eChapters

9.1 Introduction

Hydrogen is colourless and odourless gas. Hydrogen is simplest and lightest element and most abundant available element on the earth. It is not primary energy source as it does not exist in free state however it presents in compound with oxygen (water) and carbon, nitrogen and oxygen in living material and fossil fuels (natural gas, coal and biomass). Therefore, hydrogen can be produced from these sources using some external energy. Hydrogen can be burned without generating CO₂ and have clean combustion. but with air it can form very explosive mixture. Hydrogen is considered as an energy carrier. Like energy carrier allows the transport of energy in usable form from one place to another. 

INTRODUCTION
The fuel system in a tractor engine is essential for maintaining efficient engine operation by ensuring clean and well-regulated fuel is delivered to the combustion chamber for optimal performance. Proper upkeep of this system, including regular checks on fuel filters, lines, and pumps, helps extend the engine’s lifespan and guarantees smooth operation during demanding agricultural tasks. The fuel system plays a key role in supplying the engine with precisely regulated fuel for combustion. Core components like the fuel pump, fuel filter, and fuel injectors work together to deliver the right quantity of fuel at the appropriate time, ensuring the engine operates efficiently, performs reliably, and lasts longer.
FUEL PUMP
The fuel pump is responsible for drawing fuel from the fuel tank and delivering it to the engine at the correct pressure. It ensures a consistent and reliable flow of fuel to the fuel injectors or carburetor.
Types of Fuel Pumps
• Mechanical Fuel Pump: Common in older tractors, this pump is usually driven by the engine through a gear or camshaft. It delivers fuel from the tank to the fuel system at a steady pressure.
• Electric Fuel Pump: Found in modern tractors, electric pumps are powered by the tractor’s electrical system and provide more consistent pressure and flow. These are often located near the fuel tank and can be activated by a relay or switch.

INTRODUCTION
The fuel system in a tractor engine is essential for providing the engine with the right amount of fuel to enable efficient combustion. Its primary function is to guarantee a steady and reliable flow of clean, properly atomized fuel, which is crucial for achieving optimal performance and fuel efficiency. The system consists of various components that collaborate to manage different processes such as storing, filtering, and delivering the fuel to the combustion chamber.
These processes must work in harmony to ensure the engine operates smoothly, maintaining both power output and efficiency. Proper atomization of the fuel ensures that it mixes well with air, allowing for more complete combustion and minimizing the chances of fuel wastage or emission of harmful substances. From fuel storage tanks to injectors, every part of the fuel system is designed to meet the demands of the engine under various operating conditions.
A well-functioning fuel system helps maintain engine longevity, reduces fuel consumption, and ensures that the engine can perform at its best across different workloads and environments.
Fuel is a substance consumed by the engine to produce power. The common fuel for Internal Combustion engines are
1. Petrol
2. Power kerosene
3. High speed diesel
Calorific value of fuel
The heat liberated by combustion of a fuel is known as calorific value or heat value of the fuel. It is expressed in kcal/kg of the fuel

4.1 Introduction to Function in Python

Python Functions is a block of related statements designed to perform a computational, logical, or evaluative task. The idea is to put some commonly or repeatedly done tasks together and make a function so that instead of writing the same code again and again for different inputs, we can do the function calls to reuse code contained in it over and over again. Functions can be both built-in or user-defined.

Function means sub-program

1. Function definition

2. Function call

Example:

def message: #function definition

print(?hello python”)

message() #function call

Nutraceuticals and Health Foods

    1.    According to the International Food Information Council (IFIC), functional foods are “foods or dietary components that may provide a health benefit beyond basic nutrition.”

    2.    Nutraceuticals : A product isolated and purified from foods that is generally- sold in medicinal forms are usually associated with food. A nutraceutical is demonstrated to have a physiological benefit or provide protection against chronic disease (Coined originally by Stephen DeFelice in 1989, founder and chairman of the Foundation for Innovation in Medicine, USA).

    3.    The International Life Sciences Institute of North America (ILSI) has defined functional foods as “foods that by virtue of physiologically active food components provide health benefits beyond basic nutrition

    4.    Health Canada defines functional foods as “similar in appearance to a conventional food, consumed as part of the usual diet, with demonstrated physiological benefits, and/or to reduce the risk of chronic disease beyond basic nutritional functions.”

Abstract

Wheat gluten consists mainly of gliadin and glutenin polypeptides. During mixing gliadin and glutenin proteins interact to form a unique viscoelastic gluten network, which is envisaged as being necessary for holding the gases and for producing a light porous crumb textured bread. Recent work has confirmed that the elastic properties of gluten are due to the glutenin fraction, whilst the viscous properties are attributed to the gliadin fraction. Equal amount of these two major protein components of wheat gluten is required for achieving the desired bread quality, but variation in the composition and physical properties of the glutenin polypeptides appear to be largely responsible for the differences in the gluten viscoelasticity and breadmaking potential among wheat cultivars. Recently, associations of gliadin polypeptides with breadmaking quality have also been reported. Using improved protein separation and purification techniques, physical methods and genetic engineering, we are beginning to understand the structure-functional relationship of wheat gluten proteins, but much remains to be explored in the years to come. 

For electromagnetic radiation, there are four “laws” that describe the type and amount of energy being emitted by an object. In the following sections, these four laws of radiation e.g. Planck’s law, Wien’s displacement law, Steffan-Boltzman law and Kirchhoff’s law are described briefly.

