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1. Introduction

Conversion from one type of land cover to another is one of the most visible and rapid changes experienced by the earth and this conversion has profound social and environmental impacts at various scales. In the past, drivers of land cover change have been classified into two categories: proximate and distant, or indirect[[[[1]. Recently, the phenomenon of inter-site tele-coupling has been recognized as a key to understanding how remote drivers relate to nearby drivers and affect changes in local landscape.[[[[2,3,4]. Some of the main drivers of landscape change include economic, technological, institutional and policy, cultural and demographic factors[[[[5].
The growth of urban areas is causing changes in land cover in many parts of the world, especially in developing countries[[[[3,6]. Intense urbanization and increased anthropogenic activity reflect the scope, intensity, and frequency of human disturbance, and the changes it causes in ecological processes and systems in urban areas.[[[[7]. Urban areas comprise only 1-6% of the earth’s surface, but they have a large impact on local and global ecosystem functions and services, by modifying local climate conditions, eliminating and breaking down native habitats, producing anthropogenic pollutants, etc.[[[[8]. Spatial patterns of urban landscape are the result of interactions between various driving forces including natural and socioeconomic factors[[[[9]. The increasing trend in industrialization and urbanization, together with migration from rural to urban areas, is the most dominant factor influencing land cover transformation. In rural areas, employment and income opportunities are insufficient, which contributes to large differences in income and facility levels between urban and rural areas[[[[10]. In developing countries, new cities are being developed due to human migration, infrastructure development, and increasing employment opportunities[[[[10,11].
The United Nations (UN) Sustainable Development Goals (SDGs) are a collection of 17 global goals, including 232 indicators set by the UN General Assembly for 2030. These goals are an urgent call for action by all countries – developed and developed – In a global partnership. Pakistan is a signatory to the United Nations SDGs, and this study analyzes the dynamics of land use change in the Islamabad Capital Region (ICT) in the context of SDGs and relevant indicators. Target 11 SDGs, “Making cities and human settlements inclusive, safe, resilient and sustainable”, with indicator number 11.3.1 “Ratio of Land Consumption Rates to Population Growth Rates (LCRPGR)”[[[[12]is an important parameter for analyzing the sustainability of land use and land changes with population growth. LCRPGR parameters are actually based on predetermined LCR parameters[[[[13,14]and PGR[[[[15], and several studies of urban areas have been done before based on this parameter. LCRPGR parameters and terminology have been given great importance now after being linked to the UN determined SDGs. LCRPGR is very important to understand the rate of land change compared to population explosion, to understand the tradition of historical land consumption, and to guide decision makers and policy makers about urban expansion plans together with the protection of environmental, social, and economic assets. Another SDG, Goal 15, “Protect, restore and promote the use of sustainable terrestrial ecosystems, manage forests sustainably, combat desertification, and stop and reverse land degradation and stop biodiversity loss” emphasizes the protection of tree cover and sustainable forest management. SDG indicator number 15.2.1, “Progress towards sustainable forest management”[[[[16]calls for sustainable management strategies to conserve forest cover, enhance environmental education, and involve a variety of stakeholder institutions, policies, regulations and considerations that promote the sustainability and use of natural resources at various spatial scales[[[[17].
