This paper, based on panel data of 30 provinces in China from 2010—2014, uses multiple linear regression model to study the eco-efficiency influence of different environmental regulations on different resource-dependence areas, in order to provide references for local governments to manage environment. In high resource-dependence areas, mandatory environmental regulations are negatively related to regional  eco-efficiency, market-driven and voluntary- acceptance environmental regulations show an  upside-down  U shape with  eco-efficiency. In low resource-dependence areas, mandatory environmental regulations act negatively with regional eco-efficiency, market-driven environmental regulation displays an  upside-down  U shape, but  voluntary-acceptance has little influence. Hence, the paper suggests that environmental regulations vary with the types of  resource-dependence areas at different developing stages so as to maximize the performance of environmental regulations. 

The plowland protection and its sustainable development are underlined in the newround land utilization planning in China. The paramount step for land utilization planning is to determine the plowland index, which requires a prediction of preserved plowland quantity. This paper combines the land utilization general planning, studies the preserved plowland quantity in Liaoyang city by means of regression method, longterm tendency method and fuzzy system method, which provides a reference to establish the land utilization general planning in Liaoyang city.

The benchmark land price refers to an average price of different class at normal market, at some specific time point, in different utilization, one fixed year’s volume ratio. Due to some variation in connotation, selection of parameters, means and assessors during evaluating the benchmark land price, it is difficult to compare the benchmark land prices in different locations with big influence over land market, thus necessitating a balanced land price. This paper, based on a case study of Dandong city, illustrates how to calculate the balanced benchmark land price from components and spatial balance.