Planck’s Law

Planck’s law describes the spectral density of electromagnetic radiation emitted by a black body in thermal equilibrium at a given temperature T. The spectral radiance of a body, B_í, describes the amount of energy it gives off as radiation of different frequencies. It is measured in terms of the power emitted per unit area of the body, per unit solid angle that the radiation is measured over, per unit frequency. Planck showed that the spectral radiance of a body at absolute temperature T is given by

Artificial intelligence and machine learning provide the technological foundation for intelligent agricultural applications. This chapter introduces supervised, unsupervised and reinforcement learning, model-development pipelines, feature engineering and evaluation metrics. It explains how algorithms can be selected and implemented for agricultural datasets that may be noisy, incomplete, variable or weakly labelled. Advanced topics include deep-learning architectures, transfer learning and model optimization. Practical considerations involving preprocessing, interpretability and deployment constraints are also discussed. Agricultural case studies illustrate AI applications in crop-yield prediction, plant-disease detection and environmental modelling. The chapter provides the technical foundation needed to design, evaluate and responsibly implement AI-driven agricultural solutions.

Present day hydrogeomorphological research is the explanation of landscape and landforms: what they are, how they function and have developed with reference to the hydrological conditions. Research is a much more complex undertaking than giving names to landforms or even the study of processes, both in terms of what we mean by process and how explanations are approached. It is worthwhile examining some reasons for this, as it shows the increasing complexity of the subject and lead to ideas of how hydrogeomorphology can be studied. Here are some of the fundamentals required for hydrogeomorphological studies:

Mechanism and Processes

‘Mechanism’ provides explanations in detail by describing physical or chemical effects. ‘Process’ signifies the integration of mechanisms in time. Thus, for example when we talk about ‘fluvial process’ or, more specifically, about the ‘mechanism of saltation’, then we have to discuss about the energy source and processes of carrying the material. A process can thus be viewed as the simultaneous operation of a set of specific mechanisms over a specific time period.

Computational intelligence is central to the development of proactive, personalized and connected healthcare systems. This chapter examines artificial intelligence, machine learning, expert systems, medical-image analysis, IoT, big-data analytics, cloud computing and blockchain as key enabling technologies. It presents intelligent architectures for diagnosis, monitoring, treatment support and secure health-data management. Privacy, cybersecurity, explainability, bias, fairness, scalability and deployment challenges are discussed in relation to practical healthcare implementation. The chapter proposes a research roadmap involving trustworthy AI, advanced privacy-preserving mechanisms, edge-cloud intelligence, digital twins, multi-omics integration and personalized health models. It also emphasizes accessible computational-intelligence solutions for rural and resource-constrained healthcare environments

“I think that there is far too much work done in the world,” writes Bertrand Russell in In Praise of Idleness. Rightly so, a workaholic is not necessarily a valued employee. Why we work, asks Barry Schwartz. Why for most of us work is monotonous and meaningless? Why we have twice as many “actively disengaged” workers in the world as there are “engaged” workers?

Do we work only for money? Some think, work is about pay and nothing more. It is true, people work for money, but not always. Many people work for the challenge, meaning, and engagement it brings. “The lesson here is that just how important material incentives are to people will depend on how the human workplace is structured. And if we structure it in keeping with the false idea that people work only for pay, we’ll create workplaces that make this false idea true,” writes Schwartz.

Greenhouse technology development has made good progress in India during the last two decades, and steps necessary for promoting greenhouse cultivation of flower and vegetable crops have been started. Energy-efficient greenhouse cultivation continues to be an area of active research and development, and this is sought to be achieved through precision equipment and protocols. While the gap between the demand and supply of most horticultural crops remains wide and the country plans to double the production of horticultural crops by 2012, the protected cultivation technology holds the key to meet the targets. It clearly emerges that greenhouse technology has multipurpose application for sustainable development of a hilly zone. During harsh winter which otherwise threatens the survival of human beings in these remote hilly areas, popularization and further improvements in greenhouse management could provide a sign of relief in solitude of white snow cover.

Technology transfer (TT) is entering a transformative phase shaped by globalization, digitization, and the growing role of start-ups in the innovation ecosystem. Traditional linear models of TT where inventions flowed from academic laboratories to industry through licensing are being replaced by dynamic, multi-directional, and collaborative frameworks. This chapter explores emerging trends that will define TT in the coming decades, including open innovation platforms, digital TT ecosystems powered by artificial intelligence (AI) and blockchain, the rise of entrepreneurial start-ups and spin-offs, internationalization of TT through cross-border collaborations, and sector-specific shifts driven by 5G, biotechnology, drones, and green energy. Drawing from global and Indian contexts, the chapter highlights how universities, governments, and industries can leverage these trends to build inclusive, resilient, and sustainable innovation ecosystems.
Three global shifts which will redefine TT
1. Digitization of knowledge: With AI, big data, and blockchain, knowledge and IP can be shared, tracked, and commercialized faster and more transparently.
2. Entrepreneurial ecosystems: Start-ups, incubators, and accelerators are replacing traditional firms as vehicles of commercialization, particularly in deep-tech and frontier technologies.
3. Globalization of innovation: Challenges such as pandemics, climate change, and food security require cross-border TT collaborations, making TT an instrument of both economic and geopolitical significance.

