SHAH FAHAD
Jamia Millia Islamia, Geography, Graduate Student
- Shahfahad is a Senior Research Fellow (SRF) at the Department of Geography, Jamia Millia Islamia. He is doing pursuin... moreShahfahad is a Senior Research Fellow (SRF) at the Department of Geography, Jamia Millia Islamia. He is doing pursuing a PhD in Urban growth and Climate change. His areas of research are urban studies, climate change, land-use change, ecosystem services, urban landscape and use of remote sensing in urban and land resource studies. The main themes of his research are Urban Environment: issues and challenges, Climate Change and the use of Geoinformatics in Urban studies. His PhD title is 'Impact of Urbanization on Climatic Conditions in India: A Comparative Analysis of Delhi and Mumbai Metro Cities Using Geospatial Technique'.edit
The decrease in vegetation cover due to urban expansion poses serious challenge to urban sustainability. Protected areas (PAs) are the most effective tools to prevent the loss of urban vegetation cover and to control urban expansion.... more
The decrease in vegetation cover due to urban expansion poses serious challenge to urban sustainability. Protected areas (PAs) are the most effective tools to prevent the loss of urban vegetation cover and to control urban expansion. Hence, this study aims to assess the importance of PAs in protecting urban vegetation and the urban expansion in the mega city of Delhi. For this, Landsat datasets were used for land use and land cover (LULC) mapping and then land cover change rate (LCCR) and land cover intensity (LCI) were calculated. For assessing urban expansion dynamics, mean landscape expansion index (MLEI) and the area-weighted LEI (AWLEI) were calculated. To evaluate the significance of PAs in protecting vegetation cover, kernel density estimation (KDE) was applied to assess the spatial variation and concentration of vegetation cover under different PAs. The result shows that urban expansion in Delhi was initially characterized by edge expansion during 1991-2001, followed by outlying expansion of built-up area during 2001-2021, while infilling of open and vegetated areas by built-up area was consistent during 1991-2021. Vegetation cover on the other hand, has followed a fluctuating trend in the city, but has overall it has declined from 13.36% to 9.30% during 1991-2021. The vegetation cover has declined significantly in eastern, northern, and western parts of Delhi but has increased significantly in central and southern parts, especially during 2001-21. This is because the central and southern parts of Delhi are well planned and have several PAs while the western, northern, and eastern parts of Delhi are unplanned regions and have only a few PAs. The KDE chart shows that the PAs have played an important role in protecting the vegetation cover in Delhi with R 2 value > 0.70. Hence, this study suggests to give special emphasis on preservation and expansion of PAs in urban planning for the long-term conservation of urban vegetation cover and sustainable urban development.
Research Interests:
Amongst various form of urbanization induced climate change, changing thermal environment is the most widely studied and understood phenomenon. The impervious surfaces in urban areas absorb and re-emit the heat from solar radiation more... more
Amongst various form of urbanization induced climate change, changing thermal environment is the most widely studied and understood phenomenon. The impervious surfaces in urban areas absorb and re-emit the heat from solar radiation more than those of natural landscape which causes an elevated temperature in global cities. Due to increasing impervious surfaces and emissions from anthropogenic sources, the diurnal temperature range (DTR) is declining in cities while the frequency of extreme temperature events (TX X) is increasing. Hence, in this study, the trend of DTR and TX X has been examined in Delhi and Mumbai mega cities of India. For this study, India Meteorological Department (IMD) provided daily temperature data for 13 meteorological stations in Mumbai and 21 meteorological stations in Delhi. The DTR and TX X have been analysed using the RClimDex-Extraqc package while the trend of DTR and TX X has been analysed using the innovative trend analysis (ITA). The result showed that during 1991-2018, DTR has declined by about 1.5 °C in Delhi and about 0.2-0.4 °C in Mumbai, while TX X has increased by about 0.1-1.4 °C in Delhi and about 4 °C in Mumbai. The trend analysis of DTR and TX X using ITA showed that the DTR has a declining trend in both the cities while TX X has an increasing trend. The declining DTR and increasing TX X may increase the vulnerability to heat waves for the city dwellers and deteriorate the urban thermal comfort in both the cities.
