The present disclosure relates to the field of project resource planning, and more particularly relates to a method and a system for high resolution soil strata prediction for project resource planning.
BACKGROUND
[0002] With the advent of technology, network infrastructure has flourished at a rapid pace. The network infrastructure plays a vital role in providing requisite telecommunication services such as exchange of information over significant distances by electronic means via voice, data and video transmission. Of late, we have seen an increasing demand in usage of the telecommunication services. The increasing demand of the telecommunication services leads to an increase in telecommunication infrastructure deployment projects. Soil strata, location/worksite and human resources are a few parameters that play an important role in optimally planning and scheduling the telecommunication infrastructure deployment projects.
[0003] Given that the soil strata is an important parameter, soil strata describe the several layers of a column of soil. Various techniques such as surveying, modelling, mapping or the like have been suggested for approximation of information related to the soil strata. Typically, the soil strata varies with depth level and creates obstacles in the telecommunication infrastructure deployment projects because type of machinery and it's attachments also get changed according to strata information and the arrangement of those take a considerable amount of time.
[0004] Further, a network implementer involved in the telecommunication infrastructure deployment projects aims for support systems to be safe, quality adherence and to limit displacements in planned route, whereas a contractor seeks to design a most economical support, which is conflicting and may create issues. Such situations lead to delay in the telecommunication infrastructure deployment projects.
[0005] A prior art reference US7254485 mentions a soil and topography surveying method. The survey method is used for determining optimum position

to deploy a tool. According to the reference, plurality of data related to soil, land usage, topography etc. is used and a 3D kriging method is used for smooth approximation of data.
[0006] Another prior art reference JP2004272173 mentions a method for creating a support system for underground dam project. The reference mentions creating a database based on roads, rivers, house, fields, soil, vegetation and other surface and underground data and of planning methods based on underground methods such as geophysical and geological drilling. The data is combined in to a three dimensional map and based on the map, an optimal construction plan is created.
[0007] Similarly, a prior art reference US9904747 mentions a method used for agriculture planning by determining top soil condition based on 3-D topographical surveys and 3-D soil profiles.
[0008] However, none of the conventional techniques and above-mentioned prior-arts focus on smooth and optimal approximation of the soil strata information for optimally planning resources and scheduling worksites in the telecommunication infrastructure deployment projects.
[0009] In light of above discussion and in consideration with prior-arts, there is a need for a method or technique for optimal approximation of the soil strata information for project resource planning in the telecommunication infrastructure deployment projects.
[0010] Any references to methods, apparatus or documents of the prior art are not to be taken as constituting any evidence or admission that they formed, or form part of the common general knowledge.
OBJECT OF THE DISCLOSURE
[0011] A primary object of the present disclosure is to provide a method and a system for high resolution soil strata prediction.
[0012] Another object of the present disclosure is to provide a three-tier approximation technique for approximation of soil strata information for optimal project resource planning.

[0013] Another object of the present disclosure is to predict a digging force required for a project by utilizing the three-tier approximation technique.
[0014] Another object of the present disclosure is to provide soil strata information approximation for optimal and smooth planning of resources and scheduling work at worksites/locations in telecommunication infrastructure deployment projects.
SUMMARY
[0015] The present disclosure aims to achieve above-mentioned objects. The present disclosure provides a method and a system for three-tier approximation of soil strata information to predict digging force required for deploying the telecommunication infrastructure project. The method includes generating a first chainage matrix for a predefined area in an XYZ plane, wherein chainage refers to the centerline of the structure. The first chainage matrix defines a volumetric mix of soil and rock types at predefined depth intervals in a Z plane of the XYZ plane. Further, the method includes superimposing surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals, thereby generating a second chainage matrix. Further, the method includes adding geomorphological data matrix to the second chainage matrix based on the predefined depth intervals, thereby generating a third chainage matrix, wherein the geomorphological data matrix comprises topographical evolution parameters of the predefined area. Furthermore, the method includes calculating force required to dig soil strata at each point in the XYZ plane based on the third chainage matrix.
[0016] The first chainage matrix is generated by extracting a plurality of attributes of the XYZ plane, wherein the plurality of attributes is one or more of a slope, a curvature, a topographical position index, a topographical wetness index, an altitude, a lithology, land use data and land cover data; classifying the extracted plurality of attributes in a geographic information system environment to distinguish strata types at the predefined depth intervals and arranging the classified strata types in a volumetric mix of soil and rock types at the predefined

