SPAD value was measured by a portable chlorophyll instrument, which can reflect the relative chlorophyll content of vegetation well. Chlorophyll is an important organic chemical substance in plants that acquires and transmits energy during photosynthesis. The continuous spectral curve of winter wheat can be obtained rapidly in a specific band range by using hyperspectral remote sensing technology to estimate the SPAD value of winter wheat, which is of great significance to the growth monitoring and yield estimation research of winter wheat. In this study, with winter wheat as the research object, the spectral data and corresponding SPAD value in different growth stages were used as the data source, 20 kinds of data preprocessing spectra and sensitive spectral indices set the data as model input values, the partial least square regression (PLSR) model was established to estimate the SPAD value, and the model estimation results of different model input values at different growth stages were compared in detail. The results showed that the set of sensitive spectral indices selected in this study as input values can effectively improve the accuracy and stability of the PLSR model. In addition, the effects of 20 spectral data pretreatment methods on the estimation results of the SPAD value were compared and analyzed in different growth stages. It was found that the spectral data pretreated by the combination of wavelet packet denoising, first-order derivative transformation and principal component analysis can improve the accuracy and stability of PLSR model, and it is suitable for all growth stages. The results also showed that the estimation model is highly sensitive to the standard deviation of the SPAD value (STD_chl) in sample sets. When the standard deviation is greater than 5.5 SPAD, the larger the STD_chl is, the higher the model estimation accuracy is, and the more stable the model is. At this time, the model estimation accuracy is higher (R²_V is greater than 0.5, ratio of performance to deviation is greater than 1.4), which can meet the estimation requirements of the SPAD value.

The conflict between economic development and ecological protection continues to intensify, highlighting the necessity for constructing regional ecological security patterns (ESPs) to reconcile the relationship between development and protection effectively. This study used the GMOP and PLUS model to simulate future land use changes by 2030 under the following three scenarios: natural development (ND), ecological protection (EP), and economic development (ED). Employing the MSPA model and circuit theory, it identified ecological source areas and constructed the ESP for the Beijing–Tianjin–Hebei urban agglomeration (BTH) from 2000 to 2030. The results indicate that the proportion of ecological source areas increased from 22.24% in 2000 to 23.09% in 2020, the EP scenario showing the highest proportion of ecological source areas compared with the other two scenarios. These areas are densely distributed in the northern and western mountainous regions, with sparse distributions in the southern plains. The number of ecological corridors grew from 603 in 2000 to 616 in 2020, with the EP scenario having more corridors than the other two scenarios. From 2000 to 2030, corridors in the northern and western mountainous areas were denser, shorter, and more variable, while those in the southern plains were less dense, longer, and relatively stable. Over two decades, habitat areas for species in BTH increased, while landscape connectivity decreased. Compared with 2020 and the other two scenarios, the EP scenario saw an increase in habitat areas and improved landscape connectivity. The impact on ecological corridors and improvement areas primarily arose from a combination of socio-ecological drivers (e.g., elevation, slope, population), while the influence on restoration and key areas mainly stemmed from ecological factors (e.g., elevation, temperature, NDVI, precipitation). The findings demonstrate that distinguishing different geomorphological units to improve and restore the regional environment, while considering socio-ecological drivers, is crucial for restoring the overall ESP and landscape connectivity of BTH.

Frequent landslides and other geological disasters pose a serious threat to human life and infrastructure in the Upper Yellow River. Detecting active landslides and ascertaining their impact necessitate the determination of deformation characteristics. In this study, we developed an integrated method combining interferometric synthetic aperture radar and high-resolution optical satellite remote sensing to detect active landslides in the Upper Yellow River region from Longyang Gorge to Lijia Gorge. Sentinel-1 satellite data from January 2019 to April 2021 with ascending and descending orbits were adopted to obtain deformation using the STACKING and interferometric point target analysis techniques. A 97.08% overlap rate in the detected results from the two InSAR technologies confirmed the suitability of both approaches. The missing detection rates (6.79% & 8.73%) from single line-of-sight (LOS) InSAR results indicate the necessity of different orbit direction data. Slight deformation rate changes (<4 mm/month) before and after rainy seasons of the Lijia Gorge landslide group indicate that precipitation exerted little impact on slope activity. This study supports the feasibility of integrated methods for the detection and analysis of active landslides in the Upper Yellow River and other regions.

Monitoring and analyzing reservoir landslides are essential for predicting and mitigating geohazards, which are crucial for maintaining sustainability and supporting socio-economic development in reservoir areas. High spatiotemporal resolution is vital for effective reservoir landslide monitoring and analysis. For this purpose, we improved the resolution of the differential interferometric synthetic aperture radar (DInSAR) technique by fusing two-path deformation results from an overlapping Sentinel-1 area. First, we summarized the mathematical ratio relationship between deformation from the two paths. Second, time-series linear interpolation and time-reference difference removal were applied to the two separate deformation results of time-series DInSAR. Third, a ratio algorithm was adopted to fuse the deformation of the two paths into one integrated time-series result. The standard deviations of the deformation before and after fusion were similar, confirming the accuracy of the fusion results and feasibility of the method. From the integrated deformation, we analyzed the hydraulic impact, mechanisms, and physical processes associated with four reservoir landslides in the Three Gorges Reservoir area of China, accounting for rainfall and water-level data. The comprehensive analysis presented herein provides new insights on the hydraulic mechanisms of reservoir landslides and verifies the efficacy of this new integrated method for landslide investigation and monitoring.