eChapters

Throughout human history, people across the globe have sought to understand and predict the ever-changing skies. From the scorching deserts of North Africa to the lush rainforests of South America, and from the snow-capped Himalayas to the vast Australian outback, ancient cultures developed unique methods to forecast the weather. These traditional knowledge systems, often passed downthrough oral traditions and  storytelling, reflected the specific environmental contexts, mythological beliefs, and spiritual practices of each community. In ancient China, royal astronomers meticulously recorded weather patterns and planetary movements to guide agricultural planning and imperial decisionmakingIn Greece, philosophers like Aristotle and Theophrastus wrote extensively on weather signs and forecasting methods. In Africa, tribal communities observed animal migrations and plant behaviors to anticipate seasonal changes. Native American tribes used lunar cycles and star constellations to predict weather patterns, while ancient Indians studied the movements of planets and nakshatras (lunar mansions) to forecast monsoon rains.

Introduction 
Chapter 12 explores the pivotal role of animal husbandry and veterinary sciences in managing livestock and ensuring food security while addressing global environmental challenges. The chapter covers various aspects of animal care, including livestock management, nutrition, health, and the broader implications of these practices on food security and climate change. The chapter begins with an examination of livestock management and production systems, focusing on the different systems used in animal husbandry, such as extensive, intensive, and semi-intensive systems. It highlights the principles of efficient livestock management and the need for sustainable practices to optimize productivity while minimizing environmental impact. Animal nutrition and feed management are crucial for maintaining livestock health and productivity. This section discusses the importance of formulating balanced diets that meet the nutritional needs of different animal species, the role of feed management in improving feed efficiency, and the impact of nutrition on animal health and production. Animal health and disease management are central to ensuring the well-being of livestock and preventing the spread of diseases. The chapter explores common animal diseases, methods for disease prevention and control, and the role of veterinary sciences in maintaining herd health and productivity. The importance of animal sciences, poultry science, fish science, and related disciplines in food security is addressed, emphasizing how advancements in these fields contribute to reliable and efficient food production. The chapter highlights how these sciences support the development of sustainable practices and technologies that enhance food security. The impact of these sciences on global warming is examined, focusing on both direct and indirect effects. The chapter discusses how livestock production contributes to greenhouse gas emissions and explores strategies for mitigating these impacts through improved management practices and innovative technologies. Modern concepts in animal sciences, poultry science, and fish science are reviewed, showcasing recent advancements and their implications for sustainable livestock management and food security. The chapter discusses new approaches and technologies that are shaping the future of these fields

Abstract

This study was conducted at Directorate of Cashew Research (DCR) Puttur, D.K., Karnataka during 2007-12. In this study, a methodology was standardized to find the area under cashew, barren areas and other areas for expanding cashew cultivation with remote sensing. It was found that the images pertaining to the month of November was best for classifying cashew since the colour of cashew leaves changes during that period. Also, the LISS III images were found to be good for identifying cashew. It was not possible to differentiate between cashew seedling area and cashew graft area using LISS III or LISS IV images. A spatial database of soil moisture was prepared for the irrigation scheduling in cashew and a spatial database of major nutrients was prepared for the site specific nutrient management in cashew gardens. A spatial database of land slope and stream orders was prepared using GIS and suitable soil and water conservation interventions were suggested for the selected area.

Keywords: Cashew, GIS, remote sensing

Introduction

Natural Disasters are inevitable, and Indian subcontinent is prone to all type of Natural Disaster either it is flood, drought, cyclone, earthquakes, tsunami or forest fires etc. Disasters can be classified in several ways. A possible sub-division of disaster is: (i) Natural Disasters; (ii) Human made disasters; (iii) Human induced disasters. Another sub-division is related to the main controlling factors leading to a disaster. These may be meteorological, geomorphological/geological, ecological, technological, global environmental and extra terrestrial. Another useful distinction that can be made between disasters is regarding their duration of impact and the time of forewarning. Some disaster strikes within a short period with devastating outcomes; others have a slow onset period with equally or more serious repercussions. According to the available statistics 60% of the total area of Indian subcontinent is venerable to seismic activity of varying intensities, 16% of the country’s total area is drought prone. In India 68% of total sown area of the country is drought prone. Coastal areas of India is exposed to tropical cyclones, tsunami in recent years and among all the disaster occur in the country, River floods are the most frequent and often the most devastating.