depth intervals in the Z plane to create the first chainage matrix for the predefined area in the XYZ plane. The surface information is superimposed to create the second chainage matrix by refining the first chainage matrix using visual verification from a satellite image by combining a weighted value of time series enabled surface information of the predefined area with the first chainage matrix to create the second chainage matrix for the predefined area in the XYZ plane. The surface information that is superimposed on the first chainage matrix includes time series based land use information, drain line information, stream order, soil colour and land form information. Superimposing the surface information on the first chainage matrix to create the second chainage matrix further comprising adding a weighted value of quantitatively scaled additional data matrix to the second chainage matrix, wherein the additional data matrix comprises at least one or more of monsoon information, crop history and anthropogenic information.
[0017] The geomorphological data matrix is added to the second chainage matrix by scaling the geomorphological data matrix of the predefined area to a common scale that matches the second chainage matrix, wherein the topographical evolution parameters of the predefined area are matched with the second chainage matrix in the XYZ plane and adding the scaled geomorphological data matrix to the second chainage matrix to generate the third chainage matrix in the XYZ plane. The force required to dig the soil strata is calculated by calculating a geomorphological scaling factor corresponding to the scaled geomorphological data matrix and calculating the force required to dig the soil strata of the predefined area in the XYZ plane by changing digging force based on the geomorphological scaling factor of the geomorphological data matrix. The geomorphological data matrix comprises shape and feature information of landform over a period of time and information regarding chemical and physical processes that transformed the landform over that period of time.
[0018] These and other aspects herein will be better appreciated and understood when considered in conjunction with the following description and the accompanying drawings. It should be understood, however, that the following descriptions are given by way of illustration and not of limitation. Many changes

and modifications may be made within the scope of the invention herein without departing from the spirit thereof.
BRIEF DESCRIPTION OF FIGURES
[0019] The invention is illustrated in the accompanying drawings, throughout which like reference letters indicate corresponding parts in the drawings. The invention herein will be better understood from the following description with reference to the drawings, in which:
[0020] FIG. 1 illustrates a system for three-tier approximation of soil strata information to predict digging force required for deploying a telecommunication infrastructure project.
[0021] FIG. 2 is a block diagram representing the three-tier approximation technique of FIG. 1.
[0022] FIG. 3 illustrates an example format of chainage wise report.
[0023] FIG. 4 illustrates an example volume summary of a route.
[0024] FIG. 5 illustrates an example route for which the three-tier approximation technique has been applied.
[0025] FIG. 6 illustrates the chainage wise report extracted for the example route.
[0026] FIG. 7 illustrates the chainage wise strata indication graph for the example route.
[0027] FIG. 8 illustrates a surface elevation of the example route.
[0028] FIG. 9 is a flow chart illustrating a method for three-tier approximation of soil strata information to predict digging force required for deploying the telecommunication infrastructure project.

DETAILED DESCRIPTION
[0029] In the following detailed description of the invention, numerous specific details are set forth in order to provide a thorough understanding of the invention. However, it will be obvious to a person skilled in the art that the invention may be practiced with or without these specific details. In other instances, well known methods, procedures and components have not been described in details so as not to unnecessarily obscure aspects of the invention.
[0030] Furthermore, it will be clear that the invention is not limited to these alternatives only. Numerous modifications, changes, variations, substitutions and equivalents will be apparent to those skilled in the art, without parting from the scope of the invention.
[0031] The accompanying drawings are used to help easily understand various technical features and it should be understood that the alternatives presented herein are not limited by the accompanying drawings. As such, the present disclosure should be construed to extend to any alterations, equivalents and substitutes in addition to those which are particularly set out in the accompanying drawings. Although the terms first, second, etc. may be used herein to describe various elements, these elements should not be limited by these terms. These terms are generally only used to distinguish one element from another.
[0032] The key idea of the present invention is to provide a three-tier approach for approximation of soil strata information, the three tier approximation comprises, first approximation of soil and rock depth based on plurality of data and decision rule, followed by refinement by second approximation using visual verification data followed by refinement by third approximation by adding geomorphical data to the information obtained after second approximation. Unlike conventional methods and techniques, the present disclosure improves project scheduling based on the soil strata information and resource mapping details by accurately predicting the soil strata information relevant to project execution and using the predicted information for worksite (or site) resource planning and scheduling. That is, another key idea of the present invention is to use the

