eChapters

Much has been talked about the mighty river systems and their migratory histories, since Purana and Vedic times. In Mahabharata the places where the Lord Krishna is said to have played with Gopis in the banks of River Yamuna are now forming flat lands many kilometers away from the present day Yamuna. In the same way, there is a mention in ancient literature about the ‘Indo-Brahm’ river which was originated from the Himalayas and flown through Brahmaputra valley, Indo-Gangetic plains, Rajasthan desert and met the Arabian Sea in Rann of Kutch. Such a mighty river is said to have fragmented into Brahmaputra, Ganges and the Indus rivers due to Tectonic activity in Himalayan regions. Similarly there are many evidences in the Tamil literature. For example in ‘Kalingathuparani’ it is mentioned that the river ‘Palar’ was flowing north of Kanchipuram but the same river is now flowing south of it.

All these facts show that the rivers have the tendency to frequently change their courses. The advent of modern Remote Sensing Technology has opened up new vistas in studying such migratory rhythms of the rivers, as such old and buried rivers exhibit spectacular ribbon like, linear, curvilinear and contorted features with typical darker tone in black and white images and reddish tone in false color composites (FCC) and other color coded images.

Abstract

From amongst various geomorphic features the landforms generated by the river systems are significant as these are not only the records of the life histories of the rivers, but also the various dynamic processes and phenomenon operated during their origin like tectonic movements, sea level changes, flood histories, climate changes etc. In this connection a study has been conducted using the satellite borne multi spectral remote sensing data in mapping the flood plains, particularly their anomalies like symmetrical, asymmetrical, multilevel, offset and meander scrolled flood plains of some selected rivers from Asia viz: Tamirabharani, Cauvery and Brahmaputra from India, Indus river from Pakisthan and Tineg river from Phillipines. The paper discusses about these and their significance in unfurling the ongoing tectonic movements, sea level changes, palaeo – ongoing strom surge / tidal activities, ongoing earth tremors etc.

Introduction

The Rivers are not simply the carriers of water from the mountain ranges to the plains and to the oceans. But they have well defined and characteristic life histories of their own, with youthful stage in the mountains, mature stage in the plains and the old stage in the coastal regions [6] and the life histories of the rivers are often compared with man’s life. Infact, once the rivers are born on the surface of the Earth, their only aim is to attain the Mean Sea Level (MSL) or the base level of erosion as early as possible and as short as possible. So, in the mountains, which are normally their regions of origin, since the rivers occur thousands of meters above the MSL, flow vibrantly taking advantage of the slope as short and straight drainages to cut deeply the terrain so as to attain the MSL easily. Since such vibrant activities of the rivers, appear to be similar to the human youths, the rivers are said to be in youthful stage in the mountain regions and the erosion is the only dominant activity. But, on climbing down the hills and reaching the plains, as they still occur at hundreds of meters above the MSL, continue to flow towards the sea but with meandering, sinuous and oscillatory paths as they have lost their elevations when compared to the mountains and in this process of meandering perform both erosion and deposition. As such stabilized flow or “Watch and walk phase” of the rivers in the plains resembles the matured behavior of the middle aged Men, it is called as mature stage of the rivers. In contrast, when the rivers reach the coastal zones as they have attained the MSL, they don’t have any energy to carry even their own load and hence dump all the sediments as deltas, oscillate here and there and finally somehow reach the sea. Such Brownian movement of the rivers as replicates the activities of the old Men, called as the old stage of the rivers. Thus the erosion, both erosion and deposition and only the deposition are respectively the activities of the rivers in these three stages, accordingly the respective and contrasting landforms are formed in these three different stages of the rivers.

Abstract

Drainages have characteristic pattern and life histories with youthful stage in hilly areas, mature stage in plains and old stage in the coastal zones. The deviations from their normal life histories, especially aberrations in their flow pattern in the form of various drainage anomalies have been inferred to be the indications of dominantly the Eustatic and Isostatic changes. This, especially after the advent of Earth Observing Satellites, has attracted the geoscientists from all over the world, for studying such drainage anomalies. In this connection, a study has been undertaken in parts of South India falling south of 14° south latitude to comprehensively map some drainage anomalies like deflected drainages, eyed drainages and compressed meanders and to evolve the tectonic scenario therefrom. The mapping of such mega drainage anomalies and the related lineaments/faults from the satellite digital data and the integration of such lineaments/faults with the overall lineament map of South India showed that the study area is marked by active N–S block faults and NE–SW sinistral and NW–SE dextral strike slip faults. Such an architecture of active tectonic grains indicates that the northerly directed compressive force which has originally drifted the Indian plate towards northerly is still active and deforming the Indian plate.

