Characterising the land surface phenology of Africa using 500 m MODIS EVI

Vegetation phenological studies at different spatial and temporal scales offer better understanding of the relationship between the global climate and the global distribution of biogeographical zones. These studies in the last few decades have focussed on characterising and understanding vegetation phenology and its drivers especially using satellite sensor data. Nevertheless, despite being home to 17% of the global forest cover, approximately 12% of the world's tropical mangroves, and a diverse range of vegetation types, Africa is one of the most poorly studied regions in the world. There has been no study characterising land surface phenology (LSP) of the major land cover types in the different geographical sub-regions in Africa, and only coarse spatial resolution datasets have been used for continental studies. Therefore, we aim to provide seasonal phenological pattern of Africa's vegetation and characterise the LSP of major land cover types in different geographical sub-regions in Africa at a medium spatial resolution of 500 m using MODIS EVI time-series data over a long temporal range of 15 years (2001–2015). The Discrete Fourier Transformation (DFT) technique was employed to smooth the time-series data and an inflection point-based method was used to extract phenological parameters such as start of season (SOS) and end of season (EOS). Homogeneous pixels from 12 years (2001–2012) MODIS land cover data (MODIS MCD12Q1) was used to describe, for the first time, the LSP of the major vegetation types in Africa. The results from this research characterise spatially and temporally the highly irregular and multi-annual variability of the vegetation phenology of Africa, and the maps and charts provide an improved representation of the LSP of Africa, which can serve as a pivot to filling other research gaps in the African continent

Estimating and monitoring land surface phenology in rangelands: A review of progress and challenges

Land surface phenology (LSP) has been extensively explored from global archives of satellite observations to track and monitor the seasonality of rangeland ecosystems in response to climate change. Long term monitoring of LSP provides large potential for the evaluation of interactions and feedbacks between climate and vegetation. With a special focus on the rangeland ecosystems, the paper reviews the progress, challenges and emerging opportunities in LSP while identifying possible gaps that could be explored in future. Specifically, the paper traces the evolution of satellite sensors and interrogates their properties as well as the associated indices and algorithms in estimating and monitoring LSP in productive rangelands. Findings from the literature revealed that the spectral characteristics of the early satellite sensors such as Landsat, AVHRR and MODIS played a critical role in the development of spectral vegetation indices that have been widely used in LSP applications. The normalized difference vegetation index (NDVI) pioneered LSP investigations, and most other spectral vegetation indices were primarily developed to address the weaknesses and shortcomings of the NDVI. New indices continue to be developed based on recent sensors such as Sentinel-2 that are characterized by unique spectral signatures and fine spatial resolutions, and their successful usage is catalyzed with the development of cutting-edge algorithms for modeling the LSP profiles. In this regard, the paper has documented several LSP algorithms that are designed to provide data smoothing, gap filling and LSP metrics retrieval methods in a single environment

Evaluation of VEGETATION and PROBA-V Phenology Using PhenoCam and Eddy Covariance Data

High-quality retrieval of land surface phenology (LSP) is increasingly important for understanding the effects of climate change on ecosystem function and biosphere-atmosphere interactions. We analyzed four state-of-the-art phenology methods: threshold, logistic-function, moving-average and first derivative based approaches, and retrieved LSP in the North Hemisphere for the period 1999-2017 from Copernicus Global Land Service (CGLS) SPOT-VEGETATION and PROBA-V leaf area index (LAI) 1 km V2.0 time series. We validated the LSP estimates with near-surface PhenoCam and eddy covariance FLUXNET data over 80 sites of deciduous forests. Results showed a strong correlation (R2 > 0.7) between the satellite LSP and ground-based observations from both PhenoCam and FLUXNET for the timing of the start (SoS) and R2 > 0.5 for the end of season (EoS). The threshold-based method performed the best with a root mean square error of ~9 d with PhenoCam and ~7 d with FLUXNET for the timing of SoS (30th percentile of the annual amplitude), and ~12 d and ~10 d, respectively, for the timing of EoS (40th percentile)

Exploring Campylobacter seasonality across Europe (2008-2016) using The European Surveillance System TESSy

