Matches in SemOpenAlex for { <https://semopenalex.org/work/W4289562005> ?p ?o ?g. }
- W4289562005 endingPage "1397" @default.
- W4289562005 startingPage "1397" @default.
- W4289562005 abstract "Forest canopy gaps are important to ecosystem dynamics. Depending on tree species, small canopy openings may be associated with intra-crown porosity and with space among crowns. Yet, literature on the relationships between very fine-scaled patterns of canopy openings and biodiversity features is limited. This research explores the possibility of: (1) mapping forest canopy gaps from a very high spatial resolution orthomosaic (10 cm), processed from a versatile unmanned aerial vehicle (UAV) imaging platform, and (2) deriving patch metrics that can be tested as covariates of variables of interest for forest biodiversity monitoring. The orthomosaic was imaged from a test area of 240 ha of temperate deciduous forest types in Central Italy, containing 50 forest inventory plots each of 529 m2 in size. Correlation and linear regression techniques were used to explore relationships between patch metrics and understory (density, development, and species diversity) or forest habitat biodiversity variables (density of micro-habitat bearing trees, vertical species profile, and tree species diversity). The results revealed that small openings in the canopy cover (75% smaller than 7 m2) can be faithfully extracted from UAV red, green, and blue bands (RGB) imagery, using the red band and contrast split segmentation. The strongest correlations were observed in the mixed forests (beech and turkey oak) followed by intermediate correlations in turkey oak forests, followed by the weakest correlations in beech forests. Moderate to strong linear relationships were found between gap metrics and understory variables in mixed forest types, with adjusted R2 from linear regression ranging from 0.52 to 0.87. Equally strong correlations in the same forest types were observed for forest habitat biodiversity variables (with adjusted R2 ranging from 0.52 to 0.79), with highest values found for density of trees with microhabitats and vertical species profile. In conclusion, this research highlights that UAV remote sensing can potentially provide covariate surfaces of variables of interest for forest biodiversity monitoring, conventionally collected in forest inventory plots. By integrating the two sources of data, these variables can be mapped over small forest areas with satisfactory levels of accuracy, at a much higher spatial resolution than would be possible by field-based forest inventory solely." @default.
- W4289562005 created "2022-08-03" @default.
- W4289562005 creator A5004339139 @default.
- W4289562005 creator A5007958138 @default.
- W4289562005 creator A5060186297 @default.
- W4289562005 creator A5061304562 @default.
- W4289562005 creator A5089367824 @default.
- W4289562005 date "2018-09-02" @default.
- W4289562005 modified "2023-09-30" @default.
- W4289562005 title "UAV Remote Sensing for Biodiversity Monitoring: Are Forest Canopy Gaps Good Covariates?" @default.
- W4289562005 cites W1502405522 @default.
- W4289562005 cites W1522525389 @default.
- W4289562005 cites W172330513 @default.
- W4289562005 cites W1915650454 @default.
- W4289562005 cites W1954627726 @default.
- W4289562005 cites W1969136216 @default.
- W4289562005 cites W1970773573 @default.
- W4289562005 cites W1971319391 @default.
- W4289562005 cites W1981527205 @default.
- W4289562005 cites W1986644949 @default.
- W4289562005 cites W1995875735 @default.
- W4289562005 cites W1998943389 @default.
- W4289562005 cites W2002008272 @default.
- W4289562005 cites W2007221872 @default.
- W4289562005 cites W2015733718 @default.
- W4289562005 cites W2019549520 @default.
- W4289562005 cites W2021729752 @default.
- W4289562005 cites W2022591200 @default.
- W4289562005 cites W2023703534 @default.
- W4289562005 cites W2026497383 @default.
- W4289562005 cites W2043442349 @default.
- W4289562005 cites W2049452581 @default.
- W4289562005 cites W2052031343 @default.
- W4289562005 cites W2053022485 @default.
- W4289562005 cites W2058773470 @default.
- W4289562005 cites W2066790519 @default.
- W4289562005 cites W2067561407 @default.
- W4289562005 cites W2070427044 @default.
- W4289562005 cites W2071910638 @default.
- W4289562005 cites W2089212648 @default.
- W4289562005 cites W2094276423 @default.
- W4289562005 cites W2094447963 @default.
- W4289562005 cites W2095837378 @default.
- W4289562005 cites W2114181376 @default.
- W4289562005 cites W2127314075 @default.
- W4289562005 cites W2132059682 @default.
- W4289562005 cites W2133917936 @default.
- W4289562005 cites W2134420993 @default.
- W4289562005 cites W2139427406 @default.
- W4289562005 cites W2146096861 @default.
- W4289562005 cites W2151203248 @default.
- W4289562005 cites W2160690242 @default.
- W4289562005 cites W2167266720 @default.
- W4289562005 cites W2190553020 @default.
- W4289562005 cites W2194842761 @default.
- W4289562005 cites W2217905131 @default.
- W4289562005 cites W2235215170 @default.
- W4289562005 cites W2257554162 @default.
- W4289562005 cites W2284979566 @default.
- W4289562005 cites W2296685749 @default.
- W4289562005 cites W2322821744 @default.
- W4289562005 cites W2327963087 @default.
- W4289562005 cites W2329530957 @default.
- W4289562005 cites W2337442676 @default.
- W4289562005 cites W2387188207 @default.
- W4289562005 cites W2395179641 @default.
- W4289562005 cites W2397741397 @default.
- W4289562005 cites W2500871401 @default.
- W4289562005 cites W2530872033 @default.
- W4289562005 cites W2549123380 @default.
- W4289562005 cites W2556502614 @default.
- W4289562005 cites W2583095181 @default.
- W4289562005 cites W2590938687 @default.
- W4289562005 cites W2621167212 @default.
- W4289562005 cites W2755062494 @default.
- W4289562005 cites W2758602907 @default.
- W4289562005 cites W2782014286 @default.
- W4289562005 cites W2790063226 @default.
- W4289562005 cites W2790349426 @default.
- W4289562005 cites W2792384647 @default.
- W4289562005 cites W2792846923 @default.
- W4289562005 cites W2793630632 @default.
- W4289562005 cites W2795604045 @default.
- W4289562005 cites W2804625175 @default.
- W4289562005 cites W4239304042 @default.
- W4289562005 cites W824916002 @default.
- W4289562005 doi "https://doi.org/10.3390/rs10091397" @default.
- W4289562005 hasPublicationYear "2018" @default.
- W4289562005 type Work @default.
- W4289562005 citedByCount "45" @default.
- W4289562005 countsByYear W42895620052019 @default.
- W4289562005 countsByYear W42895620052020 @default.
- W4289562005 countsByYear W42895620052021 @default.
- W4289562005 countsByYear W42895620052022 @default.
- W4289562005 countsByYear W42895620052023 @default.
- W4289562005 crossrefType "journal-article" @default.
- W4289562005 hasAuthorship W4289562005A5004339139 @default.
- W4289562005 hasAuthorship W4289562005A5007958138 @default.