Agricultural decisions are frequently made under uncertainty caused by variable weather, soil conditions, crop responses and market behaviour. Conventional binary logic may not adequately represent such imprecision. This chapter explains how fuzzy sets, membership functions, linguistic variables and rule-based reasoning model conditions such as soil moisture, crop health and yield potential. Applications include irrigation scheduling, fertilizer management, disease diagnosis and greenhouse climate control. Fuzzy logic can connect deterministic mathematical models with real-world variability and complement simulations of crop growth, pests and water dynamics. Its integration with artificial intelligence, machine learning and IoT systems can support adaptive, resource-efficient and climate-resilient agricultural decision-making.

Gasification is a process that turns materials containing carbon, like wood, crops, coal, or waste, into a type of fuel called producer gas or syngas. This is done by heating the carbon-rich material with a controlled amount of oxygen at high temperatures. Gasification is a type of partial oxidation, which means using less oxygen than needed to burn the same amount of fuel. Knowing the necessary amount of air for the conversion process is important to run a gasifier correctly. This requires understanding the stoichiometry based on the composition of the biomass. A chemical formula for the biomass can be calculated by analyzing the elements present, which serves as the basis for estimating the air-fuel ratios through stoichiometric calculations. Gasification only uses 25 to 40% of the theoretical oxidant, producing heat for fuel conversion. In gasification, the main combustible products are carbon monoxide and hydrogen.

Q. 1 Choose the most appropriate word from the options given below to complete the following sentence:
His rather casual remarks on politics ………. his lack of seriousness about the subject.
(A) Masked        (B) Belied
(C) Betrayed       (D) Suppressed

2.1. What is Greenhouse Technology?

Greenhouse technology involves primarily the structural design that can take care of climate control mechanisms to create proper micro-crop-climate and secondarily it involves the technology needed for optimum growth and production of crop grown under this structure. Combination of these two aspects may be expressed as ‘greenhouse technology’.

So the ‘greenhouse technology’ may be defined as “The technology required to built a structure, covered fully, partly or porously for manipulating the inside climatic conditions, under which crops/plants can be grown with special measures”.

Introduction 
Augmented energy demand as well as impacts of employment of fossil coals on human health and environment, stresses and imposes the need to lessen the use of conventional fuels or replace them. Equally, global warming has stretched to a distressing level due to many diverse anthropogenic actions leading to increased pollution. The alternate energy sources are desirable that might be the conspicuous and sustainable approach of enabling environmental remediation, besides meeting the global energy call (Grosser et al 2016, Kanchanasutha et al 2016). A potential solution is generation of Biofuels, either conventional biofuels produced from agricultural crops or advanced biofuels produced from wastes, inedible crops or forestry products (Sreedevi Sarsan et al 2021). Advanced biofuels production especially by the utilization of agricultural and animal wastes using new technologies and processes are gaining increased interest among researchers and general public all over the world. Food waste, municipal trash, animal waste and other wastes can all be utilised as feedstocks to create biogas, a clean and sustainable energy source and thus may be the ideal replacement for traditional energy sources. The raw biomass may be converted into fuel products like biogas by briquetting, gasification, and anaerobic digestion, among other processes (Deepanraj et al 2015). In comparison to landfills, incinerations, and composting processes, anaerobic digestion (AD) is suggested as an inexpensive and environmentally benign technique for the generation of renewable energy (Van Forest et al 2012; Nishio et al 2007; Capson-Tojo et al 2016; Xu, F et al 2018; Cha, M et al 2020). The production of energy-rich biogas and alleviation of issues related to the removal of organic waste are all achieved by anaerobic digestion (AD) of organic solids (Sonakya et al 2001). This is since AD is a highly energy-efficient and ecologically benign technique. In an atmosphere devoid of oxygen, the AD system uses anaerobic microbes to transform the naturally occurring substances in the biomass into biogas. The primary byproduct of AD, biogas, has a methane content of roughly 50-70% by volume and 30- 40% atmospheric carbon dioxide (CO2) when feedstocks are digested under anaerobic circumstances, with small levels of hydrogen sulphide (H2S) (0.1-3% v/v), humidity, and other trace pollutants also present (Sahota et al. 2018). The generation of biogas is known to be influenced by factors such as waste types, pretreatment procedures, the microorganisms or enzymes added, operation circumstances and design of the digestors (Mao et al 2015).

Introduction

Spectral signature: A spectral signature is the unique pattern of reflection and emission of a target at different wavelengths. This difference helps to classify remote sensing images based on the spectral signatures of different objects.

Electromagnetic (EM) spectrum: The EM spectrum is the range of all types of EM radiation. Some examples are visible light from a lamp, radio waves from a radio station, microwaves, infrared light, ultraviolet light, X-rays, and gamma rays.

Spectral response patterns: A spectral response pattern is the amount of energy that an object reflects or emits at different wavelengths. It shows how the object interacts with the EM radiation.

ABSTRACT

Groundwater geochemistry is largely a function of mineral composition of aquifer through which water flows thus, differences in aquifer composition are reflected as differences in groundwater chemistry. To understand water quality and flow pattern multivariate statistical analysis are used due to its relative importance in combining chemical variables and organize voluminous data and group into variables of similar characters. R-mode factor analysis is used in the field of hydrogeochemistry to interpret complex hydrogeological process. A total of 216 samples representing complete lithology like peninsular gneiss, Charnockite and calc gneiss for four different seasons was collected and analyzed for major ions like Ca, Mg, Na, K, HCO₃, Cl, SO₄, NO₃, PO₄, F and H₄SiO₄. Correlation analysis reveals Mg, Cl and Na are spinal and others seasonal. Factor analysis indicates ascendancy of anthropogenic basis followed by lithological weight. Factor score superimpose indicate governing hydrogeochemical regimes spread in western and eastern part. In southern part the same has superior influence than northern part.

