A methodological framework for coastal development assessment: A case study of Fujian Province, China

Evaluation of spatial variation of water resources carrying capacity using optimal method: a case study of Fujian, China

Studying regional water resources carrying capacity (WRCC) is an important guarantee for realizing regional sustainable development. Previous evaluation of WRCC mainly focused on the construction of the index system and the optimization of multiattribute decision analysis methods (MDAMs). The selection of the weighting assignment method (WAM) is a key link in the evaluation of WRCC, but different WAMs may bring different results, which brings challenges to the actual WRCC evaluation. Therefore, this paper proposes a WAM selection framework, under which WRCC evaluation index system is firstly constructed. Secondly, from the four objective WAMs, the most suitable WAM is identified and selected to evaluate WRCC in Fujian Province in terms of the reliability and stability of the evaluation results. In addition, the main factors affecting regional WRCC are discussed using the obstacle degree model. The results show that (1) under the same evaluation index system, the CRITIC method was the suitable method with more reliability and stability than the coefficient of variation method, the entropy method, and the equal weight method. (2) The higher water resources carrying capacity (level I) is mainly located in the west of the study area, and the lower one (level V) is located in the east coast. (3) The superimposition effects ecological water use rate, water production modulus, acreage water consumption of farmland irrigation, per capita water resources, and COD emissions hindering the level of regional WRCC. The framework proposed in this study can provide methodological options for quantitative evaluation of WRCC. The results of this paper provide favorable support for decision makers to carry out rational planning of resources.

Land cover change detection in the Turkish coastal zone based on 28-year (1990-2018) Corine data

In this research, land cover changes in the coastal region of Turkey were analyzed using the Corine dataset between 1990 and 2018. Changes in each period were analyzed by using the rate of change and the annual rate of change, the transition matrix of net changes, and the transition probability matrix. In order to predict land cover change trends and to determine future land cover change probabilities, a combination of Markov and cellular automata models was used. It was determined that the highest increase in each study period was in artificial surfaces and the highest decrease was in the forest and the semi-natural area. The total forest areas were converted to the other land cover type in the first study period amounting to 2479.32 km². Also, it was decreased and transformed by about 62.47 km², 118.82 km², and 203.09 km² of the forest area that existed in the second, third, and fourth periods respectively. The results indicate that the probabilities of the increasing area will be covered by artificial surfaces and agricultural areas. It is estimated that the rate of 57% in 1990, the initial year of the forest areas, will decrease to 53.4% in 2034 and to 53% in 2050. Also, the rate of 2.1% in 1990, the initial year of the artificial surfaces, will increase to 4.5% in 2034 and to 5.0% in 2050. It is seen that more artificial surfaces will be needed in the Turkish coastal region due to the increasing population and number of tourists. It is important to evaluate and investigate the coastal areas where more artificial areas are expected to be needed within the scope of the coastal area management plans to be prepared at the national scale.

A Framework for Assessing the Dynamic Coastlines Induced by Urbanization Using Remote Sensing Data: A Case Study in Fujian, China

The coastline plays an important role in indicating the conditions of social-economic development in the coastal zone. In this study, an integrated assessment framework was proposed to address the provincial and county-level spatiotemporal dynamics of continental coastlines from the perspectives of length, position, composition, and anthropogenic utilization quantitatively, and to explore the exact impacts of urbanization on coastline changes in the Fujian Province over the period from 1985 to 2020. Results showed that the total length of coastlines decreased first and then increased due to the different patterns of economic development. The proportion of artificial coastlines and the index of coastal utilization degree increased rapidly during the same period. Moreover, the seaward movement of coastlines due to the coastal reclamation projects resulted in a considerable increment in land areas. The pressure brought by the continuous concentration of population, built-up areas, and industrial districts under the rapid urbanization was the primary factor that increased the degree of anthropogenic disturbances in the coastal zone. Furthermore, the policies issued by the local or central government can be critical tipping points for coastline changes in different periods.

