Zobrazeno 1 - 10
of 185
pro vyhledávání: '"Alina, Zare"'
Autor:
Ben G Weinstein, Sergio Marconi, Alina Zare, Stephanie A Bohlman, Aditya Singh, Sarah J Graves, Lukas Magee, Daniel J Johnson, Sydne Record, Vanessa E Rubio, Nathan G Swenson, Philip Townsend, Thomas T Veblen, Robert A Andrus, Ethan P White
Publikováno v:
PLoS Biology, Vol 22, Iss 7, p e3002700 (2024)
The ecology of forest ecosystems depends on the composition of trees. Capturing fine-grained information on individual trees at broad scales provides a unique perspective on forest ecosystems, forest restoration, and responses to disturbance. Individ
Externí odkaz:
https://doaj.org/article/7746cfcda9c54f5cb863b74cad283153
Autor:
Ben G. Weinstein, Sergio Marconi, Sarah J. Graves, Alina Zare, Aditya Singh, Stephanie A. Bohlman, Lukas Magee, Daniel J. Johnson, Phillip A. Townsend, Ethan P. White
Publikováno v:
Remote Sensing in Ecology and Conservation, Vol 9, Iss 5, Pp 656-670 (2023)
Abstract Measuring forest biodiversity using terrestrial surveys is expensive and can only capture common species abundance in large heterogeneous landscapes. In contrast, combining airborne imagery with computer vision can generate individual tree d
Externí odkaz:
https://doaj.org/article/a043d76c84c046d4afe297ff4d93f56c
Autor:
Sarah J. Graves, Sergio Marconi, Dylan Stewart, Ira Harmon, Ben Weinstein, Yuzi Kanazawa, Victoria M. Scholl, Maxwell B. Joseph, Joseph McGlinchy, Luke Browne, Megan K. Sullivan, Sergio Estrada-Villegas, Daisy Zhe Wang, Aditya Singh, Stephanie Bohlman, Alina Zare, Ethan P. White
Publikováno v:
PeerJ, Vol 11, p e16578 (2023)
Data on individual tree crowns from remote sensing have the potential to advance forest ecology by providing information about forest composition and structure with a continuous spatial coverage over large spatial extents. Classifying individual tree
Externí odkaz:
https://doaj.org/article/69acbf6fc72741f2945caa453ffee2ff
Publikováno v:
Plant Methods, Vol 19, Iss 1, Pp 1-15 (2023)
Abstract Purpose Root system architectures are complex and challenging to characterize effectively for agronomic and ecological discovery. Methods We propose a new method, Spatial and Texture Analysis of Root SystEm distribution with Earth mover’s
Externí odkaz:
https://doaj.org/article/cda3f89de978402f96d3afd290f396b9
Autor:
Allen Starke, Keerthiraj Nagaraj, Cody Ruben, Nader Aljohani, Sheng Zou, Arturo Bretas, Janise McNair, Alina Zare
Publikováno v:
IET Smart Grid, Vol 5, Iss 6, Pp 398-416 (2022)
Abstract Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment. Securing the SG is a considerably significant challenge
Externí odkaz:
https://doaj.org/article/11f344a14b884bab8dad61f1a576fb4f
Autor:
Nicholas T. Glass, Kyungdahm Yun, Eduardo A. Dias de Oliveira, Alina Zare, Roser Matamala, Soo-Hyung Kim, Miquel Gonzalez-Meler
Publikováno v:
Frontiers in Plant Science, Vol 14 (2023)
Roots optimize the acquisition of limited soil resources, but relationships between root forms and functions have often been assumed rather than demonstrated. Furthermore, how root systems co-specialize for multiple resource acquisitions is unclear.
Externí odkaz:
https://doaj.org/article/9c1ac89e251c427b8025ca294e27ac3a
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 15, Pp 9439-9456 (2022)
Heterogeneous data fusion can enhance the robustness and accuracy of an algorithm on a given task. However, due to the difference in various modalities, aligning the sensors and embedding their information into discriminative and compact representati
Externí odkaz:
https://doaj.org/article/5732923759304720b8bf295d4f986544
Publikováno v:
Remote Sensing, Vol 15, Iss 11, p 2940 (2023)
Both the vastness of pasturelands and the value they contain—e.g., food security, ecosystem services—have resulted in increased scientific and industry efforts to remotely monitor them via satellite imagery and machine learning (ML). However, the
Externí odkaz:
https://doaj.org/article/4f081fbe864e462ebee2e31a7b3b6eba
Publikováno v:
iScience, Vol 25, Iss 8, Pp 104784- (2022)
Summary: Openly available community science digital vouchers provide a wealth of data to study phenotypic change across space and time. However, extracting phenotypic data from these resources requires significant human effort. Here, we demonstrate a
Externí odkaz:
https://doaj.org/article/c67ef152fd444ccca90d7431597c68e5
Autor:
Dylan Stewart, Alina Zare, Sergio Marconi, Ben G. Weinstein, Ethan P. White, Sarah J. Graves, Stephanie A. Bohlman, Aditya Singh
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 11229-11239 (2021)
Supervised methods for object delineation in remote sensing require labeled ground-truth data. Gathering sufficient high quality ground-truth data is difficult, especially when targets are of irregular shape or difficult to distinguish from backgroun
Externí odkaz:
https://doaj.org/article/b3004e22a27c4369a7331fd04e2a81c8