approximated soil strata information for resource allocation and scheduling work to the worksite.
[0033] The three-tier approach is used to predict soil depth class. A first approximation of soil depth class and type of strata (soil, soft rock, hard rock, mixed strata) up to 2 meter depth at 50 meter interval along a cable path is predicted from the digital elevation model, terrain attributes, soil data, lithology and LULC data of a worksite is used to predict soil strata attributes such as (slope, aspect, curvature, topographic position index, topographical wetness index and altitude) where, Topographic position index used to measure topographic slope positions and to automate landform classifications, Topographic wetness index explains soil moisture, Altitude is a distance measurement, in the vertical direction, it is a distance between a reference datum and a point or object, as part of first approximation. The defined ratio of, Digital Elevation Model (DEM), lithology (1:50 K, 1:50 K is scale digital geological map data), soil data (1:1 million) and land use land cover data (1:1 million), these five data layers are processed in GIS environment to implement decision rules framed by experts to predict soil strata (i.e., first approximation). The prediction distinguishes eight soil depth/strata classes namely 0-30, 31-50,51-75,76-100,101-125,125-150,150-175,176-200 cm. These classes defines the depth range of Soil Organic Carbon. A second approximation is a revision based on visual interpretation of satellite image (usually Google Earth) to observe surface information/features such as drain-line, stream order, Google Earth Engine enabled time series of land use, soil color, landform that distinguish and characterize the cable path with focus on sideways buffer of 500 m distance from the point of interest. Expert opinion and secondary information on landform (1:1 million), monsoon data, crop history data and anthropogenic features is an additional input (if required) at this stage. Further, a geomorphological data layer is added in a second tier to refine the predictions further with value addition of force or pressure required to break the rock (if any). The geomorphological data layer gives information about changes gone through the soil over a period of time and based on the changes, gives a value that can be used to determine hardness and toughness of rock. Based on the

determined hardness and toughness, the force required to break through the strata is determined. A spatial segment data (such as soil, relief and nutrient maps) is finally aggregated for the soil depth class, depth to rock and type of rock to arrive at a volumetric estimate of cut and fill, type of rock breaker required at specific segments along the cable path.
[0034] Referring now to the drawings, and more particularly to FIGS. 1 through 9 to explain the aforementioned features.
[0035] FIG. 1 illustrates a system (100) for three-tier approximation of soil strata information to predict digging force required for deploying a telecommunication infrastructure project. The system (100) provides a high resolution soil strata prediction for project resource planning. FIG. 2 is a block diagram representing the three-tier approximation technique (200) of FIG. 1. The system (100) comprises a data capturing unit (102), a first approximation unit (104), a second approximation unit (106), a third approximation unit (108), a report generation unit (110), a processor (112), a memory (114), a communication unit (116) and an output unit (118).
[0036] The data capturing unit (102) may be a camera or a drone or a sensor or a global positioning system (GPS) or a geographic information system (GIS) or combination thereof. The data capturing unit (102) may capture or record information of a predefined area in real-time to predict soil depth class. Alternatively, the data capturing unit (102) may capture or record information of the predefined area in non-real-time to predict the soil depth class. The predefined area may be an area where the telecommunication infrastructure project needs to be deployed. In other words, the predefined area may be a project site or work site or site. Alternatively, the predefined area may be a cable (such as optical fiber cable) path.
[0037] The information may be, but not limited to, attributes related to five data layers or derived from terrain, digital elevation model (DEM), lithology (1:50 K), soil data (1:1 million) and land use land cover data (1:1 million) as shown in FIG. 2. These attributes are derived from ASTER, NBSS&LUP and SRTM where, The ASTER (Advanced Spaceborne Thermal Emission and

