The imbalance between human activities and Earth's natural surface adversely affects the sustainability of the Earth system. From an understanding of the suitability of surface functions and potential ramifications of policy decisions, this study proposes a sustainable geographical pattern. It introduces a national‐to‐provincial downscaling approach to optimizing a national‐scale zoning scheme that covers 60%–80% of land development and protection functions in China and to creating a major function zoning model. Taking China as the case study area, the following function zones are identified: urbanization zones, food security zones, ecological security zones, and heritage protection zones. This study then proposes a three‐dimensional index system and algorithm, develops individual and integrated assessments for the major functions of the land grid, and produces national‐scale and provincial‐scale major function zoning schemes consisting of county‐level administrative cells, the first schemes to create a blueprint for a sustainable national land pattern in China through optimized convergence. In total, 5% of China's land area is covered by urbanized zones, 28% by food security zones, 55% by ecological security zones, and 12% by heritage protection zones. In the future, there will be 805 urbanization administrative units, 790 food security counties, 780 ecological security counties, and 8,151 heritage protection zones. The scheme created using the model developed in this study is 95% consistent with the final scheme implemented by China's central government, and it has a high degree of robustness and precision. It can serve as a reference for scientific research and decision‐making concerning sustainable development in developing countries.

It is a matter of public consensus that China's high growth rate has been achieved at the expense of natural resources and the environment, leading to serious risks to sustainability. This research, which proposes a theoretical model to forewarn of risks to regional developmental sustainability in China, constitutes the first empirical evaluation of this to be undertaken there. The results show that: (a) the areas at risk cover almost 43% of the land and 44% of the population of mainland China. In those areas, 83.56% of people at risk are threatened by the low carrying capacity of the environment and limited water resources. (b) With 70% of the total population living in “at risk” areas, urbanization zones remain as the primary category suffering from overload across China. Extensive industrialization has resulted in environmental pollution, which contributes the most to the forewarning status, while the secondary cause is found to be the special coupling of the scarcity of natural water resources and their inefficient use. In addition, most urban conglomerations suffer from pollution by industrial production and household consumption, which tends to extend to their surrounding agricultural areas. Extensive mineral exploitation in ecologically fragile areas has made them increasingly more vulnerable to disturbances from their neighboring resource‐driven urban areas. The paper uses these findings to suggest how to intensify the special regulatory administration of resources and the environment, and to transform approaches to industrialization, in order to address sustainable development issues in developing countries.

Drought is a complex hazard that has more adverse effects on agricultural production and economic development. Studying drought monitoring techniques and assessment methods can improve our ability to respond to natural disasters. Numerous drought indices deriving from meteorological or remote sensing data are focused mainly on monitoring single drought response factors such as soil or vegetation, and the ability to reflect comprehensive information on drought was poor. This study constructed a comprehensive drought-monitoring model considering the drought factors including precipitation, vegetation growth status, and soil moisture balance during the drought process for the Jing-Jin-Ji region, China. The comprehensive drought index of remote sensing (CDIR), a drought indicator deduced by the model, was composed of the vegetation condition index (VCI), the temperature condition index (TCI), and the precipitation condition index (PCI). The PCI was obtained from the Tropical Rainfall Measuring Mission (TRMM) satellite. The VCI and TCI were obtained from a moderate-resolution imaging spectroradiometer (MODIS). In this study, a heavy drought process was accurately explored using the CDIR in the Jing-Jin-Ji region in 2016. Finally, a three-month scales standardized precipitation index (SPI-3), drought affected crop area, and standardized unit yield of wheat were used as validation to evaluate the accuracy of this model. The results showed that the CDIR is closely related to the SPI-3, as well as variations in the drought-affected crop area and standardized unit yield of crop. The correlation coefficient of the CDIR with SPI-3 was between 0.45 and 0.85. The correlation coefficient between the CDIR and drought affected crop was between −0.81 and −0.86. Moreover, the CDIR was positively correlated with the standardized unit yield of crop. It showed that the CDIR index is a decent indicator that can be used for integrated drought monitoring and that it can synthetically reflect meteorological and agricultural drought information.

Ordos City lies in a semiarid-arid farm pastoral region in north China. In recent years, as an ecological security barrier and ecological vulnerable and sensitive region, the intensification of human activities and climate change in the foreseeable future have aroused people’s attention to ecological security issues. Based on the meteorological data of MOD13Q1 and the socioeconomic activity data in the same period, the variation characteristics of annual and seasonal vegetation NDVI, the response of vegetation NDVI to climate change, and the impact of human activities on vegetation NDVI in Ordos City from 2000 to 2020 were obtained by using trend analysis, sustainability analysis, and path analysis. The results showed that: (1) Ordos City vegetation NDVI showed an obvious growth trend, except for the interannual growth rate (0.0075/a), the growth rate in autumn increased faster than in other seasons (0.0067/a); (2) the future trend of vegetation NDVI in Ordos City is mainly anti-continuous improvement. If no effective measures are taken, the vegetation NDVI will degrade in the future; (3) precipitation was the main climate factor in the vegetation growth compared with temperature. An increase in precipitation promoted vegetation growth directly, while an increase in temperature showed a negative effect by reducing precipitation in the whole growing season; (4) the utilization pattern greatly affects the spatial distribution of vegetation NDVI, and stable land use can improve the utilization of vegetation.