Applicability of the MultiTemporal Coherence Approach to Sentinel-1 for the Detection and Delineation of Burnt Areas in the Context of the Copernicus Emergency Management Service

In the framework of the Copernicus Emergency Management Service (EMS) Mapping Validation, the applicability of the MultiTemporal Coherence (MTC) technique using Sentinel-1 data and the software made available by the European Space Agency (ESA), the Sentinel Application Platform (SNAP), for the detection and delineation of burnt areas was tested. The main purpose of the study was to test a methodology that would benefit from the advantages of delineating burnt areas based on radar data with respect to optical data due to its capacity to acquire data both night and day and to avoid the interference of clouds and/or smoke. Moreover, the study aimed to acheive the delineation of the burnt areas using Sentinel-1 and SNAP in the frame of an emergency mapping where processing time is constrained due to the necessity of giving a quick response to the emergency. Four Sentinel-1 images were acquired over a mountainous area mainly covered by Mediterranean vegetation that suffered from massive forest fires in the summer of 2016. The burnt area delineation was obtained by an object-based image analysis (OBIA) of the resulting MTC image followed by a visual inspection. The effects of the polarization, the acquisition mode, and the incidence angle of the synthetic aperture radar (SAR) imagery were studied in order to assess the contribution of these sensor varaibles on the results. Results of the Sentinel-1 based delineation were compared to those using optical imagery, which is traditionally used for this application. Therefore, the fire delineation that was derived was compared to that derived using three optical images: pre- and post-event Sentinel-2 images and a post-event SPOT 6 image. The first two were used to calculate the differences of the burnt area index (dBAI), used to derive the burnt area delineation by OBIA and photo interpretation with the help of the SPOT 6 image. Results of the comparison showed the feasibility of using the MTC technique for burnt area delineation, as high overall accuracy values were observed when compared to the burnt area delineation derived from optical imagery. The importance of the incidence angle of the Sentinel-1 images was assessed as well, with lower angles resulting in higher overall accuracies. In addition, the availability of double polarization of the Sentinel-1 images, allowed us to give recommendations regarding which polarization gave the best results. The potential for the use of SAR data, obtaining equivalent results to those obtained from optical imagery, is significant in an emergency context given that radar sensors acquire images continuosly and in all weather conditions.

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Combined use of Sentinel SAR and optical data for soil moisture estimation

10.5194/egusphere-egu2020-722 ◽

2020 ◽

Author(s):

Giulia Graldi ◽

Simone Bignotti ◽

Marco Bezzi ◽

Alfonso Vitti

Keyword(s):

Land Use ◽

Soil Moisture ◽

Case Studies ◽

Agricultural Land ◽

Physiological State ◽

European Space Agency ◽

Irrigation Scheduling ◽

Optical Data ◽

Agricultural Land Use ◽

Mountainous Area

This work investigates the performance of two soil moisture retrieval methods using optical and radar satellite data. The study was conducted in areas with predominant agricultural land use since soil moisture is one of the parameters of interest in a wider study for water resource optimization in agricultural practices such as irrigation scheduling. The two methods considered are based on the identification of changes in the investigated parameter between two acquisition dates. The implemented methods have been applied to study areas characterized by different orographic complexity and land use heterogeneity. Data from the European Space Agency (ESA) Sentinel 1 and Sentinel 2 missions were used, and results were validated with field measurements from the International Soil Moisture Network (ISMN). At first, the methods were applied in a mountainous area of an irrigation consortium in Trentino (Italy), where the results pointed out the complexity of the study and the limitations of the current models in these contexts. Factors such as orographic complexity, type and physiological state of crops make the reduction of SAR data particularly complex to model. The methods were then tested in a simpler orographic context such as that of the Po Valley in Bologna (Italy), also characterized by agricultural land use. Finally, the methods were applied in a lowland with agricultural vocation located in Spain, for which an extended archive of soil moisture measurements distributed by the ISMN is available. In this context, the models were analyzed and were evaluated both functional and parametric adjustments of the models on the basis of the previous case studies. Some of the results obtained are of high quality, while others highlight the complexity of the problem faced and the need for further investigation: increasing the number of case studies and using optical or SAR vegetation index different from the mainly used NDVI, could enhanced the models used for soil moisture retrieval.

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Detection of Seasonal Inundations by Satellite Data at Shkoder Urban Area, North Albania for Sustainable Management

Sustainability ◽

10.3390/su11164454 ◽

2019 ◽

Vol 11 (16) ◽

pp. 4454 ◽

Cited By ~ 1

Author(s):

Stefano Morelli ◽

Matteo Del Soldato ◽

Silvia Bianchini ◽

Veronica Pazzi ◽

Ervis Krymbi ◽

...