Reflection Radiometer) is a Japanese sensor which is one of five remote sensory devices; provides a global digital elevation model (DEM) of land areas on Earth at a spatial resolution where, Digital Elevation Model (DEM) is a digital cartographic dataset in three (XYZ) coordinates and has been derived from contour lines or photogrammetric methods. The terrain elevations from ground positions are sampled at regularly spaced horizontal intervals. The terrain is defined as the specific physical features of an area of land. An example of the terrain is a rocky and jagged coastline; NBSS&LUP stands for National Bureau of Soil Survey and Land Use planning, one among the foremost Natural Resource Management (NRM) institutes of ICAR is mandated to undertake RD&T activities mainly in soil resource inventory and land use planning at different levels; SRTM (Shuttle Radar Topography Mission) addresses the effects of different spatial resolution DEM on performances of topographic correction and LULC classification of remotely sensed images by some well-designed experiments.
[0038] Using the captured information from the data capturing unit (102), the first approximation unit (104) performs first approximation using a decision rule. The first approximation extracts a plurality of attributes (of terrain) of an XYZ plane, such as one or more of a slope, an aspect, a curvature, a topographical position index, a topographical wetness index, an altitude, a lithology, land use data and land cover data. The XYZ plane may be defined by type of soil along a volume of soil. Further, the extracted plurality of attributes is classified in a GIS environment to distinguish strata type(s) at predefined depth intervals and the classified strata types are further arranged in a form of a volumetric mix of soil and rock types at the predefined depth intervals in a Z plane of the XYZ plane to create a first chainage matrix for the predefined area in the XYZ plane. In an example, the predefined depth intervals may be, but not limited to, 0-30, 31-50, 51-75, 76-100, 101-125, 125-150, 150-175 centimeter (cm) as shown in FIG. 3 and FIG. 4. The first chainage matrix may include, but not limited to, soil depth class, type of strata such as soil, soft rock, hard rock, mixed strata up to 2 meter depth at 50 meter interval along the cable path or the predefined area or the like.

[0039] That is, the first approximation unit (104) may be configured to have the geographic information system (GIS) to capture the attributes related to five data layers or derived from terrain, digital elevation model (DEM), lithology (1:50 K), soil data (1:1 million) and land use land cover data (1:1 million). The five data layers are processed in the GIS environment to implement decision rules to predict soil strata attributes and to identify volumetric mix of soil and rock type. Accordingly, the first approximation unit (104) generates the first chainage matrix for the predefined area in the XYZ plane at the predefined depth intervals.
[0040] In an example, the first chainage matrix includes information about route identity, analysis at every 50-meter chainage, strata information at different depth interval (Till 175 cm) as depicted in FIG. 3 and FIG. 4. It helps in estimating the efforts of execution and span-wise excavation timelines as well as helps to decide cost of installation per region, per span.
[0041] The second approximation unit (106) refines the plurality of attributes obtained from the first approximation unit (104). The second approximation unit (106) refines the plurality of attributes based on visual interpretation of satellite images. The satellite images of the predefined area may be obtained from the data capturing unit (102). Alternatively, the second approximation unit (106) may have a means in-built to obtain the satellite images. In an example, the satellite images may be considered from google earth.
[0042] In other words, the second approximation unit (106) refines the first chainage matrix using the visual interpretation and verification of/from a satellite image by combining a weighted value of time series enabled surface information of the predefined area with the first chainage matrix and accordingly, creates a second chainage matrix for the predefined area in the XYZ plane.
[0043] The weighted value of time series enabled surface information may be determined by checking an individual effect of the surface information such as, but not limited to, time series based land use information, drain line information, stream order, soil colour, land form information or other Google Earth Engine enabled time series information and then, according to nature of the surface information, for e.g., how effective it will be in the soil, the first chainage matrix

