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Given global climate change and rapid land cover changes due to human activities, accurately identifying, extracting, and monitoring the long-term evolution of wetland resources is profoundly significant, particularly in areas with fragile ecological conditions. Gansu Province, located in northwest China, contains all wetland types except coastal wetlands. The complexity of its wetland types has resulted in a lack of accurate and comprehensive information on wetland changes. Using Gansu Province as a case study, we employed the GEE platform and Landsat time-series satellite data, combining high-quality sample datasets with feature-optimized multi-source feature sets. The random forest algorithm was utilized to create wetland classification maps for Gansu Province across eight periods from 1987 to 2020 at a 30 m resolution and to quantify changes in wetland area and type. The results showed that the wetland mapping method achieved robust classification results, with an average overall accuracy (OA) of 96.0% and a kappa coefficient of 0.954 across all years. The marsh type exhibited the highest average user accuracy (UA) and producer accuracy (PA), at 96.4% and 95.2%, respectively. Multi-source feature aggregation and feature optimization effectively improve classification accuracy. Topographic and seasonal features were identified as the most important for wetland extraction, while textural features were the least important. By 2020, the total wetland area in Gansu Province was 10,575.49 km2, a decrease of 4536.86 km2 compared to 1987. The area of marshes decreased the most, primarily converting into grasslands and forests. River, lake, and constructed wetland types generally exhibited an increasing trend with fluctuations. This study provides technical support for wetland ecological protection in Gansu Province and offers a reference for wetland mapping, monitoring, and sustainable development in arid and semi-arid regions.

Background: The SPF10 LiPA-25 system for human papillomavirus (HPV) detection with high analytical performance is widely used in HPV vaccine clinical trials. To develop and evaluate more valent HPV vaccines, other comparable methods with simpler operations are needed. Methods: The performance of the LiPA-25 against that of other 7 assays, including 4 systems based on reverse hybridization (Bohui-24, Yaneng-23, Tellgen-27, and Hybribio-16) and 3 real-time polymerase chain reaction (PCR) assays (Hybribio-23, Bioperfectus-21, and Sansure-26), was evaluated in selected 1726 cervical swab and 56 biopsy samples. A total of 15 HPV genotypes (HPV 6, 11, 16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, and 66) were considered for comparison for each HPV type. Results: Among the swab samples, compared to LiPA-25, compatible genotypes were observed in 94.1% of samples for Hybribio-23, 92.8% for Yaneng-23, 92.6% for Bioperfectus-21, 92.4% for Hybribio-16, 91.3% for Sansure-26, 89.7% for Bohui-24, and 88.0% for Tellgen-27. The highest overall agreement of the 15 HPV genotypes combined was noted for Hybribio-23 (κ = 0.879, McNemar's test: P = 0.136), followed closely by Hybribio-16 (κ = 0.877, P< 0.001), Yaneng-23 (κ = 0.871, P < 0.001), Bioperfectus-21 (κ = 0.848, P < 0.001), Bohui-24 (κ = 0.847, P < 0.001), Tellgen-27 (κ = 0.831, P < 0.001), and Sansure-26 (κ = 0.826, P < 0.001). Additionally, these systems were also highly consistent with LiPA-25 for biopsy specimens (all, κ > 0.897). Conclusions: The levels of agreement for the detection of 15 HPV types between other 7 assays and LiPA-25 were all good, and Hybribio-23 was most comparable to LiPA-25. The testing operation of HPV genotyping should also be considered for vaccine and epidemiological studies.