Deepak Khare

Monitoring and modelling of urban sprawl using remote sensing and GIS techniques

Abstract The concentration of people in densely populated urban areas, especially in developing countries, calls for the use of monitoring systems like remote sensing. Such systems along with spatial analysis techniques like digital image processing and geographical information system (GIS) can be used for the monitoring and planning purposes as these enable the reporting of overall sprawl at a detailed level. In the present work, urban sprawl of the Ajmer city (situated in Rajasthan State of India) has been studied at a mid scale level, over a period of 25 years (1977–2002), to extract the information related to sprawl, area of impervious surfaces and their spatial and temporal variability. Statistical classification approaches have been used for the classification of the remotely sensed images obtained from various sensors viz. Landsat MSS, TM, ETM+ and IRS LISS-III. Urban sprawl and its spatial and temporal characteristics have been derived from the classified satellite images. The Shannons entropy and landscape metrics (patchiness and map density) have been computed in terms of spatial phenomenon, in order to quantify the urban form (impervious area). Further, multivariate statistical techniques have been used to establish the relationship between the urban sprawl and its causative factors. Results reveal that land development (160.8%) in Ajmer is more than three times the population growth (50.1%). Shannons entropy and landscape metrics has revealed the spatial distribution of the urban sprawl over a period of last 25 years.

Modelling of urban growth using spatial analysis techniques: a case study of Ajmer city (India)

The concentration of people in densely populated urban areas, especially in developing countries like India and China, calls for the use of sophisticated monitoring systems, like remote sensing and Geographical Information Systems (GIS). Time series of land use/cover changes can easily be generated using sequential satellite images, which are required for the prediction of urban growth, verification of growth model outputs, estimation of impervious area, parameterization of various hydrological models, water resources planning and management and environmental studies. In the present work, urban growth of Ajmer city (India) in the last 29 years has been studied at mid‐scale level (5–25 m). Remote sensing and GIS have been used to extract the information related to urban growth, impervious area and its spatial and temporal variation. Statistical classification approaches have been used to derive the land use information from satellite images of eight years (1977–2005). The Shannons entropy and landscape metrics (patchiness and map density) are computed in order to quantify the urban form (impervious area) in terms of spatial phenomena. Further, multivariate statistical techniques have been used to establish the relationship between the urban growth and its causative factors. Results reveal that land development (200%) in Ajmer is more than three times the population growth (59%). Shannons entropy and landscape metrics has revealed the spatial distribution of the sprawl.

Impact of Climate Change on Future Soil Erosion in Different Slope, Land Use, and Soil-Type Conditions in a Part of the Narmada River Basin, India

AbstractSoil erosion is one of the major hazards affected by the climate change, particularly the changed precipitation trend. The present paper has generated future precipitation by downscaling general circulation model (GCM, HADCM3) data of A2 scenario in a part of the Narmada River Basin in Madhya Pradesh, India, to obtain future impact of climate change on soil erosion. Least-square support vector machine (LS-SVM) and statistical downscaling model (SDSM) models were used for downscaling, and the universal soil loss equation (USLE) model was used for estimating soil loss. The results were analyzed with different slope, land use, and soil category. Outcome showed an increase in future precipitation with the resultant increase in soil erosion, with a positive change of 18.09 and 58.9% in years 2050s and 2080s respectively in LS-SVM, while it is decreasing in the year 2020s (−5.47%). Rate of change of soil erosion with SDSM is 15.52 and 105.80% in years 2050s and 2080s respectively, and decrease in the 20...

Trend analysis of climatic variables in an arid and semi-arid region of the Ajmer District, Rajasthan, India

Abstract In the present study, trends and variations in climatic variables (i.e. rainfall, wet day frequency, surface temperature, diurnal temperature, cloud cover, and reference and potential evapotranspiration) were analyzed on seasonal (monsoon and non-monsoon) and annual time scales for the Ajmer District of Rajasthan, India. This was done using non-parametric statistical techniques, i.e. the Mann–Kendall (MK) and Modified Mann–Kendall (MMK) tests, over a period of 100 years. The MK test with prewhitening (MK–PW) of climatic series was also applied to climatic variables and the results were compared to those obtained through the MK and MMK tests in order to assess the performance of trend detection methods. The Pettitt–Mann–Whitney (PMW) test was applied to detect the temporal shift in climatic series. The trend analysis revealed that annual and seasonal rainfall did not show any statistically significant trend at a 10% significant level. A noticeable trend increase was found in wet day frequency, surface temperature and reference evapotranspiration (ET) during the non-monsoon season from the three non-parametric statistical tests at a 10% significance level. A statistically significant decrease in maximum temperature was found during the non-monsoon season by the MK–PW test alone. This analysis of several climatic variables at the district scale is helpful for the planning and management of water resources and the development of adaptation strategies in adverse climatic conditions.

Remote sensing and GIS-based assessment of urbanisation and degradation of watershed health

Water resources, ecological quality, i.e. vegetation, flora-fauna, native plants, etc., and geo-morphological characteristics are some of the important elements that represent health of a watershed. Watershed health can be assessed through some of the indirect metrics, such as change in rainfall-runoff response, depletion of groundwater, groundwater pollution and degradation of geo-morphological characteristics. In the present study, application of remote sensing and geographic information system (GIS) technologies have been demonstrated for assessment of health of two urbanised sub-watersheds over a period of last 29 years (1977–2005). Investigation includes estimation of urbanisation and resulting changes in the watershed characteristics representing heath of watershed, such as change in surface runoff response, groundwater level, groundwater quality and morphological characteristics. Remote sensing images of eight years (1977–2005) have been used for extraction of land use/cover and urban growth. Change in surface runoff characteristics have been estimated using a physically based distributed storm water management model (SWMM). Groundwater analysis has been carried out in GIS to determine the change in groundwater level and quality over a period of 1992 to 2005. Results reveal that rate of land development in Ajmer is higher as compared to the population growth. Significant changes have been found in important watershed characteristics leading to deterioration of its health. Remote sensing and GIS technologies have been found to be useful for such studies.