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In the cities of developing countries like India, rapid and uncontrolled urbanization has been taking place due to continuous population growth in last few decades. As a result, land use/ land cover (LU/LC) is changing very fast in the... more
In the cities of developing countries like India, rapid and uncontrolled urbanization has been taking place due to continuous population growth in last few decades. As a result, land use/ land cover (LU/LC) is changing very fast in the cities of developing countries. Therefore, this study aims to examine the changes in LU/LC pattern in Delhi during 1991-2018 and simulate the future LU/LC pattern of Delhi for 2030. The LU/LC pattern mapping was done from Landsat datasets using k-means clustering technique. The cellular automata (CA) technique was integrated with artificial neural network (ANN) for simulating the future LU/LC patterns. The projected LU/LC pattern shows that Delhi's built-up area will increase to nearly 60% of the total area of city, while cropland and open land will decrease to 19.86 and 0.15%, respectively. The highest increase in built-up area was observed in the northern, western, and southwestern sub-districts of Delhi. Outcomes of the study may be used for future land use planning in Delhi and other cities. In addition, they can also provide valuable insights for the development of transportation network and other facilities and amenities in the areas of future urban expansion.
Research Interests:
Research Interests:
In the era of global urbanization, the cities across the world are experiencing significant change in the climate pattern. However, analysing the trend and pattern of rainfall over the urban areas has a number of challenges such as... more
In the era of global urbanization, the cities across the world are experiencing significant change in the climate pattern. However, analysing the trend and pattern of rainfall over the urban areas has a number of challenges such as availability of long-term data as well as the uneven distribution of rain-gauge stations. In this research, the rainfall regionalization approach has been applied along with the advanced statistical techniques for analysing the trend and pattern of rainfall in the Delhi metropolitan city. Fuzzy C-means and K-means clustering techniques have been applied for the identification of homogeneous rainfall regions while innovative trend analysis (ITA) along with the family of Mann–Kendall (MK) tests has been applied for the trend analysis of rainfall. The result shows that in all rain-gauge stations of Delhi, an increasing trend in rainfall has been recorded during 1991–2018. But the rate of increase was low as the trend slope of ITA and Sen’s slope in MK tests are low, which varies between 0.03 and 0.05 and 0.01 and 0.16, respectively. Furthermore, none of the rain-gauge stations have experienced a monotonic trend in rainfall as the null hypothesis has not been rejected (p value > 0.05) for any stations. Furthermore, the study shows that ITA has a better performance than the family of MK tests. The findings of this study may be utilized for the urban flood mitigation and solving other issues related to water resources in Delhi and other cities.
Research Interests:
Research Interests:
Rapid and uncontrolled population growth along with economic and industrial development, especially in developing countries during the late twentieth and early twenty-first centuries, have increased the rate of land-use/land-cover (LULC)... more
Rapid and uncontrolled population growth along with economic and industrial development, especially in developing countries during the late twentieth and early twenty-first centuries, have increased the rate of land-use/land-cover (LULC) change many times. Since quantitative assessment of changes in LULC is one of the most efficient means to understand and manage the land transformation, there is a need to examine the accuracy of different algorithms for LULC mapping in order to identify the best classifier for further applications of earth observations. In this article, six machine-learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), fuzzy adaptive resonance theory-supervised predictive mapping (Fuzzy ARTMAP), spectral angle mapper (SAM) and Mahalanobis distance (MD) were examined. Accuracy assessment was performed by using Kappa coefficient, receiver operational curve (RoC), index-based validation and root mean square error...
