The overlay of climate change and urbanization leads cities to become the centers where greenhouse gas (GHG) reduction actions and key risks of climate change simultaneously occur. How to cope with climate change has been a huge challenge facing global cities. Conducting the study on coping with climate change based on urban spatial forms has increasingly become the frontier and hot topic of urban environment and climate change research. By analyzing and summarizing current literatures, this article reviews the core aspects and progress of study on urban spatial forms to cope with climate change, including key impacts of climate change and their assessment methods, relationships between urban forms and climate change including greenhouse gas emissions and key risks of climate change, coping strategies, and urban planning practices. Based on this, key issues for future research are put forward.
Extreme heat events (EHEs) are a major cause of weather-related deaths. People who live in cities may be more vulnerable to EHE because the urban heat island (UHI) effect causes a slower cooling process at night, and thus provides little relief from the heat stresses of the day. Although UHI is a well-documented phenomenon, relatively little information in the literature is available about its characteristics during EHEs. Moreover, urban warming in addition to greenhouse gas-induced warming has not been taken into account explicitly in climate change simulations to date. Under the background of global climate change and rapid urbanization in China, the magnitude of future warming and the health risk of EHEs may be significantly underestimated in urban areas. With the forecast of global warming continuing into the foreseeable future, extreme heat events will become more intense, more frequent, and longer lasting with climate change. The impacts of urbanization on extreme heat events have attracted an increasing attention in recent years. The potential exposure of urban populations to climate change will be enhanced by local factors with the development of urbanization. This review systematically collates research results in three main areas: observational evidence of trends in EHEs in relation to urbanization, numerical simulation experiments of the impact of urbanization on temperature and heat stress during EHEs, and epidemiological study of excess mortality associated with urbanization during EHEs. Most observational and simulation studies show that urban heat island results in an increase in the extent and intensity of extreme heat in cities. Inhabitants of urban areas may experience increasing heat-related health risk. Heat island also significantly contributes to the long-term increasing trends in urban EHEs. The epidemiological studies reveal that heat island caused by urbanization has great impacts on excess mortality in cities during EHEs. Finally, future avenues of research are speculated, including: synergistic effect of extreme heat with other environmental factors, heat-health warning systems, mapping extreme heat health risk, and future projection of EHEs due to climate change and urban growth.
This article evaluates the precision of the temperature simulated by nine IPCC AR5 (the Fifth Assessment Report of the Intergovernmental Panel on Climate Change) GCMs (Global Climate Models) and the multi-model ensemble (MME), based on the observed temperature of 660 stations in China from 1996 to 2005. The results show that the correlation coefficients between the average daily temperature simulated by GCMs and station observations in China during 1996-2005 were very high, all above 0.86. The precision of the simulated average daily temperature in the southeast by the 10 models was higher than that in the west, judged by the lower Biases, mean relative errors (MREs), mean absolute errors (MAEs), and root mean square errors (RMSEs) in the southeast as compared to those in the west. The precision of the simulated temperature by IPSL-CM5A-LR, MRI-CGCM3, and NorESM1-M was poorer than that of the others—specially, the Biases, MREs, and RMSEs of the simulation result by IPSL-CM5A-LR , the Biases and RMSEs of the simulation result by MRI-CGCM3, and MREs and RMSEs of the simulation result by NorESM1-M, were larger. Taken into account the Biases, MREs, MAEs, and RMSEs, the simulation precision of MME was the highest.
