Detecting change on the face of the globe using GIS (Geographic Information System) aided by remotely sensed imagery is now becoming an indispensable tool in managing the resources of our planet. The present study wit...Detecting change on the face of the globe using GIS (Geographic Information System) aided by remotely sensed imagery is now becoming an indispensable tool in managing the resources of our planet. The present study with the help of GIS and remote sensing (RS) is also a similar attempt in recording and quantifying change in land use and land cover in district Pishin both in spatial and temporal extents. Satellite imagery was acquired from the USGS official website from three LANDSAT satellites. Theses satellites are LANDSAT 5, LANDSAT7 and LANDSAT 8. The data were acquired for the years 1992, 2003 and 2013. Satellite imagery was processed in ArcMap 10.1 and maximum likelihood supervised image classification was applied in reaching the goal of detecting change. The result of the analysis revealed that built-up area was increased by 5.84%;vegetation was increased by 3.89%;water bodies were increased by 0.05% and bare surfaces were decreased by 9.78%. The decrease in the barren surfaces was attributed to the increase in vegetation and built-up area which replaced the barren land in the study area. This paper also shows the significance and potential of digital change detection methods in managing the resources of our environment and keeping an eye on the land use and land cover of our Earth.展开更多
In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripher...In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripheral national territories,little or no solar radiation data,non-satisfactory sunshine hours data,and low quality of ground observed cloud cover data create a situation in which the spatial modeling of Extraterrestrial Solar Radiation(ESR) and its ground parameterization got sufficient scope.The Digital Elevation Model (DEM) input into Geographic Information System (GIS) is a compatible tool to demonstrate the spatial distribution of ESR over the rugged terrains of the study domain.For the first time,distributed modeling of ESR is done over the rugged terrains of Pakistan,based on DEM and ArcGIS..Results clearly depict that the complex landforms profoundly disrupt the zonal distribution of ESR in Pakistan.The screening impact of topography is higher on spatial distribution of ESR in winter and considerably low in summer.The combined effect of topography and latitude is obvious.Hence,the model was further testified by plotting Rb (ratio of ESR quantity over rugged terrain against plane surface) against azimuth at different latitudes with different angled slopes.The results clearly support the strong screening effect of rugged terrain through out the country especially in Himalayas,Karakoram and Hindukush (HKH),western border mountains and Balochistan Plateau.This model can be instrumental as baseline geospatial information for scientific investigations in Pakistan,where substantial fraction of national population is living in mountainous regions.展开更多
The monthly extraterrestrial solar radiations (ESR) have been simulated separately for all the months of the year. The subtropical location and distribution of mountains and their height determine the spatial distribu...The monthly extraterrestrial solar radiations (ESR) have been simulated separately for all the months of the year. The subtropical location and distribution of mountains and their height determine the spatial distribution and amount of ESR in Pakistan. The mountains, piedmonts, enclosed valleys and plains show distinct diversity of ESR values. The assessment acknowledged that countries like Pakistan with ever increasing demand of energy receive sufficient amount of ESR that could be linked with solar irradiance where development of solar energy has great potential. The simulation was done with the help of ArcGIS based on distributed modeling.展开更多
The monthly possible sunshine hours have been simulated separately for all the months of the year with the help of ArcGIS. The results are evident that the geography of the area plays a pivotal role in giving shape to...The monthly possible sunshine hours have been simulated separately for all the months of the year with the help of ArcGIS. The results are evident that the geography of the area plays a pivotal role in giving shape to spatial distribution of monthly possible sunshine duration (PSD). The landforms distributions and latitudinal extent are the major geographical factors behind the spatial-temporal distribution of monthly PSD. Maps of all the months depict different sunshine hours that vary from region to region in Pakistan. The maximum difference in PSD was noticed between lofty mountains in the north and Indus Plains. In addition, the variation is phenomenal from January to August and vice versa. This sort of study based on spatial modeling is significant in Pakistan where we lack appropriate ground observed data of PSD.展开更多
The spatial distribution of December temperature in Pakistan has been assessed by statistical method based on mean monthly data from 51 ground stations. The analysis is performed at decadal scale over the period of 19...The spatial distribution of December temperature in Pakistan has been assessed by statistical method based on mean monthly data from 51 ground stations. The analysis is performed at decadal scale over the period of 1950-2000. December is one of the representative months of winter season in Pakistan, the country with subtropical location and complex rugged terrains, plateaus and plains. The results support a slight rising temperature trend in December. However, this change in temperature varies from region to region as well as from decade to decade and reflects a complicated spatial-temporal structure of temperature anomalies. The assessment shows that the temperature anomalies in different national territories at local scale do not follow the assumption that winter months are warming in northern hemisphere. Both the isothermal shift and temperature anomalies confirm that the mountainous areas of Pakistan face more temperature variability than plains.展开更多
