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Measurement technology based on machine vision has been widely used in various industries. The development of vision measurement technology mainly depends on the process of photosensitive components and the algorithm of processing a target image. In the high-precision dimension measurement of machined metal parts, the high-resolution imaging device usually exposes the cutting texture of the metal surface and affects the accuracy of measurement algorithm. At the same time, the edges of machined metal parts are often chamfered, which makes the edges of objects in the picture overexposed in the lighting measurement environment. These factors reduce the accuracy of dimensioning metal parts using visual measurements. The traditional vision measurement method based on color/gray image makes it difficult to analyze the physical quantities in the light field except for the light intensity, which limits the measurement accuracy. Polarization information can more carefully depict the edge contour edge information in the scene and increase the contrast between the foreground and the background. This paper presents a method to improve the measurement accuracy of machined metal parts by using polarization vision. The incident angle of the light source is optimized according to the complex refractive index of the metal material, and the degree of polarization image with enhanced edge contour features of the ROI (region of interest) is obtained. The high-precision measurement of cylindrical brass motor components is realized by using the method of reprojection transformation correction and maximum correlation template matching (NCC) for rough positioning, as well as the method of edge extraction and optimal fitting. The experimental results show that for copper parts with a tolerance range of ±0.1 mm, the average measurement error and maximum measurement error are within 0.01 mm, which are higher than the existing color/gray image measurement methods.

Based on the daily data of 24 meteorological warfare points in Ningxia, the potential evaporation (ET0), the Mann–Kendall test (MK), and inverse distance weight interpolation were used to analyze the temporal and spatial changes in the potential evaporation at different scales, and the Pearson correlation coefficient was used to determine the growth rate in Ningxia. The atmospheric circulation influencing factors of seasonal potential evaporation were established, and the prediction model of potential evaporation in the growing season in Ningxia was established by stepwise linear regression, using mean absolute error (MAE), root mean square error (RMSE), and mean absolute percentage error (MAPE). The error test was carried out, and the results show the following: (1) The areas with larger potential evaporation during the growing season are mainly the central area of Ningxia and the northern side of the northern area. The presence on the north side tends to decrease. (2) On the monthly scale, the potential evaporation continued to increase from April to June, reached the maximum in June, continued to decrease from July to October, and was the smallest in October. (3) During the MK test in the growing season, the change in potential evaporation in the growing season showed an “increase–decrease” trend. The results of the monthly MK test show that the potential evaporation in April, May, and June has shown an increasing trend over the past 30 years, and the UF value in July, August, and October has been relatively high. The change trend of potential evaporation has been relatively stable, and the potential evaporation in September has shown a downward trend over the past 20 years. (4) The prediction model of potential evaporation in the growing season established by the circulation factor has shown a good effect in Ningxia and can be used to establish the scheduling prediction of irrigation water.

Xinjiang has a serious wind erosion problem due to its fragile ecological condition and sensitivity to climate change. Wind erosion climatic erosivity is a measure of climatic factors influencing wind erosion; evaluating its spatiotemporal variations and relationship with the large-scale circulation pattern can contribute to the understanding of the climate change effect on wind erosion risk. Thus, this study quantified the wind erosion climatic erosivity and examined the connections between climatic erosivity and climate indices using trend analysis, geo-statistical analysis, and cross-wavelet analysis based on the observed daily meteorological data from 64 weather stations in Xinjiang, China during 1969–2019 (50 years). The results indicated that the climatic erosivity showed a significant downward trend at seasonal and annual scales over the past 50 years. Strong seasonality in the C-factor was found, with its highest values in the spring and summer and its lowest values in the winter. The average climatic erosivity was weaker during El Niño events than during La Niña events. The impact of El Niño events on climatic erosivity in Xinjiang continued from the beginning of the event to two months after the end of the events. The La Niña events had a lag effect on the climatic erosivity in Xinjiang, with a lag period of 4 months. From a statistical perspective, the El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Arctic Oscillation (AO) indices showed relationships to the climatic erosivity in Xinjiang in terms of their correlation and periodicity. The relationships between the climatic erosivity and ENSO were not clearly positive or negative, with many correlations advanced or delayed in phase. The NAO and AO indices showed a consistent in-phase relationship with climatic erosivity on significant bands, whereas the profound mechanisms involved in this require further study. The results of this study provide a preliminary perspective on the effect of large-scale atmospheric circulation on wind erosion risk in arid and semi-arid regions.

Under the current urban renewal background, the subjective attitude of stakeholders directly affects the feasibility of planning projects in the development or protection activities related to brownfield redevelopment. It is key that the public effectively participates in planning and decision-making to explore the suitable expression method of public attitude. In this paper, Jigang, Jinan, Shandong Province is taken as an example. By using participatory mapping and semi-structural interviews, the landscape perceived value of 365 (342 valid) stakeholders in the original site of Jigang is investigated. By using hot spot analysis, correspondence analysis and compatibility index analysis, the spatial composition of public perceived landscape value, the correspondence between landscape value and land use and its compatibility with existing conservation and renewal schemes are revealed. On this basis, three types of brownfield land redevelopment attitude areas are identified. The results show that: 1. The attitude of Jinan Iron and Steel Group’s renewal based on the degree of compatibility is location-dependent, and the spatial difference analysis of this attitude provides more detailed data support for the protection and renewal design, planning management and conflict control; 2. The landscape perceived value of case stakeholders has regularity in spatial distribution and is related to a certain material landscape foundation (land use), which is beneficial in explaining the possible social phenomena caused by landscape change; 3. Participatory cartography combined with landscape value investigation provides an effective method for the study of perceived landscape. Through cartographic visualization, statistical analysis and index model construction, the spatial structure characteristics of perceived landscape value can be revealed. It can provide effective decision support for brownfield urban renewal projects, solve the problem that the current upper-level planning of such renewal is not matched with the actual demand, and improve the vitality of brownfield sites in the development area.