is combined with the weighted value of time series enabled surface information. For e.g., if the total weighted value of a surface information is 1, based on its reactance (assume that reactance is 0.75) on soil, the weighted value 0.75 of the surface information will be combined with the first chainage matrix. Thus, the second approximation unit (106) superimposes the surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals and generates the second chainage matrix.
[0044] It can be said that the second approximation is a revision based on the visual interpretation of the satellite image to observe the surface information such as drain-line, stream order, google earth engine enabled time series of land use, soil colour, landform that distinguishes and characterizes the cable path with focus on sideways buffer of a particular distance, such as 500 meters distance, from a point of interest. Further, an additional data matrix such as landform (1:1 million), monsoon information/data, crop history and anthropogenic information/features may be taken into consideration during the second approximation, if required. A weighted value of quantitatively scaled additional data matrix may be added to the second chainage matrix, where the additional data matrix comprises at least one or more of monsoon information, crop history and anthropogenic information.
[0045] In an example, the satellite image of the predefined area with a buffer of 500 meters from a point of interest is used to supplement the plurality of attributes obtained after the first approximation and the secondary information such as weighted monsoon information, crop history and anthropogenic information is added during the second approximation increase the accuracy of the plurality of attributes.
[0046] Lastly, the third approximation unit (108) receives the second chainage matrix from the second approximation unit (106). For obtaining more accurate and refined soil strata attributes, the third approximation unit (108) adds a geomorphological data matrix to the information or the soil strata attributes i.e., the second chainage matrix received from the second approximation unit (106). The geomorphological data matrix may comprise topographical evolution

parameters of the predefined area. The topographical evolution parameters may comprise shape and feature information of landform over a period of time and information regarding chemical and physical processes that transformed the landform over that period of time.
[0047] The geomorphological data matrix of the predefined area may be scaled to achieve a common scale that matches the second chainage matrix. That is, the topographical evolution parameters of the predefined area are matched with the second chainage matrix in the XYZ plane and the scaled geomorphological data matrix is then added to the second chainage matrix to generate the third chainage matrix in the XYZ plane. The scaled geomorphological data matrix is added to the second chainage matrix based on the predefined depth intervals to generate the third chainage matrix.
[0048] Based on the third chainage matrix, a pressure or force required to dig the soil strata at each point in the XYZ plane is calculated, where a geomorphological scaling factor corresponding to the scaled geomorphological data matrix is determined by dividing scale down data with original data and the pressure required to dig the soil strata of the predefined area in the X-Y-Z plane is determined by changing the digging pressure based on the geomorphological scaling factor of the geomorphological data matrix.
[0049] The geomorphological data matrix is added to refine the predictions further with value addition of pressure required to break a rock (if any) to get a spatial segment data. The spatial segment data are finally aggregated for the soil depth class, depth to rock and type of rock to arrive at a volumetric estimate of cut and fill, type of rock breaker required at specific segments along the cable path (or route).
[0050] In an implementation, the predefined area may be divided into a plurality of sub sites and on the captured data from the plurality of sub sites, the first approximation, the second approximation and the third approximation (i.e., the three tier approximation) may be implemented. Once the spatial segment data is identified from each of the plurality of subsites, the spatial segment data of each of the plurality of subsites is finally aggregated for the soil depth class, depth to

rock and type of rock to arrive at the volumetric estimate of cut and fill, type of rock breaker required at specific segments along the cable path.
[0051] The report generation unit (110) may further generate the result or report of the three tier approximation. The report may be a chainage wise report that includes information about the cable path or route identity, analysis at every 50-meter chainage, strata information at different depth interval (Till 175 cm) or the like as shown in FIG. 3. FIG. 3 illustrates an example chainage wise report (300) extracted for a route. Further, the report generation unit (110) may represent a volume summary that helps in estimating the efforts of execution and span-wise excavation timelines, It also helps to decide the cost of deployment per region, per span. An example volume summary (400) is depicted in FIG. 4.
[0052] The result or the report may be generated in, but not limited to, a tabular form, an MS-excel form, a PDF form, an MS-word form and displayed on the output unit (118). The output unit (118) may be a screen such as an LED, an LCD, a projector or the like.
[0053] The processor (112) is configured to process the information in the system (100). The processor (112) may be coupled to the data capturing unit (102), the first approximation unit (104), the second approximation unit (106), the third approximation unit (108), the report generation unit (110), the memory (114), the communication unit (116) and the output unit (118).
[0054] The memory (114) may be a computer-storage media in the form of volatile and/or non-volatile memory. The memory (114) may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state memory, hard drives, optical-disc drives, etc. In an implementation, the memory (114) may be a database. In another implementation, the memory (114) may be configured to have the database. The first approximation unit (104), the second approximation unit (106) and the third approximation unit (108) may be associated with the database. The memory (114) or the database may store the information related to the telecommunication infrastructure deployment projects. Alternatively, the memory (114) or the database may contain information related to resources and/or the predefined area. Alternatively, the memory (114) or the

