GIS Based Index Overlay Method in Targeting Heavy Mineral Deposits, Southern Kerala Coast, India
Melwyn Joshua R1, Palanivel K2, Rajaperumal R3

1Melwyn Joshua R, Department of Remote Sensing, Bharathidasan University, Trichy, India.
2Dr. Palanivel K, Department of Remote Sensing, Bharathidasan University, Trichy, India.
3Rajaperumal R, Department of Remote Sensing, Bharathidasan University, Trichy, India.
Manuscript received on January 02, 2020. | Revised Manuscript received on January 15, 2020. | Manuscript published on January 30, 2020. | PP: 505-511 | Volume-8 Issue-5, January 2020. | Retrieval Number: E5032018520/2020©BEIESP | DOI: 10.35940/ijrte.E5032.018520

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Abstract: Owing to the strategic importance in defence and the other industrial applications, the heavy minerals have attracted the attention of the geoscientists since long time. But they have been using mostly the traditional techniques for a long time for targeting the heavy mineral deposits. Later, the scientists have started employing modern techniques like scintillometer based field surveys, remote sensing and the laboratory based sedimentological and heavy mineral studies. But since the traditional techniques are more cumbersome and would be very difficult to cover the vast length of the Indian coasts of over 7500 km, faster and effective techniques are necessary. So, the information value method was accomplished in the present study to demonstrate the targeting of heavy minerals in parts of Kerala extending from 76° 41′ – 08° 53′ in NNW and 77° 13′ – 08° 17′ in SSE (1,811sqkm). In this study five geosystem maps, viz; Lithology, Lineament Frequency, Lineament Density, Lineament Intersection density and Geomorphology were prepared using the raw and digitally processed LANDSAT ETM 7 and IRS LISS IV FCC data sets. These geosystem maps were firstly prepared as vector GIS layers and then converted into raster maps using ARC GIS software with the pixel size of 100sq.m and the total pixels of 1,64,358. On the basis of the contribution of the above five main geosystem variables towards the heavy mineral potentials, weightages were assigned (Wi) to each of them. Similarly, depending upon the heavy mineral possibilities of the sub variables of the above five main geosystem variables, scores were assigned (Si) to each sub variables of the 5 main geosystem variables. Then, the Wi values were multiplied with the corresponding Si values of each of the sub variables of the 5 main geosystem variables and those were considered as final weightages (HMP-Heavy Mineral potentials) and assigned the same to the corresponding pixels of each sub variables of the five main variables. Followingly, the each WiSi weighted values of the 1,64,358 pixels of the lithology main geosystem variable were added with corresponding pixels of the remaining 4 main geosystem variables using ADD function menu of ARC GIS and integrated raster GIS database was generated with all the 1,64,358pixels having the cumulative WiSi values (ΣWiSi). Then, on the dynamic range of the ΣWiSi values, these pixels were classified into Very High, High, Moderate, Low and Very Low zones of heavy mineral concentrations. This was validated with heavy mineral weight percentage data derived from the field samples collected from the study area during survey. This study was basically undertaken to replicate it for the rapid appraisals of the probable heavy mineral target areas along the Indian coasts. However this can be replicated anywhere.
Keywords: Remote Sensing and GIS, Index Overlay method, heavy mineral targeting, Southern Kerala coast
Scope of the Article: Software Engineering Methodologies.