Abstract

Soil Resource Appraisal helps in characterizing the existing land resources, assessing their suitability for various land uses and then helping the user to prepare a rational land use plan suitable for the integrated development of the area. Application of Remote Sensing (RS) and Geographical Information System (GIS) helps not only in the characterization of the resource base, but also in the generation of various thematic maps and preparation of land use and action plans for effective implementation of various developmental plans at farm level.

Keywords : Soil Resource Appraisal, Land Use Plan, Farm level Developmental Plans

1.0 Introduction

A thorough knowledge and understanding of soils is basic to the development and management of agricultural resources. About 100 years ago, man began systematic study of soils in the field and tried to separate, classify and map their geographic distri­bution. Today we have sufficient knowledge about soils; however the characterisation, classification and mapping of soils is still tedious, time consuming and costly affair. Therefore the need for adopting new and more rapid and accurate methods of mapping soils has resulted in the use of satellite images with image interpretation techniques for soil survey and map­ping.

In India for the country as a whole, soil and other land resources information is available at 1:1 M scale, which was generated from the state level mapping done at 1:250,000 scale under the Soil Resources Mapping Project of India during the period from 1986 to 1995. This information is of general nature and useful for planning on a wide canvas and not particularly useful for farm or watershed level planning in the country. For site-specific needs and for developmental works at watershed level, we need detailed farm level database at 1:10,000 scale. Once this type of information is generated at village/watershed level, this will be useful for identifying site specific constraints, generation of area and site specific agro technologies, land-use options based on soil site suitability assessment, wasteland identification, identification of prime farm lands and farm clusters for zoning and Strategic planning, preparation of farm level development plans by line departments and proactive advice and technology transfer to farmers.

ABSTRACT

In Tamilnadu majority of the people are engaged in agricultural work and they mainly depend upon the water resources. But at present both surface and subsurface water has become deficient because of over exploitation. Since last few years, conventional methods were employed to improve the surface and subsurface water conditions. But these methods provide less accurate result and consume more time. So to improve the conditions modern tools, such as remote sensing and GIS are being used to identify the ground water potential zones in Tamilnadu. It provides accurate resulst and consumes less time.

A project was carried out in Gadilam lower sub basin which falls in the part of Cuddalore District, Tamilnadu. The IRS 1D imagery was collected and interpreted using image processing software and Geo media GIS Software in conjunction with collateral data to prepare Hydro geomorphology, land use, geology and lineament maps Field checks were made and transferred the field data on the base map. By application of overlay analysis of the above thematic maps, using GIS techniques, the recharge zones were identified.

The satellite image mosaic map of Gadilam lower sub basin was generated to identify ground water potential zones. Average monthly rainfall data for the past 50 years were collected. Using Remote sensing and GIS techniques, the thematic maps such as Geology, Geomorphology, Soil, Drainage, Land use, Lineament zones have been generated for this study. Geophysical survey was also conducted in various locations and the aquifer parameters were measured. Details related to land and water resources, cropping pattern, water levels and water qualities from PWD ground water division, land use and well censes data of villages from village Administrative Officer, tank details from PWD were collected and analyzed

After analyzing the various thematic maps, they were finally overlaid. Thus the groundwater potential zones of Gadilam lower sub basin was identified.

ABSTRACT

The present paper highlights the implication of geochemical strategic tools to choose suitable site selection on the coastal region. Geochemical tools and geomorphological survey have been also deployed to identify the suitable site. The geomorphology of the site A reveals enough fresh water accumulation was found and the two elevated crest and the adjacent trough (low land) with surrounding areas further support the fact. The water quality of this site exposes very good quality (< 200ppm TDS) and the dissolved major anions (HCO3, SO4, Cl) and cations (Ca, Mg, Na, K) concentration are well within drinking water standards. The soil samples are of medium to coarse sand nature showing high porosity (40 to 50%) with mica flakes acting as less permeable in nature. The water quality shows very good in nature and similar to Site A. The soil characters additionally proved good in porosity and permeability (SAR 1.5 to 2.1).

2.1 INTRODUCTION

GIS is a tool that can be used in varied disciplines ranging from civil engineering to business. Remote sensing data is often brought into GIS to have a complete data set in many natural resource application areas. Full capability of GIS is not used widely. Many a times people use GIS only for digitising maps and to do simple query on maps. But it can also be used in modeling, simulation and forecasting, only then one may regard GIS technology is utilised to its full potential. Some GIS softwares handle simple problems for location based services while other complex softwares posses advanced modules to do all types of spatial, network and 3D analysis. Integration of softwares used in natural resources study are being interfaced with GIS to create scenarios.