Abstract

Water has become a scarce resource all over the World. Water resources of Earth can be classified as surface water and groundwater in which groundwater is the main source for the drinking, domestic and agriculture. The Pudukkottai district is one of the chronic drought prone areas in Tamil Nadu. But, at the same time, the district is pitted with over 5,400 tanks/water bodies widely distributed throughout in general and clustered more in Vellar delta in particular, as the interlobel depressions have provided basic depressions for the surface water to accumulate. However, these surface water bodies are heavily silted. In Pudukkottai district, there are three divergent aquifer systems, hard rock aquifer system in the western, sedimentary aquifer system constituted by the Tertiary Sandstone (Cuddalore Sandstone) in the central and Quaternary aquifer system constituted by fluvial, fluvio-marine and marine systems in the eastern parts of the district.

Introduction to GIS

QGIS (Quantum GIS) is an open-source Geographic Information System (GIS) software has been used to showcase various exercises pertaining to viewing, editing, analyzing, and printing of the geospatial data. QGIS helps to allow the users to easily access and manage geographic data stored in folders on local disks or relational databases available on the user’s network. QGIS supports raster, vector, and mesh layers. QGIS also allows using data from external sources with the help of web services such as Web Map Service (WMS) and Web Feature Service. QGIS is a constantly developing software as anyone can add new features or update existing tools. Newer versions of QGIS are frequently released on the official website. It is a cross-platform software that can be installed in Windows, Linux, and MacOS.

More information, more accurate and timely decision. In present high tech world, the more information you have it is easier to make an accurate decision. The information comes in many different ways, from reports to digital photos. A new way to analyze data is a geographic information system (GIS). GIS allows to bring all types of data together based on the geographic and locational component of the data. GIS is a useful tool for seeking innovative ways to solve the problems.

9.1 What is GIS?

A geographic information system (GIS) is a system designed to capture, store manipulate, analyze, manage and present all types of geographically referenced data. GIS can be defined as a computer-based system for digital entry, storage, transformation, analysis and display of spatial data. A geographic information system integrates hardware, software and geographically referenced data for further analysis. GIS allows users to interpret the georeferenced data in many ways that reveal relationships, patterns and trends.

1.1 INTRODUCTION

Geographic Information System (GIS) is the new emerging field and grows at very rapid pace. Now GIS is a billion dollar industry with applications in varied disciplines. At present, GIS is being used by professionals from various disciplines. In this decade, GIS is being used by experts who are good in GIS technology for various applications. The development trend indicates that GIS will be used by common man in near future and at the same time, advanced GIS analysis will be carried out by GIS experts.

Any technology is developed out of necessity and GIS is of no exception. When a large amount of data were available for water distribution systems, road network, sewer lines, telecom lines, electricity lines, gas pipe lines, state wise population, natural resources etc, it is important to store, maintain and retrieve the data for applications. It is not possible to manually browse through the large amount of paper records. Also even if the data is available in an unorganized way in the computerized environment, it is not useful. Hence if the data are referred to locations in earth surface and the data are stored in an organized way, it is possible to retrieve and analyse the data for applications. Hence the solution is GIS and developed today into reality. Developed countries are using GIS widely in many areas but developing countries are moving towards the development of GIS database for their resources.

Remote sensing, aerial photography, cartography, surveying and other field instruments for attribute data collection contributes to the data acquisition. Cartography, surveying, geography, geodesy contributes for mapping process. Disciplines like computer science and statistics, mathematics involved in processing and analysing data . Computer science and mathematics involved in storing the data structure.

GIS maps are intelligent. It has many advantages compared with paper map in this digital age.

Spatial data means data which are referenced to earth. Maps, satellite imageries, aerial photographs are example of spatial data. Attribute data which are attached to spatial data are called as aspatial data or non-spatial data.

If these data are brought into GIS then it is stored in a standard format, it is possible to update, share, retrieve, manipulate and analyse quickly. Much of the time and money is saved in case of reproduction and better decisions could be made

In modem days, many informations receive through electronic media with instant connecting by satellite based information on social, economical, environmental etc. the informations are coded with feasible electronic encrypt and delivered to people. Similarly remote sensing, GIS (Geographical Information System) and GPS (Global Positioning System) also serve world for better understanding the ground reality along with reducing cost of operation, transforming data through electronic webs easily. In earlier phase, ground related information was not easily obtained because all kind of work had been done manually using analog maps of earth; even map draw was done by drafting from totposheet or hand maps, no interface of analog and digital world.

Introduction

A geographical information system (GIS) is a kind of database that has software tools for handling, analyzing, and presenting spatial data and descriptions of phenomena that have a location component. This system can also involve human users and support staff, procedures and workflows, a body of knowledge about relevant concepts and methods, and institutional organizations in a wider sense. GIS technology is a key part of spatial data infrastructure, which the White House describes as “the policies, technologies, standards, human resources, and related activities that are necessary to acquire, process, distribute, use, maintain, and preserve spatial data.”

Key words : NRSA, Natural Resource and Disaster Management, Agricultural Drought, Ecosystems, Biodiversity Information System, Water Resources, Sea Surface Temperature.

Introduction

A few decades ago, paper maps were the principal means to synthesize and represent geographic information. Manipulating this information was limited to a manual, non-interactive process. Since then the rapid development of new technologies to collect and digitize geographic data, together with an increasing demand for both interactive manipulation and analysis of this data, has generated a need for dedicated software’s namely geographic information systems (GISs).

