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Assessment of deforestation during the last decades in Ecuador using Noaa-AVHRR satellite data

Bibliographic Data

ID13430518
AuthorsVíctor González-Jaramillo (0000-0002-2150-7690, corresponding author), Andreas Fries (0009-0003-3249-5538), Rütger Rollenbeck (0000-0002-1423-4356), Jhoana Paladines, Fernando Oñate-Valdivieso (0000-0002-2400-0510), Jörg Bendix (0000-0001-6559-2033)
Year2016
Pages217-235
Publication date2016-08-18
Open AccessYes
TypeARTICLE
VenueErdkunde (JOURNAL)
Journal identifiersISSN: 0014-0015 • E-ISSN: 2702-5985
PublisherErdkunde (PUBLISHER • DE)
DOI10.3112/erdkunde.2016.03.02
OpenAlexW2517815455
LanguageEN
Citations received3

Human activities during the last decades provoked a notable reduction in global forest cover. Knowing that forest stands act as stock and sinks for carbon and other greenhouse gases, it is important to determine the existing forest cover at country level and to calculate annual deforestation rates. This work uses NOAA satellite images in a resolution of 1km x 1km to classify the surface of continental Ecuador in forest - non-forest pixels and to estimate the annual deforestation rate from 1986 to 2001 as well as from 2001 to 2008. The method is based on a decision tree algorithm that includes different spectral bands of the NOAA-AVHRR sensor and additional topographic and meteorological parameters. The results show that the total forest cover of continental Ecuador was reduced from 48.1% in 1986 to 36.8% in 2008. The calculated annual deforestation rates indicate that forest reduction increased during the last decade. The most affected area is the Coastal Lowland, due to the enhanced population pressure, followed by the Amazon Basin, not only caused by the governmental supported oil and mining industry, but also due to the uncontrolled timber extraction. The Andean Highland has been less affected, because the major parts of this region were deforested before, during the Pre-Columbian-Era

Climatology · Deforestation (computer science · Geography · Meteorology · Remote sensing · Satellite · Computer Science · Environmental Science · Geology · Remote Sensing and Land Use · Remote Sensing and LiDAR Applications · Satellite Image Processing and Photogrammetry

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Citations per year0.75
Citation span2022 - 2025 (4)
Highly citedNo

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Open DOIOpen Access
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