UnivTrevesV1, PascalFrancis, Corpus, bibRecord, 000189

Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data

Identifieur interne : 000189 ( PascalFrancis/Corpus ); précédent : 000188; suivant : 000190

Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data

Auteurs : M. Stellmes ; A. Röder ; T. Udelhoven ; J. Hill

Source :

Land use policy [ 0264-8377 ] ; 2013.

RBID : Pascal:13-0135759

Descripteurs français

Pascal (Inist)
- Cartographie, Syndrome, Télédétection, Série temporelle, Démographie, Donnée climatique, Occupation sol, Milieu aride, Fonctionnement écosystème, Espagne, Indice végétation, Satellite NOAA, Politique environnement, Service écosystémique, Radiomètre très haute résolution technologie avancée.

English descriptors

KwdEn :
- AVHRR radiometer, Arid environment, Cartography, Climatic data, Demography, Ecosystem functioning, Ecosystem service, Environmental policy, Land use, NOAA satellite, Remote sensing, Spain, Syndrome, Time series, Vegetation index.

Abstract

The country of Spain is representative of land change processes in Mediterranean member states of the European Union (EU). These land change processes are often triggered by European, national and sub-national policies and include widespread land abandonment and urbanisation trends, as well as an increase in land use intensities accompanied by strong exploitation of water resources. The Mediterranean is part of the dryland ecoregion, which is particularly vulnerable to ecosystem degradation. While remote sensing data permit the characterisation of the temporal dimension of land surface processes, the syndrome-based approach aims to integrate this with information on local/regional socio-economic and physical frameworks. In this study, we incorporated two major drivers of land change, climatic boundary conditions and population density change, to understand the patterns of the assessed land cover changes. We used the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS), which represents the Mediterranean Basin at a resolution of 1 km² for the period of 1989-2004 at 10-day time intervals. The long-term vegetation trend could be characterised based on a linear regression analysis of Normalised Difference Vegetation Index (NDVI) values. Further descriptors of phenology were calculated, such as the amplitude of annual cycles or the date of occurrence of the annual maximum of vegetation cover. Subsequently, trend analysis was applied to these parameters to map phenology shifts representative of changes in land use/cover. Next, a rule-based classification was employed to integrate the individual results and assign syndromes representing specific land change process patterns. For natural and semi-natural areas, locations characterised by increasing biomass are associated with areas of population loss due to migration to urban centres. By contrast, many fertile agricultural areas are associated with intensification processes, including the expansion of irrigation schemes. Furthermore, areas that are dominated by inter-annual variability in precipitation were identified by employing the results of an analysis of NDVI-rainfall relationships. The resulting data set identifies major land change syndromes for the whole of Spain and links the apparent results of change to driving factors and causes, thus serving as an excellent data source to inform policy makers of effects caused by legislative and management actions.

Notice en format standard (ISO 2709)

Pour connaître la documentation sur le format Inist Standard.

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Format Inist (serveur)

