Determination of Area Change in Water Bodies and Vegetation for Geological Applications by Using Temporal Satellite Images of IRS 1C/1D

Author(s):  
Mansi Ekbote ◽  
Ketan Raut ◽  
Yogesh Dandawate
2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.


2012 ◽  
Vol 10 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Fernanda Bruno ◽  
Paola Barreto ◽  
Milena Szafir

This on line curatorship presents a selection of 11 works by Latin American artists who incorporate in their creations technologies traditionally linked to surveillance and control processes. By Surveillance Aesthetics we understand a compound of artistic practices, which include the appropriation of dispositifs such as closed circuit video, webcams, satellite images, algorithms and computer vision among others, placing them within new visibility, attention and experience regimes. The term referred to in the title of this exhibition is intended more as a vector of research rather than the determination of a field, as pointed by Arlindo Machado under the term “surveillance culture”. (Machado 1991) In this sense, a Latin America Surveillance Aesthetics exhibition is a way to propose, starting from the works presented here, a myriad of questions. How and to what extent do the destinies of surveillance devices reverberate or are subverted by market, security and media logics in our societies? If, in Europe and in the USA, surveillance is a subject related to the war against terror and border control, what can be said about Latin America? What forces and conflicts are involved? How have artistic practices been creating and acting in relation to these forces and conflicts? Successful panoramas of so called Surveillance Art already take place in Europe and North America for at least three decades, the exhibition “Surveillance”, at the Los Angeles Contemporary Exhibitions being one of the first initiatives in this domain. In Latin America however, art produced in the context of surveillance devices and processes is still seen as an isolated event. Our intention is to assemble a selection of works indicating the existence of a wider base of production, which cannot be considered eventual.The online exhibition can be accessed here.http://www.pec.ufrj.br/surveillanceaestheticslatina/


2020 ◽  
pp. 3445-3455
Author(s):  
Heba Khudhair Abbas ◽  
Farah Faris ◽  
Sale Sami ◽  
Al Zahraa Fadel

Mathematical integration techniques rely on mathematical relationships such as addition, subtraction, division, and subtraction to merge images with different resolutions to achieve the best effect of the merger. In this study, a simulation is adopted to correct the geometric and radiometric distortion of satellite images based on mathematical integration techniques, including Brovey Transform (BT), Color Normalization Transform (CNT), and Multiplicative Model (MM). Also, interpolation methods, namely the nearest neighborhood, Bi-linear, and Bi-cubic were adapted to the images captured by an optical camera. The evaluation of images resulting from the integration process was performed using several types of measures; the first type depends on the determination of quality in the regions of the edges using a contrast measure as well as the number of edges and threshold. The second type is the global one that is based on the parameters of the image region, including the Mean (µ), Standard Deviation (SD), and Signal to Noise Ratio (SNR). The parameters also included the Amount of Information Added (AIA) to the original image, such as those for the total (AIAt) , edges (AIAe), and homogenous (AIAh) regions. The results showed the efficiency of the integration process in the image fusion with different resolutions in one image integrated resolution. The quality measures used were also capable in evaluating the most efficient techniques and determining the accurate information of the resulting image.


Urbanization plays a key role in the health of the water bodies in any region. In a rapidly growing country like India, especially Bangalore district, rapid urbanization has seen a steep decline in the number of water bodies the region is famous for. In this paper, Land Use and Land Cover change is analysed for the remotely sensed images of Bangalore District using Spectral Angle Mapper Algorithm. Data for the purpose of analysis was obtained from BHUVAN (NRSC, ISRO). The study area is Bangalore District and data was collected from the time period 2008-2016. The major classes used in the classification are Land(Built-up), water bodies (Lakes), Vegetation (Gardens), Soil (Barren and fertile). The satellite images and the accompanying classification algorithms indicate that the percentage of water bodies have drastically shrunk (from 2.9% in 2008to1.8% in 2016) in the area of study. The results of this study can be used by the civic authorities to implement decisions to conserve the water bodies in the area.


2021 ◽  
Vol 11 (1) ◽  
pp. 45-66
Author(s):  
Mete Durlu ◽  
Ozan Eski ◽  
Emre Sumer

In many geospatial applications, automated detection of buildings has become a key concern in recent years. Determination of building locations provides great benefits for numerous geospatial applications such as urban planning, disaster management, infrastructure planning, environmental monitoring. The study  aims to present a practical technique for extracting the buildings from high-resolution satellite images using color image segmentation and binary morphological image processing. The proposed method is implemented on satellite images of 4 different selected study areas of the city of Batikent, Ankara.  According to experiments conducted on the study areas, overall accuracy, sensitivity, and F1 values were computed to be on average, respectively. After applying morphological operations, the same metrics are calculated . The results show that the determination of urban buildings can be done more successfully with the suitable combination of morphological operations using rectangular structuring element. Keywords: Building Extraction; Colour Image Processing;Colour space conversion; Image Morphology; Remote Sensing        


Author(s):  
Benjamin Holt ◽  
D. Andrew Rothrock ◽  
Ronald Kwok
Keyword(s):  
Sea Ice ◽  

2021 ◽  
pp. 67-74
Author(s):  
Artem Pshenichnikov

The results of application of six spectral indices (AWEI, MNDWI, NDVI, NDWI, TCW, WRI) for the isolation of thermokarst lakes in tundra landscapes of northern Yakutia are presented. To assess the accuracy of decryption of lakes, an average quadratic error (MSE) was calculated. The minimum MSE value is 0.11 km2 and corresponds to the NDWI index. An almost identical result (0.12 km2) is found in the WRI index, slightly worse (0.15 km2) one — in the NDVI index. An MNDWI index has the highest mean square error (7.02 km2). Visual analysis also showed better decryption of water bodies using the NDWI, WRI and NDVI indices, which allows the use of these indices for automatical isolatation water bodies.


Author(s):  
Andrius Litvinaitis ◽  
Lina Bagdžiūnaitė-Litvinaitienė ◽  
Laurynas Šaučiūnas

On preparing of the first management plans of River Basin Districts have been found that diffuse agricultural pol-lution is one of the most important causing factor and the most significant impact on the quality of water bodies. Diffuse agricultural pollution can be from 45% to 80% of nitrate nitrogen pollution load of water bodies. Pollution is transported by water surface and subsurface runoff through sediments from agricultural territories. This article aims at evaluating of relation between the Quaternary sediments and Land use dissemination. The lithological factor (sandy, loamy, argillaceous) of the basin was calculated based on Quaternary map of Lithuania M 1:200000 and Lithuanian river map M 1:50000. The land-use factor of the basin was calculated based on Corine Land cover M 1:100000 using ArcGis software. In order to carry out more thorough analysis of the determination of relation between the Quaternary sediments and Land use dissemination in given territories, sections of 0–50 m, 50–200 m, 200–500 m, 500–800 m, 800–1000 m and >1000 m were established, calculating the distance in meters from the riverbank.


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