Lake ice is a sensitive proxy to climate variability as has been shown through observations and modeling. In this study, we used in-situ and satellite data to analyze lake ice change at the Nam Co Lake in Tibet in 2000-2013. The results from Moderate Resolution Imaging Spectrometer (MODIS) data showed that lake ice phenology changed significantly at the Nam Co Lake in the studied time period. The postponing freeze onset (FO) and advancing water clear of ice (WCI) dates were both obvious, resulting in the dramatic reduction of ice existence period (IEP) (2.8 days/year). Melt duration (MD), which stands for lake ice melting speed, was the most sensitive indicator of Nam Co Lake ice durations and MD was shortened by 3.1 days/year through the study period. Lake ice change at the Nam Co Lake was affected by regional climate variations, including air temperature and wind speed changes. In this study, daily air temperature from two automatic weather stations on the lakeshore showed highly consistent trend with lake ice phenology—both freeze onset (FO) and melt onset (MO) synchronized with air temperature variation. High wind speed in winter accelerates freezing. Lake ice tensile force rather than wind force can force the ice into pieces during the formation period. Lake ice phenology acts as a sensitive proxy of regional climate and can serve as an indicator of regional climate change. Further study on lake ice in the Tibetan Plateau is significant because of its sensitive response to climate change.
Using spatial analysis methods, the geographic pattern of pickpocket incidents along the Chang'an Street in Beijing was examined in this study. First, the crime distribution along the street was identified. The results demonstrate that major crime clustering areas existed in the Xidan business area (A), Jianguomen area (B), and Dawanglu-Sihui Area (C). By comparing the spatial pattern of crimes with population density and point of interest (POI) density along the street, it was found that crimes tended to be clustered around locations having higher POI density. In the next step, spatiotemporal patterns of offences in the three areas were analyzed using kernel density estimation and space-time hotspot matrix. The results indicate that zone A maintained higher crime level between 10 a.m. and 6 p.m. and the peak time appeared at 12 a.m., and the offences concentrated in the major shopping malls. However, in zones B and C, the higher level of crimes occurred in the hours around 6 a.m. and 6 p.m., which are the periods of peak traffic flow in the morning and evening. Lastly, some detailed crime prevention and suppression suggestions and strategies are proposed on the basis of the spatial attributes and blind areas theory.
Urban spatial analysis should be based on reliable measurements, and the most basic measurement of a city is its size. Defining urban boundaries objectively is fundamental for determining effective city size. In recent years, a number of Chinese and international scholars have developed improved methods of urban boundary identification. Among these, the majority apply vector data that can reflect the spatial organization relationships of entities internal of cities. However, access to these vector data is often limited. In this study, based on existing research a new method of urban boundary identification with remote sensing data as input and using neighborhood dilation and quantification is put forward. Our method takes a spatial neighboring merging approach. By changing the neighboring range of pixels, different numbers of spatial clusters are obtained. An optimal radius can be determined according to the scaling relationships between the neighboring range of pixels and the numbers of spatial clusters. GIS technology is then adopted to define urban boundaries. By applying this method to analyze remote sensing images of the Beijing area, we found the effective range of pixels. Remote sensing data used by this method are characterized by real-time acquisition and easy access. Also, the calculation procedure is straightforward. Thus, in future efforts of urban boundary identification, our new method may provide a complement to existing methods.
Existing research on evaluating the level of integrated rural-urban development by quantitative assessment methods often fails to separate the overall development index and coordinated development index and demonstrate cross-sectional and time series data simultaneously, and results in the "black box" effect by data aggregation. This article proposes a three dimensional coordinate system, including overall development index, coordinated development index, and temporal dimension and then converts the three dimensional coordinate system into a two dimensional coordinate system with the "nine squares" method, thereby making it possible to quantitatively evaluate the characteristics of change of each city within a city group. The level of balance and integration of development between urban and rural areas is divided into economic, industrial, infrastructural, and public services. An assessment on the characteristics of change of 19 cities in the Sichuan and Chongqing region during 2006-2011 was carried out. The research result shows that cities in the region achieved remarkable results in reducing the gap in economy and public services fields between urban and rural areas, but large gaps in the fields of industry and infrastructure still exist. The progress in Chongqing Municipality and the city of Chengdu is much greater than in other cities in the region. This research can provide theoretical guidance and methodological tools for improving rural-urban development in the Sichuan and Chongqing region, and can be useful for the evaluation of integrated rural-urban development in other cities of China.