database may contain information regarding work compatibility of the resources according to the soil strata attributes that may be used to map resources to the plurality of the sub sites of the predefined area (or site or worksite or project site or deployment site) after predicting the soil strata attribute using the three-tier approximation approach.
[0055] For example, for resource mapping, data from the database of resources containing information regarding work compatibility of resources according to soil attributes is used to map resources to a subsite after predicting the soil strata attribute using the three-tier approximation approach/technique. Further, for scheduling work on the subsite out of plurality of sub sites in an underground telecom infrastructure deployment project, the resource availability data is used with soil attributes data obtained after the three tier approximation to determine scheduling precedence of the subsite of the plurality of subsite. Furthermore, for deciding the depth and location of deploying underground telecom infrastructure, the soil attributes data obtained after the three tier approximation is used to determine safe depth and location of deployment of the infrastructure using the available resources.
[0056] In an example, the resources may be human resources or non-human resources or combination thereof. The non-human resources may be related to machineries, tools and equipment.
[0057] The communication unit (116) may be coupled with all the elements of the system (100) to establish required communication among them or may act as a medium to allow communication among all the elements of the system (100). In an example, the communication unit (116) may be configured to have a communication network.
[0058] The system (100) may be associated with a server such as cloud, local memory (114) etc. In general, the server is a computer program or device that provides functionality for other programs or devices. The server provides various functionalities, such as sharing data or resources among multiple users, or performing computation for the user. In an example, the server may be associated with the memory (114).

[0059] Conclusively, the system (100) implementing the first approximation by using the decision rule on the five type of data or five data layers (elevation, terrain, soil, lithology, LULC), the second approximation by visual verification using satellite image followed by secondary information addition and the third approximation, final strata prediction by adding the geomorphological data to output of the second approximation results in an efficient planning of resources for underground telecom infrastructure deployment by accurately analyzing the soil strata attribute of the project site and map the resources to the project site based on the information obtained by analyzing the soil. The approximated soil strata attribute may be used in project resource planning in the telecommunication infrastructure deployment projects such as optical fiber cable installation and/or deployment.
[0060] Further, the system (100) may schedule work on a subsite out of the plurality of subsites in the underground telecom infrastructure deployment project, wherein the resource availability data is used with the soil strata attributes, obtained after the three-tier approximation, to determine scheduling precedence of the subsite of the plurality of subsite. The system (100) may help in deciding the depth and location of deploying underground telecom infrastructure project wherein the soil attributes data, obtained after the three-tier approximation is used to determine the safe depth and location of deployment of the infrastructure project.
[0061] FIG. 5 illustrates an example route (500) for which the three-tier approximation technique has been applied. FIG. 6 illustrates the chainage wise report (600) extracted for the example route (500). FIG. 7 illustrates the chainage wise strata indication graph (700) for the example route (500). FIG. 8 illustrates a surface elevation (800) of the example route (500).
[0062] FIG. 9 is a flow chart (900) illustrating a method for three-tier approximation of the soil strata information to predict digging pressure or force required for deploying the telecommunication infrastructure project. The method provides a high resolution soil strata prediction for project resource planning. The method can be well understood in conjunction with FIG. 1.

[0063] At step (902), the method includes generating the first chainage matrix for the predefined area in the XYZ plane. The first chainage matrix defines the volumetric mix of soil and rock types at the predefined depth intervals in the Z plane of the XYZ plane.
[0064] At step (904), the method includes superimposing the surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals, thereby generating the second chainage matrix.
[0065] At step (906), the method includes adding the geomorphological data matrix to the second chainage matrix based on the predefined depth intervals, thereby generating the third chainage matrix. The geomorphological data matrix comprises topographical evolution parameters of the predefined area.
[0066] At step (908), the method includes calculating the force (pressure) required to dig the soil strata at each point in the XYZ plane based on the third chainage matrix.
[0067] The various actions, acts, blocks, steps, or the like in the flow chart (900) may be performed in the order presented, in a different order or simultaneously. Further, in some embodiments, some of the actions, acts, blocks, steps, or the like may be omitted, added, modified, skipped, or the like without departing from the scope of the invention.
[0068] The embodiments disclosed herein can be implemented using at least one software program running on at least one hardware device and performing network management functions to control the elements.
[0069] It will be apparent to those skilled in the art that other embodiments of the invention will be apparent to those skilled in the art from consideration of the specification and practice of the invention. While the foregoing written description of the invention enables one of ordinary skill to make and use what is considered presently to be the best mode thereof, those of ordinary skill will understand and appreciate the existence of variations, combinations, and equivalents of the specific embodiment, method, and examples herein. The invention should therefore not be limited by the above described

