Flood Inundation Mapping using Multi-temporal Datasets

Floods are considered the most frequent natural catastrophic events, which effect the human lives and infrastructure. Flooding causes tremendous loss of life and property every year. We used satellite imagery to map flood inundation in Jehlum river for the both pre and post flood scenarios and classified it into major landuse including vegetation, water body, buildup land and the bare soil. The results show that about 40% area was agricultural land, 29% was bare soil, 16% was build up land and 12% area was noted as water body.The categorization of the post flood areas, showed that flood has destroyed the buildup and agriculture lands.The superimposition proposed that agricultural land was 43% before the flood which reduced up to 31%,the normal flow of water was 12% before flood which was increased up to 33%, build up area and bare soil was also decreased up to 10% and 25% respectively. Remote sensing and GIS proved efficient in convergence of optimistic results. Full Tex

Flood Inundation Mapping using Multi-temporal Datasets

Floods are considered the most frequent natural catastrophic events, which effect the human lives and infrastructure. Flooding causes tremendous loss of life and property every year. We used satellite imagery to map flood inundation in Jehlum river for the both pre and post flood scenarios and classified it into major landuse including vegetation, water body, buildup land and the bare soil. The results show that about 40% area was agricultural land, 29% was bare soil, 16% was build up land and 12% area was noted as water body.The categorization of the post flood areas, showed that flood has destroyed the buildup and agriculture lands.The superimposition proposed that agricultural land was 43% before the flood which reduced up to 31%,the normal flow of water was 12% before flood which was increased up to 33%, build up area and bare soil was also decreased up to 10% and 25% respectively. Remote sensing and GIS proved efficient in convergence of optimistic results. Full Tex

Appraisal of Trans Indus, Marwat-Khisor and Bhittani Ranges Thrusting through Geo-spatial Techniques

Himalayan mountain belt was created by the Indo–Eurasian collision. The length of this seismically active mountain belt is almost 2500 km. Southern partition of this zone is marked by the main frontal thrust. We computed the isobase, relative relief, incision, vertical dissection and drainage density maps of the study site. Drainage density is inversely proportional to the rest of computed parameters. Drainage density is less where the incision/deep cutting is high. Pezu and north western parts of the study site are observed vulnerable to tectonic activity and high risks. These sites are the adjoining parts of active faults. The rates of morphological changes and the combination of stripping processes are determined through Surface dynamics maps (SDM). Although it is a handy tool used to evaluate erosion conditions of sags or sub basins. Remote sensing and GIS techniques proved efficient for appraisal of thrust in Marwat Kishore and Bhittani ranges. Full Tex

Generation of Digital Surface Model (DSM) USING UAV/ QUADCOPTER

Satellite imageries are being used as primary source of information due to their vast coverage and high temporal resolution. Unnamed Aerial Vehicle (UAV) is being used these days because of its accuracy, autonomous flights, cost effectiveness and rapid overview of data. UAV provides a fully or partially autonomous image acquiring platform which is devoid of any manned flight controller. In this research Phantom 3 advanced Quadcopter was used for an image acquisition plan for generation of Digital Surface Model (DSM). Two designs were drawn through this workflow for the reconstruction of Department of Space Science and technology in university of Punjab. For the first design 3D quadcopter is hovered at the height of 120 feet (37 meters) which covered an area of 83 x 130 meter, frontal and sidewise overlapping is 80%, and the camera is kept at an angle of 70° for the double grid type pattern. For second mission design a circular flight is taken to obtain images at the height of 27meters with coverage area of (107 x 106) meter, 45° camera angle and 10° circular angle. For reconstruction of urban area, quadcopter is hovered at relatively greater height of 210 feet (64 meters), following the double grid pattern. In order to attain desired GST, the camera is flown at a constant height over the Area of Interest (AOI). The highly overlapped images obtained using Phantom 3, advanced Quadcopter are then processed using Pix4d software for processing of images. Initially, the common points of adjacent images are matched automatically. After matching similar points, additional geographic information of coordinates and z-value of elevation associated with it is generated in 3D space by sparse point cloud. Then a detailed 3D model along the precise geo location is obtained using dense point cloud. A study surface area and its texture are generated using 3D mesh. Finally, a desired 3D surface model is accurately generated containing desired AOI. The results are analyzed using UAV imagery to generate high resolution DSM. DSM for construction of urban area of Department of Space Science was generated at a very high resolution of 3.55cm and 1.8cm respectively. The accuracy of geo locations can be improved by using GPS loggers or by taking the GCPs. It is suggested by many authors that 3D surface model of reconstruction of building is quite accurate geographically and geometrically, after the comparison of bundle block adjustments, Ground Sampling Distance (GSD) value, 3D matching and average point cloud density of DSM. Thus, the 3D surface models are used in parameters, features extraction and estimation of values including depth and elevation values, in texturing, 3D data collection for 3D visualizations, 3D roof tops and building facades and contour maps and orthodox photos.  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