Introduction

Rivers have characteristic pattern and life histories with (1) short and straight drainages performing only erosion in the hilly catchments, (2) meandering and sinuous paths doing both erosion and deposition in the plains and (3) Brownian pattern of movement doing only dumping of sediments and building up of deltas in the coastal zones. Such characteristic life history of the rivers with youthful stage in the hills, mature stage in the plains and the old stage in the coastal zones in general are controlled by the base level of erosion or Mean Sea Level (Thornbury, 1985). But, the rock types and the geological structures of the terrain related to palaeo, time transgressive and ongoing tectonism too significantly control the drainage pattern and the related river flow dynamics in all these three stages. Hence, geoscientists from all over the world have all along been showing greater interest in understanding the drainage architecture in general and their anomalies in particular. That too, after the advent of Earth Observing Satellite technology, mapping of drainage pattern and their anomalies like dentritic, semi dentritic, trellis, parallel, annular, radial, deflected, pirated, avulted, eyed, compressed, preferentially migrated and other drainage anomalies have gained greater momentum, since, besides lithology, tectonics and sea level changes, these drainage anomalies have the credibility of providing information on the flood histories, seismic vulnerability, past climates and anthropogenic phenomenon too (Chitale, 1970; Chen and Stanley, 1995; Lillesand, 1989; Matmon et al., 1999; Miller, 1937; Reid, 1992; Saintot et al., 1999; Smith et al., 1997; Twidale, 2004; Thornbury, 1985 and many others). In different parts of the Indian sub-continent too, studies have been carried out on the drainage anomalies using topographic sheets, black and white panchromatic aerial photographs and orbital multimode and multispectral satellite data, to elucidate the structural fabric, tectonic processes, climatological and other phenomenon of especially the Quaternary period (Amalkar, 1988; Babu, 1975; Bakliwal and Sharma, 1980; Barooah and Bhattacharya, 1989; Mitra et al., 2005; Murty and Mishra, 1981; Narasimhan, 1990; Oldham et al., 1901; Philip et al., 1989; Rajaguru and Kale, 1985; Ramasamy, 1991, 2006; Ramasamy and Kumanan, 2000; Ramasamy et al., 1987, 1991, 2006; Singh et al., 1996; Sood et al., 1982; Thirunaranan, 1938; Vaidyanadhan, 1971; Yashpal et al., 1980).

4.1. Introduction

Many countries have set up a network of agrometeorological observatories to regularly record important weather parameters such as clouds, rainfall, surface temperature, humidity, wind and wind direction, solar radiation, soil moisture, temperature and humidity profile of the atmosphere, etc. The observation process is performed either manually or through Automatic Weather Stations (AWS).

This recorded information is used for weather forecasting, natural resources management and for tracking agricultural production. However, these networks, which handle data of high spatial climate variability, are typically less robust than they should be. Moreover, the agrometeorological data collected from different ground stations is not transmitted in real time to a central collection point which limits the use of information.

Satellite remote sensing technology is an alternative system that is gaining popularity in the recent times which has allowed us to obtain frequent and precise measurements of vital agrometeorological parameters such as rainfall, solar radiation, temperature, evapotranspiration, albedo etc. Satellite data has many advantages over traditional ground stations, such as high spatial resolution (50 m–5 km), wide spectral bandwidth range (0.4–3.75 um) and high temporal frequency (even half an hour) and the prospect of collecting data from remote areas. In addition to routine repeated observations, satellites often provide synoptic views of the earth’s surface from space on a wide scale and have archive of information to create baseline data.

The preparation, planning and use of agricultural technologies for agriculture, needs application of agricultural meteorology. The role of agrometeorology in the last three decades has increased in terms of increasing food and nutritional security for the burgeoning population and natural resource management particularly in the context of global climate change. Agrometeorology can help to minimize inputs, thus clarifying the contribution of ecosystems and agriculture to the carbon budget in the event of global change. Agrometeorological information needs to be disseminated to users in time and space quite accurately, as agricultural activities are linked to the very local situation where the outputs of modern tools such as local area models, climate models, and dynamic crop simulation models are reduced to finer grid resolution and combined using GIS to extract practical suggestions. This chapter describes the recent applications of remote sensing in Agrometeorology.

Introduction

We use our five senses to perceive the world around us. Some senses, like touch and taste, need contact with the objects. But we get most of our information about the environment through sight and hearing, which do not need close contact with the external objects. In scientific terms, we are doing remote- sensing all the time. Remote- sensing is the process of recording/observing/ perceiving (sensing) objects or events from a distance. Remote- sensing is a way of monitoring and detecting the features, usually physical, of a specific area by measuring its reflected and emitted radiation (usually from satellite or aircraft).