This study investigates the spatial-temporal variability of winter-spring (February-March-April) precipitation (WSP) in Pakistan over the period of 1961-2006 by making use of Empirical Orthogonal Function (EOF). The E...This study investigates the spatial-temporal variability of winter-spring (February-March-April) precipitation (WSP) in Pakistan over the period of 1961-2006 by making use of Empirical Orthogonal Function (EOF). The EOF analysis is based on ground observed data, reanalysis NCEP/NCAR of various geopotential heights and NOAA extended reconstructed sea surface temperatures (ERSST.v3). The significant modes are obviously variable at interannual time scale. The leading mode shows the node of maximum spatial variability anchored over the Peshawar Valley and Azad Kashmir (PVAK) axis. The pattern is associated with strong (weak) westerly jet over the Middle East. The pattern is also found closely associated with post monsoon and early winter El Nino. The Nino4 index can be an appropriate predictor for the first consistent single node pattern. The second significant mode represents a tripole pattern with areas of prominent variability over northwestern Pakistan, Quetta-Kalat region and northeastern Punjab. The pattern is found to be pro-NAO and in relation to this pattern, warm and stable SST anomalies appearing in the southern mid-latitudes of Indian and Atlantic basins.展开更多
Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of grid...Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.展开更多
By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of g...By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.展开更多
In this paper the month of August was assessed from 1950s-2000s based on the temperature data from 53 stations that covers almost all Pakistan. The temperature coefficient has been calculated by making use of linear r...In this paper the month of August was assessed from 1950s-2000s based on the temperature data from 53 stations that covers almost all Pakistan. The temperature coefficient has been calculated by making use of linear regression. The results have been mapped that show considerable variability of temperature at decadal scale in different areas of Pakistan. The rugged terrains especially and rest of Pakistan generally reflect significant temperature variability in the decades of 1950s, 1960s, 1970s, 1980s, 1990s and 2000s as well. This change in temperature varies from region to region and decade to decade in Pakistan. The temperature anomalies achieved in the country are complicated at local level and did not follow the simple perception that winter months are warming and summer months are cooling. In this study, a geographical approach has been adopted to explain the spatial-temporal dynamics of temperature variation over the study period in Pakistan with emphasis on regional detail.展开更多
文摘Detecting change on the face of the globe using GIS (Geographic Information System) aided by remotely sensed imagery is now becoming an indispensable tool in managing the resources of our planet. The present study with the help of GIS and remote sensing (RS) is also a similar attempt in recording and quantifying change in land use and land cover in district Pishin both in spatial and temporal extents. Satellite imagery was acquired from the USGS official website from three LANDSAT satellites. Theses satellites are LANDSAT 5, LANDSAT7 and LANDSAT 8. The data were acquired for the years 1992, 2003 and 2013. Satellite imagery was processed in ArcMap 10.1 and maximum likelihood supervised image classification was applied in reaching the goal of detecting change. The result of the analysis revealed that built-up area was increased by 5.84%;vegetation was increased by 3.89%;water bodies were increased by 0.05% and bare surfaces were decreased by 9.78%. The decrease in the barren surfaces was attributed to the increase in vegetation and built-up area which replaced the barren land in the study area. This paper also shows the significance and potential of digital change detection methods in managing the resources of our environment and keeping an eye on the land use and land cover of our Earth.
文摘In Pakistan,the solar analogue has been addressed but its surface geographical parameterization has given least attention.Inappropriate density of stations and their spatial coverage particularly in difficult peripheral national territories,little or no solar radiation data,non-satisfactory sunshine hours data,and low quality of ground observed cloud cover data create a situation in which the spatial modeling of Extraterrestrial Solar Radiation(ESR) and its ground parameterization got sufficient scope.The Digital Elevation Model (DEM) input into Geographic Information System (GIS) is a compatible tool to demonstrate the spatial distribution of ESR over the rugged terrains of the study domain.For the first time,distributed modeling of ESR is done over the rugged terrains of Pakistan,based on DEM and ArcGIS..Results clearly depict that the complex landforms profoundly disrupt the zonal distribution of ESR in Pakistan.The screening impact of topography is higher on spatial distribution of ESR in winter and considerably low in summer.The combined effect of topography and latitude is obvious.Hence,the model was further testified by plotting Rb (ratio of ESR quantity over rugged terrain against plane surface) against azimuth at different latitudes with different angled slopes.The results clearly support the strong screening effect of rugged terrain through out the country especially in Himalayas,Karakoram and Hindukush (HKH),western border mountains and Balochistan Plateau.This model can be instrumental as baseline geospatial information for scientific investigations in Pakistan,where substantial fraction of national population is living in mountainous regions.