A GIS is more than a cartographic tool to produce maps. It stores geographic data, retrieves and combines this data to create new representations of geographic space, provides tools for spatial analysis, and performs simulations to help expert users to organize their work in many areas like public administration, transportation networks, military applications and environmental information systems. These above mentioned are few among many others where we are concerned with geographical locations, their present status, its potential for developmental activities, patterns of change over the years and the processes on the surface of the earth.

Geographic information technology is used to manipulate objects in geographic space, and to acquire knowledge from spatial facts. Spatial information theory provides a basis for GIS by bringing together fields that deal with spatial reasoning, the representation of space, and human understanding of space.

Key words : Flood Plains Agro-ecosystem, GIS, RS, Spatial Cropping Pattern, Radiometric Normalization, NDVI, Agricultural Systems.

Introduction

Of late, evidence is accumulating to suggest that high productivity and growth rates achieved during the Green Revolution era in the well-endowed regions of the country (i.e North West India) are no longer being sustained to meet the needs of still increasing population in the country. Past growth sources have nearly exhausted and there is also no scope for expansion of crop land. Indeed pressure for competing land uses will likely reduce area under food grain crops. Shrinking natural resource base (per capita availability of land and water devoted to agriculture), declining quality of resources and environmental degradation issues will imply increasing threat to our ability to meet the basic needs of the growing population of the region unless we shift our effort to potential regions like flood plains of the country for improving productivity.

The flood plain riverine lands of India covering approximately 42 m.ha though most endowed with natural resources and has all the potential of becoming rich, is still economically backward. The reason behind this paradox of extent of poverty in the midst of richness of resources is that the natural resources of the region are not being productively harnessed into the process of the economic development and thus are not delivering their potential and commensurate benefits to the people. The Green Revolution technologies evolved during of 60’s and 70’s had little or no impact in this region of the country. Undesirable spatio-temporal distribution of flood in these areas keeps agriculture under uncertainty and risks. These are also the areas where the poorest are concentrated and agriculture largely continues to be more of subsistence. The nature of agricultural problems are highly variable due to great diversity in the production system as also in the socio-economic conditions of the communities requiring location specific approaches to address the problems and enhance the productivity.

Key words : Glaciers, Glacial Lakes, Glacial Lake Outburst Floods (GLOF), Himachal Pradesh, Glacial Inventory, Glacier Recession.

Introduction

Glaciers are large masses of snow, re-crystallized ice and rock debris that accumulate in great quantities and begin to flow outwards and downwards under the pressure of their own weight. Glaciers form when yearly snowfall in a region far exceeds the amount of snow and ice that melts in a given summer. In this way, massive quantities of glacial material accumulate in relatively small periods of geologic time. The glaciers exist in environments of high and low precipitation and in many temperature regimes; they are found on all the continents except Australia and they span the globe from high altitudes in equatorial regions to the polar ice caps. Presently, 10% of the Earth’s land area (5.8 million square miles) is covered with glaciers storing about 75% of the world’s freshwater. However, during the last Ice Age, glaciers covered 32% of the total land area of the planet.

Introduction

Precision Farming (PF) revolves around the idea that any agricultural land contains wide spatial variations in soil types, nutrient availability, and other important factors. If these variations are not taken into account, then there may be a loss in productivity. Precision farming is one of the most scientific and modern approaches to sustainable agriculture that has gained momentum in 21^st century. Consider the situation: ‘A farmer goes to his/her field with his/her Global Positioning System (GPS) guided tractor. The GPS senses the exact location of the tractor within the field. It sends the signal to a computer on the tractor that has a Geographical Information System (GIS), storing the soil nutrient requirements map in it. GIS, in consultation with a Decision Support System, decides what is the exact requirement of the fertilizer for a given location and then commands a variable rate fertilizer applicator, attached with the tractor, to apply the exact dose at that precise location. All this is done within a second, before the tractor moves further.’ This may sound like an excerpt from a scientific fiction, but this is what precision farming means to the large growers of the United States or European countries and day is not far off when it will be feasible for large Indian farmers as well.

PF refers to a developing agricultural management system that promotes variable management practices within a field according to site or soil conditions. Within a short span of time, this concept has been described with various names viz. farming by soil; farming soil, not fields; farming by the foot; spatially prescriptive farming; computer aided farming; farming by computer; farming by satellite; high-tech sustainable agriculture; soil-specific crop management; site-specific farming; and site-specific crop management.

Key words : Wasteland Reclamation, Poverty Indicators, Food Insecurity, Alternate Livelihood Systems, Rural Infrastructure Index.

Introduction

The countries of Asia and the Pacific region accounts for nearly two-thirds of the chronically poor and undernourished in the world. FAO estimates indicate that, by 2010, Asia will still account for about one-half of the world’s malnourished population (FAO 2000). In Asia, poverty has mainly been rural phenomenon and nearly three-fourth of the poor live in rural areas, with large majority of them dependent on natural resources for employment and income. South Asia, which had a poverty incidence of 43 percent (or about 520 million people), contributed about 40 percent of the world’s poor. Development of natural resources thus offers a potentially enormous means of poverty reduction.

In developing countries poverty and environmental deterioration are often viable in proximity to each other, and have led many to infer that a two-way causality exists between human and environmental degradation. Environmental degradation usually occurs when production and consumption activities of growing population irreversibly weaken nature’s recycling capabilities. These economic activities are also attributed to the development of markets, the advent of modern technology, and the spatial integration of inaccessible areas to market systems. In many developing countries, however, environmental degradation such as soil erosion, deforestation and pollution are most visible around poor settlements, leading some policy makers to highlight the direct links between poverty and the environment.

