Results 41 to 50 of about 199,814 (261)

Spatial+: A new cross-validation method to evaluate geospatial machine learning models

International Journal of Applied Earth Observation and Geoinformation, 2023
The 2nd stage accounts for the differences in both the geographic space (locations) and feature space (covariates and target variable). It uses cluster ensembles (CE) to split folds.
Yanwen Wang, M. Khodadadzadeh, R. Zurita-Milla   +2 more
semanticscholar   +1 more source

Ontop of Geospatial Databases

, 2016
We propose an OBDA approach for accessing geospatial data stored in relational databases, using the OGC standard GeoSPARQL and R2RML or OBDA mappings. We introduce extensions to an existing SPARQL-to-SQL translation method to support GeoSPARQL features. We describe the implementation of our approach in the system ontop-spatial, an extension of the OBDA
Konstantina Bereta, Manolis Koubarakis
openaire   +3 more sources

Googling Service Boundaries for Endovascular Clot Retrieval (ECR) Hub Hospitals in Metropolitan Sydney

Frontiers in Neurology, 2019
Background and Purpose: Endovascular clot retrieval (ECR) has revolutionized acute stroke therapy but is expensive to run and staff with accredited interventional neuroradiologists 24/7; consequently, it is only feasible for each metropolitan city to ...
Thanh G. Phan, Thanh G. Phan, Richard Beare, Richard Beare, Richard Beare, Richard Beare, Velandai Srikanth, Velandai Srikanth, Velandai Srikanth, Velandai Srikanth, Henry Ma, Henry Ma   +11 more
doaj   +1 more source

Remote Sensing and Geospatial Analysis in the Big Data Era: A Survey

Remote Sensing
The present survey examines the role of big data analytics in advancing remote sensing and geospatial analysis. The increasing volume and complexity of geospatial data are driving the adoption of machine learning (ML) and artificial intelligence (AI ...
Elias Dritsas, M. Trigka
semanticscholar   +1 more source

samgeo: A Python package for segmenting geospatial data with the Segment Anything Model (SAM)

Journal of Open Source Software, 2023
Segment-Geospatial (samgeo) is an open-source Python package designed to simplify the process of segmenting geospatial data with the Segment Anything Model (Kirillov et al., 2023). The package leverages popular Python libraries, such as leafmap (Wu, 2021)
Qiusheng Wu, L. Osco
semanticscholar   +1 more source

Connecticut geospatial newsletter; Connecticut's geospatial newsletter

, 2009
Quarterly; Began with vol. 1, issue 1 (spring 2008).; Description based on: Vol. 1, issue 1 (spring 2008); title from caption (Conn. Geospatial Information System Council Web site, viewed Feb. 4, 2010).; Latest issue consulted: Vol. 2, issue 4 (winter ed.

core   +3 more sources

GeoCode-GPT: A Large Language Model for Geospatial Code Generation Tasks [PDF]

International Journal of Applied Earth Observation and Geoinformation
The increasing demand for spatiotemporal data and modeling tasks in geosciences has made geospatial code generation technology a critical factor in enhancing productivity.
Shu-Yang Hou, Zhangxiao Shen, Anqi Zhao, Jian-Yuan Liang, Zhi-Peng Gui, Xue-Feng Guan, Rui Li, Hua-Yi Wu   +7 more
semanticscholar   +1 more source

Big Data Management Algorithms, Deep Learning-Based Object Detection Technologies, and Geospatial Simulation and Sensor Fusion Tools in the Internet of Robotic Things

ISPRS Int. J. Geo Inf., 2023
The objective of this systematic review was to analyze the recently published literature on the Internet of Robotic Things (IoRT) and integrate the insights it articulates on big data management algorithms, deep learning-based object detection ...
Mihai Andronie, George Lăzăroiu, Mariana Iatagan, Iulian Hurloiu, Roxana Ștefănescu, Adrian Dijmărescu, Irina Dijmarescu   +6 more
semanticscholar   +1 more source

Geospatial Data And Scholia

, 2018
Scholia is a website that displays information about scientific works represented in Wikidata. It extracts the information via queries to the extended SPARQL endpoint Wikidata Query Service (WDQS). Scholia handles geospatial data that may be rendered on maps with the default map output format available in WDQS. We describe the use of geospatial data in
Nielsen, Finn Årup, Mietchen, Daniel, Willighagen, Egon   +2 more
openaire   +4 more sources

An Ensemble Framework for Explainable Geospatial Machine Learning Models [PDF]

International Journal of Applied Earth Observation and Geoinformation
Analyzing spatially varying effects is pivotal in geographic analysis. However, accurately capturing and interpreting this variability is challenging due to the increasing complexity and non-linearity of geospatial data.
Lingbo Liu
semanticscholar   +1 more source