Development of a Global Built-Up Area Map Using ASTER Satellite Images and Existing GIS Data

2014 ◽  
pp. 121-142
Author(s):  
Hiroyuki Miyazaki ◽  
Xiaowei Shao ◽  
Koki Iwao ◽  
Ryosuke Shibasaki
Keyword(s):  
Satellite Images ◽  
Gis Data

scholarly journals PROJECTING CHANGES IN COASTAL MORPHOLOGY BY SATISFYING PREREQUISITE CONDITIONS OF SLAMM SOFTWARE IN CONTEXT OF SUNDARBAN

2018 ◽  
Vol XLII-5 ◽  
pp. 503-510
Author(s):  
A. Chakraborty ◽  
A. Basu ◽  
N. Mukherjee ◽  
N. Chaudhary ◽  
K. Chakraborty
Keyword(s):  
Sea Level ◽  
Satellite Images ◽  
Morphological Changes ◽  
Satellite Image ◽  
Primary Source ◽  
Vegetation Coverage ◽  
Coastal Morphology ◽  
Rs And Gis ◽  
Gis Data ◽  
Final Output

<p><strong>Abstract.</strong> RS and GIS data have been acquired as a primary source for study. The satellite images mainly show the temporal changes in coastal morphology and shorelines of the area. The main aim is to analyze the applicability of a platform called SLAMM or Sea Level Affecting Marshes Model to predict the changes related to the different kinds of ecosystems in the Sundarbans with the eustatic rise in sea level. A satellite image (LANDSAT) of the year 2001 of the study area was used as a base map. Using this base map, an attempt has been made to forsee the morphological changes to the ecosystems up to the year 2016 using SLAMM (Payo, et al., 2016). It has investigated the changes in coastal scenario and also its effect on the vegetation and other factors of sundarban. The results indicate that tidal flats are increasing along with the year thus degrading the ocean beach and the amount of vegetation coverage, especially that of mangroves which has degraded between these years and may predict its changes up till the end of 21st century. The SLAMM software will also show the accuracy depending on the calibration and SLR depending on MSL and MTL to that of the real world scenario. Hence the final output will facilitate us with certain future scope which may help for better and bigger approaches of study towards the development of coastal management.</p>

An Efficient Method for Road Tracking from Satellite Images Using Hybrid Multi-Kernel Partial Least Square Analysis and Particle Filter

2017 ◽  
Vol 26 (11) ◽  
pp. 1750181 ◽  
Author(s):  
K. Madhan Kumar ◽  
A. Velayudham ◽  
R. Kanthavel
Keyword(s):  
Particle Filter ◽  
Satellite Images ◽  
Partial Least Square ◽  
Least Square ◽  
Road Extraction ◽  
The Road ◽  
Remotely Sensed Imagery ◽  
Partial Least Square Analysis ◽  
Gis Data ◽  
Road Maps

The Road extraction from the remotely sensed imagery is highly realistic for the quick road updating in the Geographic Information System (GIS) data collection. The particle filter (PF) was earlier employed to track the road maps in satellite images. In our previous work, we have introduced an efficient Gauss–Hermite Kalman Filter with Locally Excitatory Globally Inhibitory Oscillator Networks (GHKF–LEGION)-based road extraction, even though it does not properly extract the road from the complex region. In order to recover the track of the road beyond obstacles, in this work, we proposed a novel hybrid multi-kernel partial least squares (PLS) with PF approach. Here, at first, we estimate the initial leader point of the road employing the K-means clustering technique. Subsequently, the PF traces a road till a stopping benchmark is satisfied. Thereafter, without finishing the process, the outcomes are furnished to the hybrid kernel PLS technique which attempts to locate the continuance of the road after several potential road blocks or to locate the entire feasible road branches which are on the other side of the road junction. The outcomes are offered for five satellite images. The experimental results show our proposed road tracking method is better compared to other existing works.

scholarly journals Estimation of Groundwater Recharge in Kumamoto Area, Japan in 2016 by Mapping Land Cover Using GIS Data and SPOT 6/7 Satellite Images

2022 ◽  
Vol 14 (1) ◽  
pp. 545
Author(s):  
Hiroki Amano ◽  
Yoichiro Iwasaki
Keyword(s):  
Land Cover ◽  
Natural Disasters ◽  
Groundwater Recharge ◽  
Satellite Images ◽  
Sustainable Use ◽  
Paddy Fields ◽  
Fiscal Year ◽  
Domestic Water ◽  
Gis Data ◽  
Land Cover Map

