Combined Use of Sentinel-1 and Sentinel-2 for Burn Severity Mapping in a Mediterranean Region

2021 ◽  
pp. 139-154
Author(s):  
Giandomenico De Luca ◽  
João M. N. Silva ◽  
Duarte Oom ◽  
Giuseppe Modica
Keyword(s):  
Mediterranean Region ◽  
Burn Severity ◽  
Combined Use ◽  
Sentinel 2

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

2018 ◽  
Vol 10 (11) ◽  
pp. 3889 ◽  
Author(s):  
Rosa Lasaponara ◽  
Biagio Tucci ◽  
Luciana Ghermandi
Keyword(s):  
Model Development ◽  
Fire Effects ◽  
Mitigation Strategies ◽  
Decision Makers ◽  
Burn Severity ◽  
Burnt Area ◽  
Local Index ◽  
Information Translation ◽  
Burnt Areas ◽  
Sentinel 2

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.

scholarly journals Potential of Sentinel-2 Images for Estimating of Soil Resistivity over Agricultural Fields

Proceedings ◽  
2019 ◽  
Vol 24 (1) ◽  
pp. 18
Author(s):  
Remy Fieuzal ◽  
Vincent Bustillo ◽  
David Collado ◽  
Gerard Dedieu
Keyword(s):  
Electrical Resistivity ◽  
Near Infrared ◽  
Soil Layers ◽  
Digital Elevation ◽  
Combined Use ◽  
Input Variables ◽  
Elevation Model ◽  
High Level ◽  
Sentinel 2 ◽  
Soil Electrical Resistivity

The aim of this study is to assess the possibilities of the VNIR (Visible and Near InfraRed) and SWIR (Short Wavelength InfraRed) satellite data for estimating intra-plot patterns of soil electrical resistivity consistent with ground measurements. The methodology is based on optical reflectances that constitute the input variables of random forest, alone or in combination with parameters derived from a digital elevation model (DEM). Over a field located in southwestern France, the results show high level of accuracy for the 0–50 and 0–100 cm soil layers (with R² of 0.69 and 0.59, and a relative RMSE of 18% and 16%, respectively), the performances being lower for the 0–170 cm layer (R² of 0.39, relative RMSE of 20%). The combined use of optical reflectances with parameters derived from the DEM slightly improves the performances, whatever the considered layer. The influence of each reflectance on soil electrical resistivity estimates is finally analyzed, showing that the wavelengths acquired in the SWIR have a relative higher importance than VNIR reflectance.

Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation

2020 ◽  
pp. 1-11 ◽  
Author(s):  
Narissara Nuthammachot ◽  
Askar Askar ◽  
Dimitris Stratoulias ◽  
Pramaditya Wicaksono
Keyword(s):  
Biomass Estimation ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Combined Use ◽  
Sentinel 2

scholarly journals ESTIMATIVA DA EVAPOTRANSPIRAÇÃO EM SISTEMAS INTEGRADOS NO CERRADO, UTILIZANDO O ALGORITMO SAFER

Irriga ◽  
2020 ◽  
Vol 25 (3) ◽  
pp. 617-628
Author(s):  
Leonnardo Cruvinel Furquim ◽  
Daniel Noe Coaguila Nuñez ◽  
Epitácio José de Souza ◽  
José Mateus Kondo Santini ◽  
Juliana Silva Rodrigues Cabral ◽  
...  
Keyword(s):  
Satellite Images ◽  
Riparian Forests ◽  
Integrated Systems ◽  
Wet Season ◽  
Water Flows ◽  
Combined Use ◽  
Water Courses ◽  
Degraded Pasture ◽  
Weather Stations ◽  
Sentinel 2

