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The census and management of hazard-bearing entities, along with the integrity of data quality, form crucial foundations for disaster risk assessment and zoning. By addressing the challenge of feature confusion, prevalent in single remotely sensed image recognition methods, this paper introduces a novel method, Spatially Constrained Deep Learning (SCDL), that combines deep learning with spatial constraint strategies for the extraction of disaster-bearing bodies, focusing on dams as a typical example. The methodology involves the creation of a dam dataset using a database of dams, followed by the training of YOLOv5, Varifocal Net, Faster R-CNN, and Cascade R-CNN models. These models are trained separately, and highly confidential dam location information is extracted through parameter thresholding. Furthermore, three spatial constraint strategies are employed to mitigate the impact of other factors, particularly confusing features, in the background region. To assess the method's applicability and efficiency, Qinghai Province serves as the experimental area, with dam images from the Google Earth Pro database used as validation samples. The experimental results demonstrate that the recognition accuracy of SCDL reaches 94.73%, effectively addressing interference from background factors. Notably, the proposed method identifies six dams not recorded in the GOODD database, while also detecting six dams in the database that were previously unrecorded. Additionally, four dams misdirected in the database are corrected, contributing to the enhancement and supplementation of the global dam geo-reference database and providing robust support for disaster risk assessment. In conclusion, leveraging open geographic data products, the comprehensive framework presented in this paper, encompassing deep learning target detection technology and spatial constraint strategies, enables more efficient and accurate intelligent retrieval of disaster-bearing bodies, specifically dams. The findings offer valuable insights and inspiration for future advancements in related fields. [ABSTRACT FROM AUTHOR]

Simple Summary: Both the warming climate and ultraviolet-B radiation are notable environmental factors affecting tadpole development. However, the phenotypes of tadpoles living at high altitudes may be improved by moderately warming temperatures, reducing or eliminating the negative effects of oxidative damage caused by cool temperatures or strong ultraviolet-B radiation. To verify this hypothesis, Rana kukunoris tadpoles, which live at high altitudes, were exposed to ultraviolet-B radiation and ultraviolet-B radiation-free environments at 14 (cool temperature) and 22 °C (warm temperature), respectively. Ultraviolet-B radiation and a warm temperature had opposite influences on several traits of the tadpoles, and the moderate temperature could compensate for or override the negative effects of ultraviolet-B radiation by increasing the tadpoles' preferred body temperature and critical tolerance temperature, thus enhancing the locomotion ability and thermal sensitivity of their antioxidant systems. The dark skin coloration and aggregation behavior of R. kukunoris tadpoles may also be effective strategies for allowing them to resist ultraviolet-B radiation and helping them to better adapt to a warming environment with stronger ultraviolet-B radiation. Thus, a moderate degree of warming may increase the capacity of living organisms to adapt to environmental changes and thus have positive effects on the development of tadpoles living at high altitudes. Both the warming climate and ultraviolet-B radiation (UVBR) are considered to be notable environmental factors affecting amphibian population decline, with particular effects on tadpole development. However, the phenotypes of tadpoles living at high altitudes may be improved by moderately warming temperatures, reducing or eliminating the negative effects of oxidative damage caused by cool temperatures or strong UVBR at high altitudes. To verify this hypothesis, Rana kukunoris tadpoles, which live at high altitudes, were used to test the effect of the interaction of temperature and UVBR on their development and antioxidant systems in a fully factorial design. The tadpoles were exposed to UVBR and UVBR-free environments at 14 (cool temperature) and 22 °C (warm temperature), respectively. UVBR and a warm temperature had opposite influences on several traits of the tadpoles, including their survival, developmental rate, individual size, preferred body temperature, thermal tolerance temperature, oxidative damage, and enzymatic and nonenzymatic antioxidant systems. The moderate temperature could compensate for or override the negative effects of UVBR by increasing the tadpoles' preferred body temperature and critical tolerance temperature, thus enhancing the locomotion ability and thermal sensitivity of their antioxidant systems. Furthermore, the dark skin coloration and aggregation behavior of R. kukunoris tadpoles may also be effective strategies for allowing them to resist UVBR and helping them to better adapt to a warming environment with stronger UVBR. Thus, it is possible that a moderate degree of warming may increase the capacity of living organisms to adapt to environmental changes and thus have positive effects on the development of tadpoles living at high altitudes. [ABSTRACT FROM AUTHOR]