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Well-facilitated farmland (WFF) construction is greatly responsible for agricultural sustainable development. How to quantitatively plan the WFF construction distribution and schedule is still challenging. This study thus introduced a simple but robust method, and took the typical dryland Yulin city to spatially identify its potential WFF construction areas and temporally determine construction priorities based on public data. By integrating satellite-observed croplands with survey-based statistical data, this study firstly obtained density maps of constant croplands. We found that constant cropland densities decreased from west to east in Yulin city. Jingbian and Dingbian counties of the west gave relatively dense distributions. Secondly, by overlaying evaluation indictors of WFF construction, we found over 96% of constant croplands had WFF construction potentials. Slope and fractional vegetation coverage (FVC) showed evidently spatial differences, which comprehensively reflected the potentials and difficulties of WFF construction. Therefore, an index SF, by considering normalized slope and FVC, was subsequently introduced to rank potential WFF construction priorities. According to the completion ratio and the assumption that giving priorities to develop better basic condition regions, batches of WFF construction areas were identified under the equal proportion planning scenario for each county (S1). Besides, a scenario of city-wide unified planning (S2) was also discussed. WFF construction areas in S2 were further concentrated in northwestern counties compared to those in S1. Both scenarios recommended that construction priorities were given to northwestern counties. This study could provide valuable references for arranging distributions and schedules of WFF construction.

Rural development degree (RDD) evaluation is a very valuable guidance for rural sustainable development. Earlier studies of RDD evaluatons more focusd on establishing index system, analysing spatial–temporal evolving patterns and functional differentiations. Weighting assignment (WA) method selection is a vital step for rural development degree (RDD) evaluation, but impacts of different WA methods on indicator weight determination and RDD evaluation were not well clarified. This study therefore employed three dominant WA methods, covering equal weight method, entropy method and mean square error method, along with a developed RDD evaluation index system to compare the differences of indicator weights and uncertainties of RDD evaluation. The results indicated that the spatial patterns of three WA-based RDD maps had great differences although using the same evaluation indicators. The RDD types with the largest proportion generated from different WA methods were also spatially various. Spatial distributions of RDD generated by various WA methods regions performed largely differences in central, northeastern and southwestern China. Our analyses found that the differences from industrial prosperity dimension and ecology livability dimension owing to utilizing different WA methods were largely responsible for the RDD spatial distributions in this study. This study gave some potential suggestions for WA method selection in RDD evaluation according to the data characteristics, WA method principles and application requirements. Among them, entropy method was suitable for indicator data with great dispersion degree and mean square error method would be better describe indicator differences with large indicator number. Besides, this study also underlined that WA-derived uncertainties should be paid more attentions in rural development and rural revitalization evaluation.

China's Loess Plateau (LP) is one of the most typical regions with serious soil erosion. Its ecological restoration, economic development, and social progress are directly related to realizing China's national sustainable development goals (SDGs). With intensive field investigations, comprehensive analyses of statistical data, remote sensing data, and local monitoring data, this current research explored the achievements in local ecological restoration and economic development, discussed the main problems faced by the LP, and assessed the sustainable development status of the LP. Moreover, drawing from a 3C system approach (classification-coordination-collaboration), this research proposed the sustainable development strategies for more sustainable LP. We found that the LP's ecological restoration and economic development made remarkable achievements since 2000. However, the environment was still fragile and regional development was still lagging behind. In realizing SDGs, further improvements on clean water and sanitation, decent work and economic growth, industry, innovation and infrastructure, reduced inequalities, and climate action are needed. Coordinated and collaborated efforts are expected from multiple hierarchical levels including household, watershed, region, and nation in developing LP. Specifically, human-environment interactions should be highlighted at the household level, upstream-downstream interactions that are catering to the particular characteristics of the LP is encouraged at the watershed level, and regional and urban-rural interactions shall play an increasingly important role at the regional level. While at the national level, the central government should carry out a systematic overarching design. To better realize the goal of more sustainable LP, this research calls for (1) forming an actor-network consists of multi stakeholders, including the central government, local government, watershed, families, ecosystem and environment, enterprises, NGOs, and scientists, and (2) paying attention to ecosystem management, ecological restoration, industrial structure optimization, ecological agriculture, rural infrastructure, and ecological civilization construction in the future development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)