ESTIMATIVA DA EVAPOTRANSPIRAÇÃO EM SISTEMAS INTEGRADOS NO CERRADO, UTILIZANDO O ALGORITMO SAFER   LEONNARDO CRUVINEL FURQUIM1; DANIEL NOE COAGUILA NUÑEZ2; EPITÁCIO JOSÉ DE SOUZA3; JOSÉ MATEUS KONDO SANTINI4; JULIANA SILVA RODRIGUES CABRAL5 E LUÍS FERNANDO STONE6   1 Universidade Federal de Goiás, Av. Esperança, s/n - Chácaras de Recreio Samambaia, CEP: 74690-900, Goiânia, Goiás, Brasil, [email protected] 2 Faculdade Unibras, departamento de agronomia, Faculdade Unibras, Rua Doze de Outubro, 42, Jardim Adriana, CEP: 75906-577, Rio Verde, Goiás, Brasil, [email protected] 3 Faculdade Unibras, departamento de agronomia, Faculdade Unibras, Rua Doze de Outubro, 42, Jardim Adriana, CEP: 75906-577, Rio Verde, Goiás, Brasil, [email protected] 4 Faculdade Unibras, departamento de agronomia, Faculdade Unibras, Rua Doze de Outubro, 42, Jardim Adriana, CEP: 75906-577, Rio Verde, Goiás, Brasil, [email protected] 5 Faculdade Unibras, departamento de agronomia, Faculdade Unibras, Rua Doze de Outubro, 42, Jardim Adriana, CEP: 75906-577, Rio Verde, Goiás, Brasil, [email protected] 6 Embrapa Arroz e Feijão, km 12 - Zona Rural GO-462, CEP: 75375-000, Santo Antônio de Goiás, Goiás, Brasil, [email protected]     1 RESUMO   O Cerrado apresenta-se frequentemente degradado, com cursos de água assoreados, nascentes desprotegidas e ausência de matas ciliares, evidenciando a incapacidade de gerar e armazenar água para atender a demanda agrícola e populacional. Sendo assim, torna-se importante avaliar os fluxos hídricos acima do solo nos novos sistemas integrados instalados na região, com o uso combinado de imagens de satélite Sentinel-2 no período de 2017-2019 e informações provenientes de estações meteorológicas. Para tanto, utilizou-se o modelo SAFER para estimativa da evapotranspiração atual, resultando em média de 1,15 mm dia-1, com valor máximo e mínimo de 3,69 e 0,00 mm dia-1, respectivamente. No tratamento integração pecuária-floresta observou-se a maior média de ETa (1,33 mm dia-1) e, no tratamento pastagem degradada, a menor média de ETa (0,96 mm dia-1). Porém, o tratamento pastagem degradada teve a menor variabilidade (0,96 ± 0,78 mm dia-1) e o tratamento integração lavoura pecuária-floresta para silagem apresentou a maior variabilidade (1,26 ± 1,40 mm dia-1). Os sistemas integrados se adequaram à sazonalidade da região, sofrendo estresse hídrico na época seca e com heterogeneidade espaço-temporal na época úmida.   Palavras-chave: integração pecuária-floresta, modelagem, sensoriamento remoto, sentinel-2.     FURQUIM, L. C.; COAGUILA-NUÑEZ, D. N.; SOUZA, E. J. de; SANTINI, J. M. K.; CABRAL, J. S. R.; STONE, L. F. ESTIMATION OF EVAPOTRANSPIRATION IN INTEGRATED SYSTEMS IN CERRADO USING SAFER ALGORITHM       2 ABSTRACT   Cerrado is often degraded, with silted water courses, absence of riparian forests and unprotected springs, leading to the inability to generate and store water to meet current demand. Therefore, it is important to assess the water flows above ground in the new integrated systems installed in the region, with the combined use of Sentinel-2 satellite images in the period 2017-2019 and information from weather stations. Therefore, the SAFER model was used to estimate the current evapotranspiration, resulting in an average of 1.15 mm day-1, with a maximum and minimum value of 3.69 and 0.00 mm day-1, respectively. In the livestock-forest integration treatment, the highest mean ETa was observed (1.33 mm day-1) and, in the degraded pasture treatment, the lowest mean ETa (0.96 mm day-1) was observed. However, the degraded pasture treatment had the lowest variability (0.96 ± 0.78 mm day-1) and the crop-livestock-forest integration treatment for silage showed the highest variability (1.26 ± 1.40 mm day-1). The integrated systems were adapted to the region's seasonality, suffering water stress in the dry season and with space-time heterogeneity in the wet season.   Keywords: livestock-forest integration, modeling, remote sensing, sentinel-2.

