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Green residential buildings (GRBs) are an important part of the concept of green building. Although green buildings are well studied for geographic distribution and influencing factors, GRBs have not been fully explored or widely noted by parties involved in the building sectors. In this paper, we study the geographic distribution and influencing factors of 2134 GRBs that met the Green Building Evaluation Standard and obtained a green building logo in 2008–2016 in China. First, we analyze the geographic distribution and spatial correlation of GRBs with different star ratings at the provincial and municipal levels by natural break-point method and Moran’s index. Second, we study the aggregation degree of medium- and high-star GRBs in each province by development concentration index and define 42 leading cities with more favorable levels of GRB development. Third, we analyze the correlation between the GRBs’ number and 18 influencing factors covering the social economy and real estate market in the 42 leading cities. According to the analysis, this paper shows that (1) there are differences in the geographical distribution characteristics of different star green buildings in China. (2) The differences in geographical distribution and the spatial correlation of GRBs are more obvious in the study of municipal administrative division levels. (3) The local commercial residential building prices and the local residents’ economic and social statuses, education levels, and living standards are significantly positively correlated with the grade of GRBs.

The evolution of the urban agglomeration is a significant development in urban geography. Determining its spatial range for effective measurement remains a challenge for researchers. In previous studies, determining spatial range has primarily been done through distinguishing the cities that should belong to urban agglomerations from among other cities by using various indicators. Both the selection of indicators and the standards used for calculation and identification have been based on subjective choices, and have not considered spatial distribution or morphology. The urban agglomeration can be regarded as a self-organized space, and spatial features of the fractal can be regarded as one of the morphological characterizations of spatial self-organization. From the perspective of the assumption that the space of urban agglomerations is molecule like assembled, and through the extraction and analysis of spatial fractals, we present an objective method to determine the &ldquo, spatially contiguous zone&rdquo, of urban agglomeration, particularly the spatial range in which the urban agglomeration is able to exercise jurisdiction within the radius of its capacity, rather than in the administrative division. Our method is applied in this paper to the Beijing&ndash, Tianjin&ndash, Hebei urban agglomeration and produced the following results: (1) the existence of spatial fractals and the theory of space unit molecule like self-organization or assembly in the morphology of urban agglomerations has been proved, and (2) a spatially contiguous zone could be identified for the urban agglomeration has been confirmed. Compared with previous methods used for determining space, this method is centered on the spatial morphology of urban agglomerations, the recognition of a spatially contiguous zone liberates the geographical limits of the result from city boundary restrictions. Concurrently, by considering the linkages within the city as a self-organizing black box, we can circumvent the one-sidedness involved with the selection of indicators that has biased previous studies, thereby avoiding having to focus on the specific mechanism of urban dynamics, and coming much closer to its self-organizing dynamic inner nature. This approach will prove to be a useful reference for the identification of spatial ranges in future studies.

Agricultural development is determined by various factors, such as environmental, economic, demographic, or social circumstances. In order to present the level of this development as com-prehensively as possible, a multidimensional analysis should be carried out with an appropriate methodology. In this article, a taxonomic approach known as the Hellwig’s method was used to determine the level of agricultural development. The area of research was the territory of Poland, divided into voivodships, which are the main units of the administrative division of the country. The development of agriculture thus determined was correlated with activities pursued by the National Agricultural Support Centre (NASC), an institution responsible for the management of agricultural real estate owned by the State Treasury in Poland. The results showed that the NASC’s activities are related to the level of agricultural development in every voivodship. The investigated model of rural space management was shown to be a rational one, performing well in today’s market conditions. The proposed methodology could adapt to similar situations and can be used in similar research on rural areas.

Cultural ecosystem services (CES) are a significant part of the ecosystem and are considered to be a core component of human welfare and ecosystem protection. CES have been historically difficult to quantitatively evaluate because of their subjectivity and intangibility. Additionally, their evolution over time has rarely been explored. Here, we quantitatively evaluated various CES and generated corresponding value index (VI) maps. We then further explored the evolution of CES characteristics over space and time. We selected Xi’an as the study area and applied the Social Values of Ecosystem Services (SolVES) model to evaluate CES and generate three specific VI maps. A system dynamics model based on socioeconomic and survey data of CES for each administrative division was established. Finally, we simulated four developmental scenarios in order to predict potential developmental changes of CES in 2030 under these different scenarios. This study provides a method for evaluating CES and explores the application of system dynamics to different fields. Additionally, our findings may provide guidance for the formulation of regional policies and support missions to improve civilizations within ecological systems, coordinate future economic growth with ecosystem services, and achieve sustainable development.

Ordos became the new “coal capital” of China within a few decades since the country’s economic reform in 1978, as large-scale surface coal mining dramatically propelled its per capita GDP from being one of the lowest to one of the highest in China, exceeding Hong Kong in 2009. Surface coal-mining areas (SCMAs) have continued to expand in this region during recent decades, resulting in serious environmental and socioeconomic consequences. To understand these impacts and promote regional sustainability, quantifying the spatiotemporal patterns of SCMAs is urgently needed. Thus, the main objectives of this study were to quantify the spatiotemporal patterns of SCMAs in the Ordos region from 1990 to 2015, and to examine some of the major environmental and socioeconomic impacts in the study region. We extracted the SCMAs using remote-sensing data, and then quantified their spatiotemporal patterns using landscape metrics. The loss of natural habitat and several socioeconomic indicators were examined in relation to surface coal mining. Our results show that the area of SCMAs increased from 7.12 km2 to 355.95 km2, an increase of nearly 49 times from 1990 to 2015 in the Ordos region. The number of SCMAs in this region increased from 82 to 651, a nearly seven-fold increase. In particular, Zhungeer banner (an administrative division), Yijinhuoluo banner, Dongsheng District and Dalate banner in the north-eastern part of the Ordos region had higher growth rates of SCMAs. The income gap between urban and rural residents increased along with the growth in SCMAs, undermining social equity in the Ordos region. Moreover, the rapid increase in SCMAs resulted in natural habitat loss (including grasslands, forests, and deserts) across this region. Thus, we suggest that regional sustainability in Ordos needs to emphasize effective measures to curb large-scale surface coal mining in order to reduce the urban–rural income gap, and to restore degraded natural ecosystems.

In the context of a public mental health study conducted in Casablanca, the economic capital of Morocco, we encountered a serious challenge regarding the availability of consistent and accurate administrative division data. Hence, using the Google Maps API in QGIS, we proceeded to geocode the Grand Casablanca districts and overlay them on the updated Morocco’s administrative regions shapefile. The district data were summarized and gathered creating an administrative division repository from the district level up. Thus, the main contribution of the current paper, is a table containing (District, District_CP, Commune, Type_com, Prefecture/Province (PR), PR_CP, Region) and the second output is the shapefile that generated the table. The GIS data and the map are useful to other researchers in Morocco and elsewhere who have had no opportunity to access administrative division data of the location. As for foreign researchers from other developing countries the paper’s approach can be applied in their studies to create other lacking geographic repositories.