Impervious surface (English Wikipedia)

Analysis of information sources in references of the Wikipedia article "Impervious surface" in English language version.

refsWebsite

Global rank English rank

5doi.org

2^nd place

5worldcat.org

5^th place

4semanticscholar.org

11^th place

8^th place

2web.archive.org

1^st place

2sciencedirect.com

149^th place

178^th place

2usgs.gov

167^th place

198^th place

1nwsource.com

907^th place

580^th place

1cwp.org

low place

1degrowth.info

low place

1mrlc.gov

low place

1epa.gov

882^nd place

600^th place

1gvrd.bc.ca

low place

1tandfonline.com

507^th place

429^th place

1harvard.edu

18^th place

17^th place

cwp.org

Schueler, Thomas R. "The Importance of Imperviousness." Archived 2009-02-27 at the Wayback Machine Reprinted in The Practice of Watershed Protection. Archived 2008-12-23 at the Wayback Machine 2000. Center for Watershed Protection. Ellicott City, MD.

degrowth.info

Paolini, Massimo (2020-04-20). "Manifesto for the Reorganisation of the City after COVID19". Retrieved 2021-05-01.

doi.org

Slonecker, E. Terrence; Jennings, David B.; Garofalo, Donald (August 2001). "Remote sensing of impervious surfaces: A review". Remote Sensing Reviews. 20 (3): 227–255. doi:10.1080/02757250109532436. ISSN 0275-7257. S2CID 129163574.
Wang, Yuliang; Li, Mingshi (September 2019). "Urban Impervious Surface Detection From Remote Sensing Images: A review of the methods and challenges". IEEE Geoscience and Remote Sensing Magazine. 7 (3): 64–93. Bibcode:2019IGRSM...7c..64W. doi:10.1109/MGRS.2019.2927260. ISSN 2168-6831. S2CID 202729909.
Giacco, Giovanni; Marrone, Stefano; Langella, Giuliano; Sansone, Carlo (2022). "ReFuse: Generating Imperviousness Maps from Multi-Spectral Sentinel-2 Satellite Imagery". Future Internet. 14 (10): 278. doi:10.3390/fi14100278. ISSN 1999-5903.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-01-01). "Automatic extraction of impervious surfaces from high resolution remote sensing images based on deep learning". Journal of Visual Communication and Image Representation. 58: 453–461. doi:10.1016/j.jvcir.2018.11.041. ISSN 1047-3203. S2CID 67752320.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-04-01). "Automatic extraction of urban impervious surfaces based on deep learning and multi-source remote sensing data". Journal of Visual Communication and Image Representation. 60: 16–27. doi:10.1016/j.jvcir.2018.12.051. ISSN 1047-3203. S2CID 127292328.

epa.gov

U.S. Environmental Protection Agency, 2009, National Land Cover Data (NLCD) Classification Schemes "Available on-line"

gvrd.bc.ca

Greater Vancouver Sewerage and Drainage District, 1999, Assessment of current and future GVS&DD area watershed and catchment conditions--Burnaby, Vancouver British Columbia, Canada, Greater Vancouver Sewerage and Drainage District, 53 p. available at: "Available on line"

harvard.edu

ui.adsabs.harvard.edu

Wang, Yuliang; Li, Mingshi (September 2019). "Urban Impervious Surface Detection From Remote Sensing Images: A review of the methods and challenges". IEEE Geoscience and Remote Sensing Magazine. 7 (3): 64–93. Bibcode:2019IGRSM...7c..64W. doi:10.1109/MGRS.2019.2927260. ISSN 2168-6831. S2CID 202729909.

mrlc.gov

National Land Cover Data Set (NLCD)

nwsource.com

seattletimes.nwsource.com

Cappiello, Dina. "Report: EPA Failing to stop Sprawl Runoff." Seattle Times, 16 October 2008

sciencedirect.com

Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-01-01). "Automatic extraction of impervious surfaces from high resolution remote sensing images based on deep learning". Journal of Visual Communication and Image Representation. 58: 453–461. doi:10.1016/j.jvcir.2018.11.041. ISSN 1047-3203. S2CID 67752320.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-04-01). "Automatic extraction of urban impervious surfaces based on deep learning and multi-source remote sensing data". Journal of Visual Communication and Image Representation. 60: 16–27. doi:10.1016/j.jvcir.2018.12.051. ISSN 1047-3203. S2CID 127292328.

