Sentinel-2 Imagery for Mapping Cork Oak (Quercus suber L.) Distribution in Calabria (Italy): Capabilities and Quantitative Estimation

Modica, Giuseppe; Pollino, Maurizio

doi:10.1007/978-3-319-92099-3_8

Cited by 15 publications

(6 citation statements)

References 13 publications

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“…Besides, it provides red-edge spectral data that combines both sensitivity to chlorophyll content and leaf area variation. Cork oak red-edge spectral response from Sentinel-2 was compared with Landsat-8 data and in situ observations for mapping and monitoring cork oak woodlands in the Calabria region (Southern Italy) [11]. As expected, and despite the bandwidth proximity of the two sensors, Normalized Difference Red-Edge (NDRE) vegetation index [12] provided more details on cork oak phenology than NDVI obtained from Landsat-8 data, significantly improving its discrimination from other broad-leaved woodlands.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal

2019

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In Portugal, cork oak (Quercus suber L.) stands cover 737 Mha, being the most predominant species of the montado agroforestry system, contributing to the economic, social and environmental development of the country. Cork oak decline is a known problem since the late years of the 19th century that has recently worsened. The causes of oak decline seem to be a result of slow and cumulative processes, although the role of each environmental factor is not yet established. The availability of Sentinel-2 high spatial and temporal resolution dense time series enables monitoring of gradual processes. These processes can be monitored using spectral vegetation indices (VI) as their temporal dynamics are expected to be related with green biomass and photosynthetic efficiency. The Normalized Difference Vegetation Index (NDVI) is sensitive to structural canopy changes, however it tends to saturate at moderate-to-dense canopies. Modified VI have been proposed to incorporate the reflectance in the red-edge spectral region, which is highly sensitive to chlorophyll content while largely unaffected by structural properties. In this research, in situ data on the location and vitality status of cork oak trees are used to assess the correlation between chlorophyll indices (CI) and NDVI time series trends and cork oak vitality at the tree level. Preliminary results seem to be promising since differences between healthy and unhealthy (diseased/dead) trees were observed.

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Section: Introductionmentioning

confidence: 99%

Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal

2019

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“…Today it is well recognized that for a sustainable future the protection and preservation of natural resources and landscapes can be usefully supported by satellite data, in particular those provided by the Sentinel missions. The methodology herein proposed, developed for Sentinel 2 data, is expected to also provide improvements for other applications such as, for example, land use and land cover classification, as in [23], especially that addressing the monitoring of rural and urban development in order to assess: (i) the growth processes and effects of urban policies on the development of urban areas [24]; (ii) the spatial/temporal analysis of the urban-rural gradient structure [25]; (iii) urban fragmentation at the regional scale [26]; and (iv) trends of land use/land cover [27] and their potential impact on natural resources and the environment.…”

Section: Discussionmentioning

confidence: 99%

On the Use of Satellite Sentinel 2 Data for Automatic Mapping of Burnt Areas and Burn Severity

2018

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In this paper, we present and discuss the preliminary tools we devised for the automatic recognition of burnt areas and burn severity developed in the framework of the EU-funded SERV_FORFIRE project. The project is focused on the set up of operational services for fire monitoring and mitigation specifically devised for decision-makers and planning authorities. The main objectives of SERV_FORFIRE are: (i) to create a bridge between observations, model development, operational products, information translation and user uptake; and (ii) to contribute to creating an international collaborative community made up of researchers and decision-makers and planning authorities. For the purpose of this study, investigations into a fire burnt area were conducted in the south of Italy from a fire that occurred on 10 August 2017, affecting both the protected natural site of Pignola (Potenza, South of Italy) and agricultural lands. Sentinel 2 data were processed to identify and map different burnt areas and burn severity levels. Local Index for Statistical Analyses LISA were used to overcome the limits of fixed threshold values and to devise an automatic approach that is easier to re-apply to diverse ecosystems and geographic regions. The validation was assessed using 15 random plots selected from in situ analyses performed extensively in the investigated burnt area. The field survey showed a success rate of around 95%, whereas the commission and omission errors were around 3% of and 2%, respectively. Overall, our findings indicate that the use of Sentinel 2 data allows the development of standardized burn severity maps to evaluate fire effects and address post-fire management activities that support planning, decision-making, and mitigation strategies.

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“…We calculated NDVI using Sentinel-2 (S2) satellite imagery. S2 imagery has high accuracy in vegetation analysis and provides a better response in monitoring vegetation globally than Landsat imagery (Lima et al, 2019;Modica et al, 2019;Sidiq, 2021). S2 multispectral imagery has a high spatial and temporal resolution.…”

Section: Satellite Data and Processingmentioning

confidence: 99%

A Diversity Index Model based on Spatial Analysis to Estimate High Conservation Value in a Mining Area

Larekeng

Nursaputra

Nasri

et al. 2022

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Large scale land-based investments have a significant impact on natural resources and environmental conditions. It is necessary to protect areas of high conservation value (HCV) within land management investments, such as the mining sector, to minimise this impact. The existence of high conservation value sites in locations with activities related to the mining sector is intended to maintain the ecological and conservation value of a mining investment area. We demonstrate a model that can identify potential high conservation value sites in mining areas using remote sensing data and spatial analysis compiled with field observation data. The research was conducted in one of the largest nickel mining areas (71,047 ha) in South Sulawesi, Indonesia. We mapped vegetation density using the normalized difference vegetation index (NDVI), calculated from Sentinel-2 imagery. We also collected biodiversity data in predetermined inventory sampling plots, which we then used to estimate species richness using the Shannon-Wiener diversity index. Using a linear regression model to compare the normalized difference vegetation index value in each sampling plot with the biodiversity value of flora and fauna, we then estimated biodiversity distribution patterns for the entire study area. We found that potential high conservation value areas (areas likely to have high biodiversity based on our regression model) covered 40,000 ha, more than half of the total concession area.

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Sentinel-2 Imagery for Mapping Cork Oak (Quercus suber L.) Distribution in Calabria (Italy): Capabilities and Quantitative Estimation

Cited by 15 publications

References 13 publications

Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal

Assessing the Use of Sentinel-2 Time Series Data for Monitoring Cork Oak Decline in Portugal

On the Use of Satellite Sentinel 2 Data for Automatic Mapping of Burnt Areas and Burn Severity

A Diversity Index Model based on Spatial Analysis to Estimate High Conservation Value in a Mining Area

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