Assessment of deforestation in the Lower Amazon floodplain using historical Landsat MSS/TM imagery

Renó, Vivian Fróes; Novo, Evlyn Márcia Leão de Moraes; Suemitsu, Chieno; Rennó, Camilo Daleles; Silva, Thiago Sanna Freire

doi:10.1016/j.rse.2011.08.008

Cited by 81 publications

(71 citation statements)

References 19 publications

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“…Data time series are necessary to detect deforestation. Landsat data have been primarily used in monitoring forest disturbance (Griffiths et al 2012;Schroeder et al 2011;Zhu et al 2012;Grinand et al 2013;Huang et al 2010;Gorsevski et al 2012;Renó et al 2011;Goodwin and Collett 2014), mainly due to the long archive, spectral and spatial resolution properties, and the free availability of data. Tasseled Cap Transformation (TCT) indices from Landsat near-annual time series, evaluated under trajectory-based change detection methods, resulted in identifying forest disturbances within 22 years with overall accuracy (OA) 95.72% (Griffiths et al 2012).…”

Section: Degradation / Deforestationmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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Recognizing the imperative need for biodiversity protection, the Convention on Biological Diversity (CBD) has recently established new targets towards 2020, the so-called Aichi targets, and updated proposed sets of indicators to quantitatively monitor the progress towards these targets. Remote sensing has been increasingly contributing to timely, accurate, and cost-effective assessment of biodiversity-related characteristics and functions during the last years. However, most relevant studies constitute individual research efforts, rarely related with the extraction of widely adopted CBD biodiversity indicators. Furthermore, systematic operational use of remote sensing data by managing authorities has still been limited. In this study, the Aichi targets and the related CBD indicators whose monitoring can be facilitated by remote sensing are identified. For each headline indicator a number of recent remote sensing approaches able for the extraction of related properties are reviewed. Methods cover a wide range of fields, including: habitat extent and condition monitoring; species distribution; pressures from unsustainable management, pollution and climate change; ecosystem service monitoring; and conservation status assessment of protected areas. The advantages and limitations of different remote sensing data and algorithms are discussed. Sorting of the methods based on their reported accuracies is attempted, when possible. The extensive literature survey aims at reviewing highly performing methods that can be used for large-area, effective, and timely biodiversity assessment, to encourage the more systematic use of remote sensing solutions in monitoring progress towards the Aichi targets, and to decrease the gaps between the remote sensing and management communities.

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Section: Degradation / Deforestationmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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“…LULC change assessment illustrates modifications in the condition of important features over time [Singh, 1989;Yeh et al, 1996]. It evaluates the extent of changes in land degradation and desertification [Adamo and Crews-Meyer, 2006;Gao and Liu, 2010], in deforestation [Renó et al, 2011], in habitat fragmentation as well as biodiversity loss [Lung et al, 2012;Carranza et al, 2014] and urban expansion [Fichera et al, 2012;Mertes et al, 2015] for better understanding and sustainable environmental management. Despite their significant contribution to both economic and ecological services, dry forests are currently under severe threats both from anthropogenic and natural calamities [Lemenih et al, 2012;Carranza et al, 2014].…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing based multi-temporal land cover classification and change detection in northwestern Ethiopia

Zewdie¹,

Csaplovies²

2015

European Journal of Remote Sensing

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“…The range of water-level variation between scenes of higher (1975, 6.97 m) and lower (1980, 2.19 m) levels was 4.78 m. This water-level variation is enough to temporarily expose most of the floodplain lake beds during low-water and to cover much of the shrubs and herbaceous vegetation during high-water. However, forest mapping is not affected by water-level fluctuations [17], since dominant forest species are between 10 and 45 m tall [71,72], and tend to occupy areas of higher elevation in the foodplain [71,73].…”

Section: Temporal Mapping Of Forest Covermentioning

confidence: 99%

“…However, the percentage of clouds in the images is less than 9% of the study area, with less than 2% in 63% of the images. The mapping methodology used in this work was adapted from Renó et al [17] and Novo [82].…”

Section: Temporal Mapping Of Forest Covermentioning

confidence: 99%

“…The field data set includes two types of data collected by Renó et al [17] during two field campaigns carried out in 2009: (a) human settlement interviews, especially among the elderly, to collect information on currently and historical land cover type (around 30 years ago); and (b) botanical observations (including vegetation structure, species composition and diversity) which indicated the current land cover type and helped reconstruct its approximate evolution over the past~30 years, since floristic composition and structure can be diagnostic of stand age, formation type, successional stage and possible disruptions/degradations occurred in the past [17]. Based on these data, confusion matrices were built and used to estimate classification accuracy through calculation of the Kappa index of agreement.…”

Section: Temporal Mapping Of Forest Covermentioning

confidence: 99%

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Forest Fragmentation in the Lower Amazon Floodplain: Implications for Biodiversity and Ecosystem Service Provision to Riverine Populations

2016

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This article analyzes the process of forest fragmentation of a floodplain landscape of the Lower Amazon over a 30-year period and its implications for the biodiversity and the provision of ecosystem services to the riverine population. To this end, we created a multi-temporal forest cover map based on Landsat images, and then analyzed the fragmentation dynamics through landscape metrics. From the analyses of the landscape and bibliographic information, we made inferences regarding the potential impacts of fragmentation on the biodiversity of trees, birds, mammals and insects. Subsequently, we used data on the local populations' environmental perception to assess whether the inferred impacts on biodiversity are perceived by these populations and whether the ecosystem services related to the biodiversity of the addressed groups are compromised. The results show a 70% reduction of the forest habitat as well as important changes in the landscape structure that constitute a high degree of forest fragmentation. The perceived landscape alterations indicate that there is great potential for compromise of the biodiversity of trees, birds, mammals and insects. The field interviews corroborate the inferred impacts on biodiversity and indicate that the ecosystem services of the local communities have been compromised. More than 95% of the communities report a decreased variety and/or abundance of animal and plant species, 46% report a decrease in agricultural productivity, and 19% confirm a higher incidence of pests during the last 30 years. The present study provides evidence of an accelerated process of degradation of the floodplain forests of the Lower Amazon and indicate substantial compromise of the ecosystem services provision to the riverine population in recent decades, including reductions of food resources (animals and plants), fire wood, raw material and medicine, as well as lower agricultural productivity due to probable lack of pollination, impoverishment of the soil and an increase of pests.

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Assessment of deforestation in the Lower Amazon floodplain using historical Landsat MSS/TM imagery

Cited by 81 publications

References 19 publications

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Remote Sensing based multi-temporal land cover classification and change detection in northwestern Ethiopia

Forest Fragmentation in the Lower Amazon Floodplain: Implications for Biodiversity and Ecosystem Service Provision to Riverine Populations

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