This article takes the general principles and application values of the discrete choice model system as a departure point and summarizes the classical model forms with respect to their basic theories and typical applications. Important latest developments are also introduced. Multinomial logit (MNL) model is the basis of the discrete choice model system, with the advantages of simplicity, reliability, and easy implementation. However, it also has some inherent theoretic defects, which led to the need for more refined models. Nested logit model is usually used to deal with problems of correlation among alternatives, no-choice alternative, and data enrichment. Its more general form is the generalized extreme value (GEV) model system; mixed logit model is suitable for handling random preference and some kinds of correlation problems, such as correlation among alternatives, panel data, random coefficients, and data for enrichment. A similar model form named latent class model is also widely used. Multinomial probit (MNP) model is highly flexible. However, its application is limited due to the complexity of model specification and very high computation demands. With regard to the new development of discrete choice model system, four important areas are introduced. These include complex new models derived from the combination of classical models; models suitable for dealing with revealed preference/stated preference (RP/SP), ordered, ranked, and multiple choice data; models based on bounded rationality choice which is more close to reality; and models considering the spatiotemporal background of choice.
Extraction of active fault location and active fault surface deformation features is essential for the study of active fault systems, and a large number of studies have been carried out on fault extraction based on Digital Elevation Model (DEM). This article summarizes the active fault extraction methods using DEM of lower than 30 m resolution and very-high resolution DEM, such as Light Detection and Ranging (LiDAR) DEM and Structure from Motion (SfM) DEM. The fault extraction methods can be divided mainly into three categories: geomorphic feature interpretation, image interpretation and multiple interpretation. Geomorphic feature interpretation is based on GIS spatial analyses. Image interpretation identifies faults by examining linear variation of surface deformation through image processing algorithms. Multiple interpretation combines the above two methods with remote sensing image processing. Meanwhile, this article reviews the most recent progress in the extraction of surface deformation features using DEM, and enumerates the extraction of fault scarp and deformed drainage characteristics. With the progress in high-resolution DEM, DEM and its spatial analysis techniques have become a conventional geoscience research method. The integration of this method with field research, remote sensing, and dating techniques can provide a strong technical support to quantitative study in fault research.
Plant phenology is one of the most salient and sensitive indicators of terrestrial ecosystem's response to climate change. Understanding its spatiotemporal change is significantly important for understanding both land surface processes and carbon cycle and predicting changes in the terrestrial ecosystem. MODIS MOD09A1, with the spatial resolution of 500 m × 500 m and at an 8-day temporal interval, was used in this study to investigate the change in forest phenology in the Qinling zone of central China in 2001?2010. First, we used the day of year (DOY) of MOD09A1 to improve the temporal precision of EVI; we then combined the maximum ratio and the threshold method for phenology data extraction [start of growth season (SOG), end of growth season (EOG), and length of growth season (LOG)] in the Qinling zone. Results of this study show that: Accompanying the deterioration in heat and water conditions from low altitude to high altitude and southeast to northwest, SOG delayed, EOG advanced, and LOG shortened gradually. SOG and EOG mainly occurred on the 81th?120th and 270th?311th days respectively. LOG was mainly between 150 and 230 days. The phenology of forest in Qinling zone is closely related to altitude, with every 100 m rising in altitude, SOG, EOG, and LOG gradualy delayed 2 days, advanced 1.9 days, and shortened 3.9 days, respectively. From 2001 to 2010, early SOG, late EOG, and extended LOG mainly occurred in medium altitude. SOG, EOG, and LOG gradually delayed, advanced, and shortened respectively in some areas that are lowered than 1,000 m above sea level. Interannual changes at high altitude were more complicated than that at low altitude, and SOG advanced, EOG advanced, and LOG shortened above 2000 m. The reasons for these changes remain unclear. The findings quantified the differences of forest phenology with the change in elevation and revealed the spatiotemporal variations in forest phenology from 2001 to 2010. This article provides a reference for the evaluation and protection of ecological environment in the Qinling zone. In future study, reasons for the above mentioned differences in forest phenology need to be explored.
