More visible greenspace, stronger heart? Evidence from ischaemic heart disease emergency department visits by middle-aged and older adults in Hubei, C

基于“人机对抗生成照片-感知数据集”（可参考文章），我们采用武汉地区的街景打分数据训练了六种感知（美观、无聊、压抑、活力、安全和富裕）的深度网络模型，免费提供给各位老师和同学们用于科学研究。感谢中国地质大学（武汉）地理与信息工程学院2017级软件工程系的王宇同学分享。相关参考文献和下载地址请见本文末

关于延期举办SpatialDI 2022的通知 致尊敬的各位参会代表： 近期全国多地出现新冠疫情本土确诊病例，诸多省市（区）陆续出台了最新的疫情防控政策和严格的旅行禁令。为切实保障参会代表人身安全，配合武汉相关防疫部门贯彻落实疫情防控工作部署，经大会组委会和分会主席团审慎共同研究决定，将原定于2022年4月14-16日在武汉举办的“第三届中国空间数据智能学术会议（SpatialDI 2022）” ，延期至2022年6月8-10日举行，相关参会形式和内容将另行通知。 已经完成注册缴费的代表，请您保留好注册及缴费信息，相关信息对延期后会议依然有效。组委会将按照相关规定和财务管理流程妥善处理相关变更事宜，因会议延期给参会代表带来不便，我们深表歉意，敬请谅解！ 我们将充分做好本次大会延期召开的各项工作，期待在疫情得到有效控制之后，各位专家、学者继续支持本次会议的举办。 会务组联系人： 范明 15927333030 李应争 13349838503 SpatialDI 2022会务组 2022年4月6日

标题：UrbanVCA v1.5.0: 基于真实地块的城市土地利用变化模拟和预测系统Title: UrbanVCA v1.5.0: Actual Land-parcel-based Urban Land-use Simulation and Prediction System在地理智能(GeoAI)

We present a novel approach for estimating the proportional distributions of function types (i.e. functional distributions) in an urban area through learning semantics preserved embeddings of points-of-interest (POIs). Specifically, we represent POIs as low-dimensional vectors to capture (1) the spatial co-occurrence patterns of POIs and (2) the semantics conveyed by the POI hierarchical categories (i.e. categorical semantics). The proposed approach utilizes spatially explicit random walks in a POI network to learn spatial co-occurrence patterns, and a manifold learning algorithm to capture categorical semantics. The learned POI vector embeddings are then aggregated to generate regional embeddings with long short-term memory (LSTM) and attention mechanisms, to take account of the different levels of importance among the POIs in a region. Finally, a multilayer perceptron (MLP) maps regional embeddings to functional distributions. A case study in Xiamen Island, China implements and evaluates the proposed approach. The results indicate that our approach outperforms several competitive baseline models in all evaluation measures, and yields a relatively high consistency between the estimation and ground truth. In addition, a comprehensive error analysis unveils several intrinsic limitations of POI data for this task, e.g. ambiguous linkage between POIs and functions.