City-level comparison of urban land-cover configurations from 2000-2015 across 65 countries within the global Belt and Road

The configuration of urban land-covers is essential for improving dwellers' environments and ecosystem services. A city-level comparison of land-cover changes along the Belt and Road is still unavailable due to the lack of intra-urban land products. A synergistic classification methodology of sub-pixel un-mixing, multiple indices, decision tree classifier, unsupervised (SMDU) classification was established in the study to examine urban land covers across 65 capital cities along the Belt and Road during 2000-2015. The overall accuracies of the 15 m resolution urban products (i.e., the impervious surface area, vegetation, bare soil, and water bodies) derived from Landsat Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) images were 92.88% and 93.19%, with kappa coefficients of 0.84 and 0.85 in 2000 and 2015, respectively. The built-up areas of 65 capital cities increased from 23,696.25 km(2) to 29,257.51 km(2), with an average growth rate of 370.75 km(2)/y during 2000-2015. Moreover, urban impervious surface area (ISA) expanded with an average rate of 401.92 km(2)/y, while the total area of urban green space (UGS) decreased with an average rate of 17.59 km(2)/y. In different regions, UGS changes declined by 7.37% in humid cities but increased by 14.61% in arid cities. According to the landscape ecology indicators, urban land-cover configurations became more integrated (oShannon's Diversity Index (SHDI) = -0.063; oPatch Density (PD) = 0.054) and presented better connectivity (oConnectance Index (CON) = +0.594). The proposed method in this study improved the separation between ISA and bare soil in mixed pixels, and the 15 m intra-urban land-cover product provided essential details of complex urban landscapes and urban ecological needs compared with contemporary global products. These findings provide valuable information for urban planners dealing with human comfort and ecosystem service needs in urban areas

Robust drivers of urban land surface temperature dynamics across diverse landscape characters: An augmented systematic literature review

To effectively develop strategies that address the escalating surface temperatures of cities in diverse landscape characters, various and sometimes contradicting drivers are presented in the literature. A synthesis of findings and observations in this aspect is lacking. Therefore, the main tenet of our study was to identify robust landscape metrics (LMs) that drive the dynamics of urban land surface temperature (ULST) and analyse the extent to which landscape character influences their impact. We adopted a systematic literature review protocol, augmented with different geospatial datasets (at a global scale) and applied mixed approaches for our review and analyses. A total of 101 relevant articles were identified, although skewed towards Asia; various methods were utilised in analysing the LMs – ULST relationship; about 432 unique LMs were revealed with only 11 % of these confirmed to be robust. Landscape character elements are found to exert a slight to moderate significant influence on the LMs − ULST relationship reported in the literature. This further strengthened our proposition of the need to consider landscape character elements in understanding the dynamics of ULST in different environments. To this end, we developed an interactive scheme to synthesize our findings which reveal robust LMs in diverse landscape characters. Our FAIRly-open study serves as a call to the scientific community and urban stakeholders to engage and interact with our findings as this may help rethink (current) ULST mitigation strategies. Also, combining our scheme with expert and local spatial knowledge of stakeholders can offer a practical foundation for addressing ULSTs across diverse landscapes

中国における都市化総合評価及び環境への影響に関する研究

In Chapter one, research background and significance is investigated. In addition, previous studies and current situation in the research fields was reviewed and discussed. In Chapter two, an in-depth review of prior studies associated with the research topic was conducted. The literature review was carried out from three aspects: urbanization and eco-environment evalution and coordination, urban sprawl assessment and urban heat island investigation. In Chapter three, maximum entropy method was applied to help generate the evaluation system of eco-environment level and urbanization level at provincial scale. Comparison analysis and coordinate analysis was carried through to assess the development of urbanization and eco-environment as well as the balance and health degree of the city develops. In Chapter four, DMSP/OLS stable nighttime light dataset was used to measure and assess the urban dynamics from the extraction of built up area. Urban sprawl was evaluated by analyzing the landscape metrics which provided general understanding of the urban sprawl and distribution pattern characteristics could be got from the evaluation. In Chapter five, the investigation of surface urban heat island effects in Beijing city which derive from land surface temperature retrieval from remote sensing data of Landsat TM was carried out. In addition, spatial correlation and relationship between the urbanization level, vegetation coverage and surface urban heat island was carried out in this chapter. In Chapter six, all the works have been summarized and a conclusion of whole thesis is deduced.北九州市立大

Northern Eurasia Future Initiative (NEFI): facing the challenges and pathways of global change in the twenty-first century

