Zobrazeno 1 - 10
of 314
pro vyhledávání: '"Giles M Foody"'
Autor:
Giles M Foody
Publikováno v:
PLoS ONE, Vol 18, Iss 10, p e0291908 (2023)
The accuracy of a classification is fundamental to its interpretation, use and ultimately decision making. Unfortunately, the apparent accuracy assessed can differ greatly from the true accuracy. Mis-estimation of classification accuracy metrics and
Externí odkaz:
https://doaj.org/article/5e457df2f15d479f87c97d196b84c60c
Autor:
Chris J. Chandler, Geertje M. F. van der Heijden, Doreen S. Boyd, Mark E. J. Cutler, Hugo Costa, Reuben Nilus, Giles M. Foody
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 7, Iss 3, Pp 397-410 (2021)
Abstract The ability to accurately assess liana (woody vine) infestation at the landscape level is essential to quantify their impact on carbon dynamics and help inform targeted forest management and conservation action. Remote sensing techniques pro
Externí odkaz:
https://doaj.org/article/83875b43278b46d59968f8ac30f34174
Autor:
Hannes Feilhauer, András Zlinszky, Adam Kania, Giles M. Foody, Daniel Doktor, Angela Lausch, Sebastian Schmidtlein
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 7, Iss 2, Pp 292-305 (2021)
Abstract Mapping vegetation as hard classes based on remote sensing data is a frequently applied approach, even though this crisp, categorical representation is not in line with nature's fuzziness. Gradual transitions in plant species composition in
Externí odkaz:
https://doaj.org/article/30544a1db57d48c2b963691d347a70c7
Autor:
Doreen S. Boyd, Bertrand Perrat, Xiaodong Li, Bethany Jackson, Todd Landman, Feng Ling, Kevin Bales, Austin Choi-Fitzpatrick, James Goulding, Stuart Marsh, Giles M. Foody
Publikováno v:
Humanities & Social Sciences Communications, Vol 8, Iss 1, Pp 1-14 (2021)
Abstract This article provides an example of the ways in which remote sensing, Earth observation, and machine learning can be deployed to provide the most up to date quantitative portrait of the South Asian ‘Brick Belt’, with a view to understand
Externí odkaz:
https://doaj.org/article/702824472f524631970ff485dd5b41d9
Autor:
Pu Zhou, Xiaodong Li, Giles M. Foody, Doreen S. Boyd, Xia Wang, Feng Ling, Yihang Zhang, Yalan Wang, Yun Du
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 20:1-5
Publikováno v:
Remote Sensing, Vol 13, Iss 14, p 2774 (2021)
Lianas (woody vines) play a key role in tropical forest dynamics because of their strong influence on tree growth, mortality and regeneration. Assessing liana infestation over large areas is critical to understand the factors that drive their spatial
Externí odkaz:
https://doaj.org/article/653ecfd618d245d88a78880520dcf19d
Publikováno v:
Land, Vol 10, Iss 1, p 35 (2021)
Estimates of the area or percent area of the land cover classes within a study region are often based on the reference land cover class labels assigned by analysts interpreting satellite imagery and other ancillary spatial data. Different analysts in
Externí odkaz:
https://doaj.org/article/ee8d1990676741c9b700c652a42ebee4
Autor:
Geertje M. F. Heijden, Ashley D. C. Proctor, Kim Calders, Chris J. Chandler, Richard Field, Giles M. Foody, Sruthi M. Krishna Moorthy, Stefan A. Schnitzer, Catherine E. Waite, Doreen S. Boyd
Publikováno v:
JOURNAL OF ECOLOGY
Lianas (woody vines) are abundant and diverse, particularly in tropical ecosystems. Lianas use trees for structural support to reach the forest canopy, often putting leaves above their host tree. Thus they are major parts of many forest canopies. Yet
Publikováno v:
IEEE Geoscience and Remote Sensing Letters. 19:1-5
Superresolution mapping (SRM) is a commonly used method to cope with the problem of mixed pixels when predicting the spatial distribution within low-resolution pixels. Central to the popular SRM method is the spatial pattern model, which is utilized
Publikováno v:
Data in Brief, Vol 7, Iss , Pp 476-479 (2016)
Predicting species potential and future distribution has become a relevant tool in biodiversity monitoring and conservation. In this data article we present the suitability map of a virtual species generated based on two bioclimatic variables, and a
Externí odkaz:
https://doaj.org/article/dd97abf8187741f1b132a52d24bf774b