Research Interests:
Research Interests: Geography, Thermal Remote Sensing, Land Cover, Urban Heat Island Effect, Land Use, and 9 moreUrbanization and Environmental Issues, Urban heat island, Mumbai, Geomatic Engineering, Land Surface Temperature Modeling, Satellite Data, Metropolitan Areas, Land Use Land Cover Change, and Surface urban heat island
According to the World Urbanization Prospects of United Nations, the global urban population has increased rapidly over past few decades, reaching about 55% in 2018, which is projected to reach 68% by 2050. Due to gradual increase in the... more
According to the World Urbanization Prospects of United Nations, the global urban population has increased rapidly over past few decades, reaching about 55% in 2018, which is projected to reach 68% by 2050. Due to gradual increase in the urban population and impervious surfaces, the urban heat island (UHI) effect has increased manifold in the cities of developing countries, causing a decline in thermal comfort. Therefore, this study was designed to model the spatio-temporal pattern of UHI and its relationships with the land use indices of Delhi and Mumbai metro cities from 1991 to 2018. Landsat datasets were used to generate the land surface temperature (LST) using mono window algorithm and land use indices, such as normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference bareness index (NDBal), normalized difference moisture index (NDMI), and modified normalized difference water index (MNDWI). Additionally, the urban hotspots (UHS) were identified and then the thermal comfort was modelled using the UTFVI. The results showed that maximum (30.25-38.99 °C in Delhi and 42.10-45.75 °C in Mumbai) and minimum (17.70-23.86 °C in Delhi and 19.06-25.05 °C in Mumbai) LST witnessed steady growth in Delhi and Mumbai from 1991 to 2018. The LST gap decreases and the UHI zones are being established in both cities. Furthermore, the UHS and worst-category UTFVI areas increased in both cities. This research can be useful in designing urban green-space planning strategies for mitigating the UHI effects and thermal comfort in cities of developing countries. Keywords Land use indices • Urban heat island • Urban Hotspots • Urban thermal field variation index • Thermal comfort
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The rapid urbanization and land-use/land-cover (LU/LC) changes have resulted in the unplanned and unsustainable growth of the Indian cities. This has resulted in a number of environmental issues such as escalating the urban heat island... more
The rapid urbanization and land-use/land-cover (LU/LC) changes have resulted in the unplanned and unsustainable growth of the Indian cities. This has resulted in a number of environmental issues such as escalating the urban heat island (UHI) intensity over the cities. Therefore, this study was designed to model and quantify the UHI dynamics of Mumbai city in response to the LU/LC change during 1991-2018 using temporal Landsat datasets. The result shows a significant decline in vegetation cover from 215.8 to 129.27 km 2 , while the built-up areas have almost doubled, i.e., from 173.09 to 346.02 km 2 in the Mumbai city during 1991-2018. As a consequence of this, a significant increase in the LST has been noticed in both urban heat island (UHI) and non-UHI zones. Although the areas under UHI zones have not increased significantly, the land surface temperature (LST) gap (difference between minimum and maximum LST) has declined in the Mumbai city from 30.04°C in 1991 to 20.7°C in 2018. Further, the minimum and mean LST over each LU/LC classes have also shown a significant increase. On the other hand, the regression analysis shows that the association between UHI and normalized difference built-up index (NDBI) has increased in the city, while the association of vegetation density (NDVI) and normalized difference bareness index (NDBaI) has declined in the city. The study can provide useful insights into the process of urban planning and policy makings for urban spatial planning and UHI mitigation strategies. Keywords Land-use/land-cover change Á Land surface temperature Á Urban heat island Á Vegetation and built-up density Á Mumbai city
Research Interests:
Groundwater in Delhi Metropolitan Region (DMR) is suffering from multiple catastrophes, viz., asymptotic increases in groundwater withdrawal, reduced recharge due to erratic rainfall, and variable soil type. In this study, we examined... more
Groundwater in Delhi Metropolitan Region (DMR) is suffering from multiple catastrophes, viz., asymptotic increases in groundwater withdrawal, reduced recharge due to erratic rainfall, and variable soil type. In this study, we examined long-term trends in groundwater levels across the DMR from 1996 to 2018. Station level data collected by the Central Groundwater Board for 258 stations at the seasonal scale were visualized and interpreted using geospatial analysis. The spatial patterns of the trends in groundwater levels revealed increasing depths of groundwater levels, except the Yamuna River floodplains. The main cause for the decline is related to the rapid growth in population accompanied with high-density impervious urban land uses, leading to lower levels of recharge vs unlimited withdrawal of groundwater for daily needs. In addition, the local geology in the form of clayey soils in northwest DMR also contributed to the lower levels of recharge. The results of the analysis enabled us to establish the trend and delineate the zones of differential recharge. Furthermore, the level of contaminants were analyzed at the district level for fluorides and nitrates. The presence of fluoride contamination was mostly concentrated in the northwestern district, while the nitrate exceedance was more widespread. These findings will help in achieving the 6th Sustainable Development Goal (SDG) of United Nations by 2030 as well as goals identified in Delhi's master plan of 2041.
