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Land use/land cover (LULC) information is essential for the selection, planning and implementation of management strategies to meet the increasing demands for basic human needs and welfare of the ever growing population. This paper illustrates the status of land use/land cover in the Tirupati area of Andhra Pradesh state using an integrated approach of remote sensing and Geographic Information System (GIS). The National Land use/Land cover classification developed by National Remote Sensing Centre (NRSC) and Indian Space Research Organisation (ISRO) divides the land in the study area into five Level I classes, 11 Level II classes, and fifteen Level III classes. From this three-level hierarchic based classification, it was found that the Forest is the major LULC category in the Tirupati area covering 227.46 km 2 (58.55%), followed by Agricultural land, Wastelands, Built-up land and water bodies contributing to 70.36 km 2 (18.11%), 43.92 km 2 (11.31%), 32.71 km 2 (8.42%) and 14.03 km 2 (3.61%) respectively of the total geographical area. This study also reviewed the characteristics of urban sprawl and their impacts on quality of life, the evident driving forces and its impact on development activities. The study concludes that in Tirupati area forest land contributed the highest land cover (58.55%), while the lowest was contributed by water bodies (3.61%) and shows a significant impact of urbanization on the ecosystem.

Water quality of lakes, estuaries, and coastal areas serves as an indicator of the overall health of aquatic ecosystems as well as the health of the terrestrial ecosystem that drains to the water body. Land use and land cover plays not only a significant role in controlling the quantity of the exported dissolved organic matter (DOM) but also influences the quality of DOM via various biogeochemical and biodegradation processes. We examined the characteristics and spatial distribution of DOM in five major lakes, in an estuary, and in the coastal waters of the Mississippi, USA, and investigated the influence of the land use and land cover of their watersheds on the DOM composition. We employed absorption and fluorescence spectroscopy including excitation-emission matrix (EEM) combined with parallel factor (PARAFAC) analysis modeling techniques to determine optical properties of DOM and its characteristics in this study. We developed a site-specific PARAFAC model to evaluate DOM characteristics resulting in five diverse DOM compositions that included two terrestrial humic-like (C1 and C3), two microbial humic-like (C2 and C5), and one protein-like (C4) DOM. Our results showed elevated fluorescence levels of microbial humic-like or protein-like DOM in the lakes and coastal waters, while the estuarine waters showed relatively high fluorescence levels of terrestrial humic-like DOM. The results also showed that percent forest and wetland coverage explained 68 and 82% variability, respectively, in terrestrial humic-like DOM exports, while 87% variability in microbially derived humiclike DOM was explained by percent agricultural lands. Strong correlations between microbial humic-like DOM and fluorescence-derived DOM indices such as biological index (BIX) and fluorescence index (FI) indicated autochthonous characteristics in the lakes, while the estuary showed largely allochthonous DOM of terrestrial origin. We also observed higher concentrations of total dissolved phosphorous (TDP) and ammonium nitrogen (NH-N) in coastal waters potentially due to photodegradation of refractory DOM derived from the sediment-bound organic matter in the coastal wetlands. This study highlights the relationships between the DOM compositions in the water and the land use and land cover in the watershed. The spatial variability of DOM in three different types of aquatic environments enhances the understanding of the role of land use and land cover in carbon cycling through export of organic matter to the aquatic ecosystems..

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