embodiment, method, and examples, but by all embodiments and methods within the scope of the invention.
[0070] The methods and processes described herein may have fewer or additional steps or states and the steps or states may be performed in a different order. Not all steps or states need to be reached. The methods and processes described herein may be embodied in, and fully or partially automated via, software code modules executed by one or more general purpose computers. The code modules may be stored in any type of computer-readable medium or other computer storage device. Some or all of the methods may alternatively be embodied in whole or in part in specialized computer hardware.
[0071] The results of the disclosed methods may be stored in any type of computer data repository, such as relational databases and flat file systems that use volatile and/or non-volatile memory (e.g., magnetic disk storage, optical storage, EEPROM and/or solid state RAM).
[0072] The various illustrative logical blocks, modules, routines, and algorithm steps described in connection with the embodiments disclosed herein can be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. The described functionality can be implemented in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosure.
[0073] Moreover, the various illustrative logical blocks and modules described in connection with the embodiments disclosed herein can be implemented or performed by a machine, such as a general purpose processor device, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components or any

combination thereof designed to perform the functions described herein. A general purpose processor device can be a microprocessor, but in the alternative, the processor device can be a controller, microcontroller, or state machine, combinations of the same, or the like. A processor device can include electrical circuitry configured to process computer-executable instructions. In another embodiment, a processor device includes an FPGA or other programmable device that performs logic operations without processing computer-executable instructions. A processor device can also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration. Although described herein primarily with respect to digital technology, a processor device may also include primarily analog components. A computing environment can include any type of computer system, including, but not limited to, a computer system based on a microprocessor, a mainframe computer, a digital signal processor, a portable computing device, a device controller, or a computational engine within an appliance, to name a few.
[0074] The elements of a method, process, routine, or algorithm described in connection with the embodiments disclosed herein can be embodied directly in hardware, in a software module executed by a processor device, or in a combination of the two. A software module can reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of a non-transitory computer-readable storage medium. An exemplary storage medium can be coupled to the processor device such that the processor device can read information from, and write information to, the storage medium. In the alternative, the storage medium can be integral to the processor device. The processor device and the storage medium can reside in an ASIC. The ASIC can reside in a user terminal. In the alternative, the processor device and the storage medium can reside as discrete components in a user terminal.
[0075] Conditional language used herein, such as, among others, "can," "may," "might," "may," "e.g.," and the like, unless specifically stated otherwise,

or otherwise understood within the context as used, is generally intended to convey that certain embodiments include, while other embodiments do not include, certain features, elements and/or steps. Thus, such conditional language is not generally intended to imply that features, elements and/or steps are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without other input or prompting, whether these features, elements and/or steps are included or are to be performed in any particular embodiment. The terms "comprising," "including," "having," and the like are synonymous and are used inclusively, in an open-ended fashion, and do not exclude additional elements, features, acts, operations, and so forth. Also, the term "or" is used in its inclusive sense (and not in its exclusive sense) so that when used, for example, to connect a list of elements, the term "or" means one, some, or all of the elements in the list.
[0076] Disjunctive language such as the phrase "at least one of X, Y, Z," unless specifically stated otherwise, is otherwise understood with the context as used in general to present that an item, term, etc., may be either X, Y, or Z, or any combination thereof (e.g., X, Y, and/or Z). Thus, such disjunctive language is not generally intended to, and should not, imply that certain embodiments require at least one of X, at least one of Y, or at least one of Z to each be present.
[0077] While the above detailed description has shown, described, and pointed out novel features as applied to various embodiments, it can be understood that various omissions, substitutions, and changes in the form and details of the devices or algorithms illustrated can be made without departing from the scope of the disclosure. As can be recognized, certain embodiments described herein can be embodied within a form that does not provide all of the features and benefits set forth herein, as some features can be used or practiced separately from others.
[0078] The foregoing description of the specific embodiments will so fully reveal the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and,

therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.

