Evaluation of Unmanned Aerial Vehicles (UAV) as a Tool to Predict Biomass and Carbon of Tectona grandis in Silvopastoral Systems (SPS) in Costa Rica

Abstract

The main objective of this research was to evaluate the use of unmanned aerial vehicles (UAVs) in estimating the aboveground biomass and carbon, and the dasometric characteristics at three different spacings (2.5 m × 1.0 m, 2.5 m × 2.0 m and 2.5 m × 3.0 m) in a silvopastoral system (SPS) for the biomass production of Tectona grandis. A total of 90 trees were sampled, 63 of which were used to perform a dasometric evaluation (vertical and horizontal) in a spacing test in an SPS, and the rest to evaluate the use of UAVs in estimating the aboveground biomass in the spacing test. The results showed significant differences in average diameter at breast height (dbh) between spacings, and in aboveground biomass per tree. The amount of aboveground biomass and carbon per hectare increases at smaller spacings, but the differences were not statistically significant. A logarithmic model was prepared to estimate the dbh based on the crown diameter from the data collected taken in the field, since estimating this variable by means of UAVs is difficult. Significant differences were found in the aboveground biomass estimated using the field data compared to UAV data. The estimation of the crown diameter of the selected trees, hindered by the canopy closure in the SPS, was not adequate, which could influence the amount of aboveground biomass estimated using UAV data.

Use of Unoccupied Aerial Systems to Characterize Woody Vegetation across Silvopastoral Systems in Ecuador

“…In the past, only a few studies explored the use of UASs for the study of tree characteristics in livestock landscapes [29,30]. In this paper, a new methodology is proposed for using UAS surveys for the assessment of woody vegetation in silvopastoral systems.…”

“…Their findings suggest that it is possible to rely only on UAS-DTM-independent metrics to estimate ground-stand volume, with RMSE values similar to those obtained when using a high-resolution DTM. Site conditions, such as terrain slope and tree cover, have an influence on point-cloud-classification performance, although the authors of [30] suggest that tree coverage is more important for accurate DTM creation. In this study, three of the four plots that had a RMSE between 1.14 and 2.5 m (≥10% relative RMSE) were located in areas with a slope of between 20 and 29 • .…”

“…Hence, the crown-DBH relationship was altered, which may have exerted an impact on the final biomass estimates. For example, the authors of [30] reported a low R2 for equations using crown diameter as a predictor of DBH on Tectona grandis trees in SPS in Costa Rica. Although biomass estimates present differences in comparison to biomass estimates derived from field measurements, by assessing the error magnitude, these estimates can be useful for reporting carbon stocks in SPS at larger spatial extents.…”

“…Although LiDAR and NIR sensors provide a broader range of information with which to assess forest canopy characteristics, the development of open-source photogrammetry software and algorithms in recent years has made it possible to extract information from RGB sensors to assess forest characteristics (such as tree height and crown diameter), with results similar to those obtained from LiDAR surveys [23], with considerably lower costs. Several studies using UASs to assess forest characteristics have been published [24][25][26][27][28], but few have focused on the potential for studying SPS [29,30]. The use of photogrammetry to assess tree characteristics on SPS follows the same principles as in forested areas.…”

“…The main difference between forest and pasture-dominated areas is the extent of the canopy gaps, which, by definition, are considerably larger in pasture areas, thus improving ground-truth detection and digital-terrain-model (DTM) creation using structure-from-motion (SfM) workflows [27]. The accuracy of tree-characteristics estimates depends on terrain conditions, and remains a challenge in areas with steep slopes [31]; however, even in even terrain, the accuracy depends on the tree stands' density and the methods used to calculate their characteristics [30].…”