Exploring the nexus between land use land cover (LULC) changes and population growth in a planned city of islamabad and unplanned city of Rawalpindi, Pakistan.

For the last three decades, Islamabad - a planned city, and Rawalpindi - an unplanned city, have experienced massive land use and land cover changes. The main objective of this study was a comparative assessment and quantification of LULC changes in relation to population growth and urbanization from 1990 to 2021 with the help of satellite imagery and population data in planned and unplanned cities. For classification four land-use land cover classes: built-up, vegetation, bare land, and water were selected. Maximum likelihood algorithm and confusion matrix were employed for classification and accuracy assessment. Results revealed that built-up increased from 5.7% (52 km2) to 25.7% (233 km2) and 3.7% (60 km2) to 14.1% (228 km2) from 1990 to 2021 for Islamabad and Rawalpindi, respectively. Wherein the bare land decreased from 42.2% (382 km2) to 18.1% (164 km2) in Islamabad and 65.5% (1058 km2) to 32.1% (518 km2) in Rawalpindi. Vegetation showed an increment of 4.7% for Islamabad and 24.5% for Rawalpindi. Surface water bodies decreased in both study areas. Population growth showed a strong positive correlation with the built-up class and a strong negative correlation with the bare land class for both cities. The outcomes of this study may be helpful in policymaking for better planning and management of land use land cover and urban sprawl in the context of sustainable development goals.

Surface urban heat islands in the mega city of Karachi, their spatial distribution and health emergency response infrastructure.

The 2015 heat wave resulted in an estimated over 1200 deaths during the month of June. However, there were no records on the spatial distribution of the effects of this heat wave. An analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) daily data was conducted to identify regions that experienced above normal temperatures in 2015. An analysis of the monthly averages showed that in general April and May were the warmer months in Karachi, unlike the case in 2015. In addition, the general warm trends were common in the highly industrialised Sindh Industrial Trading Estate (SITE) and Liaquatabad towns, while Gadap, with its mostly barren land, and New Karachi also experience higher temperatures. Coastal towns were naturally cooler and more habitable in the given scenario. A count of the spatial presence of health facilities for the city was also extracted where Gadap and Korangi were poorly served while the more affluent towns of Defence Housing Authority (DHA) and Gulshan-e-Iqbal appeared to be better served.

Assessment of forest cover and carbon stock changes in sub-tropical pine forest of Azad Jammu & Kashmir (AJK), Pakistan using multi-temporal Landsat satellite data and field inventory.

This study aimed at estimating temporal (1989-2018) change in forest cover, carbon stock and trend in corresponding CO2 emissions/sequestration of a sub-tropical pine forest (STPF) in AJK, Pakistan. Our field inventory estimation shows an average above ground biomass (AAGB) accumulation of 0.145 Kt/ha with average carbon stock (ACS) value of 0.072 Kt/ha. Landsat TM, ETM+ and OLI images of 1989, 1993, 1999, 2005, 2010, 2015 and 2018 were used to extract vegetation fractions through Linear Spectral Mixture Analysis (LSMA) and forest area was calculated for respective years. Based on the forest area and estimated ACS value, the biomass carbon stock with corresponding CO2 emissions/sequestration was worked out for each time and change in forest carbon stock was determined for different time periods from 1989 to 2018. Our analysis shows net increase of 561 ha in forest cover and 40.39 Kt of ACS along with increase in corresponding CO2 sequestrations of 147.83 Kt over the study period. The results based on combination of remote sensing and field inventory provide valuable information and scientific basis to plan and ensure sustainable forest management (SFM) through reforestation, protection and conservation to enhance and maintain adequate forest cover and reduce CO2 emissions.

Assessment of the health impact of paper mulberry (Broussonetia papyrifera L.), an invasive plant species in Islamabad, Pakistan.

This study focuses on the risk of pollen allergy due to paper mulberry (Broussonetia papyrifera L.), an Asian invasive plant species now common in large parts of the world. Pollen plays a key role in the pathogenesis of respiratory allergic diseases, particularly rhinitis and asthma, and Islamabad, a major metropolitan city, is severely affected by allergy owing to B. papyrifera pollen. Due to its seasonality and other relationships with climatic variables, we used remote sensing to monitor the trend of pollen count. We also mapped the localisation of patients affected by pollen allergy using geographic information systems. The maximum likelihood algorithm was applied to SPOT-5 satellite imagery for land use/land cover classification. Temporal analysis of remotely sensed data revealed an increasing trend of paper mulberry density towards the southern and south-western part of Islamabad. Although not evident during rainfall, a clear positive correlation was found between patient count and pollen count. Field survey data and hotspot spatial analysis of allergy patients revealed that residents of Shakerperiyan and Lok Virsa areas (Sectors H-8, I-8, I-9, G-8, G-7 and G-6 in Islamabad) had more pronounced symptoms compared to residents of other sectors. The methodology adopted used in this study can be used to map the distribution of similar invasive species in other parts of the country.