Intersection of Physical and Anthropogenic Effects on Land-Use/Land-Cover Changes in Coastal China of Jiangsu Province

Impact of Land-Use Change on Ecosystem Services in the Wuling Mountains from a Transport Development Perspective

Transportation significantly affects regional land-use changes and ecosystem service functions. Exploring the correlations among transport development, spatial pattern of land-use changes, and ecosystem service changes are important for mitigating the deterioration of regional ecosystems due to human activities. In this study, 2000-2020 was selected as the study period to explore the effects of land-use changes on the ecosystem service value (ESV) in the Wuling Mountains. The results showed that: (1) the Wuling Mountains have experienced four stages of transport development and (2) transportation development has contributed to land-use change. The spatial pattern associated with construction land growth has evolved due to transport development. Garden land has gradually spread into the entire region with transport development. Policies from different periods have had more of an effect on ecological land and cropland. (3) During the study period, the ESV first increased and then declined. The periphery of the transportation axis formed a concentration zone of ESV cold spots. In contrast, ESV hot spots were more concentrated in areas along the Yangtze River. The results of this study provide guidance for land-use policy and spatial planning under the concept of green development.

Landscape Pattern and Ecological Risk Assessment in Guangxi Based on Land Use Change

Due to ecological environmental fragility and soil erosion in Guangxi, studies of landscape patterns and associated ecological risks are needed to guide sustainable land development and ecologically sensitive land management. This study assesses dynamic spatial and temporal change patterns in land use and ecological risks based on 30 m land-use data, analyzes spatial correlations with ecological risks, and explores natural and socio-economic factor impacts on ecological risks. The results reveal: (1) A rapid and sizeable construction land increase in Guangxi from 2000 to 2018 associated mainly with loss of woodland and grassland. (2) Guangxi had the highest number of arable land patches from 2000 to 2018, and the distribution tended to be fragmented; moreover, the construction land gradually expanded outward from concentrated areas to form larger aggregates with increasing internal stability each year. (3) Guangxi ecological risk levels were low, low–medium, and medium, with significantly different spatial distributions observed for areas possessing different ecological risk levels. Regional ecological risk gradually decreased from the middle Guangxi regions to the surrounding areas and was positively correlated with spatial distribution. (4) Socio-economic factor impacts on ecological risk exceeded natural factor impacts. These results provide guidance toward achieving ecologically sensitive regional land-use management and ecological risk reduction and control, it can also provide a reference for ecological risk research in other similar regions in the world.

Long Time-Series Mapping and Change Detection of Coastal Zone Land Use Based on Google Earth Engine and Multi-Source Data Fusion

Human activities along with climate change have unsustainably changed the land use in coastal zones. This has increased demands and challenges in mapping and change detection of coastal zone land use over long-term periods. Taking the Bohai rim coastal area of China as an example, in this study we proposed a method for the long time-series mapping and change detection of coastal zone land use based on Google Earth Engine (GEE) and multi-source data fusion. To fully consider the characteristics of the coastal zone, we established a land-use function classification system, consisting of cropland, coastal aquaculture ponds (saltern), urban land, rural settlement, other construction lands, forest, grassland, seawater, inland fresh-waters, tidal flats, and unused land. We then applied the random forest algorithm, the optimal classification method using spatial morphology and temporal change logic to map the long-term annual time series and detect changes in the Bohai rim coastal area from 1987 to 2020. Validation shows an overall acceptable average accuracy of 82.30% (76.70–85.60%). Results show that cropland in this region decreased sharply from 1987 (53.97%) to 2020 (37.41%). The lost cropland was mainly transformed into rural settlements, cities, and construction land (port infrastructure). We observed a continuous increase in the reclamation with a stable increase at the beginning followed by a rapid increase from 2003 and a stable intermediate level increase from 2013. We also observed a significant increase in coastal aquaculture ponds (saltern) starting from 1995. Through this case study, we demonstrated the strength of the proposed methods for long time-series mapping and change detection for coastal zones, and these methods support the sustainable monitoring and management of the coastal zone.

Effectiveness of Chinese Regulatory Planning in Mitigating and Adapting to Climate Change: Comparative Analysis Based on Q Methodology

With cities considered the main source of carbon emissions, urban planning could mitigate and help adapt to climate change, given the allocation and regulation of public policies of urban spatial resources. China’s regulatory planning remains the basis for building permission in the original urban and rural planning, and the new territorial spatial planning systems, determining the quality of urban plan implementation. Comprehensive regulatory plans effectively reduce carbon emissions. This study employs Q methodology to compare and analyze urban planners’ and practitioners’ perceptions of China’s regulatory planning in climate change mitigation and adaptation. The findings show that while regulatory planning is key, potential deficiencies include the gaps between regulatory from master plans, capacity shortages of designations and indicators, and unequal rights and responsibilities of local governments. However, mandatory indicators in regulatory planning, especially “greening rate,” “building density,” “land use type,” and “application of renewable energy technologies to the development of municipal infrastructure” could effectively mitigate climate change. “Greening rate” is the core indicator in regulatory planning since it provides empirical evidence for the “green space effect”. This study indicates that local customization of combined regulation of greening rate and green spaces could help mitigate and help China adapt to climate change.

Remote Sensing-Based Analysis of Landscape Pattern Evolution in Industrial Rural Areas: A Case of Southern Jiangsu, China

With the rapid economic development of industrial rural areas in Southern Jiangsu, the rural landscape and ecological environment of these industrial rural areas are getting damaged. Based on GIS and RS techniques, Landsat Satellite remote sensing images from 1981, 1991, 2001, 2011 and 2018 were collected for Jiangyin, Zhangjiagang, Changshu and Kunshan, to extract landscape pattern indexes and spatial distribution data. Landscape pattern indexes of the patch-class level and landscape level from each year were calculated by FRAGSTATS. After analyzing and comparing landscape pattern variation of five years, progress, characteristics and driving forces of landscape pattern evolution were explored. At the patch-class level, construction land had continuously encroached on green and cultivated land, exhibiting trends of expansion and centralization. At the landscape level, the number of small patches and degree of landscape fragmentation generally increased. The direct cause of landscape pattern evolution in industrial rural areas of Southern Jiangsu was the encroachment and segmentation of green and cultivated land by construction land, and the dominant factors driving the changes in construction land in the industrial rural areas of Southern Jiangsu were the effects of land and population aggregation exerted by the development of township enterprises and rural industries.