Abstract
Space Technology provides a resourceful-cost effective means to assess soil nutrients essential for soil management plan. Soil organic matter (SOM) is one of valuable controlling productivity of crops by providing nutrient in farming systems. Geospatial modeling of soil organic matter is essential if there is unavailability of soil test laboratories and its strong spatial correlation. In the present analysis, soil organic matter is modeled from satellite image derived spectral color indices. Brightness Index (BI), Coloration Index (CI), Hue Index (HI), Redness Index (RI) and Saturation Index (SI) were calculated by converting DN value to radiance and radiance to reflectance from Thematic Mapper image. Geospatial model was developed by regressing SOM with color indices and producing multiple regression model using stepwise regression technique. The multiple regression equation between SOM and spectral indices was significant with R = 0. 56 at 95% confidence level. The resulting MLR equation was then used for the spatial prediction for the entire study area. Redness Index was found higher significance in estimating the SOM. It was used to predict SOM as auxiliary variables using cokringing spatial interpolation technique. It was tested in seven VDCs of Chitwan district of Nepal using Thematic Mapper remotely sensed data. SOM was found to be measured ranging from 0.15% to 4.75 %, with a mean of 2.24 %. Remotely sensed data derived spectral color indices have the potential as useful auxiliary variables for estimating SOM content to generate soil fertility management plans.
Highlights
Soil is one of the most important natural resources providing life to all kinds of living beings as plants, animals and organism
Some attributes such as Soil organic matter (SOM) and Redness Index(RI) are dependent
When one or more variables are estimated by a linear combination using both the spatial and inter-variable dependence, the technique is known as co-kriging or co-regionalization
Summary
Soil is one of the most important natural resources providing life to all kinds of living beings as plants, animals and organism. Government of Nepal has limited soil test laboratories and recently proposed fifty new to be set up on PPP mode with a cost of NRs 2.5 million each along with strengthening of 16 existing soil test laboratories ( 7 under SMD and 9 under NARC) requiring a cost of NRs 5.0 million each to cater the demand of farmers and researchers(.Dawadi et al 2015) Estimation of this soil property at an acceptable level of accuracy is important; especially in the case when SOM exhibits strong spatial dependence and its measurement is a time,cost and labor-consuming procedure
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