CLAIM
We claim:

1. A method of generating the high resolution soil strata, the method comprising:
generating a first chainage matrix for the predefined area in an XYZ plane, wherein the first chainage matrix defines a volumetric mix of soil and rock types at predefined depth intervals in a Z plane of the XYZ plane;
superimposing surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals, thereby generating a second chainage matrix;
adding geomorphological data matrix to the second chainage matrix based on the predefined depth intervals, thereby generating a third chainage matrix, wherein the geomorphological data matrix comprises topographical evolution parameters of the predefined area; and
calculating force required to dig soil strata at each point in the XYZ plane based on the third chainage matrix.
2. A method of predicting digging force for a predefined area, the method
comprising:
predicting a first chainage matrix for the predefined area in an XYZ plane, wherein the first chainage matrix defines a volumetric mix of soil and rock types at predefined depth intervals in a Z plane of the XYZ plane;
superimposing surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals, thereby generating a second chainage matrix;
adding geomorphological data matrix to the second chainage matrix based on the predefined depth intervals, thereby generating a third chainage matrix, wherein the geomorphological data matrix comprises topographical evolution parameters of the predefined area; and
calculating force required to dig soil strata at each point in the XYZ plane based on the third chainage matrix.

3. The method as claimed in claim 1, wherein generating the first chainage matrix
comprising:
extracting a plurality of attributes of the XYZ plane, wherein the plurality of attributes is one or more of a slope, a curvature, a topographical position index, a topographical wetness index, an altitude, a lithology, land use data and land cover data;
classifying the extracted plurality of attributes in a geographic information system environment to distinguish strata types at the predefined depth intervals; and
arranging the classified strata types in a volumetric mix of soil and rock types at the predefined depth intervals in the Z plane to create the first chainage matrix for the predefined area in the XYZ plane.
4. The method as claimed in claim 1, wherein superimposing the surface
information to create the second chainage matrix comprising:
refining the first chainage matrix using visual verification from a satellite image by combining a weighted value of time series enabled surface information of the predefined area with the first chainage matrix to create the second chainage matrix for the predefined area in the XYZ plane.
5. The method as claimed in claim 1, wherein superimposing the surface
information on the first chainage matrix to create the second chainage matrix
further comprising:
adding a weighted value of quantitatively scaled additional data matrix to the second chainage matrix, wherein the additional data matrix comprises at least one or more of monsoon information, crop history and anthropogenic information.

6. The method as claimed in claim 1, wherein adding the geomorphological data
matrix to the second chainage matrix comprising:
scaling the geomorphological data matrix of the predefined area to a common scale that matches the second chainage matrix, wherein the topographical evolution parameters of the predefined area are matched with the second chainage matrix in the XYZ plane and adding the scaled geomorphological data matrix to the second chainage matrix to generate the third chainage matrix in the XYZ plane.
7. The method as claimed in claim 1, wherein calculating the force required to dig
the soil strata further comprising:
calculating a geomorphological scaling factor corresponding to the scaled geomorphological data matrix; and
calculating the force required to dig the soil strata of the predefined area in the XYZ plane by changing digging force based on the geomorphological scaling factor of the geomorphological data matrix.
8. The method as claimed in claim 1, wherein the surface information that is superimposed on the first chainage matrix includes time series based land use information, drain line information, stream order, soil colour and land form information.
9. The method as claimed in claim 1, wherein the geomorphological data matrix comprises shape and feature information of landform over a period of time and information regarding chemical and physical processes that transformed the landform over that period of time.
10. A system of predicting digging force for a predefined area, the system
comprising:

generating a first chainage matrix for the predefined area in an XYZ plane, wherein the first chainage matrix defines a volumetric mix of soil and rock types at predefined depth intervals in a Z plane of the XYZ plane;
superimposing surface information on the first chainage matrix by adding the surface information to the first chainage matrix based on the predefined depth intervals, thereby generating a second chainage matrix;
adding geomorphological data matrix to the second chainage matrix based on the predefined depth intervals, thereby generating a third chainage matrix, wherein the geomorphological data matrix comprises topographical evolution parameters of the predefined area; and
calculating force required to dig soil strata at each point in the XYZ plane based on the third chainage matrix.