The peri-urban landscape is a highly dynamic area between the urban zone and the rural belt. The heterogeneous natural landscape around the cities provides several ecosystem services, but progressive urbanization affects it and results in the loss of biodiversity, greenery, and related benefits. This study attempts to quantify the social amenities associated with ecosystem services in the peri-urban landscape of the Gujrat district, in Pakistan, by using the Contingent Valuation Method (CVM) The results show that the peri-urban landscape provides amenities for the well-being of the community. Such amenities and the related recreational opportunities represent ecosystem services that are highly regarded by the residents, so much so that a significant willingness to pay can be associated with them. Therefore, this study highlights that natural areas and green areas’ landscapes must be taken into account when facing the social and economic necessity to provide for city expansion in developing countries, especially when aiming to achieve development in alignment with the Sustainable Development Goals. The ecosystem services and their evaluation are confirmed as indispensable tools for conservation and fortification of landscape development.

A strong need exists to increase the knowledge and recognize the values of neighborhood services. This paper makes an attempt to examine the impact of neighborhood services on land values, through analysis based on results obtained from multi linear regression analysis. This case study was done in area of dense urban settlement to check the consequence of neighborhood services through the hedonic pricing model base variables which include the structural, locational, community and neighborhood services. The regression coefficient was checked at (p < 0.05) level of significance for each variable. The primary data was collect through the questionnaire filling by random sampling and Punjab Urban Gazette was used for the verification of land values in study area. The results found a valuable potential on land and property values of neighborhood services through the regression analysis results express through R (0.926), R² (0.856) and coefficient tables to represent the effect of each individual variable on property and land values. Every individual variable play role in defining the values of land and property based upon its utilization such as larger the structure of a property, more the covered area, larger size of a property more the land area higher price. Similarly, for locational factor study in geography, a piece of land adjacent to the road have high land values 50–70% compare to those located at distance. Very less attention has been paid on such issues in the world due to lack of effective urban planning and research on such crucial issues. If empirical studies on such issue has been done, effective way can be obtained for urban planning.

Neighborhood services, property attributes, and their associated amenities have positive impacts on land and property values. This impact is estimated by the hedonic pricing model, which is considered an effective method used in previous studies for such evaluations. The study uses Geographical Information Science by digitizing the point of interest in the study area for spatial modeling of data collection points and multi-linear regression as a statistical analysis of hedonic measurements. The hedonic measurements include the data of structural, locational, environmental, and community attributes of a property at a given time and space at a walkable distance from the neighborhood for measuring proximity. The results of the study are represented through the summary of the regression model, which expresses the impact of every individual variable on the entire value of the property, and the appropriateness of the results is shown by values R, R², and adjusted R². The result of the study concluded that property characteristics are varied from location to location, and that is why it is difficult to measure the exact market values, particularly in areas that lack urban planning and heterogeneous data. Research on such burning issues is essential for sustainable urban development.

Urban green spaces are considered the most important element for keeping the balance between good environmental conditions, infrastructure development, and social sustainability in cities. Nevertheless, urban green spaces are declining in developing countries due to the fast diffusion of different human activities, raising the potential risk of social injustice and urban ecology meltdown. This study brings the example of Shahdara Town, a suburban area of Lahore, the second largest city and one of the most populated ones in Pakistan. In Shahdara Town, the scarcity of urban green spaces seems to achieve an unequal distribution of restorative places within crowded residential areas. By coupling the vegetation spectral index NDVI and Lahore institutional data to detect green spaces, this study maps the urban green area distribution and compares it with the population settlement pattern. An analysis was made to assess possible spatial relationships between green areas distribution, population density, and the social–economic profile of the residents. The distribution and accessibility of green spaces resulted insufficient for Shahdara Town’s population, highlighting local issues from a social perspective. The imbalanced provision of green spaces for densely populated areas is a big challenge for urban planners and policymakers because it jeopardizes the city life-quality and local ecological justice. Only the effort of conducting a good spatial assessment during urban planning processes can lead to a balanced and equal distribution of urban green spaces in developing cities, ensuring social and ecological justice for the population.

Globally, green spaces are considered as a fundamental part of biodiversity to balance the environment in an ecosystem particularly in urban areas. Contrary to this, urban green is declining in the least developing nations particularly due to rapid urbanization. This impact alter the condition of environmental services in term of non-provision and insufficient urban green spaces for the local population. This study takes Shahdara Town as an area of interest that is a congested urban area of Lahore Pakistan, and currently facing social injustice in terms of a dense urban area with few green spaces. The study uses Geographical Information Science for the identification of green spaces, calculation of their total area, and quantification of green cover extent by using NDVI, to comparing them with population to analyzed the environmental justice. To check the social perspective of the population regarding green areas and their importance among urban people, a comparison has been made with the presence of parks in the area, their association with living conditions and quality of life of locals. This social prospective was investigated by applying the Multiple Linear Regression Model (MLRM) by taking the availability of park/urban green in area as dependent variable and accessibility to parks, its total distance from a house, and frequency of visit as independent variables. The resultant analysis shows that according to international standards, per capita green spaces are less in this town, of Lahore. This imbalance provision of environmental services is a challenging task, for policymakers and a hurdle for urban sustainability. Finally, the outcomes of the research provide a documented base evidence and social analysis for environmental sustainability in terms of provisions of environmental services for the urban dwellers in the region.

As a response to food security, urban agriculture is essential for sustainable development. The primary goal of this study is to provide the basic formulation and theoretical knowledge for sustainable urban agriculture by analyzing the impact of urbanization on urban agriculture and food security. For the food security assessment, the variables included food consumption and quality of food as the independent variables, and monthly income of local dwellers as the dependent variable; these were considered for the regression analysis and statistical analysis. The food security assessment was checked and expressed using regression values of R, which was 0.857, and an adjusted R square, with a value of 0.728. The results show extensive change in food security issues and land use due to urbanization causes, large-scale damage to agricultural land in the area, and loss of biodiversity, which threaten food security by converting natural land into built-up areas. The study concludes that urban agriculture is a fundamental environmental activity to ensure food security by increasing food production for locals and improving urban biodiversity.