The return of rural migrant workers through increasing agricultural income by expanding farming scale is significant for rural sustainable development without rural population loss. This paper selected six representative counties in Henan Province, China’s major grain-producing province, to conduct a questionnaire survey, investigated the incomes of farmers from farming and migrant workers, calculated moderate farming scale under different opportunity costs, and also estimated the agricultural population that can be supported by arable land resources. Results are as follows: (1) Under the traditional planting mode, annual per capita income of farmers in farming was USD 342.18, which was substantially lower than USD 5255.63 in migrant workers. This huge income gap has led to continuous rural population loss. (2) Under the opportunity cost of farming income equal to migrant workers income, moderate farming scales of the six selected counties were 1.39, 1.17, 1.22, 1.08, 1.34, and 1.01 ha, respectively. Under the 0.8x and 0.6x opportunity cost, corresponding moderate farming scales were 1.11, 0.94, 1.11, 0.86, 1.07, and 1.34 ha; and 0.84, 0.70, 0.73, 0.65, 0.80 and 1.01 ha, respectively. (3) On the basis of the three moderate farming scales and status quo of arable land resources, agricultural populations that can be supported by rural Henan Province were 8.0386 million, 10.0479 million and 13.3942 million, respectively. Findings can guide the formulation of rural revitalization strategic measures and the preparation of village territorial spatial planning.

Hyperspectral data are important for water color remote sensing. The inevitable noise will devalue its application. In this study, we developed a 1-D denoising method for water hyperspectral data, based on sparse representing. The denoising performance was compared with three commonly used methods in simulated and real datasets. The results indicate that: (1) sparse representing can successfully decompose the hyperspectral water-surface reflectance signal from random noises; (2) the proposed method exhibited better performance compared with the other three methods in different input signal-to-noise ratio (SNR) levels; (3) the proposed method effectively erased abnormal spectral vibrations of field-measured and remote-sensing hyperspectral data; (4) whilst the method is built in 1-D, it can still control the salt-and-pepper noise of PRISMA hyperspectral image. In conclusion, the proposed denoising method can improve the hyperspectral data of an optically complex water body and offer a better data source for the remote monitoring of water color.

Scientifically measuring the quantitative coupling relationship between urban–rural construction land (URCL) and population and formulating URCL utilization countermeasures are needed for protecting cultivated land resources, intensive utilization of land resources, and sustainable socioeconomic development. This study proposed an improved transition process theory of URCL and population and a coupling model of polar coordinates. Then, the coupling model was applied to Henan Province in China to analyze the coupling relationship between URCL and population, showing that the coupling relationship between URCL and urban–rural population (URP) in the province was unreasonable. However, the coupling rationality between rural construction land (RCL) and rural population (RP) had a significant improvement tendency. Furthermore, the coupling relationship between URCL and the population of prefecture-level cities in Henan province was analyzed, and the coupling model of polar coordinates proposed in this study achieved satisfactory results. Thus, compared with the commonly used Tapio’s decoupling model of elasticity, the coupling model further extends the concept of coupling analysis to the coupling type, coupling strength, and coupling rationality. The extension makes the measurement of the quantitative coupling relationship between URCL and population more scientific, comprehensive, and accurate.