Assessment and monitoring of land cover dynamics is essential for sustainable management of natural resources, environmental protection, biodiversity conservation, and sustainable livelihood development. Therefore, the development of applicable and systematic methods for producing and updating land cover databases is considered an urgent need[[[[18]. Around the world, the rate of expansion of urban land is higher or equal to the rate of growth of urban populations[[[[19,20,21]. Many research studies focus on big cities and big cities, where increasing population through census statistical analysis is directly related to urban land expansion; however, these statistics do not provide information on the spatial distribution, patterns, and scale of changes in urban land use. Analysis and simulation of changes in multi-temporal land cover based on remote sensing imagery of very high to very high resolution satellites become an established technique for measuring changes occurring on the surface of the earth, and airborne datasets and multi-temporal satellites are now widely used. for mapping, monitoring and modeling urban growth with a focus on spatial dimensions and structures[[[[22,23,24,25]. In urban expansion studies, spatial analysis of land cover and land use change has helped to understand the underlying natural and socio-economic factors and drivers. For example, Seto et al.[[[[26]has presented a meta-analysis of 326 studies using temporal satellite imagery to map urban land conversion. A total of 58,000 km2 an increase in urban land area was reported in thirty years (1970 to 2000) and by 2030, global urban land cover is expected to increase between 430,000 km2 and 12,568,000 km2, with an estimated 1,527,000 km2 more possible. According to Seto et al.[[[[26], in all regions and for three decades, the rate of expansion of urban land is higher or equal to the rate of growth of urban populations. Yang et al.[[[[27]study and report evidence of urban agglomeration through satellite images in four major US gulf regions (San Francisco and New York), China (Hong Kong-Macau), and Japan (Tokyo), from 1987 to 2017.
Clarke et al.[[[[28]proposes a framework for combining remote sensing and spatial metrics to improve understanding and representation of urban dynamics to produce alternative conceptions of urban spatial structure and change. Particularly with regard to urban forestry, several studies have focused on assessing, mapping, and monitoring parameters of urban forests in rapidly developing cities in developing countries. For example, Gong et al.[[[[29]conducted a 30-year study of forest fragmentation of the Shenzhen Special Economic Zone (SEZ), a city founded in 1979 in South China. Huang et al.[[[[30]uses satellite imagery from 77 metropolitan areas in Asia, the US, Europe, Latin America, and Australia to calculate and analyze seven spatial metrics (form of weighted average area, weighted patch fractal dimension average index, centrality, conciseness index, conciseness index largest fillings, open space ratio, and density). According to their analysis, the cohesiveness, density, and regularity of urban areas in developing regions generally exceeds the levels reported in all developed countries.[[[[30]. Dewan et al.[[[[31]study the dynamics of land use / cover changes through landscape fragmentation analysis in Dhaka Metropolitan, Bangladesh, calculate and analyze the following metrics: Amount of fillings, fill density, landscape shape index, largest fill index, average fill size, average fill size, average fill size, fractal mean dimensional area, Interspersion and alignment, transmission, and Shannon’s diversity index.
In Pakistan, like other developing countries, most urban development is haphazard, usually lacking an appropriate planning strategy[[[[10]. Pakistan’s urbanization rate is the highest in South Asia, and by 2030, Pakistan will have more people in cities than in rural areas. Population growth and rapid development cause major agricultural land to be encroached upon and also cause loss of tree cover[[[[32,33,34,35,36]. In the late 1960s, the capital of the Islamic Republic of Pakistan was shifted from Karachi to Islamabad (officially named Islamabad Capital Territory (ICT)). The ICT Masterplan was developed by the famous Greek architect and city planner C. A. Doxiadis[[[[37]. In terms of planned new capital, ICTs are similar to planned new post-colonial capital / relocation as in the case of Brasilia (Brazil), Nur-Sultan (named Astana from 1998 to 2019, and formerly Akmola) in Kazakhstan, and Canberra (Australia)[[[[38,39,40]. In the last few decades, with various ongoing development activities, ICTs have struggled with rapid urbanization and enormous levels of pollution from industrial, housing and transportation sources. In terms of population, ICT is considered the most diverse city in Pakistan with a large percentage of immigrants and foreign residents[[[[41]. An unprecedented influx of migrants and population increases has resulted in urban spread and conversion of arable agricultural land and green cover to concrete – a clear deviation from the original ICT master plan[[[[39,40]. Uncontrolled population growth in ICTs due to rapid urbanization has worsened the environment, and increased adverse ecological impacts on human health, flora and fauna[[[[42].

