Assessing the effectiveness of ground truth data to capture landscape variability from an agricultural region using Gaussian simulation and geostatistical techniques

Predictive modeling with remotely sensed data requires an accurate representation of spatial variability by ground truth data. In this study, we assessed the reliability of the size and location of ground truth data in capturing the landscape spatial variability embedded in the Airborne Visible Infr...

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Detalles Bibliográficos
Autores principales: Salas, Eric Ariel L., Subburayalu, Sakthi Kumaran, Slater, Brian, Dave, Rucha, Parekh, Parshva, Zhao, Kaiguang, Bhattacharya, Bimal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8264615/
https://www.ncbi.nlm.nih.gov/pubmed/34278031
http://dx.doi.org/10.1016/j.heliyon.2021.e07439

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8264615/
https://www.ncbi.nlm.nih.gov/pubmed/34278031
http://dx.doi.org/10.1016/j.heliyon.2021.e07439

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