scholarly journals Exploring the Potential of C-Band SAR in Contributing to Burn Severity Mapping in Tropical Savanna

2019 ◽  
Vol 12 (1) ◽  
pp. 49 ◽  
Author(s):  
Marius B. Philipp ◽  
Shaun R. Levick
Keyword(s):  
Satellite Imagery ◽  
Laser Scanning ◽  
Structural Changes ◽  
Fire Regime ◽  
Spatial Scales ◽  
Landscape Management ◽  
Carbon Accounting ◽  
Optical Data ◽  
Burn Severity ◽  
Sentinel 2

The ability to map burn severity and to understand how it varies as a function of time of year and return frequency is an important tool for landscape management and carbon accounting in tropical savannas. Different indices based on optical satellite imagery are typically used for mapping fire scars and for estimating burn severity. However, cloud cover is a major limitation for analyses using optical data over tropical landscapes. To address this pitfall, we explored the suitability of C-band Synthetic Aperture Radar (SAR) data for detecting vegetation response to fire, using experimental fires in northern Australia. Pre- and post-fire results from Sentinel-1 C-band backscatter intensity data were compared to those of optical satellite imagery and were corroborated against structural changes on the ground that we documented through terrestrial laser scanning (TLS). Sentinel-1 C-band backscatter (VH) proved sensitive to the structural changes imparted by fire and was correlated with the Normalised Burn Ratio (NBR) derived from Sentinel-2 optical data. Our results suggest that C-band SAR holds potential to inform the mapping of burn severity in savannas, but further research is required over larger spatial scales and across a broader spectrum of fire regime conditions before automated products can be developed. Combining both Sentinel-1 SAR and Sentinel-2 multi-spectral data will likely yield the best results for mapping burn severity under a range of weather conditions.

Evaluation and comparison of Landsat 8, Sentinel-2 and Deimos-1 remote sensing indices for assessing burn severity in Mediterranean fire-prone ecosystems

2019 ◽  
Vol 80 ◽  
pp. 137-144 ◽  
Author(s):  
Paula García-Llamas ◽  
Susana Suárez-Seoane ◽  
José Manuel Fernández-Guisuraga ◽  
Víctor Fernández-García ◽  
Alfonso Fernández-Manso ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Burn Severity ◽  
Landsat 8 ◽  
Sentinel 2 ◽  
Remote Sensing Indices

scholarly journals Analysis of cloud condition on Sentinel-2 MSI and Landsat-8 OLI images of a public supply lake in Belém-Pará-Brazil

2019 ◽  
Vol 14 (4) ◽  
pp. 1 ◽  
Author(s):  
Vítor Abner Borges Dutra ◽  
Paulo Amador Tavares ◽  
Hebe Morganne Campos Ribeiro
Keyword(s):  
Remote Sensing ◽  
Principal Component ◽  
Economic Losses ◽  
Landsat 8 ◽  
Sensing Applications ◽  
Dissolved Organic Matters ◽  
Combined Use ◽  
Cloud Regime ◽  
Remote Sensing Techniques ◽  
Sentinel 2

The eutrophication process leads to reduced water quality and economic losses worldwide. Furthermore, it is possible to apply remote sensing techniques for monitoring of aquatic environments. In this paper, we analysed the combined use of Sentinel-2 Multispectral Instrument and Landsat-8 Operational Land Imager data to monitor a eutrophic aquatic environment under adverse cloudy conditions, from July 2016 to July 2018. Data pre-selection was performed, and then the images were acquired for further investigation. After that, we created a key to the interpretation of cloud conditions for the study area and grouped each of 125 scenes in a Principal Component Analysis (PCA). The PCA grouped months with similarities in cloud conditions, highlighting their patterns in terms of the rainy and dry seasons for the study area. Another interesting result was that, even under the inherent adverse cloud regime of the Amazon, the combined use of both free satellite imagery data could be useful for further analyses, such as measuring of chlorophyll a, coloured dissolved organic matters, total suspended solids and turbidity. However, we highlight that, firstly, studies must be made to validate the data in situ, so that monitoring programs can be built through remote sensing applications.

Sign in / Sign up

Export Citation Format

Share Document