NO :	PASCAL 13-0135759 INIST
ET :	Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data
AU :	STELLMES (M.); RÖDER (A.); UDELHOVEN (T.); HILL (J.)
AF :	University of Trier, Remote Sensing Department, Behringstr. 15/54286 Trier/Allemagne (1 aut., 2 aut., 3 aut., 4 aut.)
DT :	Publication en série; Niveau analytique
SO :	Land use policy; ISSN 0264-8377; Pays-Bas; Da. 2013; Vol. 30; Pp. 685-702; Bibl. 2 p.1/4
LA :	Anglais
EA :	The country of Spain is representative of land change processes in Mediterranean member states of the European Union (EU). These land change processes are often triggered by European, national and sub-national policies and include widespread land abandonment and urbanisation trends, as well as an increase in land use intensities accompanied by strong exploitation of water resources. The Mediterranean is part of the dryland ecoregion, which is particularly vulnerable to ecosystem degradation. While remote sensing data permit the characterisation of the temporal dimension of land surface processes, the syndrome-based approach aims to integrate this with information on local/regional socio-economic and physical frameworks. In this study, we incorporated two major drivers of land change, climatic boundary conditions and population density change, to understand the patterns of the assessed land cover changes. We used the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS), which represents the Mediterranean Basin at a resolution of 1 km² for the period of 1989-2004 at 10-day time intervals. The long-term vegetation trend could be characterised based on a linear regression analysis of Normalised Difference Vegetation Index (NDVI) values. Further descriptors of phenology were calculated, such as the amplitude of annual cycles or the date of occurrence of the annual maximum of vegetation cover. Subsequently, trend analysis was applied to these parameters to map phenology shifts representative of changes in land use/cover. Next, a rule-based classification was employed to integrate the individual results and assign syndromes representing specific land change process patterns. For natural and semi-natural areas, locations characterised by increasing biomass are associated with areas of population loss due to migration to urban centres. By contrast, many fertile agricultural areas are associated with intensification processes, including the expansion of irrigation schemes. Furthermore, areas that are dominated by inter-annual variability in precipitation were identified by employing the results of an analysis of NDVI-rainfall relationships. The resulting data set identifies major land change syndromes for the whole of Spain and links the apparent results of change to driving factors and causes, thus serving as an excellent data source to inform policy makers of effects caused by legislative and management actions.
CC :	002A14D; 002A14B04
FD :	Cartographie; Syndrome; Télédétection; Série temporelle; Démographie; Donnée climatique; Occupation sol; Milieu aride; Fonctionnement écosystème; Espagne; Indice végétation; Satellite NOAA; Politique environnement; Service écosystémique; Radiomètre très haute résolution technologie avancée
FG :	Europe; Europe Sud
ED :	Cartography; Syndrome; Remote sensing; Time series; Demography; Climatic data; Land use; Arid environment; Ecosystem functioning; Spain; Vegetation index; NOAA satellite; Environmental policy; Ecosystem service; AVHRR radiometer
EG :	Europe; Southern Europe
SD :	Cartografía; Síndrome; Teledetección; Serie temporal; Demografía; Dato climático; Ocupación terreno; Medio árido; Funcionamiento ecosistema; España; Indice de vegetación; Satélite NOAA; Política medio ambiente; Servicio ecosistémico; Radiómetro avanzado de muy alta resolución
LO :	INIST-28133.354000173232970670
ID :	13-0135759

