In this work remote sensing, geographic information systems (GIS) and fieldwork techniques are combined in an attempt to identify groundwater potential zones in the hilly terrain of the Pavagarh region. The various thematic maps prepared for delineating groundwater potential zones are lineament density, drainage density, digital elevation model (DEM), slope map and land use/land cover (LULC). A multi-criteria evaluation technique (MCE) is used to investigate a number of choice possibilities and evaluate suitability according to the associated weight of each factor. A map is obtained which shows the classification of the area into good, moderate and low groundwater potential zones.

Land use/Land cover (LULC) is a fundamental concept of the Earth's system intimately connected to many phases of the human and physical environment. Earth Observation (EO) technology provides an informative source of data covering the entire globe in a spatial and spectral resolution appropriate to better and easier classify land cover than traditional or conventional methods. The use of high spatial and spectral resolution imagery from EO sensors has increased remarkably over the past decades, as more and more platforms are placed in orbit and new applications emerge in different disciplines. The aim of the present review work is to provide all-inclusive critical reflection on the state of the art in the use of EO technology in LULC mapping and change detection. The emphasis is placed on providing an overview of the different EO datasets, spatial-spectral-temporal characteristics of satellite data and classification approaches employed in land cover classification. The review concludes providing recommendations and remarks on what should be done in order to overcome hurdle faced using above-mentioned problems in LULC mapping. This also provides information on using classifier algorithms depending upon the data types and dependent on the regional ecosystems. One of the main messages of our review is that in future, there will be a need to assemble techniques specifically used in LULC with their merit and demerits that will enable more comprehensive understanding at regional or global scale and improve understanding between different land cover relationship and variability among them and these remains to be seen.