@techreport{nokey,

title = {ETC/ULS Technical Report 01/2021: Time series inconsistency in the Copernicus HRL Imperviousness. Analysis of the 2015-2018 changes, implications and conclusions},

author = {M. Gregor and M. Löhnertz and R. Milego and J. Fons and G. Maucha and E. Mancosu and A. Littkopf and E. Ivits},

url = {https://www.eionet.europa.eu/etcs/etc-di/products/etc-uls-technical-report-01-2021-time-series-inconsistency-in-the-copernicus-hrl-imperviousness-analysis-of-the-2015-2018-changes-implications-and-conclusions},

year  = {2021},

date = {2021-12-14},

abstract = {A land cover (land use) map is always an abstraction, a model of the real earth surface. Features represented in this model are influenced by many factors, including the classification system, scale / level of generalization (e.g., Minimum Mapping Unit or MMU) and other mapping instructions as well as possible database errors. As long as the data model is consistent within a time series, changes and trends derived by pixel- or grid-based approaches (“pixel counting”) may be meaningful, i.e., valid within the same model (e.g., Corine Land Cover or CLC accounting). This is in fact the core idea of “pixel counting” based accounting systems.



Copernicus High Resolution Layers (HRLs) are Earth Observation (EO)-derived and raster-based datasets which provide information about different land cover characteristics. The longest and most complete time-series is available for the HRL Imperviousness products, with the first status layer being available for the reference year 2006, then 2009, 2012, 2015 and 2018. Change information are available for all change periods (both, density change and change classified). Primary 20m resolution (and aggregated 100m resolution) products were harmonized for the 2006-2015 period in a way that imperviousness status and change layers build a consistent time series, where imperviousness density changes are equal to the difference of subsequent imperviousness status layers.



However, the introduction of the increased 10m resolution in case of all primary HRLs in 2018 caused unexpected issues. The great advantage of the increased resolution has led to the appearance of more feature details. On the flipside, this fact has made the new 10m resolution imperviousness product incompatible with the previous time series especially in a statistical sense. Thus, with the introduction of the 10m EO data as basis for the HRL production, the data model of the HRL IMD became inconsistent, i.e., the long time series is broken and we are talking about two time series (2006-2015 with 20m resolution and from 2018 onwards with 10m resolution; there is no way to use and assess changes between 2015 and 2018 at the moment). As a consequence, any assessment and product that is dependent on the time series has to be broken down into two parts. This technical note describes the reasons and implications in more detail and draws some conclusions.},

keywords = {Geotechnology},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Ivits2020,

title = {ETC/ULS Report 02/2020: Land and ecosystem accounts for Europe. Towards geospatial environmental accounting},

author = {E. Ivits and R. Milego and E. Mancosu and M. Gregor and J.E. Petersen and G. Büttner and M. Löhnertz and G. Maucha and O. Petrik and A. Bastrup-Birk and J. Tafi and G. Hazeu},

url = {https://www.eionet.europa.eu/etcs/etc-di/products/etc-uls-report-02-2020-land-and-ecosystem-accounts-for-europe-towards-geospatial-environmental-accounting},

isbn = {978-3-200-07114-8},

year  = {2020},

date = {2020-09-30},

urldate = {2020-09-30},

abstract = {Land use and land use change are fundamental for sustainable resource use and the delivery of ecosystem services, including the provision of food, nutrient cycling and climate change mitigation through carbon sequestration. Land resources are part of our shared natural capital and must be well managed to maintain a healthy environment and human well-being. As such, only if land use and its impacts are properly addressed is progress towards sustainable development in Europe possible. Land-use related policies require the development of harmonised datasets, transparent methodologies and easily interpretable statistics. Land accounts fit the bill, describing how land resource stocks change over time.},

keywords = {Conservation and management, Ecosystem, Ecosystem services, Environmental conservation, Land and soil},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Mancosu2012,

title = {The enviroGRIDS scenarios},

author = {E. Mancosu},

url = {http://envirogrids.net/indexe649.html?option=com_jdownloads&Itemid=13&view=view.download&catid=12&cid=137 / http://envirogrids.net/envirogrids_d3.8_scenariosbd3b.pdf?option=com_jdownloads&Itemid=13&view=finish&cid=137&catid=12},

year  = {2012},

date = {2012-04-24},

institution = {EnviroGRIDS},

abstract = {The enviroGRIDS scenarios comprise a number of plausible alternatives (storylines) based on a coherent set of assumptions, key relationships and driving forces, to create a set of quantitative,

internally consistent and spatially explicit scenarios of future demography, climate and land use (LU) covering the entire Black Sea Catchment (BSC).

The aim of this report is to describe the technical specification of the final scenarios, the source data used and the different methodologies applied on each of them. We describe how the different sources were used and integrated in order to obtain the four alternatives storylines (HOT, ALONE, COOP and COOL), for a yearly time series from 2008 to 2050. The method applied to obtain the demographic growth according to the different storyline for the same time series is also described. Furthermore we describe also the results of the spatially explicit scenarios on climate change for the BSC (Task 3.6) of WP3, for a daily precipitation and temperature time series between 2071 and 2100.},

keywords = {Climate Change, EnviroGRIDS, Geotechnology},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Barbosa2011,

title = {Proposed land use scenario analysis, model input parameters and allocation rules},

author = {A. Barbosa and E. Mancosu and A. Gago-Silva and A. de Bono and A. Lehmann and M. Mierla and J. Hanganu and A. Littkopf},

url = {http://envirogrids.net/indexa4c5.html?option=com_jdownloads&Itemid=13&view=view.download&catid=12&cid=120 / http://envirogrids.net/envirogrids_d3_7a10b.pdf?option=com_jdownloads&Itemid=13&view=finish&cid=120&catid=12},

year  = {2011},

date = {2011-07-06},

institution = {EnviroGRIDS},

abstract = {The enviroGRIDS scenarios comprise a number of plausible alternatives (storylines) based on a coherent set of assumptions, key relationships and driving forces, to create a set of quantitative, internally consistent and spatially explicit scenarios of future demography, climate and land use covering the entire Black Sea Catchment (BSC).

This report presents the analyses of the land use scenarios, a review of the combined method used to quantify the enviroGRIDS land use demand and the disaggregation of the global scenarios at a regional scale. Global land use demand was obtained from IMAGE 2.2 and disaggregated at regional (NUTS2) level. Afterwards a cellular automaton based land use model was applied to allocate the land use demands at local level. Land use allocation rules were assigned based on the scenario storylines and local decision rules. As a result, four alternative land use scenarios were derived: BS HOT, BS ALONE, BS COOP and BS COOL. The designation of allocation rules introduces local decisions based not only on the scenario storylines and expert knowledge but also on historical land use patterns. The method used can fill the gap between the global and regional scales and consequently translate land use patterns at various spatial levels.},

keywords = {Climate Change, EnviroGRIDS, Geotechnology, Land and soil},

pubstate = {published},

tppubtype = {techreport}

}

@techreport{Barbosa2010,

title = {Land cover model inputs and efficient data model with possibilities to be updated},

author = {A. Barbosa and E. Ivanov and E. Mancosu and J. Hanganu},

editor = {Autonomous University of Barcelona},

url = {http://envirogrids.net/indexae9e.html?option=com_jdownloads&Itemid=13&view=view.download&catid=12&cid=33},

year  = {2010},

date = {2010-03-01},

journal = {enviroGRIDS},

pages = {82},

institution = {EnviroGRIDS},

keywords = {Climate Change, EnviroGRIDS, Geotechnology, Land and soil},

pubstate = {published},

tppubtype = {techreport}

}