Remote sensing and GIS technology is useful in the following fields:

Abstract

Remote sensing is the art and science of obtaining information about an object or phenomenon without having any contact with the object concerned. Geographical information system is a tool to create, manage, retrieve and query spatial databases. Remote sensing in conjunction with Geographical Information System (GIS) has wide applications in all spheres of life and especially in agriculture. Specifically, this paper reveals some of the applications of remote sensing and GIS in the field of crop condition assessment viz., crop type classification, crop stress detection, crop yield estimation and pest and disease monitoring.

Keywords : Remote Sensing, GIS, Yield Forecasting, Crop Stress, Pest and Disease Monitoring

1.0 Introduction

Remote sensing is the art and science of obtaining information about an object or phenomenon without there being any physical contact. The information is so collected using a device called a sensor. The sensors are mounted on a platform at an advantageous position. Accordingly the remote sensing is called ground based (sensor is hand held or mounted on mast), air borne (sensor is on a balloon or aero plane) or space borne (sensor is mounted on a satellite). The basic principle in remote sensing is that each and every object has unique reflecting property like human thumb impression and when the solar energy is falling on an object a part of it gets reflected, which carries the information about the object. The reflected light is converted in to reflection percentage of incoming solar radiation. This percentage of reflection can be used to work out the vegetation indices which are surrogate measure of crop condition.

Geographical Information System (GIS) is software system which enable Collection of large volume of data with spatial relation Integration of data from different source is possible Analyze such data for our requirement Present the data in different formats (maps, table and reports)

Applications of Remote Sensing

The era of satellite remote sensing was open in the 1960s when cameras and electronic sensors were mounted on spacecraft. Nowadays there is a big assortment of satellite systems actively recording information about the Earth. A wide variety of imagery is available from satellites. Both active and passive sensors, operating from the microwave to the ultraviolet regions of the electromagnetic spectrum collect a large amount of information about the earth’s surface every day. Each of the systems vary in terms of their spatial, spectral, radiometic and temporal resolution. Those characteristics play an important role in defining which applications the sensor is best suited for. The main benefits of satellite remote sensing are the following:

Abstract

Any country’s socio-economic development essentially depends on land and water resources. Resource depletion takes place when there is an overstretching due the exploding population, calling for prudent management of the resources. Application of remote sensing and Geographical Information System (GIS) tools in the management of natural resources at different levels including watersheds is quite well known. In addition, applied geoinformatics are also used in research on management of these delicate resources also besides characterization. There is a continuous advent in technology in both hardware and software necessitating updation of application scientist/manager. Once an exclusive tool of elite institutions and government agencies, GISnow became an indispensible part of our day-to-day life. As the urge for information intensifies, new applications of GIS continue to evolve. A concerted effort is needed to develop an information system when vast expanses of natural resources are to be managed and a combination of information tools like remote sensing, global positioning system and GIS always updates the database effectively. However, the cost factor should not hinder the applications at micro level. This necessity calls for attention to popularize free and open sources of software (FOSS) and data (particularly digital elevation models (DEM) and satellite imagery) to put the techniques into use by enthusiasts at village level such that a database at a regional level can be built through participatory GIS. It is in this direc tion the av ailab le li terat ure on appl ied geoinformatics coupled with use of FOSS is reviewed and presented in this article to give an idea as to how an open ended information system could be developed to help the management.

Keywords: Natural resources, management, Remote sensing, GIS, FOSS, DEM

This chapter introduces approaches for understanding, assessing, and reducing the vulnerability of forest ecosystems to climate change. It examines the impacts of changing climatic conditions on forests and considers factors such as forest fragmentation, biodiversity, tree density, disturbance, and community dependence on forest resources. The chapter discusses methods and models for vulnerability assessment, including indicator-based and spatial approaches, and explains how vulnerability can be mapped and classified. It also considers strategies for minimizing climate impacts and enhancing forest resilience through appropriate management and conservation interventions.

