•A composite index system is established to evaluate China’s new-type urbanization.•The article studies new-type urbanization from the perspective of land transfer.•The SDM model is used to explore ...the spatial spillover effects of new-type urbanization.•The threshold panel model is used to discuss their nonlinear relationship.
With the rapid development of urbanization, land transfer has become a significant part of urban development. This article builds a comprehensive evaluation system to quantify the new-type urbanization level of urban agglomeration in the middle reaches of the Yangtze River from 2006 to 2017. To explore the relationship between the two more clearly, the spatial econometric model and the threshold panel model are used to explore how land transfer affects new-type urbanization. The results show that: the level of new-type urbanization is characterized by fluctuating increases, but that the regional differences show an expanding trend. The Moran’s I of the new-type urbanization fluctuates at approximately 0.120, showing positive spatial correlation. The estimation results of the spatial Durbin model (SDM) indicate that the coefficient of land transfer and its spatial lag coefficient are 0.040 and 0.006 respectively, indicating that it has positive impacts on new-type urbanization. The results of the threshold panel model show that there is a significant nonlinear relationship between land transfer and new-type urbanization. The impacts of land transfer on the level of new urbanization will change in both positive and negative directions with changes in government intervention.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The increase in carbon emissions has had great negative impacts on the healthy developments of the human environment and economic society. However, it is unclear how specific socio-economic factors ...are driving carbon emissions. Based on the multiscale geographically weighted regression (MGWR) model, this paper analyzes the impact mechanism of China’s carbon emission data during 2010–2017. The results show that (1) during the study period, China’s carbon emissions have obvious positive correlations in the spatial distribution, and the spatial autocorrelation of carbon emissions on the time scale has a further strengthening trend. (2) Compared with the results of the geographically weighted regression (GWR) model, the MGWR model is more robust, and the results are more realistic and reliable. The impacts of energy intensity, proportion of green coverage in built-up areas, and industrial structure on provincial carbon emissions are close to the global scale, and their spatial heterogeneity is weak. Other factors have spatially heterogeneous impacts on carbon emissions with different scale effects. (3) Except for proportion of green coverage in built-up areas, the industrial structure and trade openness have insignificant impacts on carbon emissions, but other variables have significant impacts. The total population, urbanization rate, energy intensity, and energy structure have positive impacts on carbon emissions, while the GDP per capita and foreign direct investment have negative impacts on it. This study shows that the main socio-economic factors have different degrees of impacts on carbon emissions with different scale, and we can refer to it to formulate more scientific measures to reduce carbon emissions.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•Paradigm of the theory of urban bias is an effective tool to understand China's land development policy.•Policy is measured by the extent to which compensation deviates from the market value of ...expropriated land.•Effect of urban-biased land development on the urban-rural income gap is robust, significant, and positive.•This effect is attributed to an unbalanced urban-rural income growth associated with the land development.
Developing countries generally face the challenge of significant urban-rural divides during their process of industrialization and urbanization. Following the paradigm of the theory of urban bias (TUB), this article focuses on the urban-biased land development policy (UBLDP) in contemporary China, which refers that local governments expropriate rural land with the inadequate compensation and use a considerable share of net land revenue to develop urban areas instead of rural areas. On the basis of pointing out three practical facts about and proposing the technique to measure the UBLDP, its influence on the urban-rural income gap (URIG) is investigated by employing the GMM dynamic model along with panel data from Hubei Province over the period of 2010-2016. The results show that a 1% increase in the extent to which compensation deviates from the market value of expropriated rural land (ERL) leads to a 0.46% increase in the URIG, while this effect is attributed to an unbalanced urban-rural income growth associated with the land development. These findings not only generate a broad of direct implications for Chinese policymakers but also provide lessons for other developing countries.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•Measure the land dispute intensity (LDI) at the provincial level in China.•The geodetector model, OLS, and SDM models are used to explore the spillover effects of LDI.•Panel threshold model is ...applied to explore the non-linear relationship between socioeconomic factors and land disputes.
