Abstract

It is challenging to map the spatial distribution of natural and planted forests based on satellite images because of the high correlation among them. This investigation aims to increase accuracies in classifications of natural forests and eucalyptus plantations by combining remote sensing data from multiple sources. We defined four vegetation classes: natural forest (NF), planted eucalyptus forest (PF), agriculture (A) and pasture (P), and sampled 410,251 pixels from 100 polygons of each class. Classification experiments were performed by using a random forest algorithm with images from Landsat-8, Sentinel-1, and SRTM. We considered four texture features (energy, contrast, correlation, and entropy) and NDVI. We used F1-score, overall accuracy and total disagreement metrics, to assess the classification performance, and Jeffries–Matusita (JM) distance to measure the spectral separability. Overall accuracy for Landsat-8 bands alone was 88.29%. A combination of Landsat-8 with Sentinel-1 bands resulted in a 3% overall accuracy increase and this band combination also improved the F1-score of NF, PF, P and A in 2.22%, 2.9%, 3.71%, and 8.01%, respectively. The total disagreement decreased from 11.71% to 8.71%. The increase in the statistical separability corroborates such improvement and is mainly observed between NF-PF (11.98%) and A-P (45.12%). We conclude that combining optical and radar remote sensing data increased the classification accuracy of natural and planted forests and may serve as a basis for large-scale semi-automatic mapping of forest resources.

Highlights

  • In Brazil, tropical forests cover some 5 mi km2, which corresponds to approximately 62% of its territory (MAPBIOMAS, 2019)

  • We explored the combination of passive optical and radio detection and ranging (RADAR) data to discriminate between planted, natural forest, pasture and agricultural areas in the state of Espírito Santo, southeast of Brazil

  • Concerning the baseline scenario, the improvement observed by combining LS 8 bands with RADAR data in F1-score was 2.22%, 2.9%, 3.71% and 8.01% for the natural forest (NF), planted eucalyptus forest (PF), P and A classes, respectively (Table 6)

Read more

Summary

Introduction

In Brazil, tropical forests cover some 5 mi km, which corresponds to approximately 62% of its territory (MAPBIOMAS, 2019). Tropical forests provide key ecosystem services for mankind such as soil conservation, carbon sequestration and habitat protection. They harbor the largest portion of global tree diversity, with up to 53,000 tree species or more (SLIK et al, 2015). Tropical forests store half of the global forest carbon (C) stock (PAN et al, 2011) and are responsible to fix about 70% of the terrestrial nitrogen (WANG; HOULTON, 2009). The provisioning of these important ecosystem services relies on the maintenance and conservation of forested areas. The situation is even more critical in the state of Espírito Santo (ES) that lost 90% of its natural forest areas (SOS/INPE, 2019)

Methods
Results
Discussion
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.