Remote Sensing, Fuzzy Logic and GIS in Petroleum Exploration

2006 ◽  
Author(s):  
Reza Taheri ◽  
Alan Melville Tait
Keyword(s):  
Remote Sensing ◽  
Fuzzy Logic ◽  
Petroleum Exploration

scholarly journals Summaries of certain spatial patterns retrieved from multidate remote-sensing data

2004 ◽  
Vol 2004 (2) ◽  
pp. 287-300
Author(s):  
Hema Nair
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Spatial Patterns ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Geographic Area ◽  
Image Mining ◽  
Sensing Data

This paper presents an approach to describe patterns in remote-sensed images utilising fuzzy logic. The truth of a linguistic proposition such as “Y isF” can be determined for each pattern characterised by a tuple in the database, where Y is the pattern andFis a summary that applies to that pattern. This proposition is formulated in terms of primary quantitative measures, such as area, length, perimeter, and so forth, of the pattern. Fuzzy descriptions of linguistic summaries help to evaluate the degree to which a summary describes a pattern or object in the database. Techniques, such as clustering and genetic algorithms, are used to mine images. Image mining is a relatively new area of research. It is used to extract patterns from multidated satellite images of a geographic area.

scholarly journals KLASIFIKASI HABITAT PERAIRAN DANGKAL MENGGUNAKAN LOGIKA FUZZY DAN MAXIMUM LIKELIHOOD PADA CITRA SATELIT MULTISPEKTRAL

2018 ◽  
Vol 10 (3) ◽  
pp. 667-681
Author(s):  
Muhammad Siddiq Sangadji ◽  
Vincentius Paulus Siregar ◽  
Henry Munandar Manik
Keyword(s):  
Remote Sensing ◽  
Fuzzy Logic ◽  
Maximum Likelihood ◽  
Satellite Imagery ◽  
Data Retrieval ◽  
Classification Algorithm ◽  
Benthic Habitat ◽  
Fuzzy Logic Algorithm ◽  
Accuracy Level ◽  
Sentinel 2A

ABSTRAKLogika fuzzy memiliki aplikasi di berbagai bidang, namun memiliki arti khusus untuk penginderaan jarak jauh. Logika fuzzy memungkinkan keanggotaan parsial, bagian yang sangat penting dibidang penginderaan jarak jauh, karena keanggotaan parsial diterjemahkan secara dekat dengan masalah piksel campuran. Penelitian ini bertujuan untuk menerapkan algoritma klasifikasi logika fuzzy untuk memetakan habitat dasar Perairan dangkal pada Citra Satelit SPOT 7 dan Sentinel 2A, menguji tingkat akurasinya dan membandingkan algoritma klasifikasi logika fuzzy dengan maximum likelihood. Pengambilan data lapang berlokasi di gusung Karang Lebar dan Karang Congkak, Kepuluan Seribu pada tanggal 6 Desember sampai dengan 10 Desember 2017. Keseluruhan hasil uji akurasi menunjukan bahwa algoritma logika fuzzy masih memiliki tingkat akurasi yang baik dibandingkan dengan algoritma maximum likelihood. Perbedaan ukuran pixel (resolusi spasial) dari citra satelit juga mempengaruhi hasil akurasi, dimana citra satelit SPOT 7 memiliki tingkat akurasi yang lebih besar dibandingkan dengan Sentinel 2A.ABSTRACTFuzzy logic has applications in various fields, but has special meaning for remote sensing. Fuzzy logic allows partial membership, a very important property in the field of remote sensing, since partial membership is translated closely to the problem of mixed pixels. The aim of this research is to apply fuzzy logic classification algorithm to map benthic habitat in SPOT 7 and Sentinel 2A satellite imagery, test its accuracy level and compare fuzzy logic classification algorithm with maximum likelihood. Field data retrieval located in Karang Lebar and Karang Congkak, Kepulauan Seribu on 6 December until 10 December 2017. The overall accuracy test results show that fuzzy logic algorithm still has a good accuracy level compared to the maximum likelihood algorithm. Differences in pixel size (spatial resolution) of satellite imagery also affect accuracy results, where SPOT 7 satellite imagery has greater accuracy then Sentinel 2A. 

Remote Sensing Image Fusion Based on Fuzzy Logic and Salience Measure

2020 ◽  
Vol 17 (11) ◽  
pp. 1943-1947 ◽  
Author(s):  
Yong Yang ◽  
Hangyuan Lu ◽  
Shuying Huang ◽  
Wei Tu
Keyword(s):  
Remote Sensing ◽  
Fuzzy Logic ◽  
Image Fusion ◽  
Remote Sensing Image ◽  
Remote Sensing Image Fusion
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