Mapping stone walls in Northeastern USA using deep learning and LiDAR data-Reference-Cited by-同舟云学术

Mapping stone walls in Northeastern USA using deep learning and LiDAR data

Published:2023-04-06 Issue:1 Volume:60 Page:
ISSN:1548-1603
Container-title:GIScience & Remote Sensing
language:en
Short-container-title:GIScience & Remote Sensing

Author:

Suh Ji Won¹²^ORCID,Ouimet William²³

Affiliation:

1. Department of Natural Resources and the Environment, University of Connecticut, Storrs, CT, USA

2. Department of Geography, University of Connecticut, Storrs, CT, USA

3. Department of Earth Science, University of Connecticut, Storrs, CT, USA

Funder

National Science Foundation

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/15481603.2023.2196117

Reference82 articles.

1. Deep Learning Approaches Applied to Remote Sensing Datasets for Road Extraction: A State-Of-The-Art Review

2. A Comparison of Visualization Techniques for Models Created from Airborne Laser Scanned Data

3. Object-Oriented Image Processing in an Integrated GIS/Remote Sensing Environment and Perspectives for Environmental Applications. Environmental Information for Planning, Politics and the Public;Blaschke T.;Environmental Information for Planning, Politics and the Public,2000

4. Capitol Region Council of Governments (CRCoG). 2016a. “2016 Aerial Imagery.” http://Cteco.Uconn.Edu/Data/Flight2016/Index.Htm

5. Capitol Region Council of Governments (CRCoG). 2016b. “Connecticut Statewide LiDar 2016 Bare Earth DEM.” http://www.Cteco.Uconn.Edu/Metadata/Dep/Document/LidarDEM_2016_fgdc_plus.Htm

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Broadscale deep learning model for archaeological feature detection across the Maya area;Journal of Archaeological Science;2024-09

2. Legacy impacts and recovery of δ15N, δ13C and C/N storage in soils due to historic land use;Anthropocene;2024-06

3. ASCAT2SMAP: Image-to-Image Translation to Obtain L-Band-Like Soil Moisture From C-Band Satellite Data;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. Reconstructing and identifying historic land use in northeastern United States using anthropogenic landforms and deep learning;Applied Geography;2023-12

5. Identification of historic building “genes” based on deep learning: a case study on Chinese baroque architecture in Harbin, China;Heritage Science;2023-11-20