During the past several decades, the Earth system has changed significantly, especially across Northern Eurasia. Changes in the socio-economic conditions of the larger countries in the region have also resulted in a variety of regional environmental changes that can have global consequences. The Northern Eurasia Future Initiative (NEFI) has been designed as an essential continuation of the Northern Eurasia Earth Science Partnership Initiative (NEESPI), which was launched in 2004. NEESPI sought to elucidate all aspects of ongoing environmental change, to inform societies and, thus, to better prepare societies for future developments. A key principle of NEFI is that these developments must now be secured through science-based strategies co-designed with regional decision-makers to lead their societies to prosperity in the face of environmental and institutional challenges. NEESPI scientific research, data, and models have created a solid knowledge base to support the NEFI program. This paper presents the NEFI research vision consensus based on that knowledge. It provides the reader with samples of recent accomplishments in regional studies and formulates new NEFI science questions. To address these questions, nine research foci are identified and their selections are briefly justified. These foci include warming of the Arctic; changing frequency, pattern, and intensity of extreme and inclement environmental conditions; retreat of the cryosphere; changes in terrestrial water cycles; changes in the biosphere; pressures on land use; changes in infrastructure; societal actions in response to environmental change; and quantification of Northern Eurasia’s role in the global Earth system. Powerful feedbacks between the Earth and human systems in Northern Eurasia (e.g., mega-fires, droughts, depletion of the cryosphere essential for water supply, retreat of sea ice) result from past and current human activities (e.g., large-scale water withdrawals, land use, and governance change) and potentially restrict or provide new opportunities for future human activities. Therefore, we propose that integrated assessment models are needed as the final stage of global change assessment. The overarching goal of this NEFI modeling effort will enable evaluation of economic decisions in response to changing environmental conditions and justification of mitigation and adaptation efforts

Spatiotemporal heterogeneity analysis of Yangtze River delta urban agglomeration: evidence from nighttime light data (2001-2019)

The long-term changes of the relationship between nighttime light and urbanization related built-up areas are explored using nighttime light data obtained from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS, data before 2013) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP/VIIRS, data after 2012) and information of the spatiotemporal heterogeneity of urban evolution. This study assimilates two datasets and diagnoses the spatial heterogeneity in administrative city scale based on built-up area tendencies, temporal heterogeneity in pixel scale based on nighttime light intensity tendencies, and GDP associated spatiotemporal variability over the Yangtze River Delta comparing the first two decades of this century (2001-2010 versus 2011-2019). The analysis reveals the following main results: (1) The built-up areas have generally increased in the second period with the center of fast expansion moving southward, including Suzhou-Wuxi-Changzhou, Hangzhou, Ningbo, Nanjing, and Hefei. (2) Urban development in the original city core has saturated and is spilling over to the suburbs and countryside, leading to nighttime light intensity tendency shift from a "rapid to moderate" and a "moderate to rapid" development (a "hot to cold" and a "cold to hot" spatial clustering distribution). (3) The tendency shifts of built-up area and nighttime light intensity occur most frequently in 2010, after which the urban development is transforming from light intensity growth to built-up area growth, particularly in the developed city cores. The urban agglomeration process with nighttime light intensity reaching saturation prior to the urban development spreading into the surrounding suburbs and countryside, appears to be a suitable model, which provides insights in addressing related environmental problems and contribute to regional sustainable urban planning and management

The Integrated WRF/Urban Modeling System: Development, Evaluation, and Applications to Urban Environmental Problems

To bridge the gaps between traditional mesoscale modeling and microscale modeling, the National Center for Atmospheric Research (NCAR), in collaboration with other agencies and research groups, has developed an integrated urban modeling system coupled to the Weather Research and Forecasting (WRF) model as a community tool to address urban environmental issues. The core of this WRF/urban modeling system consists of: 1) three methods with different degrees of freedom to parameterize urban surface processes, ranging from a simple bulk parameterization to a sophisticated multi-layer urban canopy model with an indoor outdoor exchange sub-model that directly interacts with the atmospheric boundary layer, 2) coupling to fine-scale Computational Fluid Dynamic (CFD) Reynolds-averaged Navier–Stokes (RANS) and Large-Eddy Simulation (LES) models for Transport and Dispersion (T&D) applications, 3) procedures to incorporate high-resolution urban land-use, building morphology, and anthropogenic heating data using the National Urban Database and Access Portal Tool (NUDAPT), and 4) an urbanized high-resolution land-data assimilation system (u-HRLDAS). This paper provides an overview of this modeling system; addresses the daunting challenges of initializing the coupled WRF/urban model and of specifying the potentially vast number of parameters required to execute the WRF/urban model; explores the model sensitivity to these urban parameters; and evaluates the ability of WRF/urban to capture urban heat islands, complex boundary layer structures aloft, and urban plume T&D for several major metropolitan regions. Recent applications of this modeling system illustrate its promising utility, as a regional climate-modeling tool, to investigate impacts of future urbanization on regional meteorological conditions and on air quality under future climate change scenarios