Modeling runoff–sediment response to land use/land cover changes using integrated GIS and SWAT model in the Beressa watershed

Land use/land cover (LU/LC) change has significant influence on runoff and sediment characteristics of any catchment. LU/LC change studies are essential for policy planners to understand the problems and take course of action such as soil and water conservation measures for improvement. The present study is conducted for Beressa watershed using hydrological model integrated with GIS. Input data like LU/LC, weather and soil data features are required to undertake watershed simulation. The model has been calibrated and validated in SWAT-CUP. The data from 1980 to 1999 were used for calibration, while the data from 2000 to 2014 were used for validation. LU/LC analysis showed that agricultural and settlement areas have increased between 1984 and 2015, while barren, grazing land and forest area have decreased. However, the share of forest cover increased in between 1999 and 2015. SWAT model has successfully simulated and calibrated runoff and sediment yield. During calibration periods (1980–1999), the values of R2, NSE, RSR and PBIAS were obtained as 0.72, 0.67, 0.52 and 3.9%, respectively, whereas during the validation periods (2000–2014) the values were 0.68, 0.64, 0.56 and 7.6%, respectively. Runoff and sediment yield has significantly increased. Thus, it is concluded that the change in LU/LC significantly influenced the runoff and sediment yield.

Long Term Rainfall Trend Analysis (1871–2011) for Whole India

Climate change has aroused serious consciousness among human beings as it has a strong impact on different parameters like rainfall, temperature, evapotranspiration etc. Change in climatic parameters also affects the agriculture and water demand of an area. The changed pattern of rainfall leads to extreme conditions like flood, drought and cyclones which have increased in frequency in the last few decades making the rainfall trend analysis extremely important for India where a large part of the economy depends upon rain-fed agriculture. The trend of rainfall for 141 years of India was analyzed in the present study from 1871 to 2011. Detection of trend was done by analyzing 306 stations of India divided into seven regions of Homogeneous Indian Monsoon, Core-Monsoon India, North West India, West Central India, Central Northeast India, North East India and Peninsular India. Temporal as well as spatial rainfall variability was shown on monthly, seasonal and annual basis. The Mann–Kendall (MK) Test and Sen’s slope was applied in the study. Mann–Whitney–Pettitt (MWP) test was used to give the break point in the series. Annually, 5 regions have decreasing trend except for core-monsoon and north-east India. Monsoon season depicted decrease in the rainfall magnitude in most of the regions. This result is extremely significant as monsoon rainfall serves the major water demand for agriculture. Change Percentage for 141 years had shown rainfall variability throughout India with the highest increase in North-West India (5.14 %) and decrease in Core-monsoon India (−4.45 %) annually.

Shifting shoreline of Sagar Island Delta, India

Shoreline mapping is extremely important in order to determine the dynamic nature of coastal areas. This paper presents shoreline mapping of the Sagar Island delta, Sundarban region, India. The island is part of mangrove ecosystem and is facing constant erosion and deposition from tidal action and cyclonic storms which have made this an area of unique importance. Mapping of shoreline has been performed 1951 to 2011 and change in the land-water boundary of the island calculated. Further shoreline prediction is performed on the basis of the extracted shorelines using the End point Rate model with a micro-level grid-based approach. The predicted maps have been validated using ground control points. Three images from 1951, 1990 and 2011 have been used for the mapping and detection of changes in the island area and shoreline over 60 years.

Uncertainty analysis of soil erosion modelling using different resolution of open-source DEMs

Abstract The Digital Elevation Model (DEM) is one of the important parameters of soil erosion assessment and notable uncertainties are found in using different resolutions of the DEM. Revised Universal Soil Loss Equation model has been applied to analyze the effect of open-source DEMs with different resolution and accuracy on the uncertainties of soil erosion modelling in a part of the Narmada river basin in Madhya Pradesh in central India. Selected open-source DEMs are GTOPO30 (1 km), SRTM (30 and 90 m), CARTOSAT (30 m) and ASTER (30 m), used for estimating erosion rate. Results with better accuracy are achieved with the high-resolution DEMs (30 m) with higher vertical accuracy than the coarse resolution DEMs with lower accuracy. This study has presented potential uncertainties introduced by the open-source DEMs in soil erosion modelling for better understanding of appropriate selection and acceptable errors for researchers.

Landuse Change Prediction and Its Impact on Surface Run-off Using Fuzzy C-Mean, Markov Chain and Curve Number Methods

The landuse change has considerable impact on the surface run-off of a catchment. With the changing landuse there is reduction in the initial abstraction which results in increasing run-off. This also has effect on future because of constant change in landuse due to urbanization. The Soil Conservation Service Curve Number (SCS-CN) model was used in the study for calculating run-off in a sub-catchment of Narmada River basin for the years 1990, 2000 and 2011 which was further validated with the observed data from the gauges. Stream flow of future for 2020 and 2030 was estimated by this method to observe the impact of landuse change on run-off. The landuse classification was done by Fuzzy C-Mean algorithm. The future landuse prediction for 2020 and 2030 was performed with the Markov Chain Model with 2011 validation. Future run-off was generated on the basis of changing landuse which shows increasing rate of run-off.