Simple statistical approach for computing land cover types and potential natural vegetation

Climate Research

Volumn 41, Issue 3, 2010, Pages 205-220

  Zampieri, M ^a   Lionello, P ^b  

^a CNR   (Italy)

^b CENTRO EURO MEDITERRANEO SUI CAMBIAMENTI CLIMATICI   (Italy)

Author keywords

Climate change; Impacts; K means clustering; Land cover; Landuse change; Potential vegetation

Indexed keywords

AUSTRALIA; BROADLEAF TREES; CENTRAL EUROPE; CLIMATE CHANGE IMPACT; CLIMATE MODEL; CLIMATE VARIABLES; DECIDUOUS TREES; DIAGNOSTIC MODEL; EASTERN EUROPE; GLOBAL SCALE; HIGH LATITUDES; HIGH-RESOLUTION DATASETS; K-MEANS CLUSTERING; LAND COVER; LAND-COVER TYPES; LAND-USE CHANGE; MIDLATITUDES; MIXED FORESTS; NATURAL VEGETATION; NORTHERN HEMISPHERES; SHRUBLANDS; SOUTH AMERICA; SOUTHERN HEMISPHERE; STATISTICAL APPROACH; URBAN AREAS;

ARID REGIONS; CLIMATE MODELS; CLUSTER ANALYSIS; FORESTRY; LANDFORMS; VEGETATION; WATER SUPPLY SYSTEMS;

CLIMATE CHANGE;

CLIMATE CHANGE; CLIMATE MODELING; CLUSTER ANALYSIS; DATA SET; DECIDUOUS FOREST; DESERT; ENVIRONMENTAL IMPACT; EVERGREEN FOREST; GRASSLAND; ICE COVER; LAND COVER; LAND USE CHANGE; LATITUDINAL GRADIENT; MIXED FOREST; MODEL TEST; NORTHERN HEMISPHERE; SAVANNA; SHRUBLAND; SNOW COVER; SOUTHERN HEMISPHERE; VEGETATION COVER; VEGETATION TYPE;

AUSTRALIA; CHINA; EUROPE; INDIA; RUSSIAN FEDERATION; SOUTH AMERICA;

EID: 77954103648     PISSN: 0936577X     EISSN: 16161572     Source Type: Journal    
DOI: 10.3354/cr00846     Document Type: Article

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