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The purpose of the study is to assess the environmental and socio‐economic impacts and risks of climate change through GIS database management system (DBMS) on land use‐informatics and climate‐informatics. The Dabka watershed constitutes a part of the Kosi Basin in the Lesser Himalaya, India in district Nainital has been selected for the case illustration.

Land use‐informatics consists of land use mapping and change diction, i.e. decadal changes and annual changes. Climate‐informatics consists of climate change detection through daily, monthly and annual weather data for a period of 25 years.

The exercise revealed that oak and pine forests have decreased, respectively, by 25 percent (4.48 km²) and 3 percent (0.28 km²) thus bringing a decline of 4.76 km² forest in the watershed during 1990 to 2010. But, due to climate change the mixed forest taking place of oak forest in certain pockets and consequently the mixed forest in the catchment increased by 18 percent (2.3 km²) during the same period which reduced the overall loss of forests in the region but its not eco‐friendly as the oak forest. Barren land increased 1.21 km² (56 percent), riverbed increased 0.78 km² (52 percent) and cultivated land increased about 0.63 km² (3 percent) during the period of 1990 to 2010. Out of the total seven classes of the land use land cover, five classes (i.e. Oak, Pine, Mixed, Barren and Riverbed) are being changed dominantly due to climate change factor and anthropogenic factors plays a supporting role whereas only two classes (scrub land and agricultural land) are being changed dominantly by anthropogenic factors and climate change factors plays a supporting role. Expansion of mixed forest land brought out due to upslope shifting of existing forest species due to climate change factor only because upslope areas getting warmer than past with the rate of 9°C‐12°C/two decades. Consequently, the results concluded that the high rate of land use change accelerating several environmental problems such as high runoff, flash flood, river‐line flood and soil erosion during monsoon season and drought during non‐monsoon period. These environmental problems cause great loss to life and property and poses serious threat to the process of development with have far‐reaching economic and social consequences.

This study generated primary data on land use‐informatics and climate‐informatics to integrate each‐other for impact assessment and mitigation through sustainable land use as constitutes a part of a multidisciplinary project, Department of Science and Technology (D.S.T.) Government of India.

The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.

Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.

The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.

As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.

Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.

The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.

This paper aims to assess the rate and land category contributing to the changes in seven land-uses in the Kintampo North Municipality of Ghana and the effect of the decisions of land users on future landscapes.

LANDSAT images were classified to generate land use/cover maps to detect changes that had occurred between 1986 and 2014. In total, 120 farmers were also interviewed to determine their perceptions on land use changes. Interval, category and transition levels of changes were determined. Savanna woodland, settlement and forest were mostly converted to farmland in both intervals (1986-2001 and 2001-2014).

Results showed that rock outcrop, plantation, cropland and savanna woodland increased at an annual rate of 13.86, 1.57, 0.82 and 0.33 per cent, respectively, whilst forest, settlement and water body decreased at 4.90, 1.84 and 1.17 per cent annual rate of change, respectively. Approximately, 74 per cent of farmers will not change land use in the future, while 84.2 per cent plan to increase farm sizes.

The study shows that more land cover will be targeted for conversion as farmers expand their farmlands. There is the need for strict implementation of appropriate land use/cover policies to sustain food production in the region in this era of changing climate and population increase.

This research assessed the land use changes in the Kintampo North Municipality and its impacts on agriculture and carbon stocks release via land use changes. It identified how the decisions of the local farmers on land management will affect future landscape.

Urban built-up has been increasing exponentially in the world. Urban population growth and migration are depleting the land resources and creating thermal discomfort. Cities all around the world are facing urban heat island effects and increased temperatures. This study aims to map land cover and formulate local climate zones for enhancing urban resilience against disaster and climate risks.

This study uses exploratory research to identify local climate zones for Lahore, Pakistan. Landsat 8 imagery was used to develop a land use land cover map. For mapping local climate zones, the standard World Urban and Access Portal Tool procedure was used.

Results have revealed that Lahore has grown exponentially. Compact low rise and open low rise were the two most common local climate zones prevalent in the city. In contrast, the outer regions of the city consisted of LCZ D (low plants) and LCZ F (bare soil).

This study highlights the need to consider local climate zones in future development plans and policies for ensuring sustainable, resilient and climate-friendly cities.

