The ESA Climate Change Initiative (CCI): A European contribution to the generation of the Global Climate Observing System

Plummer, S.; Lecomte, Pascal; Doherty, Mark

doi:10.1016/j.rse.2017.07.014

Cited by 106 publications

(58 citation statements)

References 23 publications

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“…To improve the characterisation of small fires over large areas, the European Space Agency (ESA) Climate Change Initiative (CCI) programme developed BA algorithms and products from medium resolution sensors for the generation of a small fire database (SFD) at regional to continental scales. The CCI programme aims to obtain information on different ECVs using remote sensing data to help improving climate modelling [31,32]. The SFD was initially focused on sub-Saharan Africa, the most burned continent worldwide [9,33], and was largely based on optical sensors (O) and time series (ts) analysis (Ots) [15].…”

Section: Introductionmentioning

confidence: 99%

Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa

et al. 2020

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This study provides a comparative analysis of two Sentinel-1 and one Sentinel-2 burned area (BA) detection and mapping algorithms over 10 test sites (100 × 100 km) in tropical and sub-tropical Africa. Depending on the site, the burned area was mapped at different time points during the 2015–2016 fire seasons. The algorithms relied on diverse burned area (BA) mapping strategies regarding the data used (i.e., surface reflectance, backscatter coefficient, interferometric coherence) and the detection method. Algorithm performance was compared by evaluating the detected BA agreement with reference fire perimeters independently derived from medium resolution optical imagery (i.e., Landsat 8, Sentinel-2). The commission (CE) and omission errors (OE), as well as the Dice coefficient (DC) for burned pixels, were compared. The mean OE and CE were 33% and 31% for the optical-based Sentinel-2 time-series algorithm and increased to 66% and 36%, respectively, for the radar backscatter coefficient-based algorithm. For the coherence based radar algorithm, OE and CE reached 72% and 57%, respectively. When considering all tiles, the optical-based algorithm provided a significant increase in agreement over the Synthetic Aperture Radar (SAR) based algorithms that might have been boosted by the use of optical datasets when generating the reference fire perimeters. The analysis suggested that optical-based algorithms provide for a significant increase in accuracy over the radar-based algorithms. However, in regions with persistent cloud cover, the radar sensors may provide a complementary data source for wall to wall BA detection.

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Section: Introductionmentioning

confidence: 99%

Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa

et al. 2020

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“…24 ) are already available and are being continuously developed in terms of processing methodology and sensor availability. In addition EO measurements of value for the study of climate and climate change have started to become available for example through the European Space Agency's Climate Change Initiative (CCI) 25,26 . These datasets are generally relevant for global use but in some cases can be applied to a complex mountainous context [27][28][29] .…”

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confidence: 99%

Changes in climate patterns and their association to natural hazard distribution in South Tyrol (Eastern Italian Alps)

Schlögel

Kofler

Gariano

et al. 2020

Sci Rep

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In Alpine regions changes in seasonal climatic parameters, such as temperature, rainfall, and snow amount have already been observed. Specifically, in the South Tyrol area, meteorological observations indicate that temperatures are increasing and the number of snow days has generally diminished over time with perennial snow line now observed at higher elevations. Changes in rainfall have also been observed with more events associated with higher temperatures in the summer season. Natural hazards-mainly debris and mud flows, landslides, avalanches, rock falls, and (flash) floods-that affect this area every year, damaging population and infrastructures, are either weather or cryosphere-related. While these events have been recorded sporadically since the beginning of the 20th century, a systematic approach of their inventory has been done by local authorities since the 1990s. So far, Earth observation data has not been exploited to complete or complement existing inventories nor have they been used to investigate the influence of climate perturbation on potentially dangerous natural phenomena. The research presented here thus has three objectives: (i) analyse long time series of climate data and hazard occurrence in South Tyrol to examine if these records exhibit a coherent response of hazards to changes in climate; (ii) measure the spatio-temporal evolution of climatic and natural hazard events recorded, and (iii) explore potential relations between meteorological conditions and the hazard occurrence. In this context, in-situ and satellite-based climate data are exploited to study natural hazard triggers while the potential of Earth observation data is evaluated as a complement to the existing historical records of natural hazards. Specifically, Copernicus Sentinel-1 images are used to detect the spatio-temporal distribution of slow earth surface deformations and the results used for checking the completeness of the actual slow-moving landslide inventories. Hazard-related changes in the South tyrolian landscape have also been analysed in relation to particular meteorological events at a regional scale, assessing trends and anomalies. Results show that: (i) satellite data are very useful to complement the existing natural hazard inventories; (ii) in-situ and satellite-based climate records show similar patterns but differ due to regional versus local variability; (iii) even in a data-rich region such as the analysed area, the overall response of natural hazard occurrence, magnitude, and frequency to change in climate variables is difficult to decipher due to the presence of multiple triggers and locally driven ground responses. However, an increase in the average annual duration of rainfall events and debris flow occurrence can be observed. Mountains have been acknowledged as "sentinels of environmental change" because they have physical dynamics that are readily identifiable and respond more rapidly than other geographical entities to environmental change 1 .

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“…To enable valid comparison, LC data should be sufficiently consistent and accurate. Currently, the proposed and implemented approach relies on the European Space Agency (ESA) Climate Change Initiative (CCI) (http://cci.esa.int) Land Cover data (https://www.esa-landcover-cci.org) (Plummer, Lecomte, & Doherty, 2017). National or local data can be also used.…”

Section: Methodsmentioning

confidence: 99%

Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15 – exploring the potential of data cube

et al. 2020

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Avoiding, reducing, and reversing land degradation and restoring degraded land is an urgent priority to protect the biodiversity and ecosystem services that are vital to life on Earth. To halt and reverse the current trends in land degradation, there is an immediate need to enhance national capacities to undertake quantitative assessments and mapping of their degraded lands, as required by the Sustainable Development Goals (SDGs), in particular, the SDG indicator 15.3.1 ("proportion of land that is degraded over total land area"). Earth Observations (EO) can play an important role both for generating this indicator as well as complementing or enhancing national official data sources. Implementations like Trends.Earth to monitor land degradation in accordance with the SDG15.3.1 rely on default datasets of coarse spatial resolution provided by MODIS or AVHRR. Consequently, there is a need to develop methodologies to benefit from medium to high-resolution satellite EO data (e.g. Landsat or Sentinels). In response to this issue, this paper presents an initial overview of an innovative approach to monitor land degradation at the national scale in compliance with the SDG15.3.1 indicator using Landsat observations using a data cube but further work is required to improve the calculation of the three sub-indicators.

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The ESA Climate Change Initiative (CCI): A European contribution to the generation of the Global Climate Observing System

Cited by 106 publications

References 23 publications

Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa

Burned Area Detection and Mapping: Intercomparison of Sentinel-1 and Sentinel-2 Based Algorithms over Tropical Africa

Changes in climate patterns and their association to natural hazard distribution in South Tyrol (Eastern Italian Alps)

Monitoring land degradation at national level using satellite Earth Observation time-series data to support SDG15 – exploring the potential of data cube

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