Matches in SemOpenAlex for { <https://semopenalex.org/work/W4280492517> ?p ?o ?g. }
- W4280492517 endingPage "101680" @default.
- W4280492517 startingPage "101680" @default.
- W4280492517 abstract "Information on vegetation height can be used in a variety of applications, but the high cost to obtain it in large areas using field sampling and the latest remote sensing technologies is still a barrier for low-income countries and organizations. In an attempt to overcome these limitations, we explored the possibility to estimate vegetation height in fragments of Atlantic Forest (São Paulo - Brazil) based on Sentinel 2 imagery, using LiDAR (Light Detection And Ranging) and field data as reference. The initial results showed that only wet season images appear to be related to the vegetation height, especially band 5 (red-edge) and related vegetation indices (VIs). Predictions made with Sentinel 2 and LiDAR data showed that vegetation height can be estimated with a root mean square error (RMSE) close to 3 m, with simple linear models outperforming random forest algorithms. It's also shown in a variety of validation tests, that although better results are obtained if the models are applied to the same images they were trained in, they are still able to reasonably predict vegetation height when applied to other images and locations if the right predictive variables are used. The results agree with recent studies made in other biomes and show that Sentinel 2 imagery can be used to estimate vegetation height in the Atlantic Forest as well. We conclude that vegetation height estimates with linear models can be used as a simple low cost alternative for future applications in this environment." @default.
- W4280492517 created "2022-05-22" @default.
- W4280492517 creator A5013212761 @default.
- W4280492517 creator A5014734813 @default.
- W4280492517 creator A5022679258 @default.
- W4280492517 creator A5025671621 @default.
- W4280492517 creator A5055305444 @default.
- W4280492517 creator A5087711141 @default.
- W4280492517 date "2022-07-01" @default.
- W4280492517 modified "2023-10-13" @default.
- W4280492517 title "Use of Sentinel 2 imagery to estimate vegetation height in fragments of Atlantic Forest" @default.
- W4280492517 cites W1964217023 @default.
- W4280492517 cites W1995251091 @default.
- W4280492517 cites W1996705598 @default.
- W4280492517 cites W2023118393 @default.
- W4280492517 cites W2046914842 @default.
- W4280492517 cites W2058312673 @default.
- W4280492517 cites W2078483536 @default.
- W4280492517 cites W2089441588 @default.
- W4280492517 cites W2105756833 @default.
- W4280492517 cites W2113410727 @default.
- W4280492517 cites W2113521108 @default.
- W4280492517 cites W2119150010 @default.
- W4280492517 cites W2122798004 @default.
- W4280492517 cites W2123689744 @default.
- W4280492517 cites W2136636747 @default.
- W4280492517 cites W2140774872 @default.
- W4280492517 cites W2145718502 @default.
- W4280492517 cites W2165916356 @default.
- W4280492517 cites W2181523240 @default.
- W4280492517 cites W2282742555 @default.
- W4280492517 cites W2285635524 @default.
- W4280492517 cites W2585546872 @default.
- W4280492517 cites W2725897987 @default.
- W4280492517 cites W2730541351 @default.
- W4280492517 cites W2747398809 @default.
- W4280492517 cites W2801747952 @default.
- W4280492517 cites W2911554154 @default.
- W4280492517 cites W2968347155 @default.
- W4280492517 cites W2996404009 @default.
- W4280492517 cites W3010346756 @default.
- W4280492517 cites W3034792000 @default.
- W4280492517 cites W3036218142 @default.
- W4280492517 cites W3121161634 @default.
- W4280492517 cites W4211056572 @default.
- W4280492517 cites W4237709168 @default.
- W4280492517 doi "https://doi.org/10.1016/j.ecoinf.2022.101680" @default.
- W4280492517 hasPublicationYear "2022" @default.
- W4280492517 type Work @default.
- W4280492517 citedByCount "2" @default.
- W4280492517 countsByYear W42804925172023 @default.
- W4280492517 crossrefType "journal-article" @default.
- W4280492517 hasAuthorship W4280492517A5013212761 @default.
- W4280492517 hasAuthorship W4280492517A5014734813 @default.
- W4280492517 hasAuthorship W4280492517A5022679258 @default.
- W4280492517 hasAuthorship W4280492517A5025671621 @default.
- W4280492517 hasAuthorship W4280492517A5055305444 @default.
- W4280492517 hasAuthorship W4280492517A5087711141 @default.
- W4280492517 hasBestOaLocation W42804925171 @default.
- W4280492517 hasConcept C100970517 @default.
- W4280492517 hasConcept C105795698 @default.
- W4280492517 hasConcept C106131492 @default.
- W4280492517 hasConcept C110872660 @default.
- W4280492517 hasConcept C119857082 @default.
- W4280492517 hasConcept C139945424 @default.
- W4280492517 hasConcept C140779682 @default.
- W4280492517 hasConcept C142724271 @default.
- W4280492517 hasConcept C169258074 @default.
- W4280492517 hasConcept C18903297 @default.
- W4280492517 hasConcept C205649164 @default.
- W4280492517 hasConcept C2619416 @default.
- W4280492517 hasConcept C2776133958 @default.
- W4280492517 hasConcept C31972630 @default.
- W4280492517 hasConcept C33923547 @default.
- W4280492517 hasConcept C39432304 @default.
- W4280492517 hasConcept C41008148 @default.
- W4280492517 hasConcept C51399673 @default.
- W4280492517 hasConcept C62649853 @default.
- W4280492517 hasConcept C71924100 @default.
- W4280492517 hasConcept C86803240 @default.
- W4280492517 hasConcept C89920630 @default.
- W4280492517 hasConcept C91492127 @default.
- W4280492517 hasConceptScore W4280492517C100970517 @default.
- W4280492517 hasConceptScore W4280492517C105795698 @default.
- W4280492517 hasConceptScore W4280492517C106131492 @default.
- W4280492517 hasConceptScore W4280492517C110872660 @default.
- W4280492517 hasConceptScore W4280492517C119857082 @default.
- W4280492517 hasConceptScore W4280492517C139945424 @default.
- W4280492517 hasConceptScore W4280492517C140779682 @default.
- W4280492517 hasConceptScore W4280492517C142724271 @default.
- W4280492517 hasConceptScore W4280492517C169258074 @default.
- W4280492517 hasConceptScore W4280492517C18903297 @default.
- W4280492517 hasConceptScore W4280492517C205649164 @default.
- W4280492517 hasConceptScore W4280492517C2619416 @default.
- W4280492517 hasConceptScore W4280492517C2776133958 @default.
- W4280492517 hasConceptScore W4280492517C31972630 @default.
- W4280492517 hasConceptScore W4280492517C33923547 @default.
- W4280492517 hasConceptScore W4280492517C39432304 @default.