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Policy Document

Decision No 1386/2013/EU of the European Parliament and of the Council of 20 November 2013 on a General Union Environment Action Programme to 2020 ‘Living well, within the limits of our planet’

Policy Document
1 min read
Published: 2013-11-20 Corporate author(s): Council of the European Union , European Parliament Subject: biodiversity , economic growth , environmental impact , environmental protection , EU programme , investment , management of resources , pollution control

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Indicator Specification Drought impact on ecosystems in Europe The indicator addresses anomalies and long term trends of vegetation productivity derived from remote sensing observed time series of vegetation indices in areas that are pressured by drought. Drought pressure is computed as the combination of significant Pearson correlation coefficients (r) derived between time series anomalies of yearly vegetation productivity and the anomalies of various drought hazards (dH) during the growing season. Drought impact is indicated as the most sever negative productivity anomaly under drought pressured areas as well as long term decreasing linear trends of annual vegetation productivity for areas that are pressured by drought hazards. Detailed indicators’ specifications are presented under Methodology.
Indicator Specification Vegetation productivity The indicator addresses trends in land surface productivity derived from remote sensing observed time series of vegetation indices. The vegetation index used in the indicator is the Plant Phenology Index (PPI, Jin and Eklundh, 2014). PPI is based on the MODIS Nadir BRDF-Adjusted Reflectance product (MODIS MCD43 NBAR. The product provides reflectance data for the MODIS “land” bands (1 - 7) adjusted using a bi-directional reflectance distribution function. This function models values as if they were collected from a nadir-view to remove so called cross-track illumination effects. The Plant Phenology Index (PPI) is a new vegetation index optimized for efficient monitoring of vegetation phenology. It is derived from radiative transfer solution using reflectance in visible-red (RED) and near-infrared (NIR) spectral domains. PPI is defined to have a linear relationship to the canopy green leaf area index (LAI) and its temporal pattern is strongly similar to the temporal pattern of gross primary productivity (GPP) estimated by flux towers at ground reference stations. PPI is less affected by presence of snow compared to commonly used vegetation indices such as Normalized Difference Vegetation Index (NDVI) or Enhanced Vegetation Index (EVI). The product is distributed with 500 m pixel size (MODIS Sinusoidal Grid) with 8-days compositing period.  References: Jönsson P., Eklundh L., 2004. TIMESAT—a program for analyzing time-series of satellite sensor data. Computers & Geosciences 30 (2004) 833–845. Eklundh L., Jönsson P., 2015. TIMESAT: A Software Package for Time-Series Processing and Assessment of Vegetation Dynamics. In: Kuenzer C., Dech S., Wagner W. (eds) Remote Sensing Time Series. Remote Sensing and Digital Image Processing, vol 22. Springer, Cham Jin, H., Eklundh, L. 2014. A physically based vegetation index for improved monitoring of plant phenology, Remote Sensing of Environment, 152, 512 – 525. Karkauskaite, P., Tagesson, T., Fensholt, R., 2017. Evaluation of the Plant Phenology Index (PPI), NDVI and EVI for Start-of-Season Trend Analysis of the Northern Hemisphere Boreal Zone, Remote Sensing, 9 (485), 21 pp. Jin, H.X.; Jönsson, A.M.; Bolmgren, K.; Langvall, O.; Eklundh, L., 2017. Disentangling remotely-sensed plant phenology and snow seasonality at northern Europe using MODIS and the plant phenology index. Remote Sensing of Environment 2017,198, 203-212. Abdi, A. M., N. Boke-Olén, H. Jin, L. Eklundh, T. Tagesson, V. Lehsten and J. Ardö (2019). First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems. International Journal of Applied Earth Observation and Geoinformation 78: 249-260. Jin, H., A. M. Jönsson, C. Olsson, J. Lindström, P. Jönsson and L. Eklundh (2019). New satellite-based estimates show significant trends in spring phenology and complex sensitivities to temperature and precipitation at northern European latitudes. International Journal of Biometeorology 63(6): 763-775.
Indicator Specification Changes in fish distribution in European seas This indicator looks at the temporal development of the ratio between the number of Lusitanian and Boreal fish species within ICES Statistical rectangles and ICES divisions.
Indicator Specification Land recycling and densification This indicator addresses the use of urban land for further urban development, whether that urban land is currently in use or not. The indicator comprises two concepts of urban development: land recycling and land densification. Land recycling is defined as the reuse of abandoned, vacant or underused land for redevelopment. It includes ‘grey recycling’ and ‘green recycling’. Grey recycling is when ‘grey’ urban objects, such as buildings or transport infrastructures, are built under redevelopment. Green recycling is when ‘green’ urban objects, such as green urban areas or sport facilities, are built. Land densification is defined as the land development that takes place within existing communities, making maximum use of the existing infrastructure instead of building on previously undeveloped land. The indicator examines land recycling relative to total land consumption. Total land consumption is understood as all the land use processes occurring on or ending up in developed land, i.e. urban redevelopment, urban and infrastructure sprawl, and any change in previously developed land. Land recycling includes both the densification and the recycling phenomena. Therefore, land recycling is understood broadly and includes three components: land densification, grey land recycling and green land recycling.
Indicator Specification Oxygen consuming substances in European rivers This indicator illustrates current biochemical oxygen demand ( BOD) and concentrations of total ammonium (NH 4 ) in rivers, and examines trends in both. The key indicator for the oxygenation status of water bodies is BOD, which is the demand for oxygen resulting from organisms in water that consume oxidisable organic matter.

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