scholarly journals Geospatial Analysis of Indus River Meandering and Flow Pattern from Chachran to Guddu Barrage, Pakistan

2018 ◽  
Vol 9 (2) ◽  
pp. 67-74
Author(s):  
Danish Raza ◽  
Aqeel Ahmed Kidwai
Keyword(s):  
Flow Pattern ◽  
Satellite Imagery ◽  
Information Science ◽  
Thematic Mapper ◽  
Geographical Information ◽  
Surface Model ◽  
Indus River ◽  
Natural Factor ◽  
Model Builder ◽  
Landsat Satellite

Natural and anthropogenic influence affects directly ecologic equilibrium and hydro morphologic symmetry of riverine surroundings. The current research intends to study the hydro morphologic features (meanders, shape, and size) of Indus River, Pakistan by using remote sensing (RS) and geographical information science (GIS) techniques to calculate the temporal changes. Landsat satellite imagery was used for qualitative and analytical study. Satellite imagery was acquired from Landsat Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+) and Operational Land Imager (OLI). Temporal satellite imagery of study area was used to identify the variations of river morphology for the years 1988,1995,2002,2009 and 2017. Research was based upon the spatial and temporal change of river pattern with respect to meandering and flow pattern observations for 30 years’ temporal data with almost 7 years’ interval. Image preprocessing was applied on the imagery of the study area for the better visualization and identification of variations among the objects. Object-based image analysis technique was performed for better results of a feature on the earth surface. Model builder (Arc GIS) was used for calculation of temporal variation of the river. In observation many natural factor involves for pattern changes such as; floods and rain fall. The object-oriented classification was applied for land use/land cover (LULC) features of the study area for the years 1988 and 2017 and abrupt change observed. Overall, 1988 to 2017 the Indus River in the study area has changed its path and pattern.

scholarly journals The Spatio-Temporal Evolution of River Island Based on Landsat Satellite Imagery, Hydrodynamic Numerical Simulation and Observed Data

2018 ◽  
Vol 10 (12) ◽  
pp. 2046 ◽  
Author(s):  
Haiyun Shi ◽  
Yuhan Cao ◽  
Changming Dong ◽  
Changshui Xia ◽  
Chunhui Li
Keyword(s):  
Numerical Simulation ◽  
Temporal Evolution ◽  
Thematic Mapper ◽  
Sediment Discharge ◽  
Natural Factor ◽  
River Islands ◽  
Island Evolution ◽  
Spatio Temporal ◽  
Landsat Satellite ◽  
Changing Rate

A river island is a shaped sediment accumulation body with its top above the water’s surface in crooked or branching streams. In this paper, four river islands in Yangzhong City in the lower reaches of the Yangtze River were studied. The spatio-temporal evolution information of the islands was quantitatively extracted using the threshold value method, binarization model, and cluster analysis, based on Thematic Mapper (TM) and Enhanced Thematic Mapper+ (ETM+) images of the Landsat satellite series from 1985 to 2015. The variation mechanism and influencing factors were analyzed using an unstructured-grid, Finite-Volume Coastal Ocean Model (FVCOM) hydrodynamic numerical simulation, as well as the water-sediment data measured by hydrological stations. The annual average total area of these islands was 251,224.46 m2 during 1985–2015, and the total area first increased during 1985–2000 and decreased later during 2000–2015. Generally, the total area increased during these 30 years. Taipingzhou island had the largest area and the biggest changing rate, Xishadao island had the smallest area, and Zhongxinsha island had the smallest changing rate. The river islands’ area change was influenced by river runoff, sediment discharge, and precipitation, and sediment discharge proved to be the most significant natural factor in island evolution. River island evolution was also found to be affected by both runoff and oceanic tide. The difference in flow-field caused silting up in the Leigongdao Island and the head of Taipingzhou Island, and a serious reduction in the middle and tail of Taipingzhou Island. The method used in this paper has good applicability to river islands in other rivers around the world.

scholarly journals Exploring Land use and Land cover change in the mining areas of Wa East District, Ghana using Satellite Imagery

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Prosper Laari Basommi ◽  
Qingfeng Guan ◽  
Dandan Cheng
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Geographical Information ◽  
Kappa Statistics ◽  
Image Differencing ◽  
Mining Areas ◽  
Land Cover Dynamics ◽  
Change Matrix ◽  
Landsat Satellite

AbstractSatellite imagery has been widely used to monitor the extent of environmental change in both mine and post mine areas. This study uses Remote sensing and Geographical Information System techniques for the assessment of land use/land cover dynamics of mine related areas in Wa East District of Ghana. Landsat satellite imageries of three different time periods, i.e., 1991, 2000 and 2014 were used to quantify the land use/cover changes in the area. Supervised Classification using Maximum Likelihood Technique in ERDAS was utilized. The images were categorized into five different classes: Open Savannah, Closed Savannah, Bare Areas, Settlement and Water. Image differencing method of change detection was used to investigate the changes. Normalized Differential Vegetative Index valueswere used to correlate the state of healthy vegetation. The image differencing showed a positive correlation to the changes in the Land use and Land cover classes. NDVI values reduced from 0.48 to 0.11. The land use change matrix also showed conversion of savannah areas into bare ground and settlement. Open and close savannah reduced from 50.80% to 36.5% and 27.80% to 22.67% respectively whiles bare land and settlement increased. Overall accuracy of classified 2014 image and kappa statistics was 83.20% and 0.761 respectively. The study revealed the declining nature of the vegetation and the significance of using satellite imagery. A higher resolution satellite Imagery is however needed to satisfactorily delineate mine areas from other bare areas in such Savannah zones.

