Journal on Geoinformatics, Nepal
https://www.nepjol.info/index.php/NJG
<p>Annual publication of the Survey Department, Government of Nepal. Full text articles available.</p>
Survey Department Government of Nepal
en-US
Journal on Geoinformatics, Nepal
2717-5022
© Copyright reserved by Survey Department, Government of Nepal
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Web Mapping on Land Cover Change of Kathmandu, Lalitpur and Bhaktapur District
https://www.nepjol.info/index.php/NJG/article/view/50887
<p>Land cover change is rapidly following path of environmental degradation, imbalance on ecosystem. Kathmandu, Lalitpur and Bhaktapur district has experienced a very high trend of urbanization and land use land cover change. Mapping this trend is absolutely necessary for sustainable development as well as conservation of the ecosystem. While there are desktop applications for making this mapping and analysis possible, upgrading to the web is the best possible way in order to interact with public as well as much easier way of data visualization, data analysis and data dissemination. This paper portrays the design and implementation process along with the visualization of a WebGIS platform via thin client architecture. A dynamic web map portal has been developed concerning the land cover change of Kathmandu, Lalitpur and Bhaktapur district. Among the several Free Open Source server software, OpenGeo Suite has been adopted for the project because it has a robust and flexible design that allows us to reliably handle and publish geospatial data. PostgreSQL/PostGIS, QGIS, Geoserver, Leaflet, and Apache Tomcat has been utilized as the web server in this suite. A fully functional website has been developed in order to host the maps and its components. WMS layers has also been published using Geoserver and styled as can be displayed on the web map portal. Leaflet plugins has been used with the help of which different tools like Zoom, Pan, Full Screen View and Distance Calculator are made available on the portal.</p>
Raj Ghimire
Sandesh Dhakal
Mira Sapkota
Yogesh KC
Reshma Shrestha
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
10.3126/njg.v21i1.50887
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Status of Parcel Fragmentation in Nepal
https://www.nepjol.info/index.php/NJG/article/view/50885
<p>transfer, mortgage their own land. Parcel fragmentation is the division of a parcel into two or more parcels. This research was carried out to analyse the current status of parcel fragmentation in Nepal. According to the findings of this research, parcel fragmentation in Nepal is haphazard mainly focussing on urban and peri urban arears consequently parcel being irregular in shape & smaller in size and ultimately incrementing huge number of land owners with in fixed area. In the context of Nepal, factors that drive parcel fragmentation are cultural, social, legal, economical, frequent disasters, geographic variations, unmanaged migrations, haphazard land use planning amongst others. The uncontrolled and unmanaged parcel fragmentation in Nepal is the major challenge for land use planning and its implementation. Dense parcel fragmentation has created land related disputes. it is recommended that the government should reformulate and implement the proper land use policy as well as its supporting acts that encourage land<br>consolidation in agricultural zone and reducing haphazard parcel fragmentation in urban and peri urban areas.</p>
Dr. Bharat Singh Air
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
10.3126/njg.v21i1.50885
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Prospection of Potential Iron Deposit in Gandaki and Lumbini Province of Nepal Using Remote Sensing Technology
https://www.nepjol.info/index.php/NJG/article/view/50886
<p>Integrated remote sensing and Geographic Information System provides an aid to find presence of metallic and non-metallic minerals. This approach was used to explore Iron deposits in districts of Gandaki and Lumbini province of Nepal in which 8 districts were identified as the reserves of iron ores namely Nawalpur, Palpa, Baglung, Parbat, Syangja, Tanahu, Arghakhanchi and Gulmi. These districts fall under various geological formation such as Suntar formation, Melpani formation. These formations are found to be rich in metallic minerals. Remote Sensing (RS) and Geographic Information Systems (GIS) offers a cost effective and attractive strategy in mineral prospection, notably for a mineral exploration project. Landsat 8 satellite images, processed through band rationing method highlights the hydrothermal alterations and Iron Oxide containing region. False Color Composite and Principal Component Analysis method highlights sedimentary rocks. Each method exaggerates spectral signatures which highlights the surfaces by different colors indicating presence of iron ores. Lineaments are also extracted from Landsat images combining with Digital Elevation Model (DEM).<br>Lineaments are those structures that provide information about fault and fractures on the surface and helps to identify mineral deposition zones. The result produced through different RS techniques were introduced in GIS environment. Potential iron content region were identified by using Suitability analysis i.e. multi criteria decision analysis (MCDA). Map showing the potential iron ore deposit map was generated by integrating the results together reclassified into a common scale and overlaid with suitable weightage. Final output/map indicates the best possible sites for detailed study of iron ores. The study demonstrates the usefulness and effectiveness of remote sensing and GIS in iron and other mineral mapping.</p>
