This paper, aiming at promoting a coordinated development of water works tourism in Yellow River stream, uses gravity center standard deviation ellipse, kernel density and exploring spatial data analysis method to study the temporal-spatial evolution of water works resorts in 2009, 2014, and 2021 in Yellow River stream, and combines “point-axis” theory with central function index and gravity model to define the development nodes, axis and plates in water works tourism. Development of water works resorts in Yellow River stream has 3 stages. Resorts are spreading along E-W and S-N with gravity center shifting to southwest. Their distributing density shows scattering in the upper-stream and concentrating in the middle- and down-stream, high density concentrating areas are located along banks of Yellow River, Weihe River, Fenhe River and Qinhe River. Their spatial distribution generally displays a strongly positive correlation, “high-high” concentrating in Shandong province, “low-low” in Hehuang valley and partial Gansu province. Hotspots in Yellow River stream remain unchanged, while the cold spots are concentrating toward the upper-stream, and the sub-hotspots migrating to the northwestern middle-stream. Spatial structure after being optimized is composed of three levels of water works tourism development nodes, two levels of development axes and five development domains. This paper presents suggestions on differentiating domain variance, optimizing spatial pattern of water works tourism from construction status, water resources, geographic characteristics and social-cultural environment. And improving transportation, consolidating water works tourism, boosting radiation of node cities.

Water, energy and food are three vital resources, their coordinated development provides a basis for the sustainable development of economy and society. This paper establishes an evaluation index system for Water-Energy-Food (WEF), weighted by means of entropy and variation coefficient, and calculates the coordinated development level of WEF system by means of coupling model, which is compared with WEF system by Gray Verhulst model during 2018 to 2027. The result shows a rising comprehensive evaluation index, a high coupling level of WEF system during 2002 to 2017, whose coupling coordination has undergone transition, generally coordinated and highly coordinated, and will keep premium coordination in the period of 2018 to 2027. The energy development level will still be behind water and food. This paper presents suggestions on intensifying energy developing efficiency in order to push a sustainable development of economy.

This paper, based on Chinas twelve listed rare earth companies financial results from 2004—2012, uses DEA to compare their operational performance in four foreend companies and eight rearend ones, and discusses their difference. The rearend ones have a lower performance displaying a polarization due to their poor technical input. The foreends performance varies with policy, unfavorable for industrial upgrading if rare earth resources are allocated to the foreend. This paper also presents suggestions in promoting Chinas rare earth foreend and rearends coordinating development.

The profitability and stability of REE mining impacts the survival and development of the downstreams industry due to the conductivity of the upstream products price, which relates to sustainability, sound development and global competiveness of China's REE industry. This paper analyzes Chinas REE mining's profitability change and its factors, uses regress model to determine their influences on profitability, and expands their interaction between REE policy and factors. Results show price and sales volume play a key role in REE's profitability, total cost plays little, resource, environmental and consumption tax play a little positively. So this paper presents proposals in China's REE policy that shall be turned to marketing control from administration, in forming REE pricing mechanism, in expediting REE resource and resource tax reform, and internal cost control.

Liupanshui, as one of China's 63 typical coal cities, has been largely depending upon capital investment, size expansion and resource consumption in economy over 30 years since reform an opening. Such a developing path led to a big proportion of resource industry, a weak innovation ability, and a highly dependence on resource, which largely confines a sustainable economy in Liupanshui. This paper, based on its GDP and three industries data in 1991-2011, analyzes the trending of industrial structure evolution and the issues in innovation ability of resource industry, and studies the path from resources dependence to innovative drives in Liupanshui and presents suggestions.

Resources-based cities are now facing issues such as exhausting resources, single structure, environmental pollution and slow economy. To avoid the “resources curse”, it is necessary to promote an industrial transformation in resourcesbased cities to keep a sustainable development. Liupanshui, as an important resource city in western China, is in its bloom in mining sector with a fast economic growth. Now it is the best period for urban development, and the best time for transformation as well. This paper analyzes the issues and opportunities in Liupanshui’s transformation, and presents suggestions in path and strategy.

This paper, according to Liupanshui Statistics STBX 2010 STBZ and the data of Guizhou scientific research and experimental development (R&D) resource inventory, analyzes the fees, personnel and output in Liupanshuis R&D, compares them with those in Guizhou Province and in China. It also presents the issues and approaches of adjusting industrial structure, changing economic growth modes, and promoting sound and sustainable development. It is crucial to invest more in scientific research, focus on innovation, transform economy from resourcedriving technologydriving, to carry out selfinnovation strategy, and develop new and strategic industries. All the ways help Liupanshui intensify its innovation capacity.