Local climate zone studies are missing in Pakistan. This study has empirically analyzed the ground situation of local climate zones for Lahore metropolitan city. This study will provide baseline support for future studies on urban heat island and climate change adaptation planning.

The purpose of this paper is to emphasize the conservation and management of crop diversity in traditional agro‐ecosystems as a crucial component for sustainable landscape development in the mountains of the Indian Himalayan region. The results indicate that mountain farming has the potential to produce good output from a low input system where farmers still use local resources and locally developed technology.

The discussion of major issues in this paper is based on our empirical study involving a survey of the area and field‐based experiments to evaluate the productivity in traditional mountain farming systems. Additionally, landscape change was monitored with the use of satellite data.

The paper finds that the rate of genetic erosion within the study area during the last three decades is documented and the factors responsible for such erosion identified. The efficiency of traditional agro‐ecosystems of Himalayan Mountains in terms of energy and monetary value is presented. Traditional crop cultivation in the region appears efficient from the viewpoint of ecology of the area and economy of the local people.

This paper recommends practical options to encourage cultivation of traditional crops for their conservation and management in the Himalayan agro‐ecosystems that will lead to sustainable landscape development in these mountains. Traditional agro‐ecosystems are characterized by their dependence on local resources, close links to the surrounding forests, and locally developed technologies in the Himalayas of India. Research and policy support for their conservation in traditional agro‐ecosystems in this region is required as many traditional crops and their landraces are in jeopardy due to their rapid genetic erosion in the region. The land use land cover map developed within this study enables observation of the process of the landscape change trends in the region. Local communities need proper awareness and encouragement through appropriate research, institutional and policy support to continue growing traditional crops for both their economic incentives and management of the ecosystem services.

The paper shows that traditional crop diversity can enhance the economic conditions for people without having negative implications on the surrounding landscape.

The comparative study between urban regions gathered by the 2010 National Project of Relevant Interest financed by the Italian Ministry of Education, University and Research (MIUR – PRIN 2010) re-opened, in Italy, the debate on regional comparison of data, especially the ones of land use monitoring, which are difficult to collect, and to compare. The purpose of this paper is to illustrate some results of comparative studies based on regional and national data sets of land use indicators. Further considerations of land use change (LUC) assessment and its effect on environmental policies extended to the whole metropolitan area of Milan are outlined.

The adopted methodology collects different types of information from the existent databases on land uses/land covers (national/regional) and presents an assessment between the selected case of studies (urban regions), leading a shift from a quantitative evaluation to a qualitative one. A comparative study was conducted applying a geographical and statistical difference of land uses among different time thresholds. Subsequently, a cross-tabulation analysis allows an in-depth LUC analysis for the Milan urban region.

The results of the study display an autonomous pattern for the Milan urban region, which is the most densely populated area in Italy and seems to be the only comparable to other international cases of studies due to its extension and characteristics. Nevertheless, it is not the urban region that is affected by the highest rate of land take, which takes place in the Italian context where densities of settlements are lower and sprawled. According to Soja’s (2011) interpretation, the post-metropolitan condition of Milan seems to be proved.

The study was aimed at creating the first online National Atlas which has been used to overcome traditional problems of homogenization of LUC data in Italy. The quantification and qualification of LUC patterns allow us to understand if, and where, post-metropolis condition occurs. This research gives a clear indication of the kind of ongoing phenomena for policy orientation to planners and administrators, especially the one of the green infrastructure approach at the city-region level to solving the emerging environmental challenges.

This paper aims at providing the evidence about how carbon sequestration in terrestrial ecosystems could contribute to the decrease of atmospheric CO₂ rates through the adoption of appropriate cropping systems such as agroforestry.

Stratified randomly selected plots were used to collect data on tree diameter at breast height (DBH). Composite soil samples were collected from three soil depths for soil carbon analysis. Above ground biomass estimation was made using an allometric equation. The spectral signature of each plot was extracted to study the statistical relationship between carbon stock and selected vegetation indices.