Links to Exploration step

Pascal:13-0135759

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<front><div type="abstract" xml:lang="en">The country of Spain is representative of land change processes in Mediterranean member states of the European Union (EU). These land change processes are often triggered by European, national and sub-national policies and include widespread land abandonment and urbanisation trends, as well as an increase in land use intensities accompanied by strong exploitation of water resources. The Mediterranean is part of the dryland ecoregion, which is particularly vulnerable to ecosystem degradation. While remote sensing data permit the characterisation of the temporal dimension of land surface processes, the syndrome-based approach aims to integrate this with information on local/regional socio-economic and physical frameworks. In this study, we incorporated two major drivers of land change, climatic boundary conditions and population density change, to understand the patterns of the assessed land cover changes. We used the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS), which represents the Mediterranean Basin at a resolution of 1 km<sup>2</sup>
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<fC01 i1="01" l="ENG"><s0>The country of Spain is representative of land change processes in Mediterranean member states of the European Union (EU). These land change processes are often triggered by European, national and sub-national policies and include widespread land abandonment and urbanisation trends, as well as an increase in land use intensities accompanied by strong exploitation of water resources. The Mediterranean is part of the dryland ecoregion, which is particularly vulnerable to ecosystem degradation. While remote sensing data permit the characterisation of the temporal dimension of land surface processes, the syndrome-based approach aims to integrate this with information on local/regional socio-economic and physical frameworks. In this study, we incorporated two major drivers of land change, climatic boundary conditions and population density change, to understand the patterns of the assessed land cover changes. We used the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS), which represents the Mediterranean Basin at a resolution of 1 km<sup>2</sup>
 for the period of 1989-2004 at 10-day time intervals. The long-term vegetation trend could be characterised based on a linear regression analysis of Normalised Difference Vegetation Index (NDVI) values. Further descriptors of phenology were calculated, such as the amplitude of annual cycles or the date of occurrence of the annual maximum of vegetation cover. Subsequently, trend analysis was applied to these parameters to map phenology shifts representative of changes in land use/cover. Next, a rule-based classification was employed to integrate the individual results and assign syndromes representing specific land change process patterns. For natural and semi-natural areas, locations characterised by increasing biomass are associated with areas of population loss due to migration to urban centres. By contrast, many fertile agricultural areas are associated with intensification processes, including the expansion of irrigation schemes. Furthermore, areas that are dominated by inter-annual variability in precipitation were identified by employing the results of an analysis of NDVI-rainfall relationships. The resulting data set identifies major land change syndromes for the whole of Spain and links the apparent results of change to driving factors and causes, thus serving as an excellent data source to inform policy makers of effects caused by legislative and management actions.</s0>
</fC01>
<fC02 i1="01" i2="X"><s0>002A14D</s0>
</fC02>
<fC02 i1="02" i2="X"><s0>002A14B04</s0>
</fC02>
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<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="ENG"><s0>Cartography</s0>
<s5>01</s5>
</fC03>
<fC03 i1="01" i2="X" l="SPA"><s0>Cartografía</s0>
<s5>01</s5>
</fC03>
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<s5>02</s5>
</fC03>
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<s5>02</s5>
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<s5>02</s5>
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<s5>03</s5>
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<s5>03</s5>
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<s5>03</s5>
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<s5>04</s5>
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<s5>05</s5>
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<s5>06</s5>
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<s5>06</s5>
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<s5>06</s5>
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<s5>07</s5>
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<s5>07</s5>
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<s5>07</s5>
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<s5>08</s5>
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<s5>08</s5>
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<s5>08</s5>
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<s5>09</s5>
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<s5>09</s5>
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<fC03 i1="09" i2="X" l="SPA"><s0>Funcionamiento ecosistema</s0>
<s5>09</s5>
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<s2>NG</s2>
<s5>20</s5>
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<s2>NG</s2>
<s5>20</s5>
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<fC03 i1="10" i2="X" l="SPA"><s0>España</s0>
<s2>NG</s2>
<s5>20</s5>
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<s5>28</s5>
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<fC03 i1="11" i2="X" l="ENG"><s0>Vegetation index</s0>
<s5>28</s5>
