[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-5093":3,"related-5093":67},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":9,"source_name":10,"source_url":6,"published_at":11,"category":12,"cover_url":9,"hotness":13,"is_selected":14,"score":15,"score_detail":16,"sources":18,"tags":20,"primary_topic":9,"secondary_topics":21,"classification":22,"search_phrases":43,"slug":44,"view_count":15,"doi":45,"paper":46,"created_at":66},5093,"“Calcare Cavernoso” as a key predisposing factor for sinkhole occurrence in Tuscany (Italy): inventory update, remote sensing detection, and GIS–ML susceptibility modelling","https:\u002F\u002Fdoi.org\u002F10.3301\u002Frol.2026.40","The “Calcare Cavernoso” (cavernous limestone) formation is a dolomitic carbonate unit characterized by a vacuolar texture and high intrinsic porosity, which favours groundwater-driven dissolution and cavity development and may predispose to subsidence. This study investigates the spatial relationship between sinkholes and the distribution of “Calcare Cavernoso” in Tuscany (Italy) and updates the regional subset of the ISPRA national sinkhole database. An integrated approach combined bibliographic information, targeted field surveys, historical cartography, and multi-source geospatial datasets. Geological and thematic layers were retrieved from the Tuscany “Geoscopio” portal, while Copernicus Sentinel-2 imagery was processed using the Normalized Difference Water Index (NDWI) to support the detection of flooded sinkholes. Historical maps were exploited to infer sinkhole persistence and potential evolutionary trends, including partial or complete infilling. All thematic layers (geology, faults, hydrography, quarries, mines, topography, and sinkholes) were harmonized, georeferenced, and rasterized on a 250 × 250 m grid within an ESRI ArcGIS environment. Susceptibility modelling was implemented using density-based proxies and an Extreme Gradient Boosting (XGBoost) framework, producing probability outputs subsequently grouped into classes to enhance operational usability. The results substantially expand the regional sinkhole inventory (from 88 to 1223 mapped features) and support a strong spatial association between sinkhole occurrence and “Calcare Cavernoso”, further corroborated by targeted field checks. The most influential susceptibility drivers include “Calcare Cavernoso”, low-slope settings, DTM-derived parameters, fault density, and anthropogenic underground activities (quarries and mines), while other variables show secondary or more complex contributions.","“洞穴状石灰岩”（Calcare Cavernoso）地层是一种白云质碳酸盐岩单元，以泡沫状结构和高原生孔隙率为特征，有利于地下水驱动的溶蚀作用和空洞发育，并可能诱发地面沉降。本研究探讨了意大利托斯卡纳地区天坑（sinkhole）与“洞穴状石灰岩”分布之间的空间关系，并更新了ISPRA国家天坑数据库的区域子集。研究采用综合方法，结合了文献资料、针对性野外调查、历史地图以及多源地理空间数据集。地质与专题图层取自托斯卡纳“Geoscopio”门户网站，同时利用归一化水体指数（NDWI）处理Copernicus Sentinel-2影像，以辅助识别积水天坑。历史地图用于推断天坑的持续性及潜在演化趋势，包括部分或完全充填。所有专题图层（地质、断层、水系、采石场、矿山、地形及天坑）在ESRI ArcGIS环境中进行了协调、地理配准，并栅格化为250 × 250 m网格。易发性建模采用基于密度的代理指标和极端梯度提升（XGBoost）框架，输出概率结果并进一步分组为不同类别，以增强操作实用性。研究结果大幅扩展了区域天坑编目（从88处增至1223处），并支持天坑发育与“洞穴状石灰岩”之间存在强空间关联，针对性野外核查进一步证实了这一结论。最具影响力的易发性驱动因子包括“洞穴状石灰岩”、低坡度环境、DTM衍生参数、断层密度以及人为地下活动（采石场和矿山），而其他变量则表现出次要或更为复杂的贡献。",null,"Rendiconti online della Società Geologica Italiana","2026-10-14T00:00:00Z","论文",10,false,0,{"impact":15,"substance":15,"depth":15,"authority":15,"freshness":15,"relevant":15,"comment":17},"该论文研究意大利托斯卡纳石灰岩与天坑易发性遥感与机器学习建模，属地质灾害领域，与三农、农业信息化、智慧农业、数字乡村无关。",[19],{"name":10,"url":6},[12],[],{"status":23,"locked":14,"version":24,"method":25,"evidence":26},"needs_review","2026-10-22.2","rules",{"candidates":27,"agricultural_evidence":14,"reason":42},[28,36],{"code":29,"score":30,"supported":31,"title":32,"abstract":34,"tags":35},"I3",8,true,[33],"remote sensing",[],[],{"code":37,"score":30,"supported":31,"title":38,"abstract":40,"tags":41},"I4",[39],"GIS",[],[],"农业相关性需要复核",[],"“CalcareCavernoso”asakeypredisposingfact-5093","10.3301\u002Frol.2026.40",{"doi":45,"openalex_id":47,"authors":48,"venue":10,"cited_by_count":15,"oa_url":58,"card":59,"direction":63,"ingested_from":65},"W7221776371",[49,52,55],{"name":50,"orcid":51},"Marina Funaro","https:\u002F\u002Forcid.org\u002F0009-0002-8909-173X",{"name":53,"orcid":54},"Stefania Nisio","https:\u002F\u002Forcid.org\u002F0000-0002-5422-3694",{"name":56,"orcid":57},"Sergio Madonna","https:\u002F\u002Forcid.org\u002F0000-0001-8862-0463","https:\u002F\u002Fwww.rendicontisocietageologicaitaliana.it\u002Ffulltext\u002F4337\u002Fcalcare-cavernoso-as-a-key-predisposing-factor-for-sinkhole-occurrence-in-tuscany-italy-inventory-update-remote-sensing-detection-and-gis-ml-susceptibility-modelling",{"tldr":60,"method":61,"finding":62,"direction":63,"opportunity":64},"更新托斯卡纳天坑清单，用遥感和GIS-XGBoost建模评估易发性。","Sentinel-2 NDWI、历史地图、ArcGIS栅格化、XGBoost易发","天坑从88增至1223个，与Calcare Cavernoso强相关，低坡度、断层和采矿影响大。","农业遥感与作物表型","可将天坑易发性模型迁移至农业区，评估岩溶塌陷对耕地与灌溉设施的潜在风险。","openalex","2026-10-16T23:30:28.468270Z",{"total":15,"page":68,"page_size":68,"items":69},1,[]]