Impacts of different urban canopy schemes in WRF/Chem on regional climate and air quality in Yangtze River Delta, China

AbstractYangtze River Delta (YRD) region has experienced a remarkable urbanization during the past 30years, and regional climate change and air pollution are becoming more and more evident due to urbanization. Impacts of urban canopy on regional climate and air quality in dry- and wet-season are investigated in this paper, utilizing the Weather Research and Forecasting/Chemistry (WRF/Chem) model. Four regimes of urban canopy schemes with updated USGS land-use data in actual state of 2004 base on MODIS observations are examined: (1) SLAB scheme that does not consider urban canopy parameters (the control experiment in this paper); (2) a single-layer urban model with a fixed diurnal profile for anthropogenic heat (UCM); (3) multilayer urban canopy model (BEP-Building effect parameterization); (4) multilayer urban models with a building energy model including anthropogenic heat due to air conditioning (BEP+BEM). Results show that, compared with observations, the best 2-m temperature estimates with minimum bias are obtained with SLAB and BEP+BEM schemes, while the best 10-m wind speed predictions are obtained with BEP and BEP+BEM scheme. For PM10 and ozone predictions, BEP+BEM scheme predicted PM10 well during January, while the best estimate of PM10 is obtained with UCM scheme during July, BEP+BEM and SLAB schemes best estimated ozone concentrations for both the two months. Spatial differences of meteorological factors between canopy schemes and control scheme show that compared with SLAB scheme, BEP and BEP+BEM schemes cause an increase of temperature with differences of 0.5°C and 0.3°C, respectively, UCM scheme simulates lower temperature with decrease of 0.7°C during January. In July, all the canopy experiments calculates lower air temperature with reduction of 0.5°C–1.6°C. All the canopy experiments compute lower 10-m wind speed for both January and July. Decreases were 0.7m/s (0.8m/s) with UCM, 1.7m/s (2.6m/s) with BEP, and 1.8m/s (2.3m/s) with BEP+BEM schemes in January (July), respectively. For chemical field distributions, results show that, compared with SLAB scheme, UCM scheme calculates higher PM10 concentration in both January and July, with the differences of 22.3% (or 24.4μg/m3) in January, and 31.4% (or 17.4μg/m3) in July, respectively. As large as 32.7% (or 18.3 μg/m3) of PM10 increase is found over Hangzhou city during July. While 18.6% (or 22.1 μg/m3) and 16.7% (or 24.6 μg/m3) of PM10 decreases are fund in BEP and BEP+BEM schemes during January. Compared with control experiment during January, 6.5% (or 2.6ppb) to 10.4% (4.2ppb) increases of ozone are computed over mage-cities by canopy experiments. All the three canopy schemes predict lower ozone concentrations and as large as 30.2% (or 11.2ppb) decrease is obtained with UCM scheme, and 16.5% (6.2ppb) decrease with BEP scheme during July. The SLAB scheme is suitable for real-time weather forecast while multiple urban canopy scheme is necessary when quantify the urbanization impacts on regional climate

Recent trends in vegetation greenness in China significantly altered annual evapotranspiration and water yield

There has been growing evidence that vegetation greenness has been increasing in many parts of the northern middle and high latitudes including China during the last three to four decades. However, the effects of increasing vegetation greenness particularly afforestation on the hydrological cycle have been controversial. We used a process-based ecosystem model and a satellite-derived leaf area index (LAI) dataset to examine how the changes in vegetation greenness affected annual evapotranspiration (ET) and water yield for China over the period from 2000 to 2014. Significant trends in vegetation greenness were observed in 26.1% of China\u27s land area. We used two model simulations driven with original and detrended LAI, respectively, to assess the effects of vegetation \u27greening\u27 and \u27browning\u27 on terrestrial ET and water yield. On a per-pixel basis, vegetation greening increased annual ET and decreased water yield, while vegetation browning reduced ET and increased water yield. At the large river basin and national scales, the greening trends also had positive effects on annual ET and had negative effects on water yield. Our results showed that the effects of the changes in vegetation greenness on the hydrological cycle varied with spatial scale. Afforestation efforts perhaps should focus on southern China with larger water supply given the water crisis in northern China and the negative effects of vegetation greening on water yield. Future studies on the effects of the greenness changes on the hydrological cycle are needed to account for the feedbacks to the climate