Sarthak Regmi
Bhishma Dhungana
Roshan Saud
Suyog Gautam
Pawan Thapa
Rupesh Bhandari
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
10.3126/njg.v21i1.50886
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Accuracy Assessment of UAV for Cadastral Application
https://www.nepjol.info/index.php/NJG/article/view/48745
<p>This study aims to produce accurate geospatial 3D data from unmanned aerial vehicle (UAV) images. An image of approx. 1 km2 area of the Banepa-10, Kabhrepalanchok district was captured using a DJI Mavic Pro drone. Pix4dmapper programs were used to generate the solution. The horizontal and vertical accuracies of the obtained UAV solution were computed by comparing the coordinates of 5 Ground Control Points (GCPs) with coordinates measured using the static DGPS observation method. The root mean square error (RMSE) was calculated during geo-referencing of Orthomosaic and obtained a value of 0.006.Mainly, three comparisons were made for parcels digitized from the Orthomosaic image w.r.t to Total Station and Tape measurement ; Area, Perimeter and Centroid Position. Cadastral survey using Total station, UAV and Tape measurement were confirmed to be comparable in terms of accuracy, completeness, and expenditure of time. From the result of this study, the area as well perimeter of parcels obtained from georeferenced orthorectified UAV image seems to be closer with the area as well as perimeter from total station survey compared to those obtained from tape measurement. If the area is pre-demarcated and clearly visible in Orthomosaic image, then information can efficiently be gained. Some ambiguity could be seen in the comparison of digitized parcels whose boundary information was not clear.</p>
Gyanendra Kumar Bist
Prabesh Shrestha
Girija Pokhrel
Copyright (c) 2022 Survey Department
2022-12-28
2022-12-28
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10
10.3126/njg.v21i1.48745
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Analyzing Water Poverty Components Using Geospatial Tools: Resource and Environmental Constraint in Kathmandu District
https://www.nepjol.info/index.php/NJG/article/view/48749
<p>This current paper examines water poverty situation in Kathmandu district in terms of water resource and environment constraints. Integrated methodology was adopted for the study. Water source sample survey was carried out using GPS tool. Study area comprised total of 13 water sample sites. Household questionnaire survey was carried out for water poverty mapping and analysis. Resource component of water poverty comprised indicators, namely seasonal variation in water availability, water supply frequency and groundwater recharge potential. The environment constraint component comprised water quality rate of soil erosion and topographic wetness index. The result show that the average calculated value of water resource limitation component is 6.31 and out of 13 studied communities, 7 communities fall below average. It is found that environmental constraint is less associated with urban housing density. It is found that environmental constraint is less associated with urban housing density. The average calculated value of environmental component is 3.43 and out of 13 studied communities, 8 communities fall below average. Spatial variability in water poverty is prominent and highest water poverty is found in urban cores. Communities with lower water poverty are found in peri-urban location near the foothills. The average calculated value of water poverty is 9.74 and out of 13 studied communities, 9 communities fall below the average. The study concluded that water poverty index and resultant map is a very effective tool to visualize the distribution of water poverty at local spatial scale and to present the complex nature of water poverty.</p>
Shobha Shrestha
Chhabi Lal Chidi
Copyright (c) 2022 Survey Department
2022-12-28
2022-12-28
11
21
10.3126/njg.v21i1.48749
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Detecting Surface Displacement in Kathmandu Valley with Persistent Scatterer Interferometry
https://www.nepjol.info/index.php/NJG/article/view/50878
