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295Examples of land use variation for the same land cover class are industrial and residential areas land cover build up irrigated vs rain fed cropland land cover cropland reservoirs vs natural lakes land cover water recreation vs grasslands land cover grass timbering vs environment land cover forests In case of a combination of land cover and land use classes on the same map it is preferred to use Land Use and Land Cover LULC classes There are several global scale land cover databases have been produced since the early nineties e g Global Land Cover Characteristics GLCC database carried out under the supervision of the International Geosphere Biosphere Program IGBP International Water Management Institute IWMI land cover database Global Land Cover GLC 2000 and Global land Cover Glob Cover developed by European Space Agency ESA 1 km resolution Advanced Very High Resolution Radiometer AVHRR data of monthly Normalized Difference Vegetation Index NDVI using unsupervised classification was used to develop GLCC database and later improvements were carried out to develop land cover database for the year 1992 93 Loveland et al 2000 IWMI database was based on the year 2001 02 and used Moderate Resolution Imaging Spectroradiometer MODIS 500 m NDVI datasets It was produced using unsupervised classification and refined by ground truth data GLC2000 was global land cover database developed using 9 months Satellite Probatoire d'Observation delaTerre SPOT vegetation data for the year 1999 2000 Glob Cover was developed at recent times using the 300 m resolution
Medium Resolution Imaging Spectrometer MERIS satellite data for the year 2005 06 Arino et al 2008 The mapping accuracies of these global products are sensible i e 63 83 but these were developed for use in global climate studies These data sets are most likely useful for general land cover pattern analysis at large scale These global datasets are however unsuitable to support basin level water management analysis and their applications due to lack of detailed information on land use Such global databases cannot differentiate specific crops and only detects dominant land covers leading to a large percentage of mixed classes with natural vegetation Portmann et al 2010 Since within irrigated land uses different crops are sown with different crop water requirements Therefore more specific crop based classifications are needed to implement proper water allocation plans General land cover information by means of a few classes without the land use functioning is thus insufficient and novel techniques to determine land use classes need to be developed Meyer and Turner 1994 Schwarz and Zimmermann 2005 Therefore a methodology has to be developed to derive LULC for the vast Indus Basin The methodology that will be tested is Normalized vegetation index NDVI derived from satellite based remotely sensed information supported with ground based information and crop growing pattern Another goal is to obtain Real pattern of water use by recognizing and using different crop rotations in the study area The main objective of this research is to develop up to date locally consistent and detailed LULC map with reasonable efforts that could also be used to acquire LULC information for other basins with water resources problems in other parts of the world