Digital Soil Mapping of Aurangabad District
What is Digital Soil Mapping
Digital soil mapping (DSM) represents “the creation and population of spatial soil information systems by the use of field and laboratory observational methods coupled with spatial and non-spatial soil inference systems” (Digital Soil Mapping: An Introductory Perspective 2007. Edited by P. Lagacherie, A. B. McBratney & M. Voltz, 2007 Elsevier 600 pages ISBN 0-444-52958-6). Soil science, geographic information science, quantitative methods (statistics and geostatistics) and cartography are combined within the DSM framework. DSM methods are used to estimate the spatial distribution of soil classes (e.g., soil series) and/or soil properties (e.g., soil organic matter), and can be employed at various scales (from individual fields to countries), and have proven valuable for developing more quantitative, more accurate, and more precise soil maps.
Hyperspectral and Multispectral Center of Department of CS & IT, Dr. B.A.M University "Digital Soil Mapping"
The Department of Computer Science and IT,(Dr. BAMU) Center – Hyperspectral and Multispectral SAP Research Unit has identified DSM as an important area of focus in support of soil survey activities. This DSM research projects have been supported by the DST-FIST. Numerical classification (hierarchical and fuzzy), spatial and temporal interpolation (geostatistics, wavelets), sampling design (model vs. design based), statistical analysis (visualization, ordination, regression, and classification), uncertainty analysis (error propagation, accuracy assessment), and incorporation of auxillary data (proximal and remotely sensed imagery, soil-terrain modeling) are among the methods used to develop predictive maps of soil classes and soil properties.Example of "Digital Soil Mapping"
Study Area of Aurangabad District
Study Area of Aurangabad district 10279.898581 Square kilometers Area. More information about Climate: The climate is characterized by hot summer and general dryness throughout the year except during the south west monsoon season which is from June to September while October and November constitute the post monsoon season with a temperature of 10.3°C in winter and 39.8°C in summer. The normal annual rainfall varies from about 500 mm. Most rainfall occurs during southwest monsoon (June–September) period. Agriculture is the major activity in the area and Groundwater is the major source for drinking and irrigation. [Download shape File]
Natural Color (4-3-2) Landsat 8OLI data
Result of (scale 1:668,613) The "natural color" band combination. because the visible bands are used in this combination, ground features appear in colors similar to their appearance to the human visual system, healthy vegetation is green, recently cleared fields are very light, unhealthy vegetation is brown and yellow, roads are gray, and shorelines are white. This band combination provides the most water penetration and superior sediment and bathymetric information.
Clay mineral 2013 (5-4-3 )Landsat 8OLI data
The standard “false color” composite. Vegetation appears in shades of red, urban area are cyan blue, and soils very from dark to light browns. Ice, snow and cluds are white or light cyan. Trees will appear darker red than hardwoods.
Clay mineral
Clay minerals are hydrous aluminium phyllosilicates, sometimes with variable amounts of iron, magnesium, alkali metals, alkaline earths, and other cations found on or near some planetary surfaces.Clay minerals form in the presence of water and have been important to life, and many theories of abiogenesis involve them. They are important constituents of soils, and have been useful to humans since ancient times in agriculture and manufacturing.
Evnironmental Covariates for (DSM) NDVI
Possibly the most common use of Landsat 8OLI data for digital soil mapping is the NDVI (Normalized Difference Vegetation Index), which can represent the environmental covariate of vegetation. The NDVI is often used to monitor drought, monitor and predict agricultural products, assist in predicting hazardous fire zones, and map desert encroachment. The NDVI is a standardized vegetation index which allows us to generate an image showing the relative biomass. The Chlorophyll absorption in red band and relatively high reflectance of vegetation in NIR are using for calculating NDVI
Iron oxide
Iron oxide abundance and hematite–goethite ratio spec-tral parameters were obtained from the polynomial curve that best fits the reflectance spectrum for which the conti-nuum was removed.
About Me
I am a Doctor of Philosophy research student (BSR fellow) in Department of Computer Science and Information Technology, Dr. Babasaheb Ambedkar Marathwada University, Aurangabad, MH, India.
The primary aim of this research involves the make Digital Soil Information Map using soil mapping technologies and proposes a new method of Digital Soil Mapping (DSM) and subsequent classification of the study area (Aurangabad district MH, India). Into predefined technological categories of the dataset. I implemented 1) Digital Terrain Analysis (DTA) for topographical information is derived from the Digital Elevation Model (DEM) which stores information on elevation, stream networks and other terrain-related attributes, together with their geographical location. The main primary attributes are slope gradient, slope aspect, plan and profile curvatures, upslope contributing area and 2) Digital Soil Mapping (DSM) are used number of tools and methods like (review) geostatistical, non-geostatistical and mixed. My study I used kriging, isotope and regression-based DSM techniques as regards their ability to predict soil properties.
6+ years of diverse experience in Information Technology with emphasis on building solutions with implementation of ArcGIS, ArcMap, City Engine, ENVI, ImageJ, C, C++, Java, Python and Machine Learning algorithms for classification, identification, verification of imaging and non-Imaging data processing.
My research areas of interest are Imaging and non-Imaging of Remote Sensing and GIS. I have completed Master of Philosophy in Computer Science at Dr. Babasaheb Ambedkar Marathwada University in 2015 my topic was entitled “Analysis of Cardiac MRI to find out Cardiovascular Disease using Automatic Segmentation Techniques” and we have developed auto detection techniques for cancer detection in early phase.
Technical Skills
ArcGIS
Python
ERDAS
ENVI
QGIS
My research focus
Aurangabad District
This research bridges these gaps by setting up some objectives where the continuous function of [Figure 1] soil properties in Aurangabad District, Maharashtra, India soil profiles was modelled and its distribution down to 20 cm from the soil surface was mapped for the entire District. The autocorrelation of soil properties from different study areas was also investigated to see how the variability changed over space. Similarly, different spatial techniques to predict soil properties were compared to find suitable methods applicable to current Indian conditions.
Contact Me
jaypalsing@email.com
Aurangabad, Maharashtra, India
8888880624