<p>Kathmandu Valley has been susceptible to surface displacement due to natural as well as anthropogenic causes since a long time. Previous studies till 2017 suggest that displacement (specially subsidence) with rates of several centimeters per year have occurred in the Kathmandu Valley indicating uncontrolled groundwater withdrawal as the major cause. Owing to the history of surface displacement, this study aims at detecting the nature of land subsidencein Kathmandu for years: 2017 (18th January to 26th December) and 2019 (2nd January to 28th December) based on Persistent Scatterer Interferometry (PSI) technique using Synthetic Aperture Radar (SAR) datasets from Sentinel 1. PSI is able to detect persistently backscattering targets and evaluate respective displacements from the backscattered signal. The results of 2017 and 2019 revealed significant displacement of -100.54mm and -129.19mm along Line Of Sight (LOS) of radar during the study period at Baluwatar and Lazimpat area of Kathmandu district respectively. Similarly, New Baneshwor, Bode and Imadol exhibited a substantial displacement of -88.81mm,-103.55mm, -127.35mm respectively for year 2019.</p>
Stallin Bhandari
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
23
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10.3126/njg.v21i1.50878
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Landslide Susceptibility Mapping Using Machine Learning Approach: A Case Study of Baglung District, Nepal
https://www.nepjol.info/index.php/NJG/article/view/50880
<p>Assessment of Landslide Susceptibility Map (LSM) is crucial to the reduction of risk of the landslides. This paper focusses on modelling LSM using two different machine learning algorithms namely Random Forest (RF), and Classification and Regression Tree (CART). Ten landslide causative factors along with an inventory of landslides containing 89 recent and historic landslide points, and 90 randomly generated nonlandslide points were used to prepare a susceptibility map. The study area; Baglung district is located in the Gandaki province of Nepal, a highly landslide susceptible zone. Frequency ratio (FR) of each class of conditioning factors were calculated. FR values of landslide and non-landslide points were extracted from normalized FR classified raster. The extracted FR values of each point (landslide and non-landslide) was randomly split into training (70%) and testing (30%) samples which were used for training and testing the model. The performance of each algorithm was evaluated using receiver operating characteristics (ROC) curves in combination with area under the curve (AUC) and error matrix. The AUC results introduced success rate of 1 and 0.88 for RF and CART respectively. Also, the rates of prediction were 0.86 and 0.96 for RF and CART respectively. Similarly, RF and CART showed accuracy of 0.88 and 0.83 from confusion matrix. Therefore, the RF algorithm was superior to CART in identifying the regions at risk for future landslides in the study area. The outcomes of this study is useful and essential for the government, planners, researchers, decision makers and general landuse planners.</p>
Ashish Chalise
Bipin Sinjali
Tejendra Kandel
Janak Parajuli
Sanjeevan Shrestha
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
31
41
10.3126/njg.v21i1.50880
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Online Service Delivery in Survey Offices of Nepal
https://www.nepjol.info/index.php/NJG/article/view/50881
<p>The Survey Department of Nepal has started transformation of cadastral management from offline to centralized online system. This has enabled the department to provide the online services to the clients beyond the physical boundaries of Survey Offices. This paper elaborates the present status of online service delivery in different survey offices based on recent policy, institutions and their applications. Data analysis shows that Nepal Land Information System (NeLIS) supports basic norms and values of online service delivery effectively and has become a major milestone in the e-land administration. The provision of assigning different roles and sections inside a survey office has made the system more secure, reliable and responsive. Recently, directives of digital land surveying, mapping and administration for public service delivery have been formulated to address the legal aspect of service delivery. The provision of online application for map, field book and plot register print through https://www.merokitta. dos.gov.np has simplified the working procedure for general public and institutional users too. The expansion of this system in more survey offices along with additional and more advanced features are necessary. Similarly, legal provision of data sharing between Land Records Information Management System (LRIMS) and NeLIS in a meaningful way is also essential in the days to come. </p>
Amrit Karmacharya
Grishma Pradhan
Poshan Niraula
Prakash Ghimire
Sunil Prasad Rajbhandari
Suresh Manandhar
Subash Bhandari
Susheel Dangol
Copyright (c) 2022 Survey Department, Government of Nepal
2022-12-28
2022-12-28
43
50
10.3126/njg.v21i1.50881