil moisture retrieval over croplands

Synthetic aperture radar (SAR) data have significant potential for soil moisture monitoring because of their high spatial resolution and independence from cloud coverage. However, it is challenging to retrieve soil moisture from SAR data over vegetated areas, as vegetation significantly affects backscattered radar signals. Auxiliary vegetation information obtained from optical images, such as the normalized difference vegetation index (NDVI) and the leaf area index (LAI), is commonly used to correct vegetation effects. However, it is generally difficult to obtain SAR and optical data in the same area simultaneously, because of the discrepancies in satellite coverage and the effects of cloud coverage. This study focuses on whether vegetation descriptors obtained directly from radar data at L-band can adequately parameterize the semi-empirical backscattering water cloud model (WCM) to support soil moisture retrieval. Four vegetation descriptors (three based on radar images and one based on optical images), were chosen to assess the parameterization and calibration of the WCM and the retrieval accuracy of soil moisture. The results showed that the vegetation descriptor of backscattering at VH polarization outperformed the other three vegetation descriptors (NDVI-derived vegetation water content, radar vegetation index, and the ratio of cross-polarization to VV polarization) in the investigation of four crop types (canola, corn, bean, and wheat) based on the Soil Moisture Active Passive Validation Experiment in 2012 (SMAPVEX12) in Canada. For the vegetation descriptor of VH, the overall accuracy of retrieved soil moisture was promising by separating into two growth stages, with unbiased root mean squared errors of 0.056, 0.053, 0.098, and 0.079 cm3/cm3 for canola, corn, bean, and wheat, respectively. The results also confirmed that variations in vegetation growth affect the accuracy of soil moisture retrieval. In addition, the retrieval performance was undermined when the vegetation changed dramatically, leading to variations or uncertainty in the vegetation structure. This study provides new insights into soil moisture retrieval methods with active L-band microwave observations