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<fC03 i1="11" i2="X" l="SPA"><s0>Indice de vegetación</s0>
<s5>28</s5>
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<s5>29</s5>
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<s5>29</s5>
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<s5>30</s5>
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<s5>30</s5>
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<fC03 i1="14" i2="X" l="FRE"><s0>Service écosystémique</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="14" i2="X" l="ENG"><s0>Ecosystem service</s0>
<s4>CD</s4>
<s5>96</s5>
</fC03>
<fC03 i1="14" i2="X" l="SPA"><s0>Servicio ecosistémico</s0>
<s4>CD</s4>
<s5>96</s5>
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<fC03 i1="15" i2="X" l="FRE"><s0>Radiomètre très haute résolution technologie avancée</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC03 i1="15" i2="X" l="ENG"><s0>AVHRR radiometer</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC03 i1="15" i2="X" l="SPA"><s0>Radiómetro avanzado de muy alta resolución</s0>
<s4>CD</s4>
<s5>97</s5>
</fC03>
<fC07 i1="01" i2="X" l="FRE"><s0>Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="ENG"><s0>Europe</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="01" i2="X" l="SPA"><s0>Europa</s0>
<s2>NG</s2>
</fC07>
<fC07 i1="02" i2="X" l="FRE"><s0>Europe Sud</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fC07 i1="02" i2="X" l="ENG"><s0>Southern Europe</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fC07 i1="02" i2="X" l="SPA"><s0>Europa Sur</s0>
<s2>NG</s2>
<s5>59</s5>
</fC07>
<fN21><s1>112</s1>
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<fN44 i1="01"><s1>OTO</s1>
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<fN82><s1>OTO</s1>
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<server><NO>PASCAL 13-0135759 INIST</NO>
<ET>Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data</ET>
<AU>STELLMES (M.); RÖDER (A.); UDELHOVEN (T.); HILL (J.)</AU>
<AF>University of Trier, Remote Sensing Department, Behringstr. 15/54286 Trier/Allemagne (1 aut., 2 aut., 3 aut., 4 aut.)</AF>
<DT>Publication en série; Niveau analytique</DT>
<SO>Land use policy; ISSN 0264-8377; Pays-Bas; Da. 2013; Vol. 30; Pp. 685-702; Bibl. 2 p.1/4</SO>
<LA>Anglais</LA>
<EA>The country of Spain is representative of land change processes in Mediterranean member states of the European Union (EU). These land change processes are often triggered by European, national and sub-national policies and include widespread land abandonment and urbanisation trends, as well as an increase in land use intensities accompanied by strong exploitation of water resources. The Mediterranean is part of the dryland ecoregion, which is particularly vulnerable to ecosystem degradation. While remote sensing data permit the characterisation of the temporal dimension of land surface processes, the syndrome-based approach aims to integrate this with information on local/regional socio-economic and physical frameworks. In this study, we incorporated two major drivers of land change, climatic boundary conditions and population density change, to understand the patterns of the assessed land cover changes. We used the Mediterranean Extended Daily One Km AVHRR Data Set (MEDOKADS), which represents the Mediterranean Basin at a resolution of 1 km<sup>2</sup>
 for the period of 1989-2004 at 10-day time intervals. The long-term vegetation trend could be characterised based on a linear regression analysis of Normalised Difference Vegetation Index (NDVI) values. Further descriptors of phenology were calculated, such as the amplitude of annual cycles or the date of occurrence of the annual maximum of vegetation cover. Subsequently, trend analysis was applied to these parameters to map phenology shifts representative of changes in land use/cover. Next, a rule-based classification was employed to integrate the individual results and assign syndromes representing specific land change process patterns. For natural and semi-natural areas, locations characterised by increasing biomass are associated with areas of population loss due to migration to urban centres. By contrast, many fertile agricultural areas are associated with intensification processes, including the expansion of irrigation schemes. Furthermore, areas that are dominated by inter-annual variability in precipitation were identified by employing the results of an analysis of NDVI-rainfall relationships. The resulting data set identifies major land change syndromes for the whole of Spain and links the apparent results of change to driving factors and causes, thus serving as an excellent data source to inform policy makers of effects caused by legislative and management actions.</EA>
<CC>002A14D; 002A14B04</CC>
<FD>Cartographie; Syndrome; Télédétection; Série temporelle; Démographie; Donnée climatique; Occupation sol; Milieu aride; Fonctionnement écosystème; Espagne; Indice végétation; Satellite NOAA; Politique environnement; Service écosystémique; Radiomètre très haute résolution technologie avancée</FD>
<FG>Europe; Europe Sud</FG>
<ED>Cartography; Syndrome; Remote sensing; Time series; Demography; Climatic data; Land use; Arid environment; Ecosystem functioning; Spain; Vegetation index; NOAA satellite; Environmental policy; Ecosystem service; AVHRR radiometer</ED>
<EG>Europe; Southern Europe</EG>
<SD>Cartografía; Síndrome; Teledetección; Serie temporal; Demografía; Dato climático; Ocupación terreno; Medio árido; Funcionamiento ecosistema; España; Indice de vegetación; Satélite NOAA; Política medio ambiente; Servicio ecosistémico; Radiómetro avanzado de muy alta resolución</SD>
<LO>INIST-28133.354000173232970670</LO>
<ID>13-0135759</ID>
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Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data

Mapping syndromes of land change in Spain with remote sensing time series, demographic and climatic data

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