Many times, users have to work with raster datasets of different spatial and radiometric resolutions. So, there is requirement of bringing their resolutions to the same resolution in order to facilitate their processing. Resampling is the process of deriving pixel values from the existing image to the new raster image of different pixel size. Resampling is most common pre-processing step in remote sensing. It is done both at spatial and radiometric scale. At spatial scale, resampling is done either to increase the spatial resolution i.e. decrease pixel size known as Upsampling or to decrease the spatial resolution i.e. increase pixel size known as Downsampling. Radiometric resampling is performed to increase or decrease the radiometric resolution of the image. In R, resampling of raster image is performed by raster package. The details of the resampling methods and their respective R – code with examples are discussed in this chapter.

First of all, we need to import the raster image on which we wish to perform resampling operations by using following R – code. In R, resampling is feasible on one band only. So, we will import single band raster image.

Abstract

In South India, tanks system is quiet ancient, meant for storing and supplying water towards multifunctional needs of the people. In Tamil Nadu, there are around 39,000 tanks with varying size and types. Over past few decades, irrigation rely on stable and reliable groundwater resources like dug and deep bore wells, consequently tanks lost their significance. Moreover, excessive siltation, improper maintenance and illegal encroachment further degraded the system. The deterioration factors are broadly categorised into problems in catchment, feeder channels and head works which eventually resulted in loss of storage capacity. The present study chiefly narrates an indirect method of estimating the loss in storage capacity of tanks and the catchment problem, especially soil erosion and its induced siltation of tanks in the downstream using geoinformatics technology. Using remotely sensed satellite data, by measuring surface area of tank loss in storage capacity was estimated through a linear model. Using Digital Elevation Model derived topographic wetness indices data, the catchment problem especially, soil erosion areas were identified and remedial measures were suggested. Under prevailing water crisis, it is essential to rehabilitate the tanks through which the surface water potential can be improved along with quality as well.

Land resources units or major land resources units are the suitable segmentations of land, based on available natural resources, their potential use and management. Irrespective of terms used by different organizations or institutes, these units have spatial dimension and represent a composite unit for interstate, regional, and national level planning. A typical meaning of these land units can be related to terms like land system. Christian and Stewart (1953) of the Commonwealth Scientific and Industrial Research Organization (CSIRO), Australia devised the ‘Land system’ as the composite mapping-unit which has been defined as “an area or group of areas, throughout which there is a recurring pattern of topography, soils and vegetation”. This system is based on the premise that the land system is expressed on aerial photographs by a distinctive pattern and, as such, the land system can be directly mapped from aerial photographs (Christian and Stewart 1953, Mabbutt and McAlpine 1965). It is a fact that during those period, aerial photographs were more frequently used and studies related to land systems used technique of aerial photogrammetry. As per USDA (United States Developmental Agency), the typical segmentations are; (1) Land Resource Region (LRR), which is the highest level in the hierarchy (2) Major Land Resource Area (MLRA), the second highest level and generally representing broad landforms or a geologic region at a small scale and (3) the Land Resource Unit (LRU).

1. Introduction
Nanotechnology, which involves manipulating and controlling matter at the nanoscale, offers innovative solutions for enhancing soil quality, nutrient management, and remediation of contaminated soils (Lal et al., 2019). According to the Food and Agriculture Organization (FAO, 2015), approximately 33% of global soils are degraded due to erosion, nutrient depletion, and chemical contamination. This degradation poses a severe threat to food security and environmental sustainability. Moreover, the world population is projected to reach 9.7 billion by 2050, placing further pressure on agricultural systems to produce more food without degrading soil resources (Tripathi et al., 2019). In this context, nanotechnology presents a promising avenue for sustainable soil management. The unique properties exhibited by nanomaterials enable precise monitoring, targeted delivery of nutrients, and effective remediation of soil contaminants. Nanosensors equipped with nanomaterials and nanoparticles allow real-time monitoring of soil parameters, enabling farmers to make informed decisions regarding irrigation, fertilization, and pest management (Gogos et al., 2017). For instance, a case study conducted by Smith et al. (2021) demonstrated the effectiveness of nanosensors in monitoring soil moisture levels and optimizing irrigation practices, resulting in a 20% reduction in water usage while maintaining crop yield.
Furthermore, nanotechnology offers innovative solutions for nutrient management in agricultural soils. Nanoencapsulation techniques allow controlled release of fertilizers, minimizing nutrient leaching and improving nutrient uptake by plants (Lal et al., 2019). In a case study by Johnson et al. (2020), the application of nanoencapsulated fertilizers resulted in a 15% increase in nutrient use efficiency and a reduction in fertilizer runoff by 30%, thus improving soil health and reducing environmental pollution.
Moreover, nanomaterials exhibit high sorption and catalytic properties, enabling efficient removal of heavy metal contaminants and organic pollutants from soils, thus mitigating soil contamination risks (Wang et al., 2022). A case study conducted by Chen et al. (2019) demonstrated the successful remediation of a heavily contaminated soil site using iron oxide nanoparticles, resulting in a significant reduction in heavy metal concentrations and improvement in soil health indicators.

