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

Evaluation of catastrophic global warming due to coal combustion

Coal is a carbon containing non-renewable fossil fuel and one of the major contributors of climate change and global warming. We used TANSO FTS instrument in order to obtain the level of atmospheric carbon dioxide through datasets obtained from GOSAT satellite. GIOVANNI was also used to obtain atmospheric concentration of various gases. Burning of coal causes emission of greenhouse gases (GHG) and black carbon (BC) in atmosphere which are responsible for nearly 0.3°C of 1°C rise in temperature. The annual average value of carbon emission for the year 2010 and 2019 is 388.4 ppm and 409 ppm respectively. Since the pre-industrial times CO2 concentrations have increased up to100 PPM (36%) in the last two and a half centuries (250 years).In South Asia Dhaka has the worst quality of air as CO2 concentration (6.7%) is higher than the country’s GDP (5.25%) and energy consumption (4.77%). While an increasing trend GHG has been observed in Lahore up to 5.5 %. This study concludes that the high concentration of carbon dioxide in atmosphere is responsible for average rise of 1.2 °C temperature annually. This temperature rise can lead to adverse climatic conditions i.e., melting of glaciers which will consequently rise the sea level various landmasses may disappear by 2050. Full Tex

Evaluation of catastrophic global warming due to coal combustion

Coal is a carbon containing non-renewable fossil fuel and one of the major contributors of climate change and global warming. We used TANSO FTS instrument in order to obtain the level of atmospheric carbon dioxide through datasets obtained from GOSAT satellite. GIOVANNI was also used to obtain atmospheric concentration of various gases. Burning of coal causes emission of greenhouse gases (GHG) and black carbon (BC) in atmosphere which are responsible for nearly 0.3°C of 1°C rise in temperature. The annual average value of carbon emission for the year 2010 and 2019 is 388.4 ppm and 409 ppm respectively. Since the pre-industrial times CO2 concentrations have increased up to100 PPM (36%) in the last two and a half centuries (250 years).In South Asia Dhaka has the worst quality of air as CO2 concentration (6.7%) is higher than the country’s GDP (5.25%) and energy consumption (4.77%). While an increasing trend GHG has been observed in Lahore up to 5.5 %. This study concludes that the high concentration of carbon dioxide in atmosphere is responsible for average rise of 1.2 °C temperature annually. This temperature rise can lead to adverse climatic conditions i.e., melting of glaciers which will consequently rise the sea level various landmasses may disappear by 2050. Full Tex

Geo-Spatial Dynamics of Snow Cover and Hydro-Meteorological Parameters for Gilgit Balistan, Pakistan

Snow cover dynamism is an important component of the UIB’s (Upper Indus Basin) hydrodynamics in the context of snow building up and reduction occurring seasonally.  This study incorporates investigation into the dynamics of snow covers in relation to the hydrodynamics of the region. Data acquired through remotely sensed MODIS (Moderate Resolution Imaging Spectro-Radiometer) satellite for the duration of 20 years from 2000-2020, together with additional variables of hydrometeorology was utilized in the assessment of spatial and temporal fluctuation in snow-covered areas of Gilgit Baltistan (GB). The snow cover analysis was done temporally with an evaluation of its relationship with the hydro-meteorological variables through the application of Pearson correlation, Principal Component Analysis (PCA), and basin-wise zonal analysis. The investigation revealed that glacial ice covered an area of 25 to 50% and that the SCA (Snow Covered Area) may expand to 80 to 90% of the region on the amassment of snow in the snowy season. Trends from hydro-meteorological correlativity demonstrate a greatly considerable proportionality of R = 0.78, between the maximal and minimal temperature zones and river drains. However, no noticeable correlativity was found between precipitation and river drains (R = -0.04). For the region of Hunza, a statistically important negative correlativity was observed between the river drains and precipitation i.e., R = –0.83. The minus factor indicates an increase in river drainage with increased melting of snow covers due to high temperatures. This investigation infers a close association of river runoffs of the GB area with its snow cover dynamism. Discharge of rivers is a consequence of melting snow in the basin due to rising temperature and thus it speeds up at the beginning of summers mainly during April and May. Snow and ice start melting from the bottom and then reaches the top areas that have greater upstanding glacial mass

Geo-Spatial Dynamics of Snow Cover and Hydro-Meteorological Parameters for Gilgit Balistan, Pakistan

