In biological system, Soil plays a vital role. pollution of soil is a most important problem. Fluid fresh water is important to the mankind. But less than 1% of the total water is supplied. Water bodies as source of water, food, transportation and recreation are utilized by man. The degradation of soil quality near rivers, lakes, tanks and estuaries have been accelerated by the rapid and continuous growth of industries coupled with unregulated discharge of industrial waste and municipal sewage. Conventional in-situ measurements of water quality parameters arc slow, sparse and costly. Remote sensing has significant advantages over in-situ techniques in monitoring the soil quality parameters because of its synoptic and repetitive nature. Remote sensing data cannot sense and measure all soil pollutants.
Contamination of heavy metal in Soil and water resources plays a major hazard regarding human and animal’s health. Agricultural activities and Land usage is affected because of spatial and temporal patterns of soil heavy metals. Heavy metals have the atomic mass of over 55.8 g mol − 1 or a density of over 5 g cm − 3. The most hazardous heavy metals i.eArsenic, mercury, zinc, lead, cadmium, chromium, copper, manganese, nickel and vanadium [1] are contaminated into the soil and found in the biosphere which make harmful to mankind.
Arman Nadari [1] reported that analysed the stepwise multiple linear regression (MSLR) and neural network-genetic algorithm model (ANN-GA) had been used for heavy metal distribution and the results were compared and assessed based on satellite imagery. It was evident that the accumulation of industrial wastes in roads and streams were the key factors of pollution, and the concentration of soil heavy metals can be diminished by means of increasing the distance from these sources. Weibo Ma[2] used weighted k-Nearest Neighbor (weighted k-NN) method to estimate the content of heavy metal with hyperspectral data and found that the accuracy of weighted k-NN method was higher than other methods in the inversion of heavy Zinc (Zn), Chromium (Cr) and Plumbum (Pb).
JinchunZhen[3] reported that ANN-GA has higher predicting ability of heavy metal distribution in various resources when compared to MSLR. The local Moran’s indextechnique is helpful in analysing remote sensing imagining and regional hotspots of heavy metal distributions. T.Kemper [4]reported that variable multiple endmember SMA system (VMESMA) was helpful in mapping of residual sludge and sludge derivatives which has greater flexibility and possibilities to get improved performances and more accurate interpretation of the unmixing results. This approach would endmember set of background material andthe delineation of the affected area using the RMS error with the GIS layers of the affected area.
Ali Al Maliki [5] analyzed the Pb concentrations in soils and studies have shown that the characteristics of urban and agricultural soils have heavy metal contaminations.Heavy metals are supplemented through the food chain, which damages the human health. Chronic exposure of Cd reflected the health hazards like lung cancer, prostatic proliferative lesions, bone fractures, kidney dysfunction and hypertension. Chronic oral and inhalation exposure of lead causes skin lesions and lung cancer and Pb causesplumbism, anemia, nephropathy, gastrointestinal colic and central nervous system symptoms.
Żukowska J, BiziukM[6] reported that the high concentrations of heavy metals such as Cd, low pH in soil leads human health risks. The human health risk from heavy metal contamination is not only correlated with the soil metals concentrations but is related to the overall environmental system. The land uses were considered when assessing the heavy metal health risks in this study.
Huarong Zhao, Beicheng Xia [7] stated that the size of the local population should also be considered with larger populations in a residential land since there is a higher chance of adverse human health effects. Manoj Kumar Tiwari [8] et.al reported that the concentrations of heavy metals in soil near to the dumping/disposal site is more and decreases as distance increases. Also in the depth wise analysis, it was observed that the higher concentrations of selected heavy metals are observed near the surface of ground and magnesium which has highest concentration .The higher pH (alkaline) of the disposed industrial solid wastes may reduce the leach ate generation, so suitable industrial solid waste disposal or dumping near populated vicinity has to be used. ChijiokeEmenike[9] et.al reported that the landfilling is one of the ultimate waste disposal option among Asian nations.Disposal sites are influenced by the deposited Leach ate quality waste. The studies revealed that in-site composition is similar even though there is a slight variation among the Asian landfills in leach ate quality. Hence there is an immediate need for refurbishment of existing landfills and dumps.
From the studies carried out by Nalawade P.M et. al[10] revealed that different heavy metals that are available in the fly ash dumping ground and its surrounding area can be recovered, reused and recycled. Based on the availability of metal deposited there is contamination of heavy metal surrounding the thermal power plant. It is life threatening to human. Bioremediation technique is the recent technique adopted to provide remedy of metal pollutants and to create an eco-friendly environment.
Another work to determine the levels of metals like Cu, Fe, Ni, Cd, Pb and Zn deposited on the soil surface in the locality of railway workshop is proposed by Akot[11]. In this work using geo accumulation index and enrichment value the soil pollution is measured. The enrichment value calculated showed the Pb and Cu metals were enriched by 3.47 and 2.26 respectively. Accumulation index value showed that Cd and Ni concentration are at background level and is moderately polluted by Zn and extremely polluted by Pb and Cu. Anthropogenic sources are the cause for high concentration of Zn, Pb and Cu.
Yet another method to predict the concentration of heavy metals using reflectance spectroscopy is proposed by Peters et al.[12]. The approach lacks to determine the heavy metals that are slightly concentrated in soil. C.M.Pandit et al.[13] proposed a method to estimate the contamination of heavy metals such as Cd, Cr, Pb, AS, Hg and Zn in urban areas and produced promising results using PLSR models.
Due to Urbanization in Tirupur district in Tamil Nadu there is a serious conflict between human and land. The agricultural land neighboring the river is being highly polluted by the heavy metals. Precise estimation of concentration of heavy metals in soil is crucial and vital. Usage of Remote sensing data to estimate the concentration of heavy metals in soilis time and cost effective compared to laboratory analysis. Accuracy of estimation is not as expected using the remote sensing data with the inversion of heavy metals in soil. In the previous works carried on Remote Sensing data the concentration of Pb in soil is alone estimated. In this work various heavy metals inversion in soil is estimated and classified using kriging and regression analysis method. The accuracy of estimation of heavy metal concentration in soil is improved in cultivated areas.
This paper presents the method and results based on the in-situ heavy metal concentrations and remote sensing data. The objectives are: -