Non-plan Driving Based Land Use Planning Environmental Impact Assessment In Coastal Area

The adjustment of individual land use proportion and optimization of the land use layout are the primary task in land use planning?LUP?implementation.Therefore,the LUP implementation has inevitable impacts on the regional environmental quality hence influence the humanity.However,the traditional methodology of land use planning environmental impact assessment?LUPEA?neglects the impact of non-land use planning driving land use change.It is easy to obtain an inaccurate even wrong conclusion with the traditional methods.Due to the populated people and drastic land use change,the environmental issues in the coastal area have challenged the regional even national sustainable development strategy.In this paper,a non-land use planning driving LUPEA?NPD-LUPEA?model was proposed firstly,then a rule-based method to extract the land use/cover information and a land use based method to improve the ASTER GDEM were proposed and applied to obtain the related data with high accuracy to support the LUPEA.After that,a Chinese coastal city named Lianyungang was selected as a case to validate the method using remote sensing?RS?and geographical information system?GIS?.We concluded that:?1?The land use change driven by natural and socia-economic factor expect for the implementation of land use planning scheme is defined as land use background change.The driving factor of non-land use planning scheme is the backgroud factor,and the LUP environmental impact assessment based on the land use background change is the non-planning driving LUPEA.By eliminating the influences from non-land use planning driving land use change,the NPD-LUPEA model can reflect the exact impacts on environmental quality from the implementation of land use planning.The NPD-LUPEA model can be employed in the implementation of LUPEA with the integration of state-impact-state?SIS?model and GIS technology to obtain the spatial based results.?2?According to the land use/cover?LUC?classification results in the three seasons?the winter,spring,and autumn?using seasonal RS images and their corresponding accuracy assessment,there is the lowest classification accuracy for the LUC result in the winter but the relative higher accuracy in the spring and autumn than winter.Using the rule-based land use/cover?LUC?classification methodology and seasonal imagery,by establishing the special classification rules for the study area after the analysis of seasonal and other multi-temporal change features,the accuracy for the final LUC result of Lianyungang city is higher than the seasonal results using the single temporal image.It is believed that our proposed method can improve the accuracy of LUC classification especially in the coastal area through decreasing the misclassification due to the characteristics of same spectral feature in various land use types and different spectral feature of same land use types;?3?Land use types reflect the comprehensive features of topography,vegetation,and human activities and hence influence the accuracy of ASTER GDEM.The accuracy assessment of ASTER GDEM in Lianyungang city demonstrates that different land use types have different impacts on the accuracy.The ASTER GDEM data in the area of grassland,rice land,wheat land,and mining land show lower errors than bare land,woodland,garden land,and scenic area.Two simple and multiple linear regression analysis methods based on land use type was designed to calibrate the ASTER GDEM data.Both the two linear regression analysis methods can improve the accuracy of ASTER GDEM distinctly in the study area.Especially for simple linear regression analysis method with fewer types of data,it is more feasible to apply the simple linear regression analysis method to improve GDEM2 accuracy.The simple linear regression analysis method plays a simple way to calibrate the ASTER GDEM data with distinct framework,and can provide the essential data for LUPEA.?4?There is an improvement of environmental quality from 2010 to 2020 based on the impact assessment of LUP implementation on environment which indicates the comprehensive land use change.However,more improvement of environmental quality from 2010 to 2020 is observed based on the impact assessment of non-land use planning driving change on environment.It is concluded that the implementation of LUP scheme in Lianyungang would have negative impact on the regional environment according to our proposed methodology.The application of Lianyungang City suggests that the NPD-LUPEA methodology provides more accurate assessment by eliminating the impact from non-land use planning.The weight values of individual indicators using the combination of analytic hierarchy process?AHP?and Entropy value methods shows that there are higher weight values for PM₁₀,SO₂,and the load degree of COD according to the area of land in comparison with other indicators.Among the other indicators except for the above three indicators,the indicator of woodland and water have higher weight value,suggesting that the impact on biodiversity have obtained more concerns in the area.It is therefore feasible to establish very corresponding measures according to the feature of individual indicators to mitigate the negative impact and promote the improvement of environmental quality.