Snow cover dynamism is an important component of the UIB’s (Upper Indus Basin) hydrodynamics in the context of snow building up and reduction occurring seasonally.  This study incorporates investigation into the dynamics of snow covers in relation to the hydrodynamics of the region. Data acquired through remotely sensed MODIS (Moderate Resolution Imaging Spectro-Radiometer) satellite for the duration of 20 years from 2000-2020, together with additional variables of hydrometeorology was utilized in the assessment of spatial and temporal fluctuation in snow-covered areas of Gilgit Baltistan (GB). The snow cover analysis was done temporally with an evaluation of its relationship with the hydro-meteorological variables through the application of Pearson correlation, Principal Component Analysis (PCA), and basin-wise zonal analysis. The investigation revealed that glacial ice covered an area of 25 to 50% and that the SCA (Snow Covered Area) may expand to 80 to 90% of the region on the amassment of snow in the snowy season. Trends from hydro-meteorological correlativity demonstrate a greatly considerable proportionality of R = 0.78, between the maximal and minimal temperature zones and river drains. However, no noticeable correlativity was found between precipitation and river drains (R = -0.04). For the region of Hunza, a statistically important negative correlativity was observed between the river drains and precipitation i.e., R = –0.83. The minus factor indicates an increase in river drainage with increased melting of snow covers due to high temperatures. This investigation infers a close association of river runoffs of the GB area with its snow cover dynamism. Discharge of rivers is a consequence of melting snow in the basin due to rising temperature and thus it speeds up at the beginning of summers mainly during April and May. Snow and ice start melting from the bottom and then reaches the top areas that have greater upstanding glacial mass

Estimation of relation between moisture content of soil and reflectivity index using GPS signals

The irrigation system throughout the world is affected by the variations in water content due to different soil structure, textures and climate change. The irrigation system supplies sufficient water to the agricultural fields in order to fulfill the prerequisites. The measurement of soil moisture content (62%) is crucial for precision irrigation and sustainable agricultural system. Site specific agricultural system was utilized to overcome all issues related to soil water moisture contents in the paddock. Smart technology was utilized to record GPS signals utilizing the signals reflected on the Earth’s surface. The GPS was utilized to analyze dielectric soil properties and moisture content in proposed areas. The main objective of this study was to determine water content with stimulus soil type, ground cover and compaction on the irrigation system by utilizing the GPS-based techniques. The result indicated positive relation between soil moisture content and the signals reflected on the earth surface. All factors affecting the irrigation system were not related to the reflected signals and did not affect the soil moisture content. The reflectivity was not reduced by ground cover. Whereas, comparative relationship was found between soil moisture content and reflectivity index i.e. soil moisture contents were increased with reflectivity index up to 0.02 %. The results showed that GPS signals system have significant impact on estimation of soil moisture content in precise irrigation system. Full Tex

Appraisal of Spatiotemporal Variations in Snow Cover Dynamics using Geospatial Techniques: A paradigm from Gilgit-Baltistan, Pakistan

Snow and glaciers in the mountain ranges of Hindu-Kush, Karakoram, and Himalayas (HKH), are supposed to be shrinking. Consequently, serious significances occur in respect of water accessibility for inhabitants of down streams. This investigation is an effort o identify the temporal variation in snow covers of Gilgit Baltistan (GB), northern Pakistan. For the calculation of the Normalized Difference Snow Index (NDSI) and estimation of snow-covered area (SCA), MODIS images for the period of 2000 to 2020 were used. Hunza, Astore, Gilgit, Diamir, Shyok, Ghanche, Skardu and Shigar are major sub-basins lying in GB with Hunza and Skardu being the mostly glaciated areas. Annual fluctuation in snow cover within GB was 10 to 80%. In accumulation season, from December to February, snow cover was almost 80% while in melting season, from July to September this area was reduced to 65-75%. The maximum and minimum Snow-Covered Area (SCA) detected in 2009 was almost 57687.85 km2 and 12083.40 km2 respectively. These results show fluctuations in SCA within the time duration of the last two decades. Full Tex

Appraisal of Spatiotemporal Variations in Snow Cover Dynamics using Geospatial Techniques: A paradigm from Gilgit-Baltistan, Pakistan

Snow and glaciers in the mountain ranges of Hindu-Kush, Karakoram, and Himalayas (HKH), are supposed to be shrinking. Consequently, serious significances occur in respect of water accessibility for inhabitants of down streams. This investigation is an effort o identify the temporal variation in snow covers of Gilgit Baltistan (GB), northern Pakistan. For the calculation of the Normalized Difference Snow Index (NDSI) and estimation of snow-covered area (SCA), MODIS images for the period of 2000 to 2020 were used. Hunza, Astore, Gilgit, Diamir, Shyok, Ghanche, Skardu and Shigar are major sub-basins lying in GB with Hunza and Skardu being the mostly glaciated areas. Annual fluctuation in snow cover within GB was 10 to 80%. In accumulation season, from December to February, snow cover was almost 80% while in melting season, from July to September this area was reduced to 65-75%. The maximum and minimum Snow-Covered Area (SCA) detected in 2009 was almost 57687.85 km2 and 12083.40 km2 respectively. These results show fluctuations in SCA within the time duration of the last two decades. Full Tex