1.1. Literature Review – ICT Mapping and Monitoring

In the past 20 years, several studies have been carried out on ICTs, regarding changes in land cover, estimation of biomass, monitoring of water quality, and increasing temperatures using satellite datasets. In this section, we present a synthesis of works published on the dynamics of land cover change in ICT.

Adeel[[[[43]identify urban growth potential through land use for ICT zone IV (Picture 1), based on the 2.5 m SPOT-5 panchromatic data set and population census data, and found that nearly 63% of zone IV carries the potential for ‘High’ to ‘Very High’ future growth, which is mainly located close to Islamabad Expressway. This work uses satellite imagery and field data from one year (2007) and does not report the dynamics of spatial changes. Butt et al.[[[[35]study metropolitan development in ICTs, based on growth directions and expansion trends from the city center, for the period 1972-2009 using Landsat satellite imagery. Using Principal Components Analysis (PCA), band ratios, and guided classification methods, they found that urban development had grown by 87.31 km2 in 38 years. Butt et al.[[[[44]conducting a study of land cover change analysis in the Simly watershed, ICT; the results obtained from the guided classification with maximum likelihood indicate loss of tree cover up to 26% and a 6% increase in settlements from 1992-2012, based on Landsat 5 TM and SPOT-5 imagery. Likewise, analysis of the Rawal dam watershed, ICT using Landsat 5 TM imagery, showed 3% degradation of tree cover and 2% of completion from 1992-2012[[[[45]. Another study on the dynamics of change in land cover for ICT by Hassan et al.[[[[46]using Landsat 5 TM 30 m data for 1992 and 2.5 SPOT-5 data for 2012, using the maximum likelihood algorithm for image classification. The study revealed a decrease in forest cover of about 49% and more than 213% of the acquisition of residential areas from 1992-2012. Sohail et al.[[[[47]conduct research to assess water quality indices and analyze major changes in land cover type, vegetation cover, urbanization rate and possible impacts on groundwater resources, vegetation, and barren land. They used Landsat images for 1993, 1997, 2002, 2007, 2013 and 2017 for the assessment and mapping of land cover dynamics; according to their findings, from 1993 to 2017, the vegetation area was reduced by 101.77 km2, surface water is reduced by 1.10 km2barren land is reduced by 2.90 km2, while the developed land was expanded by 105.77 km2.
The comparison of Beijing, China and ICT for the role of vegetation in “controlling environmental conditions environmentally friendly for a sustainable urban environment” was carried out by Naeem et al.[[[[42], where they use satellite images of Gaofen-1 (GF-1) and Landsat-8 Operational Land Imager (OLI) with spatial resolutions of 8 m and 30 m. They evaluated various scenarios and models for future development to predict future spatial patterns in both cities. Another study conducted by Naeem et al.[[[[48]to study the relationship between green space characteristics, analyzed through landscape metrics, and land surface temperatures for a sustainable urban environment that compares Beijing, China and ICTs.
Khalid et al.[[[[49]conducting research to measure the decline in forest reserves and associated temperature variations in the relatively unexplored ICT biodiversity hotspot, Bukit Margalla National Park (MHNP). In this work, Landsat satellite imagery from 1992, 2000, and 2011 was used to monitor changes in forest cover and a statistical significance test was used to determine the significance of temperature variations associated with shifting land cover classes. This study found that deforestation and forest degradation by local communities is a sustainable practice in MHNP; this requires the promotion of conservation practices to minimize ecological disturbance here[[[[49]. Batool and Javaid[[[[50]conducted a study on the Bukit Margalla forest valuation using Landsat imagery for 2000 and 2018, and reported that forest cover had decreased from 87% in 2000 to 74% in 2018, while the area built had increased from 5% in 2000 to 7 % in 2018, and open land in the study area increased from 2% in 2000 to 7% in 2018. Mannan et al.[[[[51]conducted research using Landsat, Markov Chain, and Cellular Automata imagery in Margalla Hills, with a focus on quantitative assessments of spatial land use and land cover changes during 1998, 2008, 2018, and 2028 simulations. In addition, a forest inventory survey was conducted to estimate biomass and carbon sinks. This work shows that the forest area has been reduced from 409.36 km2 to 392.31 km2 and residential areas have increased from 14.97 km2 up to 39.66 km2 from 1998 to 2018. The average annual biomass and carbon loss was 50.34 Gg / ha / year and 31.33 Gg C / ha / year, respectively.
ICT is a relatively new and heterogeneous city spatially surrounded by thick forests of the Himalayas compared to other developing and rapidly developing cities such as Dhaka, Bangladesh[[[[31,52,53,54,55], New Delhi, India[[[[56], Beijing, China[[[[42,48,57,58], Shanghai, China[[[[59,60,61], Tokyo, Japan[[[[27,62], etc. Based on the literature review, we observe that most studies on the dynamics of ICT land cover have used different data, methods, definitions and classification schemes from a distance, and have given mixed results. Most studies that have analyzed the dynamics of land change in the focus of ICT on the analysis of overall land cover and land use change, and detailed analysis of landscape ecology and urban forestry characteristics are absent. Furthermore, there is very little focus in this study on urban landscape metrics and indicators of sustainable urban growth such as LCRPGR.

1.2. Purpose of the Study

In this paper, established, proven, and articulated research methodologies, satellite datasets, and feature definitions are adopted with the aim of systematically achieving the following set goals:

  • Detect, measure and characterize land cover features using freely available medium-resolution Landsat satellite data (1976, 1990, 2000, 2010 and 2016) and determine the annual rate of change in land cover classes at 10-year intervals.

  • Landscape metrics and spatiotemporal analysis of forest fragmentation, for estimating and reporting changes in ICT urban ecosystems for forty years.

  • Calculation of SDG indicator number 11.3.1 “Land Consumption Rate to Population Growth Rate (LCRPGR).”