Background: Campylobacteriosis is the most commonly reported food-borne infection in the European Union, with an annual number of cases estimated at around 9 million. In many countries, campylobacteriosis has a striking seasonal peak during early/ mid-summer. In the early 2000s, several publications reported on campylobacteriosis seasonality across Europe and associations with temperature and precipitation. Subsequently, many European countries have introduced new measures against this foodborne disease. Aim: To examine how the seasonality of campylobacteriosis varied across Europe from 2008–16, to explore associations with temperature and precipitation, and to compare these results with previous studies. We also sought to assess the utility of the European Surveillance System TESSy for cross-European seasonal analysis of campylobacteriosis. Methods: Ward’s Minimum Variance Clustering was used to group countries with similar seasonal patterns of campylobacteriosis. A two-stage multivariate meta-analysis methodology was used to explore associations with temperature and precipitation. Results: Nordic countries had a pronounced seasonal campylobacteriosis peak in mid-to late summer (weeks 29–32), while most other European countries had a less pronounced peak earlier in the year. The United Kingdom, Ireland, Hungary and Slovakia had a slightly earlier peak (week 24). Campylobacteriosis cases were positively associated with temperature and, to a lesser degree, precipitation. Conclusion: Across Europe, the strength and timing of campylobacteriosis peaks have remained similar to those observed previously. In addition, TESSy is a useful resource for cross-Euro-pean seasonal analysis of infectious diseases such as campylobacteriosis, but its utility depends upon each country’s reporting infrastructure

Feasibility Study for an Aquatic Ecosystem Earth Observing System Version 1.2.

International audienceMany Earth observing sensors have been designed, built and launched with primary objectives of either terrestrial or ocean remote sensing applications. Often the data from these sensors are also used for freshwater, estuarine and coastal water quality observations, bathymetry and benthic mapping. However, such land and ocean specific sensors are not designed for these complex aquatic environments and consequently are not likely to perform as well as a dedicated sensor would. As a CEOS action, CSIRO and DLR have taken the lead on a feasibility assessment to determine the benefits and technological difficulties of designing an Earth observing satellite mission focused on the biogeochemistry of inland, estuarine, deltaic and near coastal waters as well as mapping macrophytes, macro-algae, sea grasses and coral reefs. These environments need higher spatial resolution than current and planned ocean colour sensors offer and need higher spectral resolution than current and planned land Earth observing sensors offer (with the exception of several R&D type imaging spectrometry satellite missions). The results indicate that a dedicated sensor of (non-oceanic) aquatic ecosystems could be a multispectral sensor with ~26 bands in the 380-780 nm wavelength range for retrieving the aquatic ecosystem variables as well as another 15 spectral bands between 360-380 nm and 780-1400 nm for removing atmospheric and air-water interface effects. These requirements are very close to defining an imaging spectrometer with spectral bands between 360 and 1000 nm (suitable for Si based detectors), possibly augmented by a SWIR imaging spectrometer. In that case the spectral bands would ideally have 5 nm spacing and Full Width Half Maximum (FWHM), although it may be necessary to go to 8 nm wide spectral bands (between 380 to 780nm where the fine spectral features occur -mainly due to photosynthetic or accessory pigments) to obtain enough signal to noise. The spatial resolution of such a global mapping mission would be between ~17 and ~33 m enabling imaging of the vast majority of water bodies (lakes, reservoirs, lagoons, estuaries etc.) larger than 0.2 ha and ~25% of river reaches globally (at ~17 m resolution) whilst maintaining sufficient radiometric resolution

Climate Change Impacts on Agriculture in Europe

COST Action 734 was launched thanks to the coordinated activity of 29 EU countries. The main objective of the Action was the evaluation of impacts from climate change and variability on agriculture for various European areas. Secondary objectives were: collection and review of existing agroclimatic indices and simulation models, to assess hazard impacts on European agricultural areas; to apply climate scenarios for the next few decades; the definition of harmonised criteria to evaluate the impacts of climate change and variability on agriculture; the definition of warning systems guidelines. Based on the result, possible actions (specific recommendations, suggestions, warning systems) were elaborated and proposed to the end-users, depending on their needs