Research Interests:
During past four decades, in post economic reforms period, Delhi and its surrounding regions has attracted a large number of populations which led to the rapid transformation of its LULC pattern. Therefore, this study is aimed to analyze... more
During past four decades, in post economic reforms period, Delhi and its surrounding regions has attracted a large number of populations which led to the rapid transformation of its LULC pattern. Therefore, this study is aimed to analyze the LULC changes during 1990-2018 as well as the growth and pattern of built-up surfaces in relation to the population growth and migration in the suburbs of Delhi metropolitan city which is also known as the National Capital Region (NCR). The Landsat 5 (TM) and Landsat 8 (OLI/TIRS) data has been used for the LU/LC classification of Delhi NCR. The K means clustering technique was applied on the Landsat data for the LULC classification and then the change detection technique was used to quantify the LULC change. The result shows that the considerable changes in LULC have occurred with continuous increase in built-up area and open/fallow land and decrease in agriculture land and vegetation over the study time period. Built-up area increased by about 326 percent and open/fallow land by 44 percent while the agricultural land and vegetation cover have decreased by 12 percent and 34 percent of the total area of study respectively during the study period. Built-up area has mostly increased at the expense of agricultural land and vegetation cover while vegetation cover has been transformed into Built-up area, Ridge and Agriculture. The statistical analysis shows that the association between built-up expansion and the population and migrants varies from weak to high but the coefficient of determination was always positive.
Research Interests:
Rapid and uncontrolled population growth along with economic and industrial development, especially in developing countries during the late twentieth and early twenty-first centuries, have increased the rate of land-use/land-cover (LULC)... more
Rapid and uncontrolled population growth along with economic and industrial development, especially in developing countries during the late twentieth and early twenty-first centuries, have increased the rate of land-use/land-cover (LULC) change many times. Since quantitative assessment of changes in LULC is one of the most efficient means to understand and manage the land transformation, there is a need to examine the accuracy of different algorithms for LULC mapping in order to identify the best classifier for further applications of earth observations. In this article, six machine-learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), fuzzy adaptive resonance theory-supervised predictive mapping (Fuzzy ARTMAP), spectral angle mapper (SAM) and Mahalanobis distance (MD) were examined. Accuracy assessment was performed by using Kappa coefficient, receiver operational curve (RoC), index-based validation and root mean square error (RMSE). Results of Kappa coefficient show that all the classifiers have a similar accuracy level with minor variation, but the RF algorithm has the highest accuracy of 0.89 and the MD algorithm (parametric classifier) has the least accuracy of 0.82. In addition, the index-based LULC and visual cross-validation show that the RF algorithm (correlations between RF and normalised differentiation water index, normalised differentiation vegetation index and normalised differentiation built-up index are 0.96, 0.99 and 1, respectively, at 0.05 level of significance) has the highest accuracy level in comparison to the other classifiers adopted. Findings from the literature also proved that ANN and RF algorithms are the best LULC classifiers, although a non-parametric classifier like SAM (Kappa coefficient 0.84; area under curve (AUC) 0.85) has a better and consistent accuracy level than the other machine-learning algorithms. Finally, this review concludes that the RF algorithm is the best machine-learning LULC classifier, among the six examined algorithms although it is necessary to further test the RF algorithm in different morphoclimatic conditions in the future.
Research Interests:
Special economic zones (SEZs) concept has evolved across the globe and several developing countries have adopted this policy for set-up of industrial zones that focus on exports and helps in generating economic opportunity and able to... more
Special economic zones (SEZs) concept has evolved across the globe and several developing countries have adopted this policy for set-up of industrial zones that focus on exports and helps in generating economic opportunity and able to attract Foreign direct investment. So SEZs can be defined as a geographically delimited area which is physically secured, has single window clearance system, less complicated administrative unit and duty free environment. So objective behind this paper is to evaluate the performance of SEZs in India in terms of generation of employment, attraction of Foreign Direct Investment (FDI) and contribution in Indian export. To fulfill the objective data related to employment, investment and export from SEZs are collected from different sources like Ministry of Commerce and Industries, economic survey of India and official website of SEZ. These data are organized in Ms Excel and simple tabular analysis is done. Simple and compound growth rate is calculated to show the change in the performance of SEZs. It is found in the study that SEZs helps in generation of employment, attraction of FDI and contribution in Indian export. At present scenario 1688.34 thousand people is working in SEZs at national level, FDI in SEZs is 433142 crores in 2017 and export output from SEZs in 2016 was 467337 crores which is 19.88% of total export from India.