5. Discussion

This research was conducted to quantitatively analyze the dynamics of landscape change in ICTs from 1976 to 2016 using Landsat imagery of medium spatial resolution. In this study, we observed an increase in settlements over the last forty years. Dramatic changes in land cover in settlements place great pressure on other land cover classes, especially tree and land cover. Existing urban areas can be seen expanding through the construction of rapid housing blocks in the form of housing communities, industrial blocks and road expansion, which leads to horizontal and vertical developments in the city and the development of luxury farm houses in the surrounding area (Figure 7). This rapid increase in urbanization is also associated with migration. Urban growth may have a positive or negative impact on the environment but unplanned urban growth has a negative effect. For the development of the country’s economy, the necessary planning is needed to make urbanization useful, because social, health and environmental problems often accompany the process of urbanization.
Over a span of forty years, overall decreases have been observed in tree cover class areas (ie, greater than and less than 40% of tree canopies) in ICTs, and most tree loss occurred after 2000 with a corresponding increase in built areas -up. Besides tree cutting, another important reason behind the rapid loss or degradation of trees is forest fires. On Bukit Margalla, forest fires usually occur during hot, dry climatic conditions when there is no rain for months and the temperature rises to 45 ° C. According to Khalid and Ahmad[[[[78], a total of 320 forest fires were recorded from 2002 to 2012 and around 8 km2 burned area as a result. In ICTs, due to uncontrolled urbanization and lack of awareness, large tree losses have been observed in the last sixteen years, ie, 2000-2016. Another factor for forest degradation is uncontrolled grazing[[[[78]. As such, there are no adequate plans or methods that can be managed to stop grazing activities. For ecotourism activities and public awareness, a number of jogging and hiking paths have been formed in the Bukit Margalla National Park, and a large number of visitors have greatly influenced the Bukit Margalla National Park by taking out the trash. Illegal and unsupervised activities in these forest areas cause threats to the forest ecosystem[[[[50,79].
Massive migration has occurred in the last few years from rural to urban areas, largely due to low land yields, landlessness, land subdivision, poor economy, and better education and health opportunities in urban areas. The rapid increase in population has contributed to the depletion of natural resources and rapid deforestation near settlements[[[[80].
The LCRPGR parameter is an indicator of urban sustainable development, whether urban expansion is balanced with population growth or not. According to the literature review, limited peer-reviewed scientific studies have been reported on LCRPGR monitoring and mapping. Under each SDG, a number of targets and indicators have been determined, which countries must quantify, but most developing countries do not have a comprehensive database with which they can calculate, calculate and report SDG indicators. To the best of the writer’s knowledge, only Nicolau et al.[[[[77]and Wang et al.[[[[81]has calculated and reported the scientific results of SDG proposed by LCRPGR over urban areas. Nicolau et al.[[[[77]based their studies on mainland Portugal, while Wang et al.[[[[81]conducted their research in mainland China, used earth observations and population census data, and reported an increase in LCRPGR values ​​from 1.69 in 1990-2000 to 1.78 in 2000-2010. Research findings related to LCRPGR from these studies show that in most cities, horizontal and vertical city expansion is carried out in an unplanned way that has affected the balance of land consumption versus increasing population to achieve effective development goals by 2030[[[[77,81]. In this study on ICT, the LCRPGR ratio was 0.62 from 1976 to 2000, which increased to 1.36 from 2000 to 2016. Based on studies conducted on a global scale, in most cases LCR is higher than or equal to PGR because of the high demand for luxury housing in urban areas[[[[26,30].
The cities of Shenzhen SEZ and ICT were both developed in the late 1970s. In terms of changes in urban forest cover, the Shenzhen SEZ has been restored to ~ 85% (1973–2005)[[[[29]while in this study, we detected ~ 27% of urban forest loss (1976-2016) in ICT. In both cities (KEK and ICT), the results of urban forest fragmentation revealed the loss of forest patches. In South Asia, the ICT landscape is very similar to the cities of Kathmandu (capital of Nepal) and Thimphu (capital of Bhutan), because they are cities that are topographically surrounded by pine trees. Compared to ICTs, the cities of Kathmandu and Thimphu are older but the population is very new, very encroached upon, and too shepherded. Although many studies have investigated the dynamics of land cover in the cities of Kathmandu and Thimphu using temporal satellite data[[[[82,83,84,85], detailed analysis using parameters such as landscape metrics, forest fragmentation, and LCRPGR has not been carried out. In this aspect, this research serves as a methodological framework for the application and analysis of other similar cities in developing countries.
Due to rapid tree loss and urbanization, ICTs have been observing spells of dust storms and soil erosion quickly[[[[86]. Soil erosion, dry temperatures, and dust storms that result from it have a negative impact in the form of air pollution[[[[87]and land degradation. The soil in ICT and the surrounding area is shallow and has a clay composition[[[[63]. Alluvial soils and terraces in the area tend to have low agricultural productivity and in the south and west of the Potohar highlands, the soil is thin and infertile.[[[[88]. Streams and ravines cut loose plains and cause erosion and steep slopes. This soil is generally not suitable for planting. However, large tracts of arable and fertile land are found in protected highland areas and this supports forests and small farms.[[[[89]. Butt et al.[[[[45]described the most significant land degradation problems in the Rawal watershed as soil erosion and soil nutrient loss. They further pointed out that, between 1992 and 2012, the majority of land that was previously vegetation, vacant land, or water bodies was converted to agriculture and settlements, indicating increased pressure on natural resources in the Rawal Watershed.[[[[45].
The results of the landscape analysis in this study reveal that ICT urban landscapes have become more heterogeneous, disproportionate and diverse, and tree patches have declined. Alarmingly, core forests covering> 500 hectares have declined by almost 15% in forty years. Although at the individual level, ICT residents, civil society, and local governments are trying to recover lost tree cover by planting trees, this initiative must be continuously and regularly maintained to monitor tree growth without destroying forests. mature tree stands there. Temporal forest fragmentation analysis shows that due to loss of tree cover, three categories of core forest fragments (ie, 500 hectares) have declined in forty years (1976-2016). Loss of forest fragmentation negatively affects the habitat and biodiversity of ICT on land[[[[79,90,91]. Based on the analysis of landscape metrics above the Dhaka metropolitan, a similar developing city in Asia, Dewan et al.[[[[31]revealed that cultivation areas and plantations had become highly fragmented with increasing anthropogenic disturbances and urban building categories being aggregated and convoluted.

