Ten-daily global composites of METOP-AVHRR

Eerens, Herman; Baruth, Bettina; Bydekerke, Lieven; Deronde, Bart; Dries, Jan; Goor, Erwin; Heyns, Walter; Jacobs, Tim; Ooms, Bart; Piccard, Isabelle; Royer, A.; Swinnen, Else; Timmermans, Adri; Roey, Tom Van; Vereecken, Johan; Verheijen, Yves

doi:10.1117/12.873233

Cited by 5 publications

(2 citation statements)

References 11 publications

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“…The NRT ASIS inputs are provided by the 10-daily ("dekadal" or "S10") composites, derived by the Flemish Institute for Technological Research (VITO) from the Earth Observation (EO) system METOP-AVHRR (1 km spatial resolution, since March 2007) and freely available via the portal https://www.vito-eodata.be/PDF/portal/Application.html# Home. A description of the preprocessing methodology can be found in Eerens et al [15,16]. In order to extend the time series retrospectively, similar AVHRR composites, derived from subsequent NOAA platforms, were acquired for the years from 1984 to 2012 from the portal of NOAA-STAR (Center for Satellite Applications and Research, ftp://ftp.star.nesdis.…”

Section: Data 211 Global Earth Observation Data Setsmentioning

confidence: 99%

Next Generation Agricultural Stress Index System (ASIS) for Agricultural Drought Monitoring

Rojas

2021

Remote Sensing

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Over the past 40 years, drought has affected more people in the world than any other natural hazard, affecting large segments of the population and destroying the natural resource base, livestock and livelihoods. Recent projections show that drought events are expected to increase in frequency and intensity due to climate change. According to studies conducted by the Food and Agriculture Organization of the United Nations (FAO), 83% of all damages and losses caused globally by drought between 2006 and 2016 have been absorbed by agriculture, putting a large part of the world’s population at risk of food insecurity. This study shows the advantage of scaling-up FAO’s agricultural drought monitoring and early warning system (ASIS) and building the bridge with the anticipatory action, drought financial mechanisms, social protection and other initiatives for preventing the deterioration of food security and strengthening resilience. The results of the methodology that is based on and supported by the digital innovation, machine learning, matured knowledge and experiences accumulated over the past 10 years are illustrated with practical examples from different countries, ecological environments and crops. A fused time series of Advanced Very-High-Resolution Radiometer (AVHRR) data from Meteorological Operational satellite (METOP) and National Oceanic and Atmospheric Administration (NOAA) was used to produce a consistent time series of a vegetation health index (VHI) at 1 km spatial resolution from 1984 to present. VHI is multiplied by the crop coefficient (kc) to provide more responsiveness to the VHI anomaly that occurs during sensitive phenological phases to water stress such as a flowering and grain filling. The weighted VHI (wVHI) is integrated from the start of the season (SOS) up to the end of season (EOS). Once the temporal analysis of wVHI is completed, the spatial average is calculated using the values of pixels within a specific crop mask and administrative unit. The system proposed different vegetation indices to assess the impact of drought in agriculture; including an agricultural drought forecast that provide more time to the decision makers for implementing anticipatory actions to mitigate the drought in agriculture. Next generation agricultural stress index system (ASIS) offers full capabilities to support: parametric crop insurance, social protection schemes, early action, national drought management plans and to guide public investments.

