Global NEST Journal

Because the traditional remote sensing image monitoring method has the problem of poor ability of capturing vegetation destruction, an ecological remote sensing image method for vegetation destruction in waterfront greenway based on genetic algorithm is proposed. The vegetation index data of waterfront greenway were acquired by remote sensing image, and the pseudo color image was synthesized. The on orbit radiometric calibration and geometric precision correction are carried out for the collected data, and the relationship between vegetation index and vegetation damage of waterfront greenway is analyzed, including meteorological factors, geographical factors and vegetation damage of waterfront greenway. Select the independent variables of the model, establish the ecological remote sensing image monitoring model of the vegetation damage of the waterfront greenway, and realize the ecological remote sensing image monitoring of the vegetation damage of the waterfront greenway. The experimental results show that the acquisition ability of the method based on genetic algorithm is better than that of the traditional method, and it is more suitable for the ecological remote sensing monitoring of the vegetation damage of waterfront greenway.

On the Basis of Relevant Theory and Literature Research, analyze the development of forestry enterprises in northeast China, and establish the evaluation index system of the ecological situation of forestry enterprises in northeast China. Based on the composite weights of objective and subjective empowerment, the ecological niche and potential of forestry enterprises in Northeast state-owned forest areas were evaluated, and establishes the evaluation index system of the ecological situation of forestry enterprise in northeast China. Based on this, the ecological position and potential of forestry enterprises in the northeast of the northeast are evaluated, and the model of the evolution path selection matrix of the northeast state-owned forest is constructed. Finally, based on the development of ecological path dependence and path breakthrough, passive adaptation and initiative adaptation, the functional ecological selection of forestry enterprises in the northeast state-owned forest sector is combined with the ecological potential of the forestry enterprise, which is the economic benefit priority, ecological benefit and the three main benefits. Based on the basis of the contribution of three different forestry enterprises and the potential value of different forestry enterprises, the corresponding alternative evolution path of the functional ecological evolution of forestry enterprises in the northeast state-owned forest sector is proposed.

With the increasingly prominent problem of agricultural non-point source pollution, the process of Rural Revitalization Strategy has been seriously affected. Studying the relationship between rural human capital and agricultural non-point source pollution is helpful to form talent bonus, improve rural ecological environment and realize the green development of agriculture. This paper takes 30 provinces and cities of China as the research object and uses Spatial Durbin model for empirical analysis. According to the research results, it is found that agricultural non-point source pollution has significant spatial correlation and the correlation presents a fluctuating trend; Rural human capital has obvious direct effect (-0.678) and spatial spillover effect (-0.707), which helps to alleviate agricultural non-point source pollution. After considering different forms of space matrix, the result is considered to be robust. The conclusion of this paper provides policy enlightenment for promoting the construction of rural human capital and improving the continuous development of rural ecological environment curriculum.

Urban economic development cannot be separated from energy consumption, and energy consumption directly leads to a large number of carbon emissions. It is of great significance to study the relationship between carbon dioxide emissions and economic growth for the implementation of energy conservation, emission reduction and the development of low-carbon economy in cities. A new method of dynamic relationship between urban carbon dioxide emission and economic growth is put forward. The carbon dioxide emission data in cities are calculated by using urban carbon dioxide emission measurement method. The data of economic attributes are obtained by using classification algorithm under uncertain data flow environment. Based on this data, a decoupling model of carbon emission and economic growth is constructed to measure economic growth elasticity of urban carbon emissions; Granger causality test model is established to analyze the Granger causality between urban carbon dioxide emissions and economic growth. The experimental results show that the growth rate of urban economy is obviously faster than that of carbon emissions. Economic growth is the Granger causality of carbon dioxide emissions. On the contrary, the implementation of carbon emission reduction measures will not hinder economic growth.