While our analysis of the dynamics of changes in ICT land cover in this study is important and unique, there are some caveats that are worth mentioning. First of all, for the 1976 land cover map, we relied on approximately 57 m spatial resolution of Landsat 3 Multispectral Scanner System (MSS) sensor data which is relatively spatially coarser compared to Landsat 5 and 8 (ie, 30 m), which can affect heterogeneity spatial and accuracy maps of developed land cover. Second, because Landsat was a pioneer of the Earth Observation (EO) satellite program that began in 1972, so it is not possible to obtain remote sensing imagery from previous years, and thus we cannot obtain maps of land cover before the 1960s, when the Republic Pakistani Islam made a capital shift from Karachi to Islamabad. Third, from satellite data of 30 m Landsat spatial resolution, we cannot detect and delineate the boundaries of the area built and can be done from VHRS sub-meter images available from 2000 onwards. However, VHRS data sets come at a high cost, especially when acquisitions must be obtained several times, and therefore may not be feasible for study locations in developing countries. Of course, research in this domain is ongoing in connection with the use of VHRS data for the study of urban areas, using methods such as object-based image analysis, machine learning, etc. Fourth, there may be some level of uncertainty for field measurement data, because there is always the potential for human error especially when basic truths are collected in a wider area. Fifth, in this study, we only used temporal optical satellite data, which can cause optical signal saturation in closed canopy forests, and atmospheric effects (eg, cloud cover, haze and haze).

6. Conclusion

This study sheds new light on the dynamics of systematic land cover ICTs for four decades, underscoring the large decrease in tree cover along with significant increases in settlements and land. The findings from the analysis of land cover change, landscape metrics, forest fragmentation, and LCRPGR, are well aligned and overall agreed with work previously published on a regional and global scale. LCRPGR calculations are very important to understand the rate of land change compared to population explosion, to understand historical land consumption traditions, and to guide decision makers and policy makers about planned urban expansion while ensuring protection of environmental, social, and economic assets. It is a scientifically accepted phenomenon that in most cities, the level of overall land consumption is much faster than the rate of population growth, due to the high demand for luxury residents in urban areas.

Both natural and anthropogenic activities are responsible for land cover changes in ICT. In terms of landscape and fragmentation, the ecology of the urban landscape of ICTs is continually threatened because of the encroachment of residential communities, and influential business communities. Findings from the urban landscape matrix and forest fragmentation analysis in this study can help the ICT Capital Development Authority (CDA) and the Islamabad Wildlife Management Board (IWMB) in making strategic decisions to prevent tree loss, forest degradation, and encroachment in ICT urban landscapes, and also planning future urban growth using remote sensing imagery and geospatial analysis. The methodology described in this study is cost effective and can easily be replicated in other countries / regions, especially in developing countries, through the integration of freely available satellite images at intervals of 5-10 years.



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