Abstract
Mapping tropical tree species at landscape scales to provide information for ecologists and forest managers is a new challenge for the remote sensing community. For this purpose, detection and delineation of individual tree crowns (ITCs) is a prerequisite. Here, we present a new method of automatic tree crown delineation based only on very high resolution images from WorldView-2 satellite and apply it to a region of the Atlantic rain forest with highly heterogeneous tropical canopy cover – the Santa Genebra forest reserve in Brazil. The method works in successive steps that involve pre-processing, selection of forested pixels, enhancement of borders, detection of pixels in the crown borders, correction of shade in large trees and, finally, segmentation of the tree crowns. Principally, the method uses four techniques: rolling ball algorithm and mathematical morphological operations to enhance the crown borders and ease the extraction of tree crowns; bimodal distribution parameters estimations to identify the shaded pixels in the gaps, borders, and crowns; and focal statistics for the analysis of neighbouring pixels. Crown detection is validated by comparing the delineated ITCs with a sample of ITCs delineated manually by visual interpretation. In addition, to test if the spectra of individual species are conserved in the automatic delineated crowns, we compare the accuracy of species prediction with automatic and manual delineated crowns with known species. We find that our method permits detection of up to 80% of ITCs. The seven species with over 10 crowns identified in the field were mapped with reasonable accuracy (30.5–96%) given that only WorldView-2 bands and texture features were used. Similar classification accuracies were obtained using both automatic and manual delineation, thereby confirming that species’ spectral responses are preserved in the automatic method and thus permitting the recognition of species at the landscape scale. Our method might support tropical forest applications, such as mapping species and canopy characteristics at the landscape scale.
Highlights
The world’s forests play key roles in maintaining environmental processes, such as the water cycle, soil conservation, carbon sequestration and habitat protection (FAO, 2016)
On the other hand, identifying individual tree crowns (ITCs) from the spectral signature has three major limitations in a tropical forest: (i) trees may be partially covered by lianas, thereby altering the spectral response of species (Kalacska et al, 2007), (ii) a tree can have new leaves only on a part of its crown, which results in markedly different spectral responses in the same crown (Lopes et al, 2016) and (iii) due to the diverse architecture and leaf characteristics of tropical trees, the intra-crown spectral variability among different species is likely to be highly diverse (Ferreira et al, 2016). All these challenges make it difficult to select a single, unique forest-wide threshold for the spectrum-based methods for ITC detection, such as the region-growing algorithms (Culvenor, 2002; Erickson, 2004). Based on these identified limitations in tropical forests, we explored a method of automatic tree crown delineation based only on border detection
The objectives of this work are (i) to provide a simple, automatic and reproducible method to detect and delineate canopy tree crowns in highly diverse tropical forests, taking advantage of commercial very high resolution WorldView-2 imagery and (ii) to test if the spectral signature of the species is conserved in the delineated crown, and, if so, produce forest inventory maps of seven selected tree species based on field and spectral data and automatic delineated tree crowns
Summary
The world’s forests play key roles in maintaining environmental processes, such as the water cycle, soil conservation, carbon sequestration and habitat protection (FAO, 2016). One of the most documented roles of tropical forests is their potential to act as a carbon sink, which accounts for approximately half (1.19 ± 0.41 PgC yr−1) of the global sink of established forests (Pan et al, 2011; Baccini et al, 2012). This carbon sink service is significant, for example, the mature Amazon forests alone mitigated the carbon emissions of all the Amazon countries between 1980 and 2010 (Phillips and Brienen, 2017). While mortality rates have increased across the Amazon forest plots (Phillips et al, 2009; Brienen et al, 2015), the time between the censuses hinders the analysis of the potential annual or intra-annual climate drivers of mortality
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