Abstract

This study evaluates the potential of remote sensing techniques for assessing the relationship between land degradation and poverty in Pali development block of Rajasthan. Due to climatic conditions that prevail in this area of the country, less facilities and management practices to conserve land and its fertility becomes an important factor for intensifying poverty. The other countenance of this is that it is poverty which leads to land degradation. This paper assesses the impact of poverty and land degradation on each other. The desertification intensity and BPL density is calculated and relation is seen using Chi square test. The goodness of fit is seen up to 5 per cent level of significance for land degradation and demographic data.  The desertification in agricultural area is also considered. The total degradation in the block calculated is 8.39 per cent. It is found that village with highest BPL density has more degradation intensity particularly in agricultural area, proving the agricultural based economy of the dry lands in Rajasthan. An example study is also done at village level.  Using cadastral map and satellite image classification, fields that require immediate attention have been identified. Demographic and degradation maps are also prepared.

Abstract

A very strong shallow focus submarine earthquake (of magnitude 9.0) occurred off the west coast of Sumatra Island due to the movement of Indian Plate and Burma Plate on 26th December 2004 at 06:18:53 IST. A vast area around its epicentre was rocked including Andaman and Nicobar Islands and parts of the eastern and western coasts of the Indian mainland. This earthquake had generated a global tsunami, which had also pounced on the Andaman and Nicobar Islands and the coasts of Andhra Pradesh, Tamil Nadu and Kerala and caused severe damage to the coastal population and infrastructure. Considering the devastation of this tsunamigenic earthquake, the Department of Science & Technology, Govt. of India has launched a coordinated programme for imparting S & T inputs with futuristic approach to support rehabilitation programme in the affected areas on a sustainable manner. The main objective of the programme is to generate geospatial databases on damages and risk zonation using pre and post-tsunami remote sensing (RS) data along with collateral attribute data in GIS platform. This paper speaks on the damage assessment (both natural / physical resources and human resources) caused by the earthquake and tsunami covering parts of Andaman Islands along with strategies for risk management and constraints and alternatives for micro level planning.

Keywords: Tsunamigenic earthquake, Damage Assessment, Remote Sensing and GIS, Andaman - Nicobar.

Abstract
 
Mention about the Great Himalayan river of Vedic Period (10000-8000 BC) is found in ancient Indian literature. The river called as ‘Saraswati’ in India and ‘Hakra’ in Pakistan, was flowing with full majesty through Thar Desert around 6000 BC and dried up during 3000 BC due to climatic and tectonic changes in Himalayan region. The relict of this lost river is still found as palaeochannels in this region. Large numbers of archaeological sites of Harappan civilization occur along the dry river bed. 

Abstract

This paper sets out to describe key results and experiences obtained during the assessment of the crop response to water which varies strongly from crop to crop depending on its specific genetic characteristics and adaptation to ecological conditions. The specific crop water information for the different crops is compiled in a crop-based data base. This includes crop water parameters, yield response to water, as well as selection of economy crops. Existing natural water resources can sustain the crop production with high yield as well as economic value with minimal environment impact. Most of the crop varieties get all of its required water from rainfall- water but due to climate change there is always a demand of irrigation water from the ground water resources. Thus, there is a need to evaluate the crop water information in relation to ground water extraction as a source of irrigation.

Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the buildup of noise and signal distortion during processing. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems. Introduction to image processing 
Image processing is a method to convert an image into digital form and perform some operations on it, in order to get an enhanced image or to extract some useful information from it. It is a type of signal dispensation in which input is image, like video frame or photograph and output may be image or characteristics associated with that image. Usually image processing system includes treating images as two dimensional signals while applying already set signal processing methods to them.
Image processing is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it. It is a type of signal processing in which input is an image and output may be image or characteristics/features associated with that image. Now-a-days, image processing is among rapidly growing technologies. It forms core research area within engineering and computer science disciplines too.

Mahatma Gandhi mentioned to those who wanted to serve rural India that their most useful contribution would be in linking brain with brawn.  Only such a combination of intellect and labour can lead to sustainable advances in the productivity and profitability of agricultural holdings.  West Bengal’s Bidhan Chandra Krishi Vishwavidyalaya (BCKