Unmanned aerial vehicle (UAV) equipped with multispectral cameras for remote sensing (RS) has provided new opportunities for ecological and agricultural related applications for modelling, mapping, and monitoring. However, when the multispectral images are used for the quantitative study, they should be radiometrically calibrated, which accounts for atmospheric and solar conditions by converting the digital number into a unit of scene reflectance that can be directly used in quantitative remote sensing (QRS). Indeed, some of the present applications using multispectral images are processed without precise calibration or with coarse calibration. The radiometric calibration of images from the UAV platform is quite difficult to perform, as the imaging condition is different for every single image. Thus, a standard procedure is necessary for a systematical radiometric calibration method to generate multispectral images with unit reflectance. Further, these images can be used to calculate vegetation indices, which are useful in monitoring vegetation phenology. These vegetation indices are considered as a potential screening tool to know the plant status, such as nitrogen, chlorophyll content, green leaf biomass, etc. This study focuses on a series of radiometric calibrations for multispectral images acquired from different flight altitudes, time instants, and weather conditions. Radiometric calibration for multispectral images is performed using the linear regression method (LRM). The main contribution involves (1) affirming the optimal calibration targets and assessing the atmospheric effects of different flights using the single scene of images; (2) to evaluate the effects of mosaic images with the LRM; (3) to propose and validate a universal calibration equation for the Mini Multiple Camera Array (MCA) 6 camera. The obtained results show that the three calibration targets, such as the dark, moderate, and white, are better for the Mini MCA 6 camera. The atmospheric effects increase with the increase of flight altitudes for each band, and the camera effect is of a fixed number. However, the camera effect and atmospheric attenuation to reflectance from different altitudes were relatively low considering the accuracy assessment. The performance measures namely, mean absolute deviation (indicated as V) and root mean square error (RMSE) between single and mosaic images show that the mosaic will not influence too much reflectance. The LRM performs well in all weather conditions. The universal calibration equation is suitable to apply to the images acquired during a sunny day and even with a little cloud.

Land use transition is essentially one of the manifestations of land use/cover change (LUCC). Although a large number of studies have focused on land use transitions on the macro scale, there are few studies on the micro scale. Based on the data of two high-resolution land use surveys, this study used a land use transfer matrix and GeoDetector model to explore the spatial-temporal patterns and driving forces of land use transitions at the village level in Pu County over a ten-year period. Results show that Pu County has experienced a drastic process of land use transition. More than 80% of cropland and grassland have been converted to forest land, and over 90% of the expansion of built-up land came from the occupation of forest land, cropland, and grassland. The driving forces of land use transition and its magnitude depended on the type of land use. The implementation of the policy of returning farmland to forest, or grain-for-green (GFG) was the main driving force for the large-scale conversion of cultivated land to forest land in Pu County. In the context of policy of returning farmland to forests, the hilly and gully regions of China’s Loess Plateau must balance between protecting the ecology and ensuring food security. Promoting the comprehensive consolidation of gully land and developing modern agriculture may be an important way to achieve a win-win goal of ecological protection and food security.

Drought disasters jeopardize the production of vegetation and are expected to exert impacts on human well-being in the context of global climate change. However, spatiotemporal variations in drought characteristics (including the drought duration, intensity, and frequency), specifically for vegetation areas within a growing season, remain largely unknown. Here, we first constructed a normalized difference vegetation index to estimate the length of the growing season for each pixel (8 km) by four widely used phenology estimation methods; second, we analyzed the temporal and spatial patterns of climate factors and drought characteristics (in terms of the Standardized Precipitation Evapotranspiration Index (SPEI)), within a growing season over vegetation areas of the northern hemisphere before and after the critical time point of 1998, which was marked by the onset of a global warming hiatus. Finally, we extracted the highly drought-vulnerable areas of vegetation by examining the sensitivity of the gross primary production to the SPEI to explore the underlying effects of drought variation on vegetation. The results revealed, first, that significant (p < 0.05) increases in precipitation, temperature, and the SPEI (a wetting trend) occurred from 1982 to 2015. The growing season temperature increased even more statistically significant after 1998 than before. Second, the duration and frequency of droughts changed abruptly and decreased considerably from 1998 to 2015; and this wetting trend was located mainly in high-latitude areas. Third, at the biome level, the wetting areas occurred mainly in the tundra, boreal forest or taiga, and temperate coniferous forest biomes, whereas the highly drought-vulnerable areas were mainly located in the desert and xeric shrubland (43.5%) biomes. Our results highlight the fact that although the drought events within a growing season decreased significantly in the northern hemisphere from 1998 to 2015, the very existence of a mismatch between a reduction in drought areas and an increase in highly drought-vulnerable areas makes the impact of drought on vegetation nonnegligible. This work provides valuable information for designing coping measures to reduce the vegetative drought risk in the Northern Hemisphere.