Keyword(s):

European Space Agency ◽

Temporal Analysis ◽

Radar Data ◽

Optical Data ◽

Future Perspective ◽

Management Service ◽

Surface Mapping ◽

Water Index ◽

Space Agency ◽

Sentinel 2

The European Space Agency satellites Sentinel-1 radar and Sentinel-2 optical data are widely used in water surface mapping and management. In this work, we exploit the potentials of both radar and optical images for satellite-based quick detection and extent mapping of inundations/water raising events over Shkodër area, which occurred in the two last years (2017–2018). For instance, in March 2018 the Shkodër district (North Albania) was affected twice by the overflow of the Drin and Buna (Bojana) Rivers and by the Shkodër lake plain inundation. Sentinel-1 radar data allowed a rapid mapping of seasonal fluctuations and provided flood extent maps by discriminating water surfaces (permanent water and flood areas) from land/non-flood areas over all the informal zones of Shkodër city. By means of Sentinel-2 data, two color composites maps were produced and the Normalized Difference Water Index was estimated, in order to further distinguish water/moisturized soil surfaces from built-up and vegetated areas. The obtained remote sensing-based maps were combined and discussed with the urban planning framework in order to support a sustainable urban and environmental management. The provided multi-temporal analysis could be easily exploited by the local authorities for flood prevention and management purposes in the inherited territorial context. The proposed approach outputs were validated by comparing them with official Copernicus EMS (Emergency Management Service) maps available for one of the chosen events. The comparison shows good accordance results. As for a further enhancement in the future perspective, it is worth to highlight that a more accurate result could be obtained by performing a post-processing edit to further refine the flooded areas, such as water mask application and supervised classification to filter out isolated flood elements, to remove possible water-lookalikes and weed out false positives.

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Synergistic use of radar Sentinel-1 and optical Sentinel-2 imagery for crop mapping: a case study for Belgium

10.20944/preprints201808.0066.v1 ◽

2018 ◽

Author(s):

Kristof Van Tricht ◽

Anne Gobin ◽

Sven Gilliams ◽

Isabelle Piccard

Keyword(s):

Remote Sensing ◽

Random Forest ◽

Satellite Remote Sensing ◽

Incidence Angle ◽

Random Forest Classifier ◽

Optical Observations ◽

Optical Data ◽

Crop Types ◽

Optical Imagery ◽

Sentinel 2

A timely inventory of agricultural areas and crop types is an essential requirement for ensuring global food security. Satellite remote sensing has proven to be an increasingly more reliable tool to identify crop types. With the Copernicus program and its Sentinel satellites, a growing source of satellite remote sensing data is publicly available at no charge. Here we use joint Sentinel-1 radar and Sentinel-2 optical imagery to create a crop map for Belgium. To ensure homogenous radar and optical input across the country, Sentinel-1 12-day backscatter composites were created after incidence angle normalization, and Sentinel-2 NDVI images were smoothed to yield dekadal cloud-free composites. An optimized random forest classifier predicted the 8 crop types with a maximum accuracy of 82% and a kappa coefficient of 0.77. We found that a combination of radar and optical imagery always outperformed a classification based on single-sensor inputs, and that classification performance increased throughout the season until July, when differences between crop types are largest. Furthermore we showed that the concept of classification confidence derived from the random forest classifier provided insight in the reliability of the predicted class for each pixel, clearly showing that parcel borders have a lower classification confidence. We concluded that the synergistic use of radar and optical data for crop classification led to richer information increasing classification accuracies compared to optical-only classification. Further work should focus on object-level classification and crop monitoring to exploit the rich potential of combined radar and optical observations.

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A Tool for Pre-Operational Daily Mapping of Floods and Per-Manent Water Using Sentinel-1 Data

Remote Sensing ◽

10.3390/rs13071342 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1342

Author(s):

Luca Pulvirenti ◽

Giuseppe Squicciarino ◽

Elisabetta Fiori ◽

Luca Ferraris ◽

Silvia Puca

Keyword(s):