One has to recognize that both poverty and the environment are descriptions of states of human and natural resource attributes and cannot be reduced to simple one-dimensional cause-effect relationships. Apart from conceptual difficulties in modeling linkages, another handicap has been the absence of adequate or reliable data sets on poverty and environment characteristics. The challenge for operational research is exploring how circumstantial evidence and inductive logic can be used to explain the nature of interactions between the two states. Based on nationwide wasteland statistics vis-à-vis state and district wise poverty estimates available with the concerned agencies, this study is one such attempt, and evaluates the incidence of poverty with the backdrop of natural resources degradation and role of institutional interventions with illustrations from India.

Abstract

The Pudukkottai district located in the southeastern tip of Tamil Nadu, India provides a complex geological setting with three litho-tectonic blocks membered by the hard Crystalline rocks of Archaeozoic-Proterozoic Era in the west,Mio-Pliocene Sandstone/Cuddalore Sandstone in the centre and Quaternary sediments in the east. While the western and central blocks are separated by a well-defined NNE-SSW trending fault, the central Mio-Pliocene Sandstone block is cut into two parts by a N-S fault with western static block and the eastern uplifted counterpart. Besides the above, the various drainage anomalies viz; Annular, Deflected and Eyed drainages and compressed meanders interpreted using the raw and digitally enhanced satellite multispectral data show that the N-S oriented faults with oscillations from NNW-SSE to NNE-SSW, NE-SW and E-W orientations are tectonically active in the area. The integration of these active faults with known geothermal springs and the maxima axes drawn from the contours deducted from the temperature of groundwater measured during the predawn hours from the wells revealed that the N-S and NE-SW faults are the probable locales for geothermal resources in the study area. Thus the study demonstrates a newer methodology for locating the geothermal prospects.

Abstract

The Tamil Nadu is one of the leading states in groundwater development. Since the surface water resources have been fully exploited for irrigation, the groundwater is massively mined for agriculture, domestic and industrial purposes. The paper provides a synthesis of whole groundwater related issues including basin wise groundwater conditions, the aquifer types, geogenic water quality and quality deterioration due to anthropogenic activities, need for recharge, the utility of Remote Sensing & GIS etc. The paper has come out with set of recommendations as the concluding remarks.

Introduction

Geomorphology is the study of earth’s landscapes over time and space, and involves an analysis of both its surface features as well as the processes responsible. Historically, the subject evolved through monumental studies on supposed evolution of the landscape, based on intuitive knowledge of the researchers on landscape response to endogenic and exogenic forces, as well as visions of possible changes over a time scale of centuries to millennia or more. Too much emphasis on the study of possible landscape evolution in an era of little technological back-up facilities meant that the discourses were largely philosophical in nature, with fewer measurable parameters to substantiate the concepts or the reasoning, although reflecting deep understanding of the researchers involved. As older concepts began to be confronted with newer ones, and applied aspects started receiving greater attention, a need was felt for quantification of the features and processes. This was more so for an understanding of the fluvial landscape, although aeolian and other process-based studies also gradually incorporated quantitative analysis as a means of understanding the landscape. Despite the awareness, lack of adequate equipment hindered the progress of quantification in the pre-World War II period.

Abstract

Natural resources and agricultural production processes vary spatially. Capturing the spatial variations in data and knowledge of natural resources and production processes has been a major challenge for efficient and sustainable management of agricultural production systems. Geographical Information Systems (GIS) provide an effective platform for storing and mapping spatial data and modeling the relevant processes. Huge volumes of geospatial data on specific themes such as soils, water, climate, and other natural resources, are being collected by public and private agencies. However, currently it is difficult for most users to access the data and integrate them into a GIS platform to derive useful information and knowledge for specific applications. There is a need to create geospatial data and knowledge systems that can provide efficient, on-demand and remote access of spatial data to users to enable development of a variety of GIS applications for agricultural and natural resources management. The design of a prototype geospatial library to provide web-based access to geospatial data, services, and learning and knowledge resources that can support agricultural and natural resources management is presented. The design is scalable and sufficiently general to allow a range of agricultural and natural resources management applications across different spatial scales.

Keywords: Agriculture, GIS, Geospatial library, Knowledge Management, Natural Resources

Abstract

Any naturally occurring phenomena varies both in space and time. This variability is a result of various natural process and hence deterministic. Geostatistics is a tool to help us to characterize spatial variability and uncertainty resulting from imperfect characterization of the variability. Geostatistics involves the theory of regionalized variables, which dates back to the early fifties and includes concepts of random function and stationarity. Geostatistical mapping can be defined as analytical production of maps by using field observations, explanatory information, and a computer program that calculates values at locations of interest. There area number of spatial prediction models depending on the amount of statisticsinvolved in the analysis. Kriging is a generic name adopted by the geostatisticians for a family of generalized least- squares regression algorithms and various kriging algorithms viz., punctual kriging, block kriging, co-kriging and universal kriging are explained in this paper. Applications of geostatistics can be found in many varied disciplines ranging from the geology to soil science, hydrology, meteorology, environmental sciences, agriculture and even structural engineering and some of its applications are summarized in this paper.

