A combined approach utilizing UAV 3D imaging methods, in-situ measurements, and laboratory experiments to assess water evaporation and trace element uptake by tree species growing in a red gypsum landfill

Does sulfate improve the Mn bioremediation efficiency of Polygonum lapathifolium Linn?

“…Meanwhile, S signi cantly (P < 0.05) increased the Pn and Tr in Mn mine soil but not the Ci and Gs, indicating that the photosynthetic potential ability of P. lapathifolium was not determined by stomatal restriction but by the transpiration rate. This result is not consistent with that reported by Malabad et al, where Ostrya carpinifolia, Betula pendula, and Salix aquatica grandis with a high Mn content had high stomatal conductance, which was favorable to photosynthesis (Malabad et al 2022). These results indicated that even under high-Mn conditions, plants can have high photosynthetic e ciency, but this phenomenon is not always attributed to an increase in stomatal conductance.…”

Machine learning assisted remote forestry health assessment: a comprehensive state of the art review

“…In the work presented by Li et al (2021), leaf water content estimation was performed using hyper-spectral VIs in various growth stages of vegetation reaching a correlation factor of 0.9 with the appropriate VI. Regression models were also used to assess water evaporation models and trace element uptake by trees growing on red gypsum landfill (Malabad et al, 2022). Cęzkowski et al (2020) used thermal indices used to predict various indicators of water stress in wetlands (soil moisture, chlorophyll content, and photosynthetic active radiation (fAPAR)), the correlation factors for soil moisture and fAPAR were of 0.62 and 0.70 respectively, thus the index could be an indicator of water stress.…”

“…These indicators comprise in their nucleus, a previous examination of factors associated with the physical and chemical forest attributes, such as greenness of the leaves, nitrogen content, tree height, canopy height, diameter at breast height, and others. Their importance lies in the study of water absorption, drought response, moisture content, changes in vegetation, and detection of tree diseases (Abdollahnejad and Panagiotidis, 2020;Raddi et al, 2021;Malabad et al, 2022;Zhuo et al, 2022).…”

“…Unmanned aerial vehicles have been used in recent years as mechanisms to gather massive information about various ecosystems (Eugenio et al, 2020;Osco et al, 2021;Sangjan and Sankaran, 2021). Coupling UAVs with computer vision systems (RGB, multi-spectral, hyper-spectral and thermal cameras) and other sensors as LiDAR has allowed researchers to estimate forest parameters like height, canopy cover, DBH, vegetation indexes (Abdollahnejad and Panagiotidis, 2020;Kopackova-Strnadovaé t al., 2021;Raddi et al, 2021;Malabad et al, 2022;Zhuo et al, 2022). The promising use of UAVs in the assessment of forest health allows the experimentation with larger-scale satellite monitoring systems, particularly LANDSAT, SENTINEL, and even Google Earth (Ahmad et al, 2021).…”