Analisis Perbedaan Hasil Perekaman Garis Pantai di Pesisir Tuban menggunakan Aplikasi GPS Smartphone dan GPS

Kebutuhan pengukuran untuk penentuan posisi sudah sangat diperlukan. namun GPS terlalu mahal untuk proyek berbiaya rendah atau kelas konsumen. Smartphone telah menjadi alat umat manusia di mana-mana, karena jutaan orang sekarang menjalani hari-hari mereka dengan komputer kecil berkemampuan GPS di tangan atau saku mereka. Kedua perangkat ini memiliki perbedaan harga yang cukup besar. Oleh karena itu diduga ada perbedaan hasil perekaman garis pantai yang dilakukan menggunakan GPS dan GPS Smartphone. Penelitian ini dilakukan dengan membandingkan tingkat akurasi perekaman garis pantai pada GPS Smartphone dengan GPS, sebagai bahan pertimbangan untuk dapat menggunakan GPS Smartphone sebagai alat untuk perekaman data garis pantai menggantikan GPS untuk dalam penelitian. Penelitian ini dilakukan di Kabupaten Tuban merupakan Kabupaten yang berada di Jawa Timur. Kabupaten tuban berada di Pulau Jawa bagian utara yang berbatasan langsung dengan Laut Jawa. Garis pantai yang dimiliki oleh Kabupaten Tuban sepanjang 65 km dan tutupan lahan yang bervariasi Penelitian dilaksanakan pada 31 Maret 2022 di kawasan pemukiman Desa Socorejo, tutupan lahan kosong di Desa Tasikharjo, Desa Kaliuntu dengan pantai dengan Batasan tembok laut dan tutupan lahan tambak, dan tutupan lahan vegetasi di Desa Kajenom, Kecamatan Jenu, Kabupaten Tuban, Jawa Timur. Data yang digunakan adalah data hasil perekaman menggunakan GPS pada tiap perangkat yang selanjutnya dilakukan analisis dengan metode DSAS (Digital Shoreline Analysis System) menggunakan perhitungan NSM (Net Shoreline Movement) yang dilanjutkan oleh analisis nilai rata-rata, grafik serta standar eror. Samsung A50 memiliki rata-rata sebesar 1.49 meter dengan Garmin Montana 650 dan sebesar 1.99 meter dengan GPS Map 585. Xiaomi Redmi 9A memiliki rata-rata sebesar 2.07 meter dengan Garmin Montana 650 dan sebesar 1.87 meter dengan GPS Map 585. Samsung A50 memiliki standar eror sebesar 0.19 dengan Garmin Montana 650 dan sebesar 0.17 dengan GPS Map 585. Xiaomi Redmi 9A memiliki standar errro sebesar 0.16 dengan Garmin Montana 650 dan sebesar 0.14 dengan GPS Map 585.. Standar ketelitian posisi yang diberikan oleh survei GPS berdasarkan SNI 19-6724-2002 untuk posisi absolut tidak lebih dari 8 meter sampai 10 meter dan nilai eror Idealnya mendekati nol

Riverbank Erosion & Consequent Land Settlement Issues: A Case of River Chenab, District Hafizabad

When calamity strikes, it causes damage but it also provides opportunities for newer learnings opportunities and better preparedness to combat menace. Pakistan is agrarian economy and comprises fertile plains. According to Pakistan Bureau of Statistics, agriculture contributes to 24 percent of national Gross Domestic Product. Agriculture is dependent on water needs, met through water channels fed by rivers originating mostly from glacial sources existing in northern part of the country. The country hosts five major rivers, namely Indus Jhelum, Chenab, Ravi, and Sutlej. The dendritic river patterns follow gravity flow causing frequent morphological changes and riverbank erosion is the most significant phenomenon which acts as hazard for farming communities in terms of loss of shelter, livelihood, and landholdings. An in-time identification of the issue is the real concern nowadays. Presently, different tools are available for instant interpretation of riverbank erosion like Remote Sensing (RS) and Geographical Information System (GIS), which are not only good for instant identification but also helpful for precise estimation of historical losses. Landsat images for years 2009, 2013, and 2017 have used to make an initial assessment of erosion hotspots. High-resolution satellite imagery from Google Earth is also used for meticulous analysis. The analysis shows that beyond other factors, average riverbank displacement rate due to erosion directly depends on rise in water levels. The study provides systematic bases to estimate the losses precisely. The study is useful for damages assessment of land and livelihood to device relief packages for the affected communities. The study also builds the capacity in resolving land settlement issues consequent to the riverbank erosion phenomenon. Full Tex