Region Growing ◽

Open Water ◽

Optical Data ◽

Management Service ◽

Data Generation ◽

End User ◽

Mapping Algorithm ◽

Output Layer ◽

Water Mapping ◽

Flood Maps

An automated tool for pre-operational mapping of floods and inland waters using Sentinel-1 data is presented. The acronym AUTOWADE (AUTOmatic Water Areas DEtector) is used to denote it. The tool provides the end user (Italian Department of Civil Protection) with a continuous, near real-time (NRT) monitoring of the extent of inland water surfaces (floodwater and permanent water). It implements the following operations: downloading of Sentinel-1 products; preprocessing of the products and storage of the resulting geocoded and calibrated data; generation of the intermediate products, such as the exclusion mask; application of a floodwater/permanent water mapping algorithm; generation of the output layer, i.e., a map of floodwater/permanent water; delivery of the output layer to the end user. The open floodwater/permanent water mapping algorithm implemented in AUTOWADE is based on a new approach, denoted as buffer-from-edge (BFE), which combines different techniques, such as clustering, edge filtering, automatic thresholding and region growing. AUTOWADE copes also with the typical presence of gaps in the flood maps caused by undetected flooded vegetation. An attempt to partially fill these gaps by analyzing vegetated areas adjacent to open water is performed by another algorithm implemented in the tool, based on the fuzzy logic. The BFE approach has been validated offline using maps produced by the Copernicus Emergency Management Service. Validation has given good results with a F1-score larger than 0.87 and a kappa coefficient larger than 0.80. The algorithm to detect flooded vegetation has been visually compared with optical data and aerial photos; its capability to fill some of the gaps present in flood maps has been confirmed.

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A Comparison of Leaf Area Index Maps Derived from Multi-Sensor Optical Data Acquired over Agricultural Areas

Italian Journal of Agronomy ◽

10.4081/ija.2010.167 ◽

2010 ◽

Vol 5 (2) ◽

pp. 167 ◽

Cited By ~ 3

Author(s):

Giuseppe Satalino ◽

Francesco Mattia ◽

Anna Balenzano ◽

Michele Rinaldi ◽

Sergio Ruggieri ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Optical Data ◽

Area Index ◽

Agricultural Areas ◽

Index Maps

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The history and characteristics of the 1980–2005 Portuguese rural fire database

Natural Hazards and Earth System Science ◽

10.5194/nhess-11-3343-2011 ◽

2011 ◽

Vol 11 (12) ◽

pp. 3343-3358 ◽

Cited By ~ 78

Author(s):

M. G. Pereira ◽

B. D. Malamud ◽

R. M. Trigo ◽

P. I. Alves

Keyword(s):

Urban Areas ◽

Unit Area ◽

Fire Regime ◽

Minimum Area ◽

Burnt Area ◽

Forested Areas ◽

Large Fires ◽

Burnt Areas

Abstract. We focus here on a mainland Continental Portuguese Rural Fire Database (PRFD) that includes 450 000 fires, the largest such database in Europe in terms of total number of recorded fires in the 1980–2005 period. In this work, we (a) list the most important factors for triggering and controlling the fire regime in mainland Continental Portugal, (b) describe the dataset's production, (c) discuss procedures adopted to identify and correct different fire data inconsistencies, creating a modified PRFD which we use here and make available as Supplement, (d) explore some basic temporal and completeness properties of the data. We find that the dataset's minimum measured burnt areas have changed with time between AF = 0.1 ha (1980–1990), AF = 0.01 ha (1991–1992), and AF = 0.001 ha (1992–2005), with varying degrees of completeness down to these values. These changes in minimum area measured are responsible for greater numbers of fires being recorded. A relatively small number of large fires in the PRFD are responsible for the majority of the burnt area. For example, fires with AF > 100 ha represent about 1% of all fire records but 75% of total burnt area. Finally, we consider for each Continental Portugal district and for the 26-yr period, the total number of rural fires and area burnt in forests and shrublands, each normalized by district areas. We find that the highest numbers of fires per unit area are in highly populated districts, and that the largest fraction of burnt area is in forested areas, coinciding with large parcels of continuous forests (predominantly rural and moderately urban areas).

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COHERENT CHANGE DETECTION FOR REPEATED-PASS INTERFEROMETRIC SAR IMAGES: AN APPLICATION TO EARTHQUAKE DAMAGE ASSESSMENT ON BUILDINGS

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-w4-383-2018 ◽

2018 ◽

Vol XLII-3/W4 ◽

pp. 383-388 ◽

Cited By ~ 2

Author(s):

D. Oxoli ◽

P. Boccardo ◽

M. A. Brovelli ◽

M. E. Molinari ◽

A. Monti Guarnieri

Keyword(s):