Analyse der Wasserfarbe von Seen mithilfe räumlich hoch und mittel auflösender Satelliten

Remote sensing techniques can assist traditional lake monitoring approaches by supplying spatial information on optically active lake ecology indicators, i.e. chlorophyll-a (CHL), total suspended matter (TSM), coloured dissolved organic matter (CDOM), and, especially in optically shallow waters, water depth and substrate composition. The present thesis provides an overview on the current research status concerning lake remote sensing and the benefit of time series analyses for lake ecology. To investigate the suitability of Sentinel-2 and Landsat 8 for lake monitoring and their combination with other sensors this thesis focused on two study areas with highly different optical characteristics, i.e. the oligotrophic Lake Starnberg (southern Germany) and the mesotrophic-eutrophic Lake Kummerow (northern Germany). Using the bio-optical model WASI-2D, Sentinel-2A turned out to be suited for retrieving low TSM and CDOM values. The high spatial resolution enabled the differentiation between bare ground and areas covered by submerged aquatic vegetation. Water depth estimations performed well until half Secchi disk depth. Cross-sensor comparisons demonstrated high correlation of CHL among timely acquired, spatially high and medium resolved sensors. Evaluations with in situ data showed that most of the sensor-in situ match-ups were within an uncertainty range of in situ measurements. Analysing a 9-year MERIS time series with FUB/WeW revealed unprecedented information on temporal trends and seasonal behaviour of CHL, TSM and CDOM at the study area Lake Kummerow. Combining CHL, retrieved with the Modular Inversion and Processing System, from different satellite sensors (MODIS, Landsat 7/ 8, Sentinel-2A) enabled detailed observations of phytoplankton development. Such combinations are a step forward to future lake analyses which may integrate remote sensing data, in situ measurements and environmental modelling.Fernerkundungstechniken können das Seemonitoring mit räumlichen Informationen über optisch aktive Indikatoren der Gewässerökologie liefern, z.B. Chlorophyll-a (CHL), suspendierte Schwebstoffe (TSM), Gelbstoffe (CDOM) und insbesondere in optisch flachen Gewässern, Wassertiefe und Substratbedeckung. Die vorliegende Arbeit gibt einen Überblick über den aktuellen Forschungsstand zur Seefernerkundung und den Nutzen von Zeitreihenanalysen für die Seeökologie. Um die Eignung von Sentinel-2 und Landsat 8 für ein Seenmonitoring und deren Kombination mit anderen Sensoren zu untersuchen, konzentrierte sich diese Arbeit auf zwei Untersuchungsgebiete mit sehr unterschiedlichen optischen Eigenschaften: den oligotrophen Starnberger See (Süddeutschland) und den mesotroph-eutrophen Kummerower See (Norddeutschland). Mit dem bio-optischen Modell WASI-2D erwies sich Sentinel-2A als geeignet, um niedrige TSM- und CDOM-Werte zu bestimmen. Die hohe räumliche Auflösung ermöglichte eine Unterscheidung zwischen unbewachsenem und mit Makrophyten bewachsenem Untergrund. Die Wassertiefenbestimmung verlief bis zur halben Sichttiefe gut. Sensorübergreifende Vergleiche zeigten eine hohe Korrelation von CHL zwischen zeitnah erfassten, räumlich mittel und hoch aufgelösten Sensoren. Auswertungen mit in-situ-Daten zeigten, dass die meisten Sensor-in-situ-Match-ups innerhalb eines Unsicherheitsbereichs von in-situ-Messungen lagen. Die Analyse einer 9-jährigen MERIS-Zeitreihe mit FUB/WeW ergab neue Informationen über zeitliche Trends und saisonales Verhalten von CHL, TSM und CDOM im Untersuchungsgebiet Kummerow See. Die Kombination von CHL aus verschiedenen Satellitensensoren (MODIS, Landsat 7/ 8, Sentinel-2A) mit dem Modular Inversion and Processing System ermöglichte detaillierte Beobachtungen der Phytoplanktonentwicklung. Solche Kombinationen sind ein Schritt für zukünftigen Gewässeranalysen, die Fernerkundungsdaten, in-situ-Messungen und Umweltmodellierung integrieren sollten