Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Ian W. Housman"'
Autor:
Melissa M. Rohde, Tanushree Biswas, Ian W. Housman, Leah S. Campbell, Kirk R. Klausmeyer, Jeanette K. Howard
Publikováno v:
Frontiers in Earth Science, Vol 9 (2021)
Groundwater dependent ecosystems (GDEs) are increasingly threatened worldwide, but the shallow groundwater resources that they are reliant upon are seldom monitored. In this study, we used satellite-based remote sensing to predict groundwater levels
Externí odkaz:
https://doaj.org/article/6f6855dd90c34cccacde42e854bbfdf1
Autor:
David Saah, Karis Tenneson, Ate Poortinga, Quyen Nguyen, Farrukh Chishtie, Khun San Aung, Kel N. Markert, Nicholas Clinton, Eric R. Anderson, Peter Cutter, Joshua Goldstein, Ian W. Housman, Biplov Bhandari, Peter V. Potapov, Mir Matin, Kabir Uddin, Hai N. Pham, Nishanta Khanal, Sajana Maharjan, Walter L. Ellenberg, Birendra Bajracharya, Radhika Bhargava, Paul Maus, Matthew Patterson, Africa Ixmucane Flores-Anderson, Jeffrey Silverman, Chansopheaktra Sovann, Phuong M. Do, Giang V. Nguyen, Soukanh Bounthabandit, Raja Ram Aryal, Su Mon Myat, Kei Sato, Erik Lindquist, Marija Kono, Jeremy Broadhead, Peeranan Towashiraporn, David Ganz
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 85, Iss , Pp 101979- (2020)
Land cover maps play an integral role in environmental management. However, countries and institutes encounter many challenges with producing timely, efficient, and temporally harmonized updates to their land cover maps. To address these issues we pr
Externí odkaz:
https://doaj.org/article/ffad2459771643118c354e7207e58160
Autor:
David Saah, Karis Tenneson, Mir Matin, Kabir Uddin, Peter Cutter, Ate Poortinga, Quyen H. Nguyen, Matthew Patterson, Gary Johnson, Kel Markert, Africa Flores, Eric Anderson, Amanda Weigel, Walter L. Ellenberg, Radhika Bhargava, Aekkapol Aekakkararungroj, Biplov Bhandari, Nishanta Khanal, Ian W. Housman, Peter Potapov, Alexandra Tyukavina, Paul Maus, David Ganz, Nicholas Clinton, Farrukh Chishtie
Publikováno v:
Frontiers in Environmental Science, Vol 7 (2019)
Land cover maps are a critical component to make informed policy, development, planning, and resource management decisions. However, technical, capacity, and institutional challenges inhibit the creation of consistent and relevant land cover maps for
Externí odkaz:
https://doaj.org/article/b8fcad68b6e547069e9ab6ca230e67ee
Publikováno v:
Remote Sensing, Vol 10, Iss 8, p 1184 (2018)
The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agricultu
Externí odkaz:
https://doaj.org/article/225701d6f4254c2da30a02378cb9f3dc
Publikováno v:
Remote Sensing of Environment. 221:274-285
Remote sensing landscape monitoring approaches frequently benefit from a dense time series of observations. To enhance these time series, data from multiple satellite systems need to be integrated. Landsat image data is a valuable 30-meter resolution
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c56ddd8fd755dd36561efca1fb01ca9f
https://doi.org/10.1016/j.rse.2018.11.012
https://doi.org/10.1016/j.rse.2018.11.012
Autor:
Patrick L. Zimmerman, Charles H. Perry, Robert Chastain, J.B. Webb, Ian W. Housman, Mark Finco
Publikováno v:
Remote Sensing of Environment. 128:176-185
The increasing availability of satellite imagery has spurred the production of thematic land cover maps based on satellite data. These maps are more valuable to the scientific community and land managers when the accuracy of their classifications has
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ad31f82b8d8046e7e8aa82a95e901d2
https://doi.org/10.1016/j.rse.2012.09.017
https://doi.org/10.1016/j.rse.2012.09.017
Publikováno v:
Remote Sensing; Volume 10; Issue 8; Pages: 1184
Remote Sensing, Vol 10, Iss 8, p 1184 (2018)
Remote Sensing, Vol 10, Iss 8, p 1184 (2018)
The Operational Remote Sensing (ORS) program leverages Landsat and MODIS data to detect forest disturbances across the conterminous United States (CONUS). The ORS program was initiated in 2014 as a collaboration between the US Department of Agricultu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7241892506c97dfabd321bd2f30c3d25
https://doi.org/10.3390/rs10081184
https://doi.org/10.3390/rs10081184