Change Detection ◽

Emergency Management ◽

Performance Assessment ◽

Damage Assessment ◽

Earthquake Damage ◽

Detection Sensitivity ◽

Management Service ◽

Sar Images ◽

Coherent Change Detection ◽

Interferometric Sar

Abstract. During disaster response, the availability of relevant information, delivered in a proper format enabling its use among the different actors involved in response efforts, is key to lessen the impact of the disaster itself. Focusing on the contribution of geospatial information, meaningful advances have been achieved through the adoption of satellite earth observations within emergency management practices. Among these technologies, the Synthetic Aperture Radar (SAR) imaging has been extensively employed for large-scale applications such as flood areas delineation and terrain deformation analysis after earthquakes. However, the emerging availability of higher spatial and temporal resolution data has uncovered the potential contribution of SAR to applications at a finer scale. This paper proposes an approach to enable pixel-wise earthquake damage assessments based on Coherent Change Detection methods applied to a stack of repeated-pass interferometric SAR images. A preliminary performance assessment of the procedure is provided by processing Sentinel-1 data stack related to the 2016 central Italy earthquake for the towns of Ametrine and Accumoli. Damage assessment maps from photo-interpretation of high-resolution airborne imagery, produced in the framework of Copernicus EMS (Emergency Management Service &ndash; European Commission) and cross-checked with field survey, is used as ground truth for the performance assessment. Results show the ability of the proposed approach to automatically identify changes at an almost individual building level, thus enabling the possibility to empower traditional damage assessment procedures from optical imagery with the centimetric change detection sensitivity characterizing SAR. The possibility of disseminating outputs in a GIS-like format represents an asset for an effective and cross-cutting information sharing among decision makers and analysts.

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Size of wildfires in the Euro-Mediterranean region: observations and theoretical analysis

Natural Hazards and Earth System Sciences Discussions ◽

10.5194/nhessd-3-1203-2015 ◽

2015 ◽

Vol 3 (2) ◽

pp. 1203-1230 ◽

Cited By ~ 1

Author(s):

C. Hernandez ◽

P. Drobinski ◽

S. Turquety ◽

J.-L. Dupuy

Keyword(s):

Wind Speed ◽

Percolation Threshold ◽

Eastern Europe ◽

Mediterranean Region ◽

Burnt Area ◽

Fire Propagation ◽

Wind Speeds ◽

The Mediterranean ◽

Hot Weather ◽

Burnt Areas

Abstract. MODIS satellite observations of fire size and ERA-Interim meteorological reanalysis are used to derive a relationship between burnt area and wind speed over the Mediterranean region and Eastern Europe. As intuitively expected, the burnt area associated to the largest wildfires is an increasing function of wind speed in most situations. It is always the case in Eastern Europe. It is also the case in the Mediterranean for moderate temperature anomaly. In situations of severe heatwaves and droughts, the relationship between burnt area and wind speed displays bimodal shape. Burnt areas are large for low 10 m wind speed (lower than 2 m s−1), decrease for moderate wind speed values (lower than 5 m s−1 and larger than 2 m s−1) and increase again for large wind speed (larger than 5 m s−1). To explain such behavior fire propagation is investigated using a probabilistic cellular automaton model. The observed relationship between burnt area and wind speed can be interpreted in terms of percolation threshold which mainly depends on local terrain slope and vegetation state (type, density, fuel moisture). In eastern Europe, the percolation threshold is never exceeded for observed wind speeds. In the Mediterranean Basin we see two behaviors. During moderately hot weather, the percolation threshold is passed when the wind grows strong. On the other hand, in situations of severe Mediterranean heatwaves and droughts, moderate wind speed values impair the propagation of the wildfire against the wind and do not sufficiently accelerate the forward propagation to allow a growth of wildfire size.

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Spatial and Temporal Distribution of Biomass Open Burning Emissions in the Greater Mekong Subregion

Climate ◽

10.3390/cli8080090 ◽

2020 ◽

Vol 8 (8) ◽

pp. 90

Author(s):

Agapol Junpen ◽

Jirataya Roemmontri ◽

Athipthep Boonman ◽

Penwadee Cheewaphongphan ◽

Pham Thi Bich Thao ◽

...