Research Interests:
Special economic zone (SEZ) is a geographically delimited area which is physically secured, has single management and administrative unit and duty free environment (Zeng, 2015). In India SEZs established to solve the problem of... more
Special economic zone (SEZ) is a geographically delimited area which is physically secured, has single
management and administrative unit and duty free environment (Zeng, 2015). In India SEZs established to
solve the problem of infrastructural deficiency, complex business procedure, bureaucratic hassles and
barriers raised by monetary, trade, fiscal, taxation, tariff and labour policies (Doharmann, 2008). SEZ in
India was conceived by the Commerce and Industries Minister Murosoli Maran during a visit to Special
Economic Zone in China in 1999. The scheme was announced at the time of annual review of Export Import
Policies from 1.4.2000. The basic idea is to establish the zone as area where economic activities could take
place free from all rules and regulations and to give them operational flexibility. So this paper aims at
analyzing establishment of SEZ in India and to assess their spatial and sectoral distribution. To fulfill this
objective data related to notification, establishment of SEZs, spatial and sectoral distribution of SEZs and
contribution of SEZs in Indian GDP are collected from different sources such as Development
Commissioner of SEZ and ministry of commerce and industries on temporal basis. These data are tabulated
in MS Excel, where analysis part is carried out. The whole research is based on descriptive research and
comparative study and analytical logic developed through the understandings from various research papers,
reports, books, journals, newspapers and online data bases. Simple growth rate is calculated to show the
temporal change in approval of SEZs in India. It is found in this study that SEZs causes uneven
geographical developments in India. Recent developments of SEZs suggest that advanced state and city
regions have attracted much of the investment in SEZs like Maharashtra, Andhra Pradesh, Tamil Nadu,
Karnataka, Gujarat and Haryana have attracted a large number of SEZs in comparison to other states while
under-developed areas have been ignored by the SEZ developers. In the sector-wise composition of SEZs,
majority of IT/ITES SEZs are either formally approved or notified. However, as far as SEZs in principle are
concerned, the numbers of Multi-product SEZs are greater as compared to other categories of SEZs. Typewise
distribution of SEZs provides that most of the SEZs belong to the category of IT/ITES, but a large area
is allocated to multi-product SEZs. Size-wise distribution of SEZs shows that maximum numbers of SEZs
are either tiny or small. But most of the area is allocated to large SEZs. It has also been observed that most
of the tiny SEZs carry out IT/ITES activities and almost all the large size SEZs are Multi-product SEZs. It is
evident from the analysis that SEZs contributes in the export and GDP of India.
management and administrative unit and duty free environment (Zeng, 2015). In India SEZs established to
solve the problem of infrastructural deficiency, complex business procedure, bureaucratic hassles and
barriers raised by monetary, trade, fiscal, taxation, tariff and labour policies (Doharmann, 2008). SEZ in
India was conceived by the Commerce and Industries Minister Murosoli Maran during a visit to Special
Economic Zone in China in 1999. The scheme was announced at the time of annual review of Export Import
Policies from 1.4.2000. The basic idea is to establish the zone as area where economic activities could take
place free from all rules and regulations and to give them operational flexibility. So this paper aims at
analyzing establishment of SEZ in India and to assess their spatial and sectoral distribution. To fulfill this
objective data related to notification, establishment of SEZs, spatial and sectoral distribution of SEZs and
contribution of SEZs in Indian GDP are collected from different sources such as Development
Commissioner of SEZ and ministry of commerce and industries on temporal basis. These data are tabulated
in MS Excel, where analysis part is carried out. The whole research is based on descriptive research and
comparative study and analytical logic developed through the understandings from various research papers,
reports, books, journals, newspapers and online data bases. Simple growth rate is calculated to show the
temporal change in approval of SEZs in India. It is found in this study that SEZs causes uneven
geographical developments in India. Recent developments of SEZs suggest that advanced state and city
regions have attracted much of the investment in SEZs like Maharashtra, Andhra Pradesh, Tamil Nadu,
Karnataka, Gujarat and Haryana have attracted a large number of SEZs in comparison to other states while
under-developed areas have been ignored by the SEZ developers. In the sector-wise composition of SEZs,
majority of IT/ITES SEZs are either formally approved or notified. However, as far as SEZs in principle are
concerned, the numbers of Multi-product SEZs are greater as compared to other categories of SEZs. Typewise
distribution of SEZs provides that most of the SEZs belong to the category of IT/ITES, but a large area
is allocated to multi-product SEZs. Size-wise distribution of SEZs shows that maximum numbers of SEZs
are either tiny or small. But most of the area is allocated to large SEZs. It has also been observed that most
of the tiny SEZs carry out IT/ITES activities and almost all the large size SEZs are Multi-product SEZs. It is
evident from the analysis that SEZs contributes in the export and GDP of India.