scholarly journals Semantics of Voids within Data: Ignorance-Aware Machine Learning

2021 ◽  
Vol 10 (4) ◽  
pp. 246
Author(s):  
Vagan Terziyan ◽  
Anton Nikulin
Keyword(s):  
Spatial Data ◽  
Information Science ◽  
Nearest Neighbor ◽  
Geographical Information ◽  
Two Dimensional ◽  
Prototype Selection ◽  
Data Space ◽  
Important Concern ◽  
Traditional Classification ◽  
Nearest Neighbor Classifiers

Operating with ignorance is an important concern of geographical information science when the objective is to discover knowledge from the imperfect spatial data. Data mining (driven by knowledge discovery tools) is about processing available (observed, known, and understood) samples of data aiming to build a model (e.g., a classifier) to handle data samples that are not yet observed, known, or understood. These tools traditionally take semantically labeled samples of the available data (known facts) as an input for learning. We want to challenge the indispensability of this approach, and we suggest considering the things the other way around. What if the task would be as follows: how to build a model based on the semantics of our ignorance, i.e., by processing the shape of “voids” within the available data space? Can we improve traditional classification by also modeling the ignorance? In this paper, we provide some algorithms for the discovery and visualization of the ignorance zones in two-dimensional data spaces and design two ignorance-aware smart prototype selection techniques (incremental and adversarial) to improve the performance of the nearest neighbor classifiers. We present experiments with artificial and real datasets to test the concept of the usefulness of ignorance semantics discovery.

scholarly journals Mapping and Monitoring Erosion-Accretion in an Alluvial River Using Satellite Imagery – The River Bank Changes of the Padma River in Bangladesh

2018 ◽  
Vol 37 (3) ◽  
pp. 87-95 ◽  
Author(s):  
Mohammad Maruf Billah
Keyword(s):  
Satellite Imagery ◽  
Bank Erosion ◽  
River Bank ◽  
River Bank Erosion ◽  
Island Area ◽  
River Bed ◽  
Drastic Increase ◽  
Padma River ◽  
Landsat Satellite ◽  
The Right

Abstract The Padma river is widely known for its dynamic and disastrous behaviour, and the river has been experiencing intense and frequent bank erosion and deposition leading to the changes and shifting of bank line. In this paper, a time series of Landsat satellite imagery MSS, TM and OLI and TIRS images and are used to detect river bank erosion-accretion and bank line shifting during the study period 1975–2015. This study exhibits a drastic increase of erosion and accretion of land along the Padma river. The results show that from 1975 to 2015, the total amount of river bank erosion is 49,951 ha of land, at a rate of 1,249 ha a−1 and the total amount of accretion is 83,333 ha of land, at a rate of 2,083 ha a−1. Throughout the monitoring period, erosion-accretion was more pronounced in the right part of the river and bank line had been shifting towards the southern direction. The paper also reveals that the total area of islands had been increased significantly, in 2015 there was about 50,967 ha of island area increased from 20,533 ha of island area in 1975, and the results evidence consistency of sedimentation in the river bed.

Geographical Information Science and Maps

Cartography ◽  
2020 ◽  
pp. 1-21
Author(s):  
Menno-Jan Kraak ◽  
Ferjan Ormeling
Keyword(s):  
Information Science ◽  
Geographical Information

scholarly journals EXPRESSION AND ORGANIZATION OF GEOGRAPHIC SPATIAL RELATIONS BASED ON TOPIC MAPS

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 1257-1261
Author(s):  
H. J. Liang ◽  
H. Wang ◽  
T. J. Cui ◽  
J. F. Guo
Keyword(s):  
Information Science ◽  
Spatial Database ◽  
Spatial Relation ◽  
Spatial Relations ◽  
Geographical Information ◽  
Knowledge Network ◽  
Effective Management ◽  
Topic Maps ◽  
Complex Knowledge ◽  
Topic Map

Spatial Relation is one of the important components of Geographical Information Science and Spatial Database. There have been lots of researches on Spatial Relation and many different spatial relations have been proposed. The relationships among these spatial relations such as hierarchy and so on are complex and this brings some difficulties to the applications and teaching of these spatial relations. This paper summaries some common spatial relations, extracts the topic types, association types, resource types of these spatial relations using the technology of Topic Maps, and builds many different relationships among these spatial relations. Finally, this paper utilizes Java and Ontopia to build a topic map among these common spatial relations, forms a complex knowledge network of spatial relations, and realizes the effective management and retrieval of spatial relations.

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