semanticscholar.org

api.semanticscholar.org

Slonecker, E. Terrence; Jennings, David B.; Garofalo, Donald (August 2001). "Remote sensing of impervious surfaces: A review". Remote Sensing Reviews. 20 (3): 227–255. doi:10.1080/02757250109532436. ISSN 0275-7257. S2CID 129163574.
Wang, Yuliang; Li, Mingshi (September 2019). "Urban Impervious Surface Detection From Remote Sensing Images: A review of the methods and challenges". IEEE Geoscience and Remote Sensing Magazine. 7 (3): 64–93. Bibcode:2019IGRSM...7c..64W. doi:10.1109/MGRS.2019.2927260. ISSN 2168-6831. S2CID 202729909.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-01-01). "Automatic extraction of impervious surfaces from high resolution remote sensing images based on deep learning". Journal of Visual Communication and Image Representation. 58: 453–461. doi:10.1016/j.jvcir.2018.11.041. ISSN 1047-3203. S2CID 67752320.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-04-01). "Automatic extraction of urban impervious surfaces based on deep learning and multi-source remote sensing data". Journal of Visual Communication and Image Representation. 60: 16–27. doi:10.1016/j.jvcir.2018.12.051. ISSN 1047-3203. S2CID 127292328.

tandfonline.com

Slonecker, E. Terrence; Jennings, David B.; Garofalo, Donald (August 2001). "Remote sensing of impervious surfaces: A review". Remote Sensing Reviews. 20 (3): 227–255. doi:10.1080/02757250109532436. ISSN 0275-7257. S2CID 129163574.

usgs.gov

webdmamrl.er.usgs.gov

Granato, G.E., 2010, Overview of Methods Used to Estimate Imperviousness in a Drainage Basin Appendix 6 in Methods for development of planning-level estimates of stormflow at unmonitored sites in the conterminous United States: Federal Highway Administration, FHWA-HEP-09-005 "Available on-line." Archived 2015-09-06 at the Wayback Machine

landcover.usgs.gov

U.S. Geological Survey, 2007, The USGS Land Cover Institute NLCD land cover statistics database--View the NLCD land cover statistics database "Available on line"

web.archive.org

Schueler, Thomas R. "The Importance of Imperviousness." Archived 2009-02-27 at the Wayback Machine Reprinted in The Practice of Watershed Protection. Archived 2008-12-23 at the Wayback Machine 2000. Center for Watershed Protection. Ellicott City, MD.
Granato, G.E., 2010, Overview of Methods Used to Estimate Imperviousness in a Drainage Basin Appendix 6 in Methods for development of planning-level estimates of stormflow at unmonitored sites in the conterminous United States: Federal Highway Administration, FHWA-HEP-09-005 "Available on-line." Archived 2015-09-06 at the Wayback Machine

worldcat.org

Slonecker, E. Terrence; Jennings, David B.; Garofalo, Donald (August 2001). "Remote sensing of impervious surfaces: A review". Remote Sensing Reviews. 20 (3): 227–255. doi:10.1080/02757250109532436. ISSN 0275-7257. S2CID 129163574.
Wang, Yuliang; Li, Mingshi (September 2019). "Urban Impervious Surface Detection From Remote Sensing Images: A review of the methods and challenges". IEEE Geoscience and Remote Sensing Magazine. 7 (3): 64–93. Bibcode:2019IGRSM...7c..64W. doi:10.1109/MGRS.2019.2927260. ISSN 2168-6831. S2CID 202729909.
Giacco, Giovanni; Marrone, Stefano; Langella, Giuliano; Sansone, Carlo (2022). "ReFuse: Generating Imperviousness Maps from Multi-Spectral Sentinel-2 Satellite Imagery". Future Internet. 14 (10): 278. doi:10.3390/fi14100278. ISSN 1999-5903.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-01-01). "Automatic extraction of impervious surfaces from high resolution remote sensing images based on deep learning". Journal of Visual Communication and Image Representation. 58: 453–461. doi:10.1016/j.jvcir.2018.11.041. ISSN 1047-3203. S2CID 67752320.
Huang, Fenghua; Yu, Ying; Feng, Tinghao (2019-04-01). "Automatic extraction of urban impervious surfaces based on deep learning and multi-source remote sensing data". Journal of Visual Communication and Image Representation. 60: 16–27. doi:10.1016/j.jvcir.2018.12.051. ISSN 1047-3203. S2CID 127292328.