The change detection in coastal settlements using image processing techniques: a case study of Korfez

Coastal areas all over the world are usually exposed to intensive change and transformation processes resulting in a variety of natural, physical, and socio-economic problems. Körfez province, located along the İzmit Bay of Marmara Sea, Turkey, has been one of these coastal areas that has become a major point for industrial facilities and highly populated urbanized area since 1960s. Therefore, the analysis of the spatial changes in the land use patterns of the province has a critical role in the success of the physical planning processes and the protection of the coastal areas. In order to highlight this critical role, temporal change detection analysis for Körfez province covering a 6-year period and 5 land use classes was made using 2009 and 2015 SPOT imagery and thematic maps. Reclassified CORINE data, development plans, and land survey results were benefited for the supervised classification of the images. Four hundred eighty control points for each year were used to achieve a strong accuracy tested by Kappa coefficient. The spatio-temporal change detection results revealed a 22.5% and 2.3% decrease in agricultural lands and sea areas respectively, while there was an increase of 16.6% in forest-green areas, 6.4% in settlement areas, and 74.1% in lake areas. The results are believed to be significant input data to facilitate coastal and physical development planning over the area, and thus make sustainable land use decisions to protect the delicate landscape and coastal characteristics, while providing a sound risk management plan.

Construction and Evaluation of the Integrated Perception Ecological Environment Indicator (IPEEI) Based on the DPSIR Framework for Smart Sustainable Cities

Ecological environment evaluation is of great significance to achieve the Sustainable Development Goals (SDGs) and promote the harmonious development of economy, society, and environment. To evaluate environmental SDGs, single environmental indicators have been analyzed at national or large regional scale in some literature, while the urban integrated environment is ignored. Therefore, it is necessary to systematically and quantically evaluate the sustainability of ecological environment integrating the water, soil, and air environment at the urban scale. This study aims to construct the Integrated Perception Ecological Environment Indicator (IPEEI) based on the Driver-Pressure-State-Impact-Response (DPSIR) framework to solve the above-mentioned problems. The IPEEI model was proposed based on the three-level association mechanism of the Domain-Theme-Element, and the DPSIR framework conforming to the relevant standards for indicator determination. Moreover, the multi-dimensional, multi-thematic, and multi-urban quantitative evaluations were conducted using the entropy weight method, and the comprehensive evaluation grades by the Jenks natural breaks classification method of the geospatial analysis. Nine cities in the Wuhan Metropolitan Area were selected as the experimental areas. The results were consistent with the Ecological Index and local government’s planning and measures, which demonstrated that IPEEI can be effectively verified and applied for the evaluation of urban ecological environment sustainability.

Marine resource congestion in China: Identifying, measuring, and assessing its impact on sustainable development of the marine economy

Research on the sustainable development of the marine economy has conventionally revolved around the relationship between efficiency and development. However, most studies have neglected examining how excessive marine resource inputs under certain conditions may lead to resource congestion that restricts output efficiency and sustainable development. To fill this research gap, we optimized an index system to evaluate the input level of marine resources. Using the data of 11 coastal provinces and cities in China from 2000 to 2016, we calculated the congestion of marine resources and analyzed its spatiotemporal evolution and primary influencing factors. Finally, we separated the inefficiency driven by congestion from pure technical inefficiency. The results showed the following: (1) Grave, long-term marine resource congestion does exist in China, and it has evolved from fast to slow, strong to weak, and agglomeration to dispersion; (2) Congestion in the coastal areas has gradually weakened from north to south, and the center of gravity has experienced a shift from the center of China toward the north; (3) Marine resource congestion is mainly affected by the input of resource and capital, resource endowment, and industrial structure; (4) Factors leading to inefficiencies include resource congestion and long-term pure technical inefficiency. By combining congestion and efficiency, we produce values for studying inefficiency and the sustainable development of the marine economy, with the benefit of providing targeted strategies.