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Section: Data 211 Global Earth Observation Data Setsmentioning

confidence: 99%

Next Generation Agricultural Stress Index System (ASIS) for Agricultural Drought Monitoring

Rojas

2021

Remote Sensing

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“…METOP has a local stable overpass time at around 9:30 h. The AVHRR-instrument onboard METOP is used to generate 10-daily NDVI by the LSA-SAF (http://landsaf.meteo.pt). The AVHRR S10 TOC surface reflectance and NDVI are processed in a very similar way to those of PROBA-V, with the same water vapor and ozone inputs, and a similar atmospheric correction and compositing method [26]. There are however differences in calibration, cloud detection, and overpass time stability.…”

Section: Metop/avhrrmentioning

confidence: 99%

Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening

et al. 2018

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PROBA-V (PRoject for On-Board Autonomy-Vegetation) was launched in May-2013 as an operational continuation to the vegetation (VGT) instruments on-board the Système Pour l'Observation de la Terre (SPOT)-4 and -5 satellites. The first reprocessing campaign of the PROBA-V archive from Collection 0 (C0) to Collection 1 (C1) aims at harmonizing the time series, thanks to improved radiometric and geometric calibration and cloud detection. The evaluation of PROBA-V C1 focuses on (i) qualitative and quantitative assessment of the new cloud detection scheme; (ii) quantification of the effect of the reprocessing by comparing C1 to C0; and (iii) evaluation of the spatio-temporal stability of the combined SPOT/VGT and PROBA-V archive through comparison to METOP/advanced very high resolution radiometer (AVHRR). The PROBA-V C1 cloud detection algorithm yields an overall accuracy of 89.0%. Clouds are detected with very few omission errors, but there is an overdetection of clouds over bright surfaces. Stepwise updates to the visible and near infrared (VNIR) absolute calibration in C0 and the application of degradation models to the SWIR calibration in C1 result in sudden changes between C0 and C1 Blue, Red, and NIR TOC reflectance in the first year, and more gradual differences for short-wave infrared (SWIR). Other changes result in some bias between C0 and C1, although the root mean squared difference (RMSD) remains well below 1% for top-of-canopy (TOC) reflectance and below 0.02 for the normalized difference vegetation index (NDVI). Comparison to METOP/AVHRR shows that the recent reprocessing campaigns on SPOT/VGT and PROBA-V have resulted in a more stable combined time series.are widely used to monitor environmental change and the evolution of vegetation cover in different thematic domains [2], hence the relevance to the continuity of the service.On board the PROBA-V, the optical instrument provides data at 1 km, 300 m, and 100 m consistent with the 1 km resolution data products of SPOT/VGT [3]. To support the existing SPOT/VGT user community, the PROBA-V mission continues provision of projected segments (Level 2A, similar to the SPOT/VGT P-products), daily top-of-canopy (TOC) synthesis (S1-TOC) and 10-day synthesis (S10-TOC) products. In addition, top-of-atmosphere (TOA) daily synthesis (S1-TOA) products and radiometrically/geometrically corrected data (level 1C) products in raw resolution (up to 100 m) are provided for scientific use [4,5]. Since PROBA-V has no onboard propellant, the overpass time (10:45 h at launch) will decrease as a result of increasing atmospheric drag [6].In previous years, vegetation monitoring applications were built on PROBA-V data, e.g., on cropland mapping [7], crop identification [8], estimation of biophysical parameters [9,10], and crop yield forecasting [11]. A method was also developed to assimilate data of PROBA-V 100 and 300 m [12]. For the Copernicus Global Land Service, PROBA-V is one of the prime sensors for operational vegetation products [13,14]. Access to and exploitation of the SPOT/...

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Derivation of air temperature of agricultural areas of Morocco from remotely land surface temperature based on the updated Köppen-Geiger climate classification

Hadria¹,

Benabdelouahab²,

Elmansouri

et al. 2019

Model. Earth Syst. Environ.

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Ten-daily global composites of METOP-AVHRR

Cited by 5 publications

References 11 publications

Next Generation Agricultural Stress Index System (ASIS) for Agricultural Drought Monitoring

Next Generation Agricultural Stress Index System (ASIS) for Agricultural Drought Monitoring

Evaluation of PROBA-V Collection 1: Refined Radiometry, Geometry, and Cloud Screening

Derivation of air temperature of agricultural areas of Morocco from remotely land surface temperature based on the updated Köppen-Geiger climate classification

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