Drought and extreme precipitation events can have major environmental and socioeconomic impacts. Yet, how drought and wetness are changing in China in the context of climate change is still under debate. Here, the standardized precipitation evapotranspiration index (SPEI) was calculated based on high-quality and more densely distributed daily meteorological observation data from 655 stations across China during the period of 1965–2017. National and regional trends in drought and wetness and their various characteristics, including intensity, duration, frequency, and percentage of area affected, were investigated at multiple timescales. We found that (1) China as a whole has undergone a significant (p < 0.01, trend significant at the level of 0.01) wetting trend, with an annual SPEI increase of 0.5 per decade from 1965 to 2017. A seasonal wetting trend was also observed, with summer being particularly significant (p < 0.01). (2) Regionally, each subregion also showed a wetting trend during the study period except for southwest China, and these wetting trends were significant in the western region of northwest China (p < 0.05, trend significant at the level of 0.05), the Tibetan Plateau (p < 0.05), and eastern China (p = 0.06). (3) Decadal trends in drought and wetness intensity, frequency, duration, and affected areas indicated that the drought events also became more severe and more frequent in the last two decades, and the areas showing drying trends were mainly located in southwest China (especially for the autumn drought) and the southwestern parts of eastern northwest China (spring drought). Our results highlight the fact that although a wetting trend was observed in most regions of China, the frequent occurrence of severe drought in southwest China and the southwestern parts of eastern northwest China still present a considerable threat to both the environment and society. Therefore, how to effectively coordinate the allocation of regional water resources to cope with drought risk under future climate change will be particularly important.

The sector that suffers the most directly from drought is agriculture, and drought is expected to become more serious in the context of global warming. Effectively evaluating the agricultural drought risk is fundamental to establishing present water resource management and guaranteeing food security. Therefore, southeast Gansu province was selected for this study as a typical region for which to analyze drought trends and assess agricultural drought risk. Trends for the period from 1967 to 2018 were analyzed at 21 locations by using the Mann–Kendall method, and drought was quantified by using the Standardized Precipitation Evapotranspiration Index (SPEI). Spatial characteristics of the agricultural drought risk that emphasized the combined role of hazards and vulnerability were investigated at a 1-km grid scale. Results showed that the annual SPEI exhibited a nonsignificant increasing trend from 1967 to 1990 but that after 1990, the SPEI showed a steep downward trend of 0.1 per decade. The drying trend from 1990 to 2018 was mainly attributed to a significant increase in the reference evapotranspiration. Approximately 16.1% of the agricultural areas are exposed to an extremely high risk and 42.2% are exposed to high risk of drought. Moreover, 56.7% of the extremely high-risk agricultural areas are located in the Longnan region, which strongly suggests that more attention must be paid to preparedness for and mitigation of drought in the Longnan region. This study offers a scientific approach to evaluating the risk of agricultural drought in dry agricultural regions.

Increasing temperatures, greater carbon dioxide concentrations, and changes in related climatic variables will continue to affect the growth and yields of agricultural crops. Rice (Oryza sativa L.) is extremely vulnerable to these climatic changes. Therefore, investigating the degree to which climate changes could influence rice yields and what effective adaptive strategies could be taken to mitigate the potential adverse impacts is of vital importance. In this article, the impacts of climate change on rice yields in Zhejiang province, China, were simulated under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. The impacts of climate change, with and without CO₂ fertilization effects, were evaluated and the three most effective adaptive measures were examined. Compared with the yield for the baseline time of 1981–2010, the simulated average yields of all cultivars were inevitably projected to decrease under both RCPs when the CO₂ fertilization effects were not considered during the three periods of the 2020s (2011–2040), 2050s (2041–2070), and 2080s (2071–2099), respectively. Declines in rice yields were able to be alleviated when the CO₂ fertilization effects were accounted for, but the yields were still lower than those of the baseline. Therefore, the three adaptive measures of advancing planting dates, switching to high-temperature-tolerant cultivars, and breeding new cultivars were simulated. The results indicated that adaptive measures could effectively mitigate the adverse effects of climate change. Although the simulation had uncertainties and limitations, the results provide useful insights into the potential impacts of climate change in Zhejiang province while also proposing adaptive measures.