Keywords :Geostatistics, spatial variability, kriging, model

13.1 Introduction

Geothermal energy is the nature-based heat generated from within the earth. Underneath the earth’s relatively thin crust, temperature range from 1000 to 4000°C & in some areas, pressures exceed 138 MPa is available. Geothermal energy is most likely generated from radioactive thorium, potassium and uranium dispersed evenly throughout the earth’s interior which produce heat as part of the decaying process. This process generates enough heating, keep the core of the earth at temperature approaching 400°C. Composed primarily of molten nickel & iron, the core is thought to be surrounded by a layer of molten rock, the mantle at approximately 100°C. Nine major crustal plates float on the mantle & currents in the mantle cause the plates to drift, colliding in some areas and diverting in others. When two continental plates converge a complex series of chemicals in the form of molten magna rises in the earth’s crust and depending upon its magnitude, it may break the crust and reach at the earth surface. Volcano, hot spring, geysers & fumaroles are natural geothermal resources near the surface and perhaps where economic drilling operations can tap their heat and pressure.

Abstract

The sustainable management of plant genetic resources is of great concern as increasing population and rapid technological strides are putting enormous pressure on this country’s nutritional and food security. Management of plant genetic resources at national level generates and uses enormous data and analysis of these data is crucial to the effectiveness of PGR management process and can add significantly to the value of genetic resources. A GIS is a database management system that can simultaneously handle data representing spatial objects and their attribute data. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts. It can play an important role in the management of large and complex PGR datasets. The article analyses the potential uses of GIS in plant genetic resources management in India covering various activities such as germplasm exploration and collection, characterization and evaluation, plant health management, documentation and conservation.

Key words : plant genetic resources, germplasm, conservation, documentation, DIVA-GIS,

Abstract

The study area falls in the southern part of the Indian Peninsular comprising hard crystalline rocks of Archaeozoic and Proterozoic Era. In the present study, the GIS based 3D visualizations of gravity, magnetic, resistivity and topographic datasets were made and therefrom the basement lineaments, shallow subsurface lineaments and surface lineaments/faults were interpreted. These lineaments were classified as category-1 i.e. exclusively surface lineaments, category-2 i.e. surface lineaments having connectivity with shallow subsurface lineaments and category-3 i.e. surface lineaments having connectivity with shallow subsurface lineaments and basement lineaments. These three classified lineaments were analyzed in conjunction with known mineral occurrences and historical seismicity of the study area in GIS environment. The study revealed that the category-3 NNE-SSW to NE-SW lineaments have greater control over the mineral occurrences and the N-S, NNE-SSW and NE-SW faults/lineaments control the seismicities in the study area.

Abstract

Runoff from rainfall is an important component of the hydrological cycle. Estimation of runoff is critical for the design of hydrological structures and drainage systems in watersheds. Different soils, land use, and water management practices affect runoff differently. In real watersheds, land use, soils and weather conditions vary spatially over the geographical area of the watershed leading to spatial variations in runoff. Also, most watersheds form a part of larger drainage basin or a large watershed consisting of several such subwatersheds. Each subwatershed is hydrologically connected to the other subwatersheds of the basin. A comprehensive GIS based decision support system (DSS) for estimation of runoff that includes the spatial variations in rainfall and natural resources is presented. The DSS is developed as a deployable application by integrating independent GIS layers of watershed features created in ArcGIS with MapObjects in VB, for a case study watershed - the KK3 watershed in Mahbubnagar district of Andhra Pradesh, India. The DSS generates thematic maps of spatial variations in runoff on individual rainy days for the subwatersheds.

Keywords : GIS, GUI, Land use, Rainfall, Remote Sensing, Runoff, Soil, Sub-watershed, Watershed 228 Geospatial Technologies for Natural Resources Management

INTRODUCTION

Coastal zones are always dynamic and active, because of the multivariate morpho tectonic and morpho dynamic processes, viz: tectonic, fluvial, marine and aeolian which act in varying degrees and duration along the coasts. As these geomorphic / morpho dynamic processes act in varying permutations and combinations in different segments of the coasts, the land - ocean interactive phenomenon vary greatly in time and space, which in turn frequently and dynamically alter the coastal environment, and cause fragility to the coastal ecosystems. Further, as the coastal zones act as the junction between the Continents and the oceans, even mild earth movements exhibit exemplified expressions in land - water distribution pattern along the coasts. The green house effect and the much apprehended sea level rise and the disasters like cyclones also contribute in their own way in accelerating such land - water distribution / land - ocean interactive phenomenon.

Abstract

The emergence of Remote Sensing and GIS technologies has substantially eased the problems of groundwater targeting in hard rock aquifer systems. Proper utilization of these can provide more vital information in managing such scarce resource. In this context, a new technique of GIS based visualization of groundwater levels of different periods (1985- 1990 -1995) was attempted for a part of Western Ghats hill-plain region of Tamil Nadu and various groundwater features viz: ridges, valleys, domes and basins were interpreted. The integration of such groundwater features of different periods and their analysis with structural features provided some newer information on geosystem processes and their interface dynamics with hydrosystems, from which, certain strategies were suggested for better groundwater management in hard rock areas.

Topology building

Boolean operations

Query and model building

Customization

Introduction

At human scales, the world consists of objects, events, processes, and a background environment. Cognition is about knowledge: its acquisition, storage and retrieval, manipulation, and use by humans and other intelligent creatures. Cognition includes sensation and perception, thinking, imagery, reasoning and problem-solving, memory, learning, and language. Cognitive structures and process are part of the mind, which emerges from a brain and nervous system inside of a body that exists in a social and physical world. Spatial cognition deals with the cognition of spatial properties of the world, including location, size, distance, direction, shape, pattern, movement, and inter-object relations. GIS design will be largely influenced by spatial cognition.