This chapter integrates case studies, scientific examples, and policy perspectives to illustrate how AI and ML can transform agricultural weather intelligence. The discussion spans from advanced predictive models in developed nations to emerging applications in technology-limited regions, while also addressing the urgent need for resilient crisis management systems in the face of natural and human-caused conditions. Advanced scientific techniques can not only optimize food production and resource management but also play a critical role in recovery efforts during times of crisis. Agriculture is intrinsically linked to the natural world—a domain defined by fluctuating weather patterns, seasonal shifts, and unpredictable environmental factors. Today, Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing how we analyze and predict weather patterns, and their applications in agriculture are far-reaching (Fig. 5.1). From forecasting crop yields and fishery conditions to managing plantations and monitoring livestock health, these technologies are creating a paradigm shift in agricultural weather intelligence. Scientific organizations worldwide are leveraging AI and ML to refine predictive models, enable multi-variate analysis, and provide advanced warning systems for extreme events such as droughts, tsunamis, earthquakes, and even crises caused by human-made conflicts. Emerging nations with rapidly growing technological capabilities stand to benefit immensely from these innovations, tailoring solutions to local challenges while contributing to global food security and crisis resilience.

Abstract

Higher temperature and altered rainfall patterns accompanied by extreme weather events are being considered indications of climate change. These factors impact vegetation growth in natural forest, open scrub and in agriculture land. Vegetation index based on satellite data was used to analyse agricultural vulnerability in India to understand impact of rainfall variability. Time-series Normalized Difference Vegetation Index (NDVI) data products obtained from AVHRR (1982 to 2006) and MODIS (2000-2011) were analyzed to assess spatial and temporal variability. Coefficient of variation of maximum NDVI was assessed for the study period and results were corroborated with Standard Precipitation Index (SPI) instead of actual rainfall. Resolution of AVHRR time-series data facilitated study at regional-scale while MODIS datasets with 250m pixel resolution helped in identifying vulnerability at district-level. Study indicated that over 241 Mha areas in the country may not be vulnerable to rainfall variability induced climate change while over 81.3 Mha in arid, semi-arid and dry sub- humid regions may be vulnerable. Study indicated that over 12.1 and 1.81 Mha of Kharif cropland would be mildly and severally vulnerable while 6.86 and 0.5 Mha of Rabi cropland may be adversely affected in a similar manner. Study indicated that length of cropping season was decreasing due to delay in start of season. The paper also presents analysis of variations in SPI and resultant NDVI in typical drought and flood years in the country.

Keywords: MODIS, AVHRR, NDVI, Rainf ed Agricul ture, Vulnerability, Climate Change

Abstract

Land development in urbanized watersheds poses a potential of increasing storm runoff rates, and therefore increasing the risk of flooding in the downstream areas of a watershed. To investigate the impact of change in land use practices on the watershed hydrology, an hydrological analysis was conducted on Little Kitten Creek watershed located near Manhattan city of Riley county, Kansas, USA. Prior to development, land use types in the watershed included woodland, pasture, and fallow land. However, rapid development has occurred in the watershed in the last ten years. Post development land use practices include commercial development, residential housing, and conservation (woodland and grasslands). Data collected and analyzed included digital elevation model (DEM) of study site, stream network and soil data using ArcGIS (ESRI, 2006) and Arc-Hydro Software (Maidment, 2000). Watershed characteristics such as slopes, channel length, circularity ratios, and drainage density were also computed. The delineated watershed boundary, stream segments and soil data layers were over laid to produce soil maps. Time of concentration (Tc) was determined for the pre and post development conditions in the watershed using seven different methods. The time of concentration values computed using Kerby, Federal Aviation Agency, Kinematic Wave and NRCS (SCS) methods found more reasonable compared to the remaining three methods used.

These computed time of concentration values were observed to be shorter for the post-development condition when compared to the pre-development condition of the watershed. The reduced time of concentration in the post development condition is attributed to increase in percentage of impervious areas due to increased residential development in the watershed; therefore increased rates of runoff in the watershed are expected.

Keywords: Rezoning, Time of Concentration, DEM, Kinematic Wave, Drainage density, Circularity ratio.

1. Introduction

Biochar, produced from pyrolytic decomposition of lignocellulosic biomass, is a solid hard product and a unique green material for soil amendments. Its use has been identified in Amazon fertility as ancient indigenous practice. Through ‘pyrolysis’ (heating without oxygen) process (‘pyro’ which means caused by heat whereas ‘lysis’ means dis-integration), there are three types of yields we get: a solid product (biochar), a gaseous product (syngas/ synthesis gas), and a liquid (bio-oil). The solid item, biochar, is applied for soil amendments. It can be used in agricultural, industrial, and environmental as a functional material. Solid char, a common pyrolytic outcome is charcoal, typically used to designate the solid char product that is ignited for fuel, whereas “biochar” designates the unique solid char purposively used as a soil amendment agent. On the other hand, the gaseous and liquid counterparts of pyrolysis have commercial applications like green energy, feedstock raw materials, and precursors (Fig.1).