文摘The monthly extraterrestrial solar radiations (ESR) have been simulated separately for all the months of the year. The subtropical location and distribution of mountains and their height determine the spatial distribution and amount of ESR in Pakistan. The mountains, piedmonts, enclosed valleys and plains show distinct diversity of ESR values. The assessment acknowledged that countries like Pakistan with ever increasing demand of energy receive sufficient amount of ESR that could be linked with solar irradiance where development of solar energy has great potential. The simulation was done with the help of ArcGIS based on distributed modeling.
文摘The monthly possible sunshine hours have been simulated separately for all the months of the year with the help of ArcGIS. The results are evident that the geography of the area plays a pivotal role in giving shape to spatial distribution of monthly possible sunshine duration (PSD). The landforms distributions and latitudinal extent are the major geographical factors behind the spatial-temporal distribution of monthly PSD. Maps of all the months depict different sunshine hours that vary from region to region in Pakistan. The maximum difference in PSD was noticed between lofty mountains in the north and Indus Plains. In addition, the variation is phenomenal from January to August and vice versa. This sort of study based on spatial modeling is significant in Pakistan where we lack appropriate ground observed data of PSD.
文摘The spatial distribution of December temperature in Pakistan has been assessed by statistical method based on mean monthly data from 51 ground stations. The analysis is performed at decadal scale over the period of 1950-2000. December is one of the representative months of winter season in Pakistan, the country with subtropical location and complex rugged terrains, plateaus and plains. The results support a slight rising temperature trend in December. However, this change in temperature varies from region to region as well as from decade to decade and reflects a complicated spatial-temporal structure of temperature anomalies. The assessment shows that the temperature anomalies in different national territories at local scale do not follow the assumption that winter months are warming in northern hemisphere. Both the isothermal shift and temperature anomalies confirm that the mountainous areas of Pakistan face more temperature variability than plains.
文摘This study investigates the spatial-temporal variability of winter-spring (February-March-April) precipitation (WSP) in Pakistan over the period of 1961-2006 by making use of Empirical Orthogonal Function (EOF). The EOF analysis is based on ground observed data, reanalysis NCEP/NCAR of various geopotential heights and NOAA extended reconstructed sea surface temperatures (ERSST.v3). The significant modes are obviously variable at interannual time scale. The leading mode shows the node of maximum spatial variability anchored over the Peshawar Valley and Azad Kashmir (PVAK) axis. The pattern is associated with strong (weak) westerly jet over the Middle East. The pattern is also found closely associated with post monsoon and early winter El Nino. The Nino4 index can be an appropriate predictor for the first consistent single node pattern. The second significant mode represents a tripole pattern with areas of prominent variability over northwestern Pakistan, Quetta-Kalat region and northeastern Punjab. The pattern is found to be pro-NAO and in relation to this pattern, warm and stable SST anomalies appearing in the southern mid-latitudes of Indian and Atlantic basins.
文摘Empirical Orthogonal Function (EOF) was performed to investigate spatial variation in January precipitation over Pakistan using ground observed mean monthly precipitation data from 1950-2000 with a combination of gridded reanalysis data of sea level pressure (SLP) and 500 hPa geopotential height. The leading EOF mode captures 37.51% of the total variance and the spatial-temporal variability of January precipitation was consistent in the study area. The temporal changes explicate non-periodic interannual variability and some tacit interdecadal variation. The anomalous condition is more prominent along the western bordering mountains and northern high mountainous region than any other region of Pakistan. Based on results the study reveals spatial-temporal variation in January precipitation and possible links with global teleconnections located both in the proximity as well as in the remote areas from the study locus.
文摘By making use of Empirical Orthogonal Function (EOF) analysis the spatial and temporal variability was investigated in January over the period of 1950 to 2000 in Pakistan. The analysis is based on the combination of ground observed mean monthly temperature data and National Centre for Environmental Prediction (NCEP) reanalysis data of sea level pressure (SLP) and 500-hPa fields. The results reasonably reveal that the variation in January temperature have links with global teleconnections at SLP and 500-hPa pressure heights. The analysis shows variability at interannual to interdecadal time scale. The interannual variation is more prominent than the interdecadal signal of temperature anomaly. The simulated coefficient patterns show reasonable variation with regional detail from south (north) to north (south) in the study area. The study could be useful as baseline information for climate change studies in Pakistan.
文摘In this paper the month of August was assessed from 1950s-2000s based on the temperature data from 53 stations that covers almost all Pakistan. The temperature coefficient has been calculated by making use of linear regression. The results have been mapped that show considerable variability of temperature at decadal scale in different areas of Pakistan. The rugged terrains especially and rest of Pakistan generally reflect significant temperature variability in the decades of 1950s, 1960s, 1970s, 1980s, 1990s and 2000s as well. This change in temperature varies from region to region and decade to decade in Pakistan. The temperature anomalies achieved in the country are complicated at local level and did not follow the simple perception that winter months are warming and summer months are cooling. In this study, a geographical approach has been adopted to explain the spatial-temporal dynamics of temperature variation over the study period in Pakistan with emphasis on regional detail.