Keyword(s):

Fine Particulate Matter ◽

Temporal Distribution ◽

Landsat 8 ◽

Total Biomass ◽

Burnt Area ◽

Fire Emissions ◽

Vegetation Fires ◽

Agricultural Burning ◽

Burnt Areas ◽

Greater Mekong Subregion

Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area products are widely used to assess the damaged area after wildfires and agricultural burning have occurred. This study improved the accuracy of the assessment of the burnt areas by using the MCD45A1 and MCD64A1 burnt area products with the finer spatial resolution product from the Landsat-8 Operational Land Imager/Thermal Infrared Sensor (OLI/TIRS) surface reflectance data. Thus, more accurate wildfires and agricultural burning areas in the Greater Mekong Subregion (GMS) for the year 2015 as well as the estimation of the fire emissions were reported. In addition, the results from this study were compared with the data derived from the fourth version of the Global Fire Emissions Database (GFED) that included small fires (GFED4.1s). Upon analysis of the data of the burnt areas, it was found that the burnt areas obtained from the MCD64A1 and MCD45A1 had lower values than the reference fires for all vegetation fires. These results suggested multiplying the MCD64A1 and MCD45A1 for the GMS by the correction factors of 2.11−21.08 depending on the MODIS burnt area product and vegetation fires. After adjusting the burnt areas by the correction factor, the total biomass burnt area in the GMS during the year 2015 was about 33.3 million hectares (Mha), which caused the burning of 109 ± 22 million tons (Mt) of biomass. This burning emitted 178 ± 42 Mt of CO2, 469 ± 351 kilotons (kt) of CH4, 18 ± 3 kt of N2O, 9.4 ± 4.9 Mt of CO, 345 ± 206 kt of NOX, 46 ± 25 kt of SO2, 147 ± 117 kt of NH3, 820 ± 489 kt of PM2.5, 60 ± 32 kt of BC, and 350 ± 205 kt of OC. Furthermore, the emission results of fine particulate matter (PM2.5) in all countries were slightly lower than GFED4.1s in the range between 0.3 and 0.6 times.

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Detection of Archaeological Looting from Space: Methods, Achievements and Challenges

Remote Sensing ◽

10.3390/rs11202389 ◽

2019 ◽

Vol 11 (20) ◽

pp. 2389 ◽

Cited By ~ 7

Author(s):

Deodato Tapete ◽

Francesca Cigna

Keyword(s):

Remote Sensing ◽

Image Processing ◽

High Resolution ◽

Satellite Data ◽

Satellite Images ◽

Google Earth ◽

Optical Data ◽

Mena Region ◽

Processing Methods ◽

Optical Imagery

Illegal excavations in archaeological heritage sites (namely “looting”) are a global phenomenon. Satellite images are nowadays massively used by archaeologists to systematically document sites affected by looting. In parallel, remote sensing scientists are increasingly developing processing methods with a certain degree of automation to quantify looting using satellite imagery. To capture the state-of-the-art of this growing field of remote sensing, in this work 47 peer-reviewed research publications and grey literature are reviewed, accounting for: (i) the type of satellite data used, i.e., optical and synthetic aperture radar (SAR); (ii) properties of looting features utilized as proxies for damage assessment (e.g., shape, morphology, spectral signature); (iii) image processing workflows; and (iv) rationale for validation. Several scholars studied looting even prior to the conflicts recently affecting the Middle East and North Africa (MENA) region. Regardless of the method used for looting feature identification (either visual/manual, or with the aid of image processing), they preferred very high resolution (VHR) optical imagery, mainly black-and-white panchromatic, or pansharpened multispectral, whereas SAR is being used more recently by specialist image analysts only. Yet the full potential of VHR and high resolution (HR) multispectral information in optical imagery is to be exploited, with limited research studies testing spectral indices. To fill this gap, a range of looted sites across the MENA region are presented in this work, i.e., Lisht, Dashur, and Abusir el Malik (Egypt), and Tell Qarqur, Tell Jifar, Sergiopolis, Apamea, Dura Europos, and Tell Hizareen (Syria). The aim is to highlight: (i) the complementarity of HR multispectral data and VHR SAR with VHR optical imagery, (ii) usefulness of spectral profiles in the visible and near-infrared bands, and (iii) applicability of methods for multi-temporal change detection. Satellite data used for the demonstration include: HR multispectral imagery from the Copernicus Sentinel-2 constellation, VHR X-band SAR data from the COSMO-SkyMed mission, VHR panchromatic and multispectral WorldView-2 imagery, and further VHR optical data acquired by GeoEye-1, IKONOS-2, QuickBird-2, and WorldView-3, available through Google Earth. Commonalities between the different image processing methods are examined, alongside a critical discussion about automation in looting assessment, current lack of common practices in image processing, achievements in managing the uncertainty in looting feature interpretation, and current needs for more dissemination and user uptake. Directions toward sharing and harmonization of methodologies are outlined, and some proposals are made with regard to the aspects that the community working with satellite images should consider, in order to define best practices of satellite-based looting assessment.

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