The nitrogen nutrition index (NNI) is a significant agronomic statistic used to assess the nitrogen nutrition status of crops. The use of remote sensing to invert it is crucial for accurately diagnosing and managing nitrogen nutrition in crops during critical periods. This study utilizes the UHD185 airborne hyperspectral imager and the ASD Field Spec3 portable spectrometer to acquire hyperspectral remote sensing data and agronomic parameters of the winter wheat canopy during the nodulation and flowering stages. The objective is to estimate the NNI of winter wheat through a winter wheat nitrogen gradient experiment conducted in Leling, Shandong Province. The ASD spectral reflectance data of the winter wheat canopy were selected as the reference standard and compared with the UHD185 hyperspectral data obtained from an unmanned aerial vehicle (UAV). The comparison focused on analyzing the trends in the spectral curve changes and the spectral correlation between the two datasets. The findings indicated a strong agreement between the UHD185 hyperspectral data and the spectral data obtained by ASD in the range of 450–830 nm. A spectrum index was developed to estimate the nitrogen nutritional index utilizing the bands within this range. The linear model, based on the first-order derivative ratio spectral index (RSI) (FD₆₆₆, FD₈₂₆), demonstrated the highest accuracy in estimating the nitrogen nutrient index in winter wheat. The model yielded R² values of 0.85 and 0.75, respectively, and may be represented by the equation y = −2.0655x + 0.156. The results serve as a benchmark for future utilization of the UHD185 hyperspectral data in estimating agronomic characteristics of winter wheat.

A nuanced grasp of land use/cover changes, along with their drivers, is essential for effective land use management and ecological restoration. A new perspective on land use/cover changes analysis was proposed, which involves analyzing land use/cover changes and their driving forces at scales such as regional, geomorphological (plains, hilly area and mountainous area), and territorial spatial planning (core area and expansion collaborative area) scales based on the 2000, 2010, and 2020 land use/cover data in the Yellow River Basin of Henan Province. The land use/cover changes were scrutinized by employing the degree of land use/cover dynamics, transfer matrix, and change mapping model. The key drivers at each scale were unearthed by utilizing a geo-detector. The results show that: 1) The distribution characteristics of land types under different scale areas in the Henan section of the Yellow River Basin have obvious differences in that farmland is gathered in the plains, woodland in the mountains, and water in the core area. 2) From the dynamic attitude, it can be seen that the land use pattern of the plains and the core fluctuates sharply between 2000 and 2020, and the fluctuation of the mountain area is smaller, but the construction land in the mountain area has the most drastic change, the forest in the plains shrinks most obviously, and the core area has a large fluctuation of agricultural land. Compared with 2000-2010, the fluctuation amplitude between 2010 and 2020 is significantly reduced. 3) The dominant type of land change at all scales is the flow of agricultural land into construction land, while construction land also encroaches heavily on forest land. In the whole region, the plains and the core area, farmland also flows mainly into wetlands and waters, in the mountainous area, farmland flows heavily into forests and grasslands, and construction land continues to encroach on shrublands, and in the expansion and collaboration area, farmland encroaches heavily on grasslands. 4) Areas of intense land use change at all scales are concentrated in and around built-up areas. 5) The drivers of GDP and population dominate in the whole region, plains, core and extended collaboration areas, population and slope have the greatest influence in the hilly areas, slope and temperature play a major role in the mountainous areas, and the interactions of all factors show an increasing trend. The results of the study show that there are differences in land changes and their drivers at different scales in the Yellow River Basin of Henan, so the overall or local ecological restoration measures concerning the Yellow River Basin should be formulated with attention to problem orientation, comprehensiveness of the measures, and pertinence. The spatial layout of ecological, production, and living areas should be rationally planned according to local conditions and the rationalization of resource utilization.