There was a significant difference in vegetation and soil carbon stocks among the different land use/land cover types (P < 0.05). The potential carbon stock was highest in the vegetation found in sparsely cultivated land (13.13 ± 1.84 tons ha⁻¹) and in soil in bushland (19.21 ± 3.79 tons ha⁻¹). Carbon sequestration potential of the study area significantly increased (+127174.5 tons CO₂e) as a result of conversion of intensively cultivated agricultural lands to agroforestry systems. The amount of sequestered carbon was found to be dependent on species diversity, tree density and tree size. The vegetation indices had a better correlation with soil and total carbon.

The paper has addressed an important aspect in curbing greenhouse gases in integrated land systems. The paper brings a new empirical insight of carbon sequestration potentials of agroforestry systems with a focus on drylands.

Cesspits are the means for each house to dispose of wastewater in the Bani Kinanah District (BKD) of Jordan, which creates severe environmental complications. This research aimed to find a suitable site for a wastewater treatment plant (WWTP) in BKD.

Geographic Information System (GIS)-based multicriteria decision analysis (MCDA) was used for an optimal site selection for a sewage treatment plant. Several datasets were obtained to prepare the maps of the criteria influencing the choice of the most suitable site for the WWTP. The analytic hierarchy process was used to apply the weights for each factor.

Five classes of suitability were generated: 0.23% very high suitability, 8.49% high suitability, 47.12% moderate suitability, 37.67% low suitability and 6.49% very low suitability. According to Analytical Hierarchy Process (AHP) results, the elevations, slope and groundwater depth have high importance; where their weights 21%, 19% and 17%, respectively. The most suitable site for establishing a WWTP was found in the northern part of the study area, where it is characterized by relatively low elevations (−90 to −93 m), low slope (0–2.5 %), distance from groundwater level (47–82 m) and the space is sufficient for building the plant (25328 m², 8861 m² and 8586 m²).

This research is limited by the availability of data.

The research is invaluable for decision makers involved in urban planning.

Wastewater treatment plants are essential for communities with limited resources such as Jordan. It has also profound impacts on the surrounding environment.

From the present study, it can be concluded that GIS is essential in urban utility establishment, like urban domestic wastewater treatment site selection. Although the study area has adequate potential areas for establishing WWTP, further assessment of flood vulnerability, wastewater amount quantification, population growth and urban expansion must be seriously considered before implementation.

Floods are considered as one of the most lethal natural disasters having the potential to cause havoc to entire communities. Pakistan is the land of wide topographic and climatic variations which make it vulnerable to floods. The purpose of this paper is to identify flood susceptible zones in the Panjkora Basin using frequency ratio model.

A total of seven parameters or flood conditioning factors were considered, and weights were assigned according to the frequency ratio technique. For the preparation of layers, satellite imageries and digital elevation model data were used. Frequency ratio was calculated using correlation between these parameters and flood. Flood susceptibility index map was divided into five zones through quantile method in ArcMap.

Findings of the study reveal that near half of the area (43%) is located in the very high susceptible zone, while only 20% area is classified as low to very low susceptible.

This paper is entirely based on original research. The approach used in this study has not been applied to the study area before.

Khan Jahan Ali (KJA) Bridge was constructed to promote industrial and commercial activity and improve economic and employment activity for local people. This study assessed the post-socioeconomic and environmental impacts of KJA Bridge on the inhabitants living adjacent to 2 Km from the bridge. As there is a slum adjacent to the bridge, the bridge has impacted much on the improvement of the social economic condition and lifestyle of the slum people.

The study approached a questionnaire-based field survey data collection through interviewing the people in the surrounding areas. To assess the environmental impacts, land cover change (LCC), carbon emissions and land surface temperature (LST) data were derived from Landsat images and processed in geospatial environment.

The study suggests that after bridge construction, 84% people have new jobs and about 87% people's income level has been increased. As a tourist spot, the bridge served employment opportunities for the 12% of the inhabitants. About 83% house structures have been improved, where the percentages of pucca and semi-pucca houses increased by 11% and 23%, respectively. The frequency of school-going children and literacy rate also increased. Despite all the socioeconomic development, 7.48% agricultural, 9.75% vegetation, 1.74% waterbodies were declined. Net carbon emissions increased to 13,432.39 tons from 3,323.46 tons; average LST increased from 25.750 to 32.550°C after the bridge construction.

This study focused on descriptive statistical analysis and portrayed the impact of the bridge on social, economic and environment from a micro point of view.