CLASSIFICATION OF THE SUCCESSIONAL STAGE OF VEGETATION IN ATLANTIC FOREST AREAS WITH THE USE OF AERIAL AND TERRESTRIAL 3D POINT CLOUD
Name: RICARDO PINHEIRO CABRAL
Publication date: 22/08/2022
Advisor:
Name |
Role |
|---|---|
| GILSON FERNANDES DA SILVA | Advisor * |
Examining board:
| Name |
Role |
|---|---|
| ANDRÉ QUINTÃO DA ALMEIDA | External Examiner * |
| GILSON FERNANDES DA SILVA | Advisor * |
Summary: The definition of strategies for conducting, recovering and restoring deforested and or degraded areas is due to the stage of ecological succession it is in. Usually, the classification of the successional stage is carried out in the field, from forest inventory campaigns. However, these campaigns are considerably costly and require a high execution time, and still have limited spatial coverage. Currently, forest inventories are being enhanced from the use of three-dimensional data obtained by remote sensing, with emphasis on metrics derived from Light Detection And Ranging (LiDAR) and Digital Aerial Photogrammetry (DAP). Therefore, the main objective of this work was to estimate some parameters of forest interest and to classify the stage of ecological succession of areas with degraded vegetation of the Atlantic Forest Biome with the use of 3D DAP data obtained by Remotely Piloted Aircraft (ARP). An analysis of the costs of traditional and improved inventory was also performed. Initially, the field estimation of the values of total height (h), diameter at 1,30 m of soil (dbh) and basal area (ba) of the individuals of 40 inventory plots (30 x 30 m each) was estimated in the field. In the same plots, 3D point clouds were generated by DAP-RPA and Portable LiDAR (PLS). Next, regression models were adjusted and validated to estimate the values of mean h and dbh, and ab from the traditional metrics based on the heights of the DAP and LiDAR point cloud. Finally, maps of the successional stage of the vegetation were generated with spatial resolution of 30 m. The maps were created based on pre-established intervals of mean h and dbh and ab, according to CONAMA resolution 29/94. Expenses were considered in the cost analysis for equipment acquisition, collection, processing and data analysis. Finally, the costs of inventories were compared. The estimation models based on DAP showed performance similar to models adjusted with LiDAR, with Values of R² ranging from 88,3% to 94% and RMSE (%) between 11,11 and 28,46 for DAP and R² between 83,6% and 96,4% and RMSE (%) between 8,58 and 33,63 for LiDAR. The maps of the succession stages estimated by DAP were compatible with the succession classes estimated in the 40 field plots. The cost of acquiring the equipment used in the dap was twice as high as the traditional method and ten times lower than the enhanced inventory performed with LiDAR. Analyzing the costs of data acquisition and processing per hectare, DAP presented a cost of only R$83,40, against R$16449,16 and R$26268,33 for LiDAR and the traditional method, respectively. DAP metrics can be used to estimate the values of average height, diameter to breast height and basal area of vegetation analyzed with accuracy similar to those performed with LiDAR. In addition to presenting the lowest cost, the estimates made by DAP-RPA allowed the classification of successional stages in the secondary forest areas of Atlantic vegetation analyzed.
Keywords: Enhanced forest inventory, digital aerial photogrammetry, LiDAR.
