Massively-Parallel Break Detection for Satellite Data

The field of remote sensing is nowadays faced with huge amounts of data. While this offers a variety of exciting research opportunities, it also yields significant challenges regarding both computation time and space requirements. In practice, the sheer data volumes render existing approaches too slow for processing and analyzing all the available data. This work aims at accelerating BFAST, one of the state-of-the-art methods for break detection given satellite image time series. In particular, we propose a massively-parallel implementation for BFAST that can effectively make use of modern parallel compute devices such as GPUs. Our experimental evaluation shows that the proposed GPU implementation is up to four orders of magnitude faster than the existing publicly available implementation and up to ten times faster than a corresponding multi-threaded CPU execution. The dramatic decrease in running time renders the analysis of significantly larger datasets possible in seconds or minutes instead of hours or days. We demonstrate the practical benefits of our implementations given both artificial and real datasets.Comment: 10 page

Spatial aggregation of low resolution satellite data for the monitoring of vegetation response to climatic stresses : analysis of the spatial heterogeneity of aggregated entities.

peer reviewedOur PhD research consists in analysing and modelling the vegetation response or sensitivity to climatic stresses with low satellite imagery. In that framework, the selection of optimal calibration sites is very important. These sites should be characterised by a stable and homogenous land cover over large area. Here we analyse the spatial heterogeneity of the aggregation entities (EU-NUTS 2) used by the MARSFOOD programme for the extraction of regional NDVI-means

Improved Drought Monitoring in the Greater Horn of Africa by Combining Meteorological and Remote Sensing Based Indicators

Drought is a complex and insidious natural hazard. It is hence difficult to detect in its early stages and to monitor its spatial evolution. Defining drought is already a challenge and can be done differently by meteorologists, hydrologists or socio-economists. In each one of these research areas, various indicators were already set up to depict the development of drought. However they are usually considering only one aspect of the phenomenon. The development of integrated indicators could help to detect faster/better the onset of drought, to monitor more efficiently its evolution in time and space, and therefore to better trigger timely and appropriate actions on the field. In this study, meteorological and remote sensing based drought indicators were compared over the Greater Horn of Africa in order to better understand: (i) how they depict historical drought events ; (ii) if they could be combined into an integrated drought indicator. The meteorological indicator selected for our study is the well known Standardized Precipitation Index, SPI. This statistical indicator is evaluating the lack or surplus of precipitation during a given period of time as a function of the long-term average precipitation and its distribution. Two remote sensing based indicators were tested: the Normalized Difference Water Index (NDWI) derived from SPOT-VEGETATION and the Global Vegetation Index (VGI) derived form MERIS. The first index is sensitive to change in leaf water content of vegetation canopies while the second is a proxy of the amount and vigour of vegetation. For both indexes, anomalies were estimated using available satellite archives. Cross-correlations between remote sensing based anomalies and SPI were analysed for five land covers (forest, shrubland, grassland, sparse grassland, cropland and bare soil) over different regions in the Greater Horn of Africa. The time window for the statistical analysis was set to the rainy season, as it is the most critical period for vegetation growth. Moreover the behaviour of those indicators was also investigated during major historical droughts reported in the Emergency Database (EM-DAT) of the Centre for Research on the Epidemiology of Disasters (CRED, Leuven Belgium). Results of both analyses will be discussed during the conference.JRC.DDG.H.7-Land management and natural hazard

Global Ecosystem Response Types Derived from the Standardized Precipitation Evapotranspiration Index and FPAR3g Series

Observing trends in global ecosystem dynamics is an important first step, but attributing these trends to climate variability represents a further step in understanding Earth system changes. In the present study, we classified global Ecosystem Response Types (ERTs) based on common spatio-temporal patterns in time-series of Standardized Precipitation Evapotranspiration Index (SPEI) and FPAR3g anomalies (1982–2011) by using an extended Principal Component Analysis. The ERTs represent region specific spatio-temporal patterns of ecosystems responding to drought or ecosystems with decreasing severity in drought events as well as ecosystems where drought was not a dominant factor in a 30-year period. Highest explanatory values in the SPEI12-FPAR3g anomalies and strongest SPEI12-FPAR3g correlations were seen in the ERTs of Australia and South America whereas lowest explanatory value and lowest correlations were observed in Asia and North America. These ERTs complement traditional pixel based methods by enabling the combined assessment of the location, timing, duration, frequency and severity of climatic and vegetation anomalies with the joint assessment of wetting and drying climatic conditions. The ERTs produced here thus have potential in supporting global change studies by mapping reference conditions of long term ecosystem changes

JRC Experience on the Development of Drought Information Systems

From the definition of drought to its monitoring and assessment, this report summarizes the main steps towards an integrated drought information system. Europe, Africa and Latin America are examples, based on the experience of the JRC, that illustrate the challenges for establishing continental drought observatory initiatives. The document is structured in the following way: first an introduction explains what drought is and gives some examples of its impact in society; secondly the framework for establishing a drought monitoring system is described giving examples on the European Drought Observatory and on on-going activities in Africa and Latin America; thirdly the fundamental data and information for measuring drought is described; finally the setting up of an Integrated Drought Information System is discussed and two recent case studies, on Europe and on the Horn of Africa, are presented to illustrate the concept.JRC.H.7-Climate Risk Managemen

Uncovering Dryland Woody Dynamics Using Optical, Microwave, and Field Data—Prolonged Above-Average Rainfall Paradoxically Contributes to Woody Plant Die-Off in the Western Sahel

Dryland ecosystems are frequently struck by droughts. Yet, woody vegetation is often able to recover from mortality events once precipitation returns to pre-drought conditions. Climate change, however, may impact woody vegetation resilience due to more extreme and frequent droughts. Thus, better understanding how woody vegetation responds to drought events is essential. We used a phenology-based remote sensing approach coupled with field data to estimate the severity and recovery rates of a large scale die-off event that occurred in 2014–2015 in Senegal. Novel low (L-band) and high-frequency (Ku-band) passive microwave vegetation optical depth (VOD), and optical MODIS data, were used to estimate woody vegetation dynamics. The relative importance of soil, human-pressure, and before-drought vegetation dynamics influencing the woody vegetation response to the drought were assessed. The die-off in 2014–2015 represented the highest dry season VOD drop for the studied period (1989–2017), even though the 2014 drought was not as severe as the droughts in the 1980s and 1990s. The spatially explicit Die-off Severity Index derived in this study, at 500 m resolution, highlights woody plants mortality in the study area. Soil physical characteristics highly affected die-off severity and post-disturbance recovery, but pre-drought biomass accumulation (i.e., in areas that benefited from above-normal rainfall conditions before the 2014 drought) was the most important variable in explaining die-off severity. This study provides new evidence supporting a better understanding of the “greening Sahel”, suggesting that a sudden increase in woody vegetation biomass does not necessarily imply a stable ecosystem recovery from the droughts in the 1980s. Instead, prolonged above-normal rainfall conditions prior to a drought may result in the accumulation of woody biomass, creating the basis for potentially large-scale woody vegetation die-off events due to even moderate dry spells