Wagner, Fabien Hubert
Ferreira, Matheus Pinheiro
Hirye, Mayumi C. M.
Phillips, Oliver L.
de Souza Filho, Carlos Roberto
Shimabukuro, Yosio Edemir
Aragao, Luiz E. O. C.
Total Authors: 10
 Natl Inst Space Res INPE, Remote Sensing Div, BR-12227010 Sao Jose Dos Campos, SP - Brazil
 Mil Inst Engn IME, Cartog Engn Sect, Praca Gen Tiburcio 80, BR-22290270 Rio De Janeiro, RJ - Brazil
 IBM Res Brazil, Ave Pasteur 138, BR-22290240 Rio De Janeiro, RJ - Brazil
 Univ Leeds, Sch Geog, Ecol & Global Change, Leeds LS2 9JT, W Yorkshire - England
 Univ Estadual Campinas, Geosci Inst, R Joao Pandia Calogeras 51, BR-13083870 Campinas, SP - Brazil
 Univ Exeter, Coll Life & Environm Sci, Exeter EX4 4RJ, Devon - England
Total Affiliations: 6
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING;
Web of Science Citations:
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. (AU)