Land disputes pose significant challenges to social stability and development. In this paper, land dispute intensity (LDI) is measured at the provincial level in China from 2009 to 2018 and its spatiotemporal evolution characteristics and influencing factors are explored. The ordinary least squares(OLS), spatial durbin model (SDM), geodetector model, and panel threshold model are used to explore the spatial spillover effects of LDI and its potential non-linear relationship with socio-economic factors. The results reveal that LDI is spatially distributed in a decentralized form, with local areas showing the structural characteristics of “single core, multiple clusters”. The LDI exhibits a significant positive spatial autocorrelation and follows a “logarithmic” upward trend over time. The urbanization rate (UR), social security expenditures (SSE), and the number of land and resources institutions (NLRI) are important driving forces affecting LDI. The SSE and NLRI have a single threshold effect on the LDI, with a “V” shaped weakening trend, and the UR is an important factor causing nonlinear effects. Interestingly, the effect shifts from inhibition to stimulation when the SSE and NLRI cross the corresponding threshold value. This paper can provide new insights into the governance of land disputes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The changes of land use/land cover (LULC) are important factor affecting the intensity of the urban heat island (UHI) effect. Based on Landsat image data of Wuhan, this paper uses cellular automata ...(CA) and artificial neural network (ANN) to predict future changes in LULC and LST. The results show that the built-up area of Wuhan has expanded, reaching 511.51 and 545.28 km2, while the area of vegetation, water bodies and bare land will decrease to varying degrees in 2030 and 2040. If the built-up area continues to expand rapidly, the proportion of 30~35 °C will rise to 52.925% and 55.219%, and the affected area with the temperature >35 °C will expand to 15.264 and 33.612 km2, respectively. The direction of the expansion range of the LST temperature range is obviously similar to the expansion of the built-up area. In order to control and alleviate UHI, the rapid expansion of impervious layers (built-up areas) should be avoided to the greatest extent, and the city’s “green development” strategy should be implemented.
New outlying development zones are a common phenomenon in the development of Chinese cities, and exploring their development level is a matter of great interest. Using geographic big data that cover ...the entire country, this paper analyzes the urban development level (UDL) of newly added outlying patches within 275 cities at the prefecture level or above in China from 2005 to 2015. The results revealed the following. 1) High-value cities are primarily located in the east, whereas low-value cities are primarily located in the west. The Beijing-Tianjin-Hebei urban agglomeration (BTHUA) is a major area with low UDLs, whereas the Yangtze River Delta urban agglomeration (YRDUA) and the Pearl River Delta urban agglomeration (PRDUA) are major areas with high UDLs. 2) The results of a multivariate regression demonstrate that GDP per capita (GDPPC), average elevation (AE), the distance between the new outlying urban patches, the proportion of secondary industry in GDP (PSI), the average land price in the city (ALP), the original urban land areas (DIS), and economic balance (GDPSD) significantly affect the UDL values of these cities. Relatively higher GDPPC and ALP are associated with a significant increase in the UDL, while more AE, DIS, GDPSD and PSI will decrease the UDL. The results of this paper provide a reference to understand the conditions of outlying developmental zones in China over the past 10 years as well as to explore healthy and reasonable urban spatial expansion forms.
•The development level of new outlying development zones in China' 275 cities was evaluated using multisource big data.•The causes of the differences in the urban development levels across different cities were explored.•The higher the rank of the city is, the higher the average development level of the outlying expansion patches.•A patch-based indicator showed that 79 cities belong to the desirable urban expansion group.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The ecological environment is important for the survival and development of human beings, and objective and accurate monitoring of changes in the ecological environment has received extensive ...attention. Based on the normalized difference vegetation index (NDVI), wetness (WET), normalized differential build-up and bare soil index (NDBSI), and land surface temperature (LST), the principal component analysis method is used to construct a comprehensive index to evaluate the ecological environment’s quality. The R package “Relainpo” is used to estimate the relative importance and contribution rate of NDVI, WET, NDBSI, and LST to the remote sensing ecological index (RSEI). The optimal parameter geographic detector (OPGD) model is used to quantitatively analyze the influencing factors, degree of influence, and interaction of the RSEI. The results show that from 2001 to 2020, the area with a poor grade quality of the RSEI in Guangzhou decreased from 719.2413 km2 to 660.4146 km2, while the area with an excellent quality grade of the RSEI increased from 1778.8311 km2 to 1978.9390 km2. The NDVI (40%) and WET (35%) contributed significantly to the RSEI, while LST and NDBSI contributed less to the RSEI. The results of single factor analysis revealed that soil type have the greatest impact on the RSEI with a coefficient (Q) of 0.1360, followed by a temperature with a coefficient (Q) of 0.1341. The interaction effect of two factors is greater than that of a single factor on the RSEI, and the interaction effect of different factors on the RSEI is significant, but the degree of influence is not consistent. This research may provide new clues for the stabilization and improvement of ecological environmental quality.
