Regional Mapping and Spatial Distribution Analysis of Canopy Palms in an Amazon Forest Using Deep Learning and VHR Images

Author(s)

Wagner, Fabien H. ^[1] ; Dalagnol, Ricardo ^[2] ; Casapia, Ximena Tagle ^{[3, 4]} ; Streher, Annia S. ^[2] ; Phillips, Oliver L. ^[5] ; Gloor, Emanuel ^[5] ; Aragao, Luiz E. O. C. ^{[2, 6]}

Affiliation

^[1] Fdn Sci Technol & Space Applicat FUNCATE, GeoProc Div, BR-12210131 Sao Jose Dos Campos, SP - Brazil

^[2] Natl Inst Space Res INPE, Remote Sensing Div, BR-12227010 Sao Jose Dos Campos, SP - Brazil

^[3] Inst Invest Amazonia Peruana IIAP, Probosques, Av A Jose Quinones Km 2-5, Iquitos 784, AP - Peru

^[4] Wageningen Univ & Res, Lab Geoinformat Sci & Remote Sensing, Droevendaalsesteeg 3, NL-06708 PB Wageningen - Netherlands

^[5] Univ Leeds, Sch Geog, Leeds LS2 9JT, W Yorkshire - England

^[6] Univ Exeter, Coll Life & Environm Sci, Geog, Exeter EX4 4RJ, Devon - England

• Document type: Journal article
• Source: REMOTE SENSING; v. 12, n. 14 JUL 2020.
• Web of Science Citations: 0

Abstract

Mapping plant species at the regional scale to provide information for ecologists and forest managers is a challenge for the remote sensing community. Here, we use a deep learning algorithm called U-net and very high-resolution multispectral images (0.5 m) from GeoEye satellite to identify, segment and map canopy palms over similar to 3000 km(2) of Amazonian forest. The map was used to analyse the spatial distribution of canopy palm trees and its relation to human disturbance and edaphic conditions. The overall accuracy of the map was 95.5% and the F1-score was 0.7. Canopy palm trees covered 6.4% of the forest canopy and were distributed in more than two million patches that can represent one or more individuals. The density of canopy palms is affected by human disturbance. The post-disturbance density in secondary forests seems to be related to the type of disturbance, being higher in abandoned pasture areas and lower in forests that have been cut once and abandoned. Additionally, analysis of palm trees' distribution shows that their abundance is controlled naturally by local soil water content, avoiding both flooded and waterlogged areas near rivers and dry areas on the top of the hills. They show two preferential habitats, in the low elevation above the large rivers, and in the slope directly below the hill tops. Overall, their distribution over the region indicates a relatively pristine landscape, albeit within a forest that is critically endangered because of its location between two deforestation fronts and because of illegal cutting. New tree species distribution data, such as the map of all adult canopy palms produced in this work, are urgently needed to support Amazon species inventory and to understand their distribution and diversity. (AU)

• FAPESP's process: 16/17652-9 - Functional diversity of intact and regenerating Amazon, Atlantic Forest and Cerrado systems using hyperspectral imagery
• Grantee: Fabien Hubert Wagner
• Support Opportunities: Scholarships in Brazil - Young Researchers
• FAPESP's process: 13/50533-5 - Understanding the response of photosynthetic metabolism in tropical forests to seasonal climate variations
• Grantee: Luiz Eduardo Oliveira e Cruz de Aragão
• Support Opportunities: Regular Research Grants
• FAPESP's process: 15/50484-0 - Functional diversity of intact and regenerating Amazon, Atlantic Forest, and Cerrado systems using hyperspectral imagery
• Grantee: Fabien Hubert Wagner
• Support Opportunities: Research Grants - Young Investigators Grants
• FAPESP's process: 19/09248-1 - Using deep-learning convolutional network for estimating canopy traits from high-resolution imagery
• Grantee: Annia Susin Streher
• Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
• FAPESP's process: 15/22987-7 - Assessment of climate change impacts on the biomass and carbon dynamics in the Amazon
• Grantee: Ricardo Dal'Agnol da Silva
• Support Opportunities: Scholarships in Brazil - Doctorate