Abstract

Climate change is the biggest problem of today, resulting in thawing glaciers, changes in crop yield, and disturbances of water resources not only in India but in the entire world. Crop yield were predicted according mid century (2050s) by using IPCC Scenario A2 and studied impact of climate change. Out of 80 districts of Uttar Pradesh the three were selected for the case study areas namely Meerut, Kanpur and Hamirpur. FAO based model ET₀ Calculator 3.1 and Aquacrop 3.1 Plus were used to estimate reference evapotranspiration and crop yields respectively by using two major food crops rice and wheat. Crop yield were estimated the present climatic conditions (2005) and mid-century condition (2050s). According to the comparison of simulation results for present and future scenarios, crop yield of rice and wheat was predicted to increase in the mid- century (2050s). However, food security was predicted to become a threat in future, because the increase in population till the 2050s is projected, and yield was increases in the major food crops. In order to sustain the growing population, there would be required in the future, a large area for growing rice and wheat in comparison to the area presently, to meet the same food availability per capita. Hence, there would be a need to increase the production of the food crops in order to meet the growing demands of food in the study areas.

Keywords: Crop yield, Global warming, Future, Production

ABSTRACT

A watershed is a topographically delineated area that is drained by a stream system, i.e. the total land area above some point on a stream or river that drains past that point. The watershed is a hydrologic unit that often is used as a physical – biological unit and a social – economic political unit for the planning and management of natural resources. Remote Sensing (RS) and Geographic Information System (GIS) techniques can be used effectively to generate the land use/land cover for evaluating the changes in an area. Conventional methods of runoff measurements are not easy for inaccessible terrain of Tamilnadu. Remote sensing technology can augment the conventional method to a great extent in rainfall-runoff studies. In this study, SCS Curve Number technique modified for Indian condition has been used for generation of CN for an ungauged watershed. A sub watershed of Manimuktha watershed is considered as study area. The daily rainfall data of Virudhachalam rain gauge station is collected and used to predict the daily runoff from the watershed using GIS based Soil Conservation Service -Curve Number (SCS – CN) method (USDA, 1972). Monthly and annual runoff values are obtained from the daily runoff values of the watershed. Base map, Soil map and Land use map of the study area are prepared by using Remote Sensing data and Survey of India (SOI) toposheets. PC Arc/Info GIS software is used for analysis.

2.1 Introduction
Building upon the foundational understanding of meteorology and data science established in Chapter 1, we now turn our focus to the fundamental physical processes that govern our atmosphere and the essential principles behind how we measure them. The Earth’s atmosphere is a dynamic fluid system, and its behavior is dictated by a complex interplay of physical laws. To truly comprehend weather phenomena, from the smallest updraft to the largest global circulation patterns, one must grasp the underlying atmospheric physics. This includes understanding how energy is transferred, how gases and
water vapor behave, and how forces shape atmospheric motion.
This chapter will delve into these core physical concepts, providing the theoretical bedrock necessary for a deeper appreciation of meteorological processes. Furthermore, accurate and reliable data is the lifeblood of modern meteorology and, by extension, data science applications within the field. Therefore, we will also explore the fundamental principles that underpin the measurement of key atmospheric variables.

Imagine the air around us. Even though we can’t see it, air has weight. Atmospheric pressure is essentially the force exerted by the weight of the air molecules above a particular point on the Earth’s surface.
Think of it like this: Imagine you’re at the bottom of a swimming pool. The water above presses you down, and you feel that pressure. Similarly, the atmosphere, a giant ocean of air, has layers of air molecules, and their weight presses down on everything below, including us.
• Atmospheric pressure is defined as the force per unit area exerted by the weight of the air column extending from the surface of the earth ,to the top of the atmosphere above that area
• It can be explain in simple terms like:
• Air has weight: Just like water or a pile of books, the air surrounding the Earth has mass, and thus, weight due to gravity.
• Weight creates pressure: This weight of the air presses down on the surface. The more air there is above a certain point, the greater the pressure.
• Like a stack: Imagine a stack of blankets. The blanket at the bottom has to support the weight of all the blankets above it, so it experiences more pressure. Similarly, the air at lower altitudes has the weight of all the air above pressing down on it.