Combining Satellite and UAV Imagery to Delineate Forest Cover and Basal Area after Mixed-Severity Fires

Abstract

In northern Argentina, the assessment of degraded forests is a big challenge for both science and practice, due to their heterogeneous structure. However, new technologies could contribute to mapping post-disturbance canopy cover and basal area in detail. Therefore, this research assesses whether or not the inclusion of partial cover unmanned aerial vehicle imagery could reduce the classification error of a SPOT6 image used in an area-based inventory. BA was calculated from 77 ground inventory plots over 3944 ha of a forest affected by mixed-severity fires in the Argentinian Yungas. In total, 74% of the area was covered with UAV flights, and canopy height models were calculated to estimate partial canopy cover at three tree height classes. Basal area and partial canopy cover were used to formulate the adjusted canopy cover index, and it was calculated for 70 ground plots and an additional 20 image plots. Four classes of fire severity were created based on basal area and adjusted canopy cover index, and were used to run two supervised classifications over a segmented (algorithm multiresolution) wall-to-wall SPOT6 image. The comparison of the Cohan’s Kappa coefficient of both classifications shows that they are not significantly different (p-value: 0.43). However, the approach based on the adjusted canopy cover index achieved more homogeneous strata (Welch t-test with 95% of confidence). Additionally, UAV-derived canopy height model estimates of tree height were compared with field measurements of 71 alive trees. The canopy height models underestimated tree height with an RMSE ranging from 2.8 to 8.3 m. The best accuracy of the canopy height model was achieved using a larger pixel size (10 m), and for lower stocked plots due to high fire severity.

Estimating Forest Canopy Cover in Black Locust (Robinia pseudoacacia L.) Plantations on the Loess Plateau Using Random Forest

“…The active sensors, such as LiDAR and SAR, can penetrate forest canopy and generate vertical structure of vegetation [14,20]. The UAV, which offer high acquisition flexibility and resolution at relatively low costs, have been used to estimate forest cover and basal area successfully [21]. An attractive next step is to using UAV to evaluate forest CC on the Loess Plateau.…”

“…Different type of sensors such as aerial photo, satellite images and active sensors (e.g., LiDAR, SAR, and RADAR) have been applied to estimate forest CC [18][19][20]. The unmanned aerial vehicle (UAV) with high acquisition flexibility and resolution appears to be very promising for the assessment of CC, but only if the forest is widely open and a precise digital terrain model is available [21]. Ma et al [20] compared LiDAR, aerial imagery and satellite imagery in CC estimation, and found that LiDAR-derived CC were marginally influenced by the estimation algorithms and generate comparable results.…”

An Automatic UAV Based Segmentation Approach for Pruning Biomass Estimation in Irregularly Spaced Chestnut Orchards

“…The results obtained are strongly in line with those extracted with a reference manually segmented mask. Applying a calibration performed on supervised UAV data extraction, the method reports a high accuracy in terms of R 2 and RMSE values, suggesting this approach as a fast and cost-effective tool for fast monitoring of large areas. The dataset was acquired before and after a pruning management practice in four study sites identifying three different DBH classes (around 0.50 m,~0.60 m,~0.80 m).…”

Use of Unmanned Aerial Vehicle to Execute Water Conservation Design for Hillsides

“…(8) Alternatively, the use of UAVs with optical or laser sensors has been shown to support forest inventories, but is limited in scale (100 to 1000 ha). (9,10) A UAV is generally any type of remote-controlled aircraft that does not require an onboard pilot, and it commonly refers to unmanned military reconnaissance aircraft. UAVs are generally divided into two categories: (a) Fixed wing: similarly to gliders, they are energy saving (fuel/electricity), incapable of fixed point hovering, and must fly at a specific altitude to avoid blurry images.…”