Analysis of land use and land cover change in a coastal area of Rio de Janeiro using high-resolution remotely sensed data

Avelar, Silvania; Tokarczyk, P.

doi:10.1117/1.jrs.8.083631

Cited by 14 publications

(18 citation statements)

References 10 publications

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“…5. Land use and biodiversity-land area covered by major infrastructure (including buildings, roads, ports) and agriculture, land conversion rates (Avelar and Tokarczyk 2014) and coastal land impacts, protection of bio-and geodiversity, legislation and planning available. For example, activities for control of deforestation, forest burning and pollution.…”

Section: Key Topics To Monitor Sustainable Developmentmentioning

confidence: 99%

Community Perceptions for Geoconservation of a Coastal Area in Rio de Janeiro, Brazil

et al. 2014

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We collected socio-environmental data from the inhabitants of a coastal area in the State of Rio de Janeiro, Brazil, in order to investigate the local knowledge about environmental, economic and cultural particularities of the area and the main human activities that impact the environment. Community perceptions from 11 localities in the Região dos Lagos were evaluated. The data analysis can help in the development of specific geoconservation activities for the study area, which is located in the aspirant Geopark 'Costões e Lagunas do Rio de Janeiro'. This initiative of considering community perceptions can help to maintain and protect local geological sites, raise public awareness of environmental matters and help to manage the development of the new Geopark. Furthermore, it can also contribute to the sustainable development of the area and to the planning of effective policies to sustain progress. Taking into consideration the answers and needs of the interviewed communities, the key topics requiring geoconservation activities in the study area are land use planning and biodiversity, urban mobility, continuous monitoring strategy, environmental awareness, wastewater, urbanisation, geotourism, sense of place, waste and economical activities.

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Section: Key Topics To Monitor Sustainable Developmentmentioning

confidence: 99%

Community Perceptions for Geoconservation of a Coastal Area in Rio de Janeiro, Brazil

et al. 2014

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“…We put forward this approach in order to cope with limited access to ground truth data and minimize misclassification issues reported in the literature regarding the correct delineation of land cover features in desert areas. Furthermore, we needed to satisfy the requirement of extracting a higher number of land-cover classes than the average low number of classes (commonly between four and seven classes) usually obtained through traditional classification schemes at local-regional scales (Ceccarelli 2013;Nutini et al 2013;Avelar and Tokarczyk 2014;Li 2014;Marconcini et al 2014;Zhang et al 2014). Moreover, several researchers have emphasized the importance of a polyvalent or hybrid methodological approach for mapping and detecting changes spatially and temporally with an increased accuracy (Aleksandrowicz et al 2014;Olofsson et al 2014;Zhu and Woodcock 2014).…”

Section: Introductionmentioning

confidence: 99%

Classification methods for detecting and evaluating changes in desertification-related features in arid and semiarid environments

Afrasinei

Melis

Buttau

et al. 2017

Euro-Mediterr J Environ Integr

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Land cover, land use, soil salinization, and sand encroachment, which are desertification-indicating features, were integrated in a diachronic assessment, obtaining quantitative and qualitative information on the ecological state of the land, particularly degradation tendencies. In arid and semi-arid study areas of Algeria and Tunisia, sustainable development requires the understanding of these dynamics as it withstands the monitoring of desertification processes. Both visual interpretation and automated classification approaches have been set up for salt and sand features extraction using historical and present Landsat imagery. The automated one includes a decision tree classifier and an unsupervised classification applied to the principal components extracted from Knepper ratios composite. New spectral indices are employed in the decision tree classifier for the extraction of features of interest. The validation of the classification methods showed that the decision tree had an overall accuracy over 85% in both areas. Integrating results with ancillary spatial data, we could identify driving forces and estimate the metrics of desertification processes. In the Biskra area (Algeria), it emerged that the expansion of irrigated farmland in the past three decades has been contributing to an ongoing secondary salinization of soils, with an increase of over 75%. In the Oum Zessar area (Tunisia), there has been substantial change in several landscape components in the last decades related to increased anthropic pressure and settlement, agricultural policies, and national development strategies. One of the most concerning aspects is the expansion of sand-encroached areas over the last three decades of around 27%.

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“…Through the DTC, we managed to extract a higher number of land cover classes (12) than the average low number of classes (commonly between four and seven classes) usually obtained through traditional classification schemes at local-regional scales. 23,[24][25][26]94,95 The decision nodes and the resulting map are thus obtained for each of the eight dates. According to the lithological and vegetation cover of the area, the DTC and legend were adapted to classify the main land cover classes and classes of lithology distinguishable according to their spectral lithological response, which are described in Table 3.…”

Section: Decision Tree Classificationmentioning

confidence: 99%

“…The final objective of this paper is the engagement of remote sensing imagery in change detection in an area presenting specific restraints, both environmentally or from the accessibility point of view; hence, a consistent number of works have been reviewed for the current study that discuss or use satellite imagery 26,52,55,56 which reported issues regarding discrepancy of results and the degree of the replicability of algorithms or methods applied. 57 We tried to minimize these issues through the proposed aforementioned methodology and approaches described in the following sections.…”

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confidence: 99%

“…Moreover, several researchers have emphasized the importance of a polyvalent or hybrid methodological approach for mapping and detecting changes spatially and temporally with an increased accuracy. [24][25][26][27][28][29][30] In arid and semiarid areas, in particular, problems regarding automated image misclassification of high-albedo desert features have been reported by the scientific community. Among these, salt features classification issues also have been reported, either with supervised or unsupervised classifications, or with spectral mixture methods, mainly regarding spectral confusion of salt features with other land ones, especially urban fabric, bare soil, or carbonaterich lithology.…”

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confidence: 99%

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Assessment of remote sensing-based classification methods for change detection of salt-affected areas (Biskra area, Algeria)

Afrasinei

Melis

Buttau

et al. 2017

J. Appl. Remote Sens

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In the Wadi Biskra arid and semiarid areas, sustainable development is restricted by land degradation processes such as secondary salinization of soils. Being an important highquality date production region of Algeria, this area needs continuous monitoring of desertification indicators, hence highly exposed to climate-related risks. Given the limited access to field data, appropriate methods were assessed for the identification and change detection of salt-affected areas, involving image interpretation and automated classifications employing Landsat imagery, ancillary and multisource ground truth data. First, a visual photointerpretation study of the land cover and land use classes was undergone according to acknowledged methodologies. Second, two automated classification approaches were developed: a customized decision tree classification (DTC) and an unsupervised one applied to the principal components of Knepper ratios composite. Five indices were employed in the DTC construction, among which also is a salinity index. The diachronic analysis was undergone for the 1984 to 2015 images (including seasonal approach), being supported by the interpreted land cover/land use map for error estimation. Considering also biophysical and socioeconomic data, comprehensive results are discussed. One of the most important aspects that emerged was that the accelerated expansion of agricultural land in the last three decades has led and continues to contribute to a secondary salinization of soils

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Analysis of land use and land cover change in a coastal area of Rio de Janeiro using high-resolution remotely sensed data

Cited by 14 publications

References 10 publications

Community Perceptions for Geoconservation of a Coastal Area in Rio de Janeiro, Brazil

Community Perceptions for Geoconservation of a Coastal Area in Rio de Janeiro, Brazil

Classification methods for detecting and evaluating changes in desertification-related features in arid and semiarid environments

Assessment of remote sensing-based classification methods for change detection of salt-affected areas (Biskra area, Algeria)

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