Land contracting is an important system in China. As we know, farmers and agricultural organizations acquire land management rights from collective economic organizations to carry out agricultural ...production. Over the past few decades, it has proved to make a huge contribution to food security and agricultural development in China. However, as land values increased, landowners, contractors, and operators were increasingly in competition over land interests and, as a result, the number of land contract disputes has rapidly increased. Land contract disputes are not only involved in social and economic issues but also related to government management and grassroots governance. Studying the temporal and spatial changes of disputes is the premise to deal with this subject. Based on the data of China Judgment Online from 2016 to 2021, this paper used descriptive statistical methods, spatial analysis tools, and Markov Chains to reveal the temporal evolution characteristics, spatial distribution trends, and grade transfer tendency of land contract disputes in the Yangtze River Economic Belt (YEB). The results showed the following: (1) From 2016 to 2021, the number of land contract disputes in the YEB increased sharply and then decreased gradually; (2) In terms of spatial distribution, land contract disputes were significantly clustered, and the level of clustering has increased in volatility. Meanwhile, the agglomeration area has continuously transferred; (3) There existed the “club convergence effect” and “spatial spillover effect” in the process of dispute grade transfer, but the overall trend was to change for the better. This study attempted to comprehensively describe the changes in land contract disputes in the YEB, and the results would serve as a useful reference for relevant regions to explore the differentiated paths to deal with land contract disputes.
Land use planning is always officially implemented as an effective tool to control urban development and protect farmland. However, its impact on land use change remains untested in China. Using a ...case study of Hang-Jia-Hu region, the main objective of this paper was to investigate the influence of different land use spatial control schemes on farmland conversion and urban development. Comparisons of farmland conversion and urban development patterns between the urban planning area and the non-urban planning area were characterized by using remote sensing, geographical information systems, and landscape metrics. Results indicated that farmland conversion in the non-urban planning area was more intensive than that in the urban planning area, and that farmland patterns was more fragmented in the non-urban planning area. Built-up land patterns in the non-urban planning area showed a trend of aggregation, while those in the urban planning area had a dual trend of fragmentation and aggregation. Existing built-up areas had less influence on built-up land sprawl in the non-urban planning area than that in the urban planning area. Built-up land sprawl in the form of continuous development in the urban planning area led to farmland conversion; and in the non-urban planning area, built-up land sprawl in the form of leapfrogging development resulted in farmland areal declines and fragmentation. We argued that it is a basic requirement to integrate land use plans in urban and non-urban planning areas for land use planning and management.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Land disputes have significantly disrupted legal order, production, and social harmony, and has been regarded as a quintessential challenge in public governance, attracting worldwide attentions from ...scholars. As an emblematic feature of China’s latest reform and opening-up strategy, the Yangtze River Economic Belt (YREB) in China has experienced rapid development after entering the new era (2012–2021) alongside substantial risks and challenges, particularly regarding land disputes. Better understanding of the manifestation and formation mechanism of new characteristics of land disputes is beneficial for contemporary public governance and for achieving a high-quality development of the YREB, whose Gross Domestic Product (GDP) accounted for 46.3% of the national GDP in 2023. A total of 325,105 land dispute cases in 11 provinces or municipalities of the YREB from 2012 to 2021 were collected and analyzed. On this basis, an evaluation index system of the new characteristics of land disputes, named the overall land dispute (OLD) index, was constructed according to measurement theory by coupling the interactions of quantity, claim amounts, duration periods, and the appeal rate of land dispute. Then, the OLD index was evaluated by descriptive statistical methods, a geographic information system (GIS) spatial analysis, a center of gravity model, kernel density estimation, and Theil index methods, to reveal the new characteristics and formation mechanisms of land disputes in the YREB from 2012 to 2021. The results indicated that: (1) The OLD index exhibited a trend of an initial increase followed by a decline, indicating that land disputes in the YREB showed signs of alleviation. (2) The government’s capacity for resolving land disputes was significantly improved, as evidenced by the decline in the OLD index from 0.59 in 2018 to 0.51 in 2021. This improvement could be attributed to the effectiveness of enhanced governmental working mechanisms, regulatory standards, and the integration of digital technologies. (3) The analysis of the center of gravity model indicated that the focus of land disputes shifted westward, propelled by national policy support for upstream regions of the YREB and the need for land ecological protection. (4) The analysis of kernel density estimation indicated that regional disparities in land disputes within the YREB had declined, driven by a positive trend toward balanced regional development and rural governance. This study provides scientific insights into the new characteristics of land disputes in the YREB and guidance for policy decision making on effective land dispute management.
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