Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Keely L. Roth"'
Publikováno v:
Remote Sensing, Vol 7, Iss 11, Pp 14276-14291 (2015)
Airborne hyperspectral and thermal infrared imagery acquired in 2013 and 2014, the second and third years of a severe drought in California, were used to assess drought impacts on dominant plant species. A relative green vegetation fraction (RGVF) ca
Externí odkaz:
https://doaj.org/article/3a55e451b7684b1ab7eb1f83348c3ae7
Autor:
Philip E. Dennison, Yi Qi, Susan K. Meerdink, Raymond F. Kokaly, David R. Thompson, Craig S. T. Daughtry, Miguel Quemada, Dar A. Roberts, Paul D. Gader, Erin B. Wetherley, Izaya Numata, Keely L. Roth
Publikováno v:
Remote Sensing, Vol 11, Iss 18, p 2072 (2019)
Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by
Externí odkaz:
https://doaj.org/article/e6097264c01d497994fe58c53b82101a
Publikováno v:
Remote Sensing, Vol 11, Iss 9, p 1100 (2019)
Accurate information about ecosystem structure and biogeochemical properties is essential to providing better estimates ecosystem functioning. Airborne LiDAR (light detection and ranging) is the most accurate way to retrieve canopy structure. However
Externí odkaz:
https://doaj.org/article/12b0cf5e031b4aa38e1101b13df4822b
Publikováno v:
IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::333e7a2138967146e25d6ae5a2555312
https://doi.org/10.1109/igarss46834.2022.9883061
https://doi.org/10.1109/igarss46834.2022.9883061
Autor:
Jennifer Y. King, Susan K. Meerdink, Philip E. Dennison, Dar A. Roberts, Cibele Hummel do Amaral, Keely L. Roth, Simon J. Hook
Publikováno v:
Remote Sensing of Environment. 186:322-338
Vegetation traits provide critical information on ecosystem function that can be used to assess the effects of disturbance, land use, and climate change. Recent studies have demonstrated the use of spectroscopy to predict vegetation traits accurately
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::168e0f705a92cd8d2c3864e4f29d5969
https://doi.org/10.1016/j.rse.2016.08.003
https://doi.org/10.1016/j.rse.2016.08.003
Autor:
Yi Qi, Raymond F. Kokaly, Dar A. Roberts, Miguel Quemada, Izaya Numata, Philip E. Dennison, Keely L. Roth, David R. Thompson, Craig S. T. Daughtry, Erin B. Wetherley, Paul D. Gader, Susan K. Meerdink
Publikováno v:
Remote Sensing; Volume 11; Issue 18; Pages: 2072
Remote Sensing, Vol 11, Iss 18, p 2072 (2019)
Remote Sensing, Vol 11, Iss 18, p 2072 (2019)
Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b89ce2cea2fb153b300b502678187e9
Publikováno v:
Remote Sensing, Vol 11, Iss 9, p 1100 (2019)
Remote Sensing
Volume 11
Issue 9
Pages: 1100
Remote Sensing
Volume 11
Issue 9
Pages: 1100
Accurate information about ecosystem structure and biogeochemical properties is essential to providing better estimates ecosystem functioning. Airborne LiDAR (light detection and ranging) is the most accurate way to retrieve canopy structure. However
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::514d2359527f36d22d02d6fef208df55
https://www.mdpi.com/2072-4292/11/9/1100
https://www.mdpi.com/2072-4292/11/9/1100
Publikováno v:
Hyperspectral Indices and Image Classifications for Agriculture and Vegetation ISBN: 9781315159331
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8e72aa72ff9bfca945880fe252ab0ec8
https://doi.org/10.1201/9781315159331-1
https://doi.org/10.1201/9781315159331-1
Autor:
Maria Mar Alsina, Keely L. Roth, Susan L. Ustin, Michael L. Whiting, Margarita Huesca, Angeles Casas, Spencer A. Mathews
Publikováno v:
Remote Sensing of Environment. 184:229-246
Our ability to measure and map plant function at multiple ecological scales is critical for understanding current and future changes in Earth's ecosystems and the global carbon budget. Conventional plant functional types (cPFTs) based on a few produc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f0dc12aadfa3f0be08bc4123b8abaa21
https://doi.org/10.1016/j.rse.2016.07.014
https://doi.org/10.1016/j.rse.2016.07.014
Autor:
Shruti Khanna, Sarai C. Piazza, Keely L. Roth, Dar A. Roberts, Susan L. Ustin, Seth H. Peterson, Michael Beland, Raymond F. Kokaly, Trent W. Biggs
Publikováno v:
Remote Sensing of Environment. 182:192-207
The April 2010 Deepwater Horizon (DWH) oil spill was the largest coastal spill in U.S. history. Monitoring subsequent change in marsh plant community distributions is critical to assess ecosystem impacts and to establish future coastal management pri
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::533780cbf832e6d5e11836a20090b6d2
https://doi.org/10.1016/j.rse.2016.04.024
https://doi.org/10.1016/j.rse.2016.04.024