Agricultural fields, grasslands, and forests are very important areas for groundwater recharge. However, these types of land cover in the Kumamoto area, Japan, were damaged by the Kumamoto earthquake and heavy rains in 2016. In this region, where groundwater provides almost 100% of the domestic water supply for a population of about 1 million, quantitative evaluation of changes in groundwater recharge due to land cover changes induced by natural disasters is important for the sustainable use of groundwater in the future. The objective of this study was to create a land cover map and estimate the groundwater recharge in 2016. Geographic information system (GIS) data and SPOT 6/7 satellite images were used to classify the Kumamoto area into nine categories. The maximum likelihood classifier of supervised classification was applied in ENVI 5.6. Eventually, the map was cleaned up with a 21 × 21 kernel filter, which is larger than the common size of 3 × 3. The created land cover map showed good performance of the larger filter size and sufficient validity, with overall accuracy of 91.7% and a kappa coefficient of 0.88. The estimated total groundwater recharge amount reached 757.56 million m3. However, if areas of paddy field, grassland, and forest had not been reduced due to the natural disasters, it is estimated that the total groundwater recharge amount would have been 759.86 million m3, meaning a decrease of 2.30 million m3 in total. The decrease of 2.13 million m3 in the paddy fields is temporary, because the paddy fields and irrigation channels have been improved and the recharge amount will recover. On the other hand, since the topsoil on the landslide scars will not recover easily in natural conditions, it is expected to take at least 100 years for the groundwater recharge to return to its original state. The recharge amount was estimated to decrease by 0.17 million m3 due to landslides. This amount is quite small compared to the total recharge amount. However, since the reduced recharge amount accounts for the annual water consumption for 1362 people, and 12.1% of the recharge decrease of 1.41 million m3 each year to fiscal year 2024 is expected by municipalities, we conclude that efforts should be made to compensate for the reduced amount due to the disasters.

scholarly journals Use of GIS in Decision Making for Geotechnical Investigation

2021 ◽  
Author(s):  
Farhan Rafique Khan ◽  
Bhumika Das ◽  
R.K Mishra
Keyword(s):  
Satellite Images ◽  
Preliminary Survey ◽  
Geotechnical Investigation ◽  
Composite Image ◽  
Gis Technique ◽  
Topographic Survey ◽  
Gis Data ◽  
Geological Information ◽  
Landsat 7 ◽  
Human Effort

Geological Information System (GIS) is a tool which is used in different Areas to subside the human effort. The GIS was earlier developed to maintain the geological data of earth, but during the time GIS is used in different areas for research. The purpose of the study is to utilize GIS technique in the field of geotechnical engineering in different work like preliminary survey, availability of digitize Soil data of location, topographic survey. Due to availability of GIS, data can easily digitize according to the geographical coordinates. The satellite imageries of Nagpur city are collected from Earth Explorer a digital platform for researchers to access the satellite images of any Location. This satellite images are Landsat 7 ETM+, these images are later used to form composite image to develop Landuse Landcover map.

Detection of Building Damage Areas of the 2006 Central Java, Indonesia, Earthquake through Digital Analysis of Optical Satellite Images

2013 ◽  
Vol 29 (2) ◽  
pp. 453-473 ◽  
Author(s):  
Hiroyuki Miura ◽  
Saburoh Midorikawa ◽  
Norman Kerle
Keyword(s):  
Image Analysis ◽  
Satellite Images ◽  
Building Damage ◽  
Bare Ground ◽  
Central Java ◽  
Gis Data ◽  
Before And After ◽  
Collapsed Buildings ◽  
Optical Satellite Images ◽  
The Relationship

In order to evaluate the capability of building damage detection from optical satellite images, a procedure for digital image analysis is examined and applied to images captured before and after the 2006 Central Java, Indonesia, earthquake. In the image analysis, the pixels of the images are classified into vegetation, bare ground, and built-up areas. The damage areas are detected by the differential of the digital numbers in the built-up areas. The estimated damage distribution is validated by comparing it with the GIS data on building damage obtained from a field survey. The results show that the severely damaged areas were well detected by the analysis. In the densely vegetated areas, however, the damage was underestimated because many of the buildings were obscured by trees. For assessing quantitative damage information, the relationship between the number of collapsed buildings and the areas detected by the image analysis is evaluated.

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