Research Interests:
Public open spaces and green cover are a connection between people and nature and are necessary to retain the quality of the urban landscape. Rapid urban growth and population increase put tremendous pressure on public open spaces, which... more
Public open spaces and green cover are a connection between people and nature and are necessary to retain the quality
of the urban landscape. Rapid urban growth and population increase put tremendous pressure on public open spaces,
which reduces the quality of the urban landscape. The fast urban growth leads to utilize remaining green and open areas
of the city for different purposes. As a result, the size of the urban green and open space is decreasing at an alarming
rate. Therefore, the study analyses the availability of per capita public open spaces to assess the landscape quality. The
green space available per capita in Delhi is about 20 m2, and public open space is 30 m2. Weights have been assigned
to five variables selected to assess the landscape quality, and then, it was multiplied by the respective z score (scalefree)
of each variable. Finally, we have calculated composite index score to develop a landscape quality index. The per
capita share of public open spaces in East Delhi is 7.01 m2 to its total area. Wards with high population density have a
comparatively low proportion of public open spaces. It is seen that most of the wards did not match the criteria of WHO
and UN for per capita availability of public open spaces. The landscape quality index shows that in more than two-thirds
of the wards, the landscape quality is poor. The wards of the central and northern parts of the study area are densely
populated and have a low concentration of public open spaces; therefore, they have the least index score on landscape
quality. At the same time, the wards of southeastern and eastern parts, where the population density is the lowest, the
score of the landscape quality index is high.
of the urban landscape. Rapid urban growth and population increase put tremendous pressure on public open spaces,
which reduces the quality of the urban landscape. The fast urban growth leads to utilize remaining green and open areas
of the city for different purposes. As a result, the size of the urban green and open space is decreasing at an alarming
rate. Therefore, the study analyses the availability of per capita public open spaces to assess the landscape quality. The
green space available per capita in Delhi is about 20 m2, and public open space is 30 m2. Weights have been assigned
to five variables selected to assess the landscape quality, and then, it was multiplied by the respective z score (scalefree)
of each variable. Finally, we have calculated composite index score to develop a landscape quality index. The per
capita share of public open spaces in East Delhi is 7.01 m2 to its total area. Wards with high population density have a
comparatively low proportion of public open spaces. It is seen that most of the wards did not match the criteria of WHO
and UN for per capita availability of public open spaces. The landscape quality index shows that in more than two-thirds
of the wards, the landscape quality is poor. The wards of the central and northern parts of the study area are densely
populated and have a low concentration of public open spaces; therefore, they have the least index score on landscape
quality. At the same time, the wards of southeastern and eastern parts, where the population density is the lowest, the
score of the landscape quality index is high.
Research Interests:
Delhi is the second largest metropolitan city of India after Mumbai which is still growing. In any city smooth traffic movement is a prerequisite for its development but it is very difficult to achieve because of increase in population,... more
Delhi is the second largest metropolitan city of India after Mumbai which is still growing. In
any city smooth traffic movement is a prerequisite for its development but it is very difficult
to achieve because of increase in population, commercial and industrial activities. Besides
this high vehicle ownership and poor supporting public transport facilities cause serious
problems of transport. Primary data related to user satisfaction is collected through a
structured interview done in the area of Hauz Khas metro station in Delhi in June 2018. It is
seen in the study that there is rapid growth of population in Delhi i.e. 5.64% average annual
growth rate between 1981 and 2011 and the number of vehicles and road length also
increased during this period but increase of length of road is not as much as the increase in
the number of vehicles. Vehicles increased with about 49% annual average growth rates
whereas length of road increased at about 4% annual average growth rate. It is found in the
study that people are satisfied with the service as it provides a safe, secured and fast mode
of transport.
any city smooth traffic movement is a prerequisite for its development but it is very difficult
to achieve because of increase in population, commercial and industrial activities. Besides
this high vehicle ownership and poor supporting public transport facilities cause serious
problems of transport. Primary data related to user satisfaction is collected through a
structured interview done in the area of Hauz Khas metro station in Delhi in June 2018. It is
seen in the study that there is rapid growth of population in Delhi i.e. 5.64% average annual
growth rate between 1981 and 2011 and the number of vehicles and road length also
increased during this period but increase of length of road is not as much as the increase in
the number of vehicles. Vehicles increased with about 49% annual average growth rates
whereas length of road increased at about 4% annual average growth rate. It is found in the
study that people are satisfied with the service as it provides a safe, secured and fast mode
of transport.