@Article{WagnerPSHZGPSSA:2018:InTrCr,
author = "Wagner, Fabien Hubert and Perreira, Matheus Pinheiro and Sanchez
Ipia, Alber Hamersson and Hirye, Mayumi C. M. and Zortea, Maciel
and Gloor, Emanuel and Phillips, Oliver L. and Souza Filho, Carlos
Roberto de and Shimabukuro, Yosio Edemir and Arag{\~a}o, Luiz
Eduardo Oliveira e Cruz de",
affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto
Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de
Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas
Espaciais (INPE)} and {IBM Research Brazil} and {University of
Leeds} and {University of Leeds} and {Universidade Estadual de
Campinas (UNICAMP)} and {Instituto Nacional de Pesquisas Espaciais
(INPE)} and {Instituto Nacional de Pesquisas Espaciais (INPE)}",
title = "Individual tree crown delineation in a highly diverse tropical
forest using very high resolution satellite images",
journal = "ISPRS Journal of Photogrammetry and Remote Sensing",
year = "2018",
volume = "145",
number = "pt B",
pages = "362--377",
month = "Nov.",
keywords = "Image segmentation, Multispectral image, Tropical forests, Species
identification, Rolling ball algorithm, Mathematical morphology.",
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 (30.596%) 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.",
doi = "10.1016/j.isprsjprs.2018.09.013",
url = "http://dx.doi.org/10.1016/j.isprsjprs.2018.09.013",
issn = "0924-2716",
language = "en",
targetfile = "wagner_individual.pdf",
urlaccessdate = "02 maio 2024"
}