This thesis aims to establish analytical frameworks to map urban growth patterns with spaceborne remote sensing data and to evaluate environmental impacts through Landscape Metrics and Ecosystem Services. Urbanization patterns at regional scale were evaluated in China's largest urban agglomerations and at metropolitan scale in Shanghai, Stockholm and Beijing using medium resolution optical satellite data. High-resolution data was used to investigate changes in Shanghai’s urban core. The images were co-registered and mosaicked. Tasseled Cap transformations and texture features were used to increase class separabilities prior to pixel-based Random Forest and SVM classifications. Urban land cover in Shanghai and Beijing were derived through object-based SVM classification in KTH-SEG. After post-classification refinements, urbanization indices, Ecosystem Services and Landscape Metrics were used to quantify and characterize environmental impact. Urban growth was observed in all studies. China's urban agglomerations showed most prominent urbanization trends. Stockholm’s urban extent increased only little with minor environmental implications. On a regional/metropolitan scale, urban expansion progressed predominately at the expense of agriculture. Investigating urbanization patterns at higher detail revealed trends that counteracted negative urbanization effects in Shanghai's core and Beijing's urban-rural fringe. Beijing's growth resulted in Ecosystem Services losses through landscape structural changes, i.e. service area decreases, edge contamination or fragmentation. Methodological frameworks to characterize urbanization trends at different scales based on remotely sensed data were developed. For detailed urban analyses high-resolution data are recommended whereas medium-resolution data at metropolitan/regional scales is suggested. The Ecosystem Service concept was extended with Landscape Metrics to create a more differentiated picture of urbanization effects.​ / <p>QC 20160205</p>

Numerous studies indicate that the hydrology of a river basin is influenced by Land Use Land Cover (LULC) and climate. LULC affects the quality and quantity of water resources through its influence on Evapotranspiration (ET) and initiation of surface runoff while climate affects the intensity and spatial distribution of rainfall and temperature which are major drivers of the hydrologic cycle. Literature reports several works on either the effect of changing LULC or climate on the hydrology. However, changes in LULC and climate occur simultaneously in reality. Thus, there is a need to perform an integrated impact assessment of such changes on the hydrological regime at a basin scale. In order to carry out the impact assessment, physically-based hydrologic models are often employed. The present study focuses on assessment of the effect of changing LULC and climate on the hydrology of the Upper Ganga basin (UGB), India, using the Variable Infiltration Capacity (VIC) hydrologic model. In order to obtain the changes that have occurred in the LULC of the basin over a time period, initially LULC analysis is carried out. For this purpose, high resolution multispectral satellite imageries from Landsat are procured for the years 1973, 1980, 2000 and 2011. The images are pre-processed to project them to a common projection system and are then co-registered. The processed images are used for classification into different land cover classes. This step requires training sites which are collected during the field visit as part of this work. The classified images, thus obtained are used to analyse temporal changes in LULC of the region. The results indicate an increase in crop land and urban area of the region by 47% and 122% respectively from 1973 to 2011. After initial decline in dense forest for the first three decades, an increase in the dense forest is observed between 2000- 2011 (from 11.44% to 14.8%). Scrub forest area and barren land are observed to decline in the study region by 62% and 96% respectively since 1973. The land cover information along with meteorological data and soil data are used to drive the VIC model to investigate the impact of LULC changes on streamflow and evapotranspiration (ET) components of hydrology in the UGB. For the simulation purpose, the entire basin is divided into three regions (1) upstream (with Bhimgodha as the outlet), (2) midstream (with Ankinghat as the outlet) and (3) downstream (with Allahabad as the outlet). The VIC model is calibrated and validated for all the three regions independently at monthly scale. Model performance is assessed based on the criterion of normalized root mean square error (NRMSE), coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE). It is observed that the model performed well with reasonable accuracy for upstream and midstream regions. In case of the downstream region, due to lack of observed discharge data, model performance could not be assessed. Hence, the simulations for the downstream region are performed using the calibrated model of the midstream region. The model outputs from the three regions are aggregated appropriately to generate the total hydrologic response of the UGB. Using the calibrated models for different region of the UGB, sensitivity analysis is performed by generating hydrologic scenarios corresponding to different land use (LU) and climate conditions. In order to investigate the impact of changing LU on hydrological variables, a scenario is generated in which climate is kept constant and LU is varied. Under this scenario, only the land cover related variables are altered in the model keeping the meteorological variables constant. Thus, the effect of LU change is segregated from the effect of climate. The results obtained from these simulations indicated that the change in LU significantly affects peak streamflow depth which is observed to be 77.58% more in August 2011 in comparison with the peak streamflow of August, 1973. Furthermore, ET is found to increase by 46.44% since 1973 across the entire basin. In order to assess the impact of changing climate on hydrological variables, a scenario is generated in which LU is kept constant and climate is varied from 1971-2005. Under this scenario, land cover related variables are kept constant in the model and meteorological variables are varied for different time periods. The results indicate decline in the simulated discharge for the years 1971, 1980, 1990, 2000 and 2005, which is supported by decline in observed annual rainfall for the respective years. Amongst 1971 and 2005, year 2005 received 26% less rainfall resulting in 35% less discharge. Furthermore, ET is observed to be negligibly affected. To understand the integrated impact of changing LU and climate on hydrological variables, a scenario is generated in which both climate and LU are altered. Based on the data available, three years (1973, 1980 and 2000) are considered for the simulations. Under this scenario, both land cover and meteorological variables are varied in the model. The results obtained showed that the discharge hydrograph for the year 1980 has significantly higher peak compared to the hydrographs of years 1973 and 2000. This could be due to the fact that the year 1980 received maximum rainfall amongst the three years considered for simulations. Although the basin received higher rainfall in the year 1980 compared to that in 2000, ET from the basin in the year 1980 is found to be 21% less than that of the year 2000. This could be attributed to the change in LU that occurred between the years 1980 and 2000. Amongst the years 1973 and 2000, there is not much difference in the observed rainfall but ET for the year 2000 is observed to be significantly higher than that of year 1973. It is concluded from the present study that in the UGB, changing LULC contributes significantly to the changes in peak discharge and ET while rainfall pattern considerably influences the runoff pattern of the region. Future work proposed includes assessment of hydrologic response of basin under future LULC and climate scenarios. Also the model efficiency can be assessed by performing hydrologic simulations at different grid sizes.