Land-type mapping and its application to land-use zoning: a case study of Jiangsu province, eastern China

Ecosystem services are comprehensive and quantitative indicators for describing ecosystem–human interactions. China has experienced rapid urbanization in the past 30 years, which has created a significant impact on regional ecosystem services. However, whether the impact is linear is not clear as yet. In this study, the Jiangsu province, a main body of the Chinese Yangtze River Delta city cluster, was chosen as a case study. Multi-source remotely-sensed geospatial data, including meteorological, land use, vegetation, and socio-economic data, were collected to estimate the total amount of ecosystem services (TESV) and urbanization levels. Subsequently, the relationships between TESV and urbanization indices (i.e., gross domestic product (GDP) per unit area, GPUA; population per unit area, PPUA; and built-up land proportion, BULP) were determined using the Pearson correlation analysis and piecewise linear regression. The primary findings of this study were as follows: (1) There was a distinct spatial pattern in TESV, which gradually increased from west to east with high-value areas located in eastern coastal areas of Jiangsu. Among different land use types, cropland and woodland contributed the most to TESV; (2) The three urbanization indices had spatial patterns, indicating higher urbanization in southern Jiangsu than in central or northern Jiangsu; and (3) Once GPUA and PPUA exceeded threshold values of 3719.55 × 104 yuan/km2 and 744.37 person/km2, respectively, TESV sharply decreased with an increase in these indices. However, the BULP showed a linear and significantly negative relationship with TESV at all values, which indicated that the impacts of economic and population growth on TESV lagged behind that of built-up land expansion. These findings provide a potentially significant reference for decision-makers to rationally enhance regional ecosystem services during rapid urbanization processes.

Download Full-text

Coastal Landscape Vulnerability Analysis in Eastern China—Based on Land-Use Change in Jiangsu Province

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17051702 ◽

2020 ◽

Vol 17 (5) ◽

pp. 1702

Author(s):

Yangfan Zhou ◽

Lijie Pu ◽

Ming Zhu

Keyword(s):

Land Use ◽

Human Activities ◽

Large Scale ◽

Positive Impact ◽

Eastern China ◽

Landscape Management ◽

Vulnerability Index ◽

Jiangsu Province ◽

Assessment Model ◽

Rapid Urbanization

The unreasonable land use in rapid urbanization areas induced by large-scale urban construction activities have caused massive ecological issues. In this study, landscape vulnerability index (LVI) and landscape human interference index (LHAI) were originally addressed and calculated using multi-temporal land-use data from 2000 to 2015. Then, the spatial-temporal relationship assessment model of landscape fragility caused by human activities were constructed for each county of Jiangsu Province, China, so as to analyze the spatial distribution of landscape vulnerability and determine the impacts of artificial disturbance on landscape vulnerability. The results showed: (1) The number of counties with middle and high landscape vulnerability increased from 20 in 2000 to 27 in 2015 with a peak value (33) in 2010. (2) Counties with high-intensity human activities showed an upward trend. (3) Land use generally has a significant and diverse impact on landscape vulnerability. At the county level, the LVI was positively correlated with the LHAI before 2010 and was followed by a negative correlation of them. As concluded from this study, a total of four sub-regions (continuous benefit zones, variable benefit zones, continuous harmful zones, and variable harmful zones) have been identified for sustainable landscape management in the future. (4) The LVI suggests that the landscape vulnerability in Jiangsu did not continue to deteriorate in the study period. Further, accelerated land exploitation has produced a positive impact on regional economic development and ecological protection. This study provided an effective method set for analyzing the environmental impacts caused by human activities and promoting future ecosystem management in coastal areas.

Download Full-text

Spatial Pattern Simulation of Land Use Based on FLUS Model under Ecological Protection: A Case Study of Hengyang City

Sustainability ◽

10.3390/su131810458 ◽

2021 ◽

Vol 13 (18) ◽

pp. 10458

Author(s):

Chuchu Zhang ◽

Peng Wang ◽

Pingsheng Xiong ◽

Chunhong Li ◽

Bin Quan

Keyword(s):

Land Use ◽

Spatial Distribution ◽

Prediction Method ◽

Distribution Area ◽

Kappa Index ◽

Land Type ◽

Marginal Areas ◽

Ecological Protection ◽

Regulation Function

With rapid economic development in China, the excessive expansion of cities has led to the imbalance of land use structure, and then the ecological regulation function of the land ecosystem experiences problems, which has become an obstacle to sustainable development. Therefore, in order to protect the ecological environment, regulate urban development and pursue the maximization of ecological benefits, it is necessary to analyze, simulate and predict land use change. In this study, Hengyang City was taken as the study area, and based on the current land use data of Hengyang City in 2010, 2015, and 2018, the land use type transfer during 2010–2015 and 2015–2018 was analyzed. Then, starting from 2010, the FLUS model was used to simulate the spatial distribution of land use in 2015 and 2018, and then the spatial distribution of land use in Hengyang City in 2025 was predicted with the Markov prediction method under the premise of ecological protection priority. The results show that the change in ecological land in Hengyang City is mainly distributed in the surrounding and marginal areas, because the topography of Hengyang City is a basin. Changes in land type in Hengyang City in 2015 were subtle and difficult to observe. However, in 2018, the transformation of non-ecological land into ecological land was obvious, and the distribution area of ecological land expanded significantly. The Kappa index of the results simulated by the FLUS model based on neural network is above 0.72, and overall accuracy is above 0.9, which is highly consistent with the actual situation. It is reasonable and convincing to predict the spatial distribution of land use in the context of ecological protection. The predicted results can be useful for urban planning and land use distribution and provide a reference for relevant decision-makers.

Download Full-text