Spatiotemporal Analysis of Land Use / Land Cover in Swat, Pakistan Using Supervised Classification in Remote Sensing: 2000 to 2015

Changes in land use and land cover affect the social, economic and natural aspects of any area. Mostly land use and land cover (LULC) changes are the result of population growth and human activities in the form of urban agglomerations and industrialization etc. Physical factors like soil structure and type, slope condition, topography are main aspects. Land use change defines the historical pattern that how people used that specific land which depends on the availability of resources and economic conditions. LULC changes may trigger the detrimental effects like increase in natural hazard events and changes in climatic patterns. Climatic pattern directly affects the precipitation, groundwater recharge, the amount of evapotranspiration and runoff generation. On regional and local scale, LULC change is a far-reaching issue because environment and climate condition depend on i

Above Ground Biomass Estimation of Dalbergia sissoo Forest Plantation from Dual-Polarized ALOS-2 PALSAR Data

In this study, ALOS-2 PALSAR L-band dual-pol (HH and HV) synthetic aperture radar (SAR) images were used for above ground biomass (AGB) estimation of Shisham (Dalbergia sissoo) tree species in the managed forest of Chichawatni Irrigated Plantation, Sahiwal District, Punjab, Pakistan. A total of 15 plots were surveyed during the field campaign and locally developed tree species-specific allometric equation was used for AGB calculation. The SAR images were pre-processed and calibrated to sigma nought (dB) for statistical AGB modeling. Nonlinear regression models between field-based AGB (ton/ha) and SAR backscatter sigma nought (dB) values give R2 (0.47 and 0.55) and RMSE (1.18 and 1.87) values for HH and HV-pol data, respectively. AGB maps generated through these regression models from both HH and HV-pol data show similar AGB values and spatial patterns. Due to a small number of sample plots, the Leave-One-Out Cross-Validation (LOOCV) proxy validation method was used for model validation, between estimated and predicted backscatter sigma nought (dB) values. The validation R2 values are small; however, outliers are identifiable in the validation scatterplots. The AGB maps from this study are useful as a first estimate of AGB values from remote sensing in the study region, especially in the context of the REDD+ program

Appraisal of Urban Sprawl in Mega Cities of Punjab Pakistan in context of Socio-Political Issues using RS/GIS.

Urbanization has become a hot issue in context of environmental and socio-political scenarios which is addressed at every forum internationally. The mega cities are considered the main origin of socio-economic development which caused to emerge a number of issues like biodiversity, environmental degradation, resource consumption, implementation of law and order and provision of basic facilities to the general public. The area under investigation consists of Lahore, Gujranwala and Sheikhupura. The study site was bounded by 73-75 E longitudes and 31-33 N latitudes. We used Landsat satellite data to map Spatio-temporal variations in urban sprawl from 1990 to 2019 with a temporal window of 15 years. The Landsat data is free, highly reliable and considered as primary source. The classification results show that the total area of study site was site was 29355 km2 including 21933km2 were green index 4595 km2 was under human settlements and 2827 km2 was the waterbody in 1990. The classification of Landsat image of the year 2005 describes that area of human settlements was increased to 9366 km2, the volume of water body was reduced to 2111km2 and the vegetation was also degraded to 17878km2. Again, the urban area was computed using satellite imagery for the year 2019 which was 16105km2 in 2019. Kappa stat proved the accuracy of supervised classification what was around 87%. Remotely sensed datasets proved the reliability of Landsat satellite images for estimation of urban sprawl during last three decades. Full Tex

Analysis of Flood Damage Assessment through WorldView-2, Quick Bird and Multispectral Satellite Imagery in Southern Punjab, Pakistan

Pakistan has faced numerous natural disasters like floods, earthquakes, landslides and environmental degradation which severely affects the Pakistan’s economy and results in various problems like causalities, diseases, water stress and severe damages (e.g., houses, public infrastructure and agricultural land erosion). There is a lack of systematic approaches to analyze pre and post damage assessment for estimation of exact loses and the total cost for rehabilitation of damaged infrastructure in an efficient way. There exist a variety of mechanisms but GIS based flood mapping is considered the most efficient to manage the flood situation. This study is focused on evaluation of flood affected areas especially in Punjab using WorldView-2, 8-band multi-spectral imagery by applying Remote Sensing (RS) and GIS techniques. The research area is comprised of Kot Addu and Muzaffargarh Districts in Punjab province of Pakistan that faced a catastrophic super flood of 2010. The WorldView-2, Quick Bird and multispectral satellite imagery are capable of making better decisions and assessment of flood effected area accurately. RS and GIS techniques can achieve the objectives and significant analyses through visual interpretations. These techniques are also used to identify the flood affected regions. The study site was examined by applying supervised classification on the basis of the training areas which were obtained during the field surveys in the study site. Supervised classification determines that 16900.96 Hectors of agriculture land was damaged while Sparse Riverine Forest had the area 44.52 hectors. The damaged built-up area was 1805.78 Hectors. RS and GIS techniques are efficient for flood mapping. Full Tex

Public Awareness and Practices Towards Self-Medication with Antibiotics Among Malaysian Population: Questionnaire Development and Pilot Testing

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