8.1 INTRODUCTION

To implement a good GIS project, a well structured project design and management are essential. Well planned project will give fruitful result within the stipulated time. Project not completed in time will not incur more cost and also the time delay will add negative value to the project. Hence all the elements in project planning and implementation should be considered to have a desired result. Some of the issues are also present in GIS and they will be rectified in the next decade.

8.2 PROBLEM IDENTIFICATION

Any project is coming into reality due to necessity. If water scarcity is more in a hard rock region with sufficient rainfall, it is important to augment groundwater resource using rain water harvesting structures. It is important to build water harvesting structures like check dam, percolation pond in suitable locations so that groundwater recharge will be more. Hence a problem is identified and the project work may be carried out by a government or private organisation and the result is given to the government to implement the project. Likewise many area may require a project in GIS environment for planning. Once a project is created any development taking place can be added and GIS database is updated.

3.1 INTRODUCTION

Geographic Information System handles large volumes of data. It is important to know the nature of data, instruments from which the data is collected and represented in computers. GIS data is either spatial or aspatial. Data is an important component in GIS. Digital data are available for some projects. but for many projects, input data may not be available. Now-a-days, data is supplied by many government, private organizations and also available on internet. If data for a particular project is not available, then the user has to collect the data from satellite imageries, GPS and other instruments and maps from various sources.

Spatial Data

All locations in the earth surface are spatial data. Location of a city, location of a river, location of a lake are represented in earth by their latitude or longitude in global coordinate system or as x,y coordinate in Cartesian coordinate system. Spatial data consists of location, shape and size in earth. A village boundary is represented as a polygon in map. The village is having certain shape of irregular polygon with definite area. As all these are mappable , they are called as spatial data. But name of the village, revenue of a village and description about a village and called as non-spatial or aspatial data.

Abstract

Geographical Information Systems (GIS) application in plant genetic resource management allow capture, manipulate, process and display of georeferenced data integrated with genetic resource database for operations such as query and statistical analysis, visualization and geographic representation. GIS based several spatial tools have been developed that model species’ ecological niches finding a relationship between crop or variety with a set of environmental parameters and useful for planning exploration, evaluation trials, in situ and ex situ conservation sites. GIS technologies have direct practical application in elucidation of genetic, ecological and geographic patterns in the distribution of crops and wild relatives; mapping of richness, diversity, distribution of useful traits and, location of areas with complementary diversity; gene bank information management and strategies for future explorations and gap analysis; selection of suitable accessions/sites for ex situ evaluation; searching germplasm for abiotic stress tolerance and developing core collections. With the increasing availability of high- speed computers and software development in the area of GIS tools specific to PGR management increasing trend in application of these is expected. Apart from ecogeographic survey for locating diversity and germplasm collection and design, management and monitoring of in situ reserves, introduction of new varieties, and development of core collection, locating gene donors for biotic and abiotic stresses are the areas to be benefited with the GIS application.

Keywords: GIS, genetic resource, distribution, diversity, core collection, gap analysis, mapping

Introduction

Rainfall is one of the climatic variables that varies very highly spatially and temporally. Understanding this micro-level variation is a crucial indicator for planning future water requirements and preparing for management strategies. Numerous researchers have delved into the distribution, variability, and trends of rainfall across diverse spatial scales, ranging from global to regional and basin levels. Nair et al. (2014) analyzed the rainfall trend and seasonality index for Kerala state in India over the last 100 years. The rainfall trend was found to be decreasing significantly in almost all the regions of the state. Nischitha et al. (2013) provide insights into the spatial and temporal variability of daily monsoon rainfall in the Tunga and Bhadra River basins in Karnataka state. Paradkar et al. (2019) evaluated the pattern of weekly rainfall by using statistical parameters such as mean, standard deviation, skewness, and kurtosis for five stations in Pratapgarh district.

Geographical Information System (GIS) proved to be an effective tool in handling information and analyzing rainfall patterns, providing visual representations, and facilitating the decision-making process (Kadir et al. (2016) and Rao et al. (2017)). Anand et al. (2020) analyzed the long-term spatial and temporal trends of rainfall in the Lower Bhavani basin in Tamil Nadu, India using GIS and statistical methods. Earls et al. (2007) compared different interpolation methods such as Inverse Distance Weighting, Spline, and Kriging (ordinary and universal) to generate a 30 m representation of the rainfall data. Spatial interpolation techniques perform differently and their evaluation should not rely solely on quantitative assessment. Wu & Hung (2016) compared the performance of three spatial interpolation techniques i.e., IDW, kriging, and spline using quantitative assessment, 2D visualization, and 3D visualization. IDW and kriging performed similarly in terms of quantitative assessment, while spline performed worse. IDW and spline performed similarly in 2D visualization, while kriging showed different behavior. Kriging was observed to be an inexact interpolation in 3D visualization, while spline tended to create extreme values along the edges of the study area. Some studies discovered that the accuracy of Kriging in the study area is higher than that of IDW or Thiessen interpolations (Earls et al. 2007; Song et al. 2008; Chen et al. 2010). GIS applications have the capability to integrate spatial data and non-spatial data like rainfall and to visualize, model, and analyze how rainfall distribution varies across space and over time, providing insights into climate change, water resource management, agricultural planning, and disaster management. The present study aims to analyze annual rainfall data pertaining to Kerala state in the GIS environment.