This study analyzed the time series curves of enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), and land surface water index (LSWI) of paddy rice areas in Hunan Province based on MODIS data. Single and double-season paddy rice was distinguished with the classification and regression tree (CART) decision tree method. The inflection method and the dynamic threshold method were applied to retrieve the growth periods of double-season paddy rice. The result shows that double-season paddy rice of Hunan Province was mainly distributed in the Dongting Lake area, the plain area surrounding the main stream and tributaries of the section between Hengyang and Zhuzhou of the Xiangjiang River, and the panhandle between the Yangming Mountains and the Nanling Mountains in Yongzhou and Chenzhou. Single-season paddy rice was mainly distributed on the periphery of the zones planted with double-season paddy rice and the valleys in Xiangxi and Huaihua. The growth periods of double-season paddy rice planted in the southern part of the Dongting Lake area and the hilly areas in southern Hunan are earlier than other regions. The distribution of single/double-season paddy rice and their growth periods in the most part of Hunan Province were spatially un-contiguous and this pattern is relatively consistent across space. These findings can provide support for future study of the relationship between natural disasters that affect paddy rice and the risk of climate change in Hunan Province.
：Land use form of rural settlements transformed profoundly in the process of rapid industrialization and urbanization in China. By selecting seven rural settlements of different geomorphic types in the Aluke'rqin Banner located in the farming-pastoral transitional zone in Inner Mongolia and examining land use change through a survey, we discuss the relationship between morphological features of the rural settlements and farmers’ livelihood. Participatory rural appraisal method and geographic information system and remote sensing techniques were employed in the survey and analysis. The results show that: (1) Morphological features of rural settlements were closely related to livelihood of rural households, especially with regard to the quantity and quality of cultivated land and grassland and livelihood activities. Along with the increase of population, conversion of grassland to cultivated land, and diversification of rural household livelihood activities, rural pastoral settlements transformed into agro-pastoral settlements. (2) Land use types of agro-pastoral settlements were gradually diversified through time. Before the Reform and Opening-up of China in 1978, agricultural production was the dominant livelihood activity of rural households. Homestead was the primary land use type of rural settlements. After the Reform and Opening-up, however, livelihood activities of rural households gradually diversified and became increasingly non-agricultural. Commercial land, industrial warehousing land, and land for public service provision expanded rapidly in the rural settlements. (3) Homestead takes a significant share in agro-pastoral settlements. Cropping and animal husbandry are important productive activities for rural households. Corresponding to the livelihood demands of rural households,within the settlements homesteads are divided into production and ancillary production lands including colony house, vegetable garden, and warehouse in rural households. Both per capital construction land and homestead area in the case study settlements are larger than the national standard, which indicates an adaptive land use in response to the livelihood demands of the agro-pastoral resettlements. Therefore, the authors recommend that the governments should take concrete measures in the process of rural residential land consolidation that take into consideration the livelihood demands of rural households in this particular area.
Siberia is an important sensitive area with regard to global environmental change. Due to the limited availability of high resolution remote sensing data, previously there was a general lack of in-depth understanding of land cover and change in Siberia. Based on the land cover classification of China's 30 m global land cover (GLC) data product (GlobeLand30) in 2000 and 2010, this study analyzed the progress of land cover change in Siberia between 2000 and 2010 using spatial statistical method and land cover type transition matrix. Land cover changes in Siberia showed significant spatial and temporal variations between 2000 and 2010. Overall, the area that experienced most clear land cover change was west Siberia. The area of forests and grasslands decreased substantially and the change mainly took place in the traditional forest industry regions. The total area of wetland significantly increased and this change occurred mainly in the River Ob and Yenisei in west Siberia. Cultivated land decreased slightly mainly in the traditional agricultural region of the southwest. Built-up areas expanded rapidly, which mainly distributed in cities along the Trans-Siberian Railway. Land cover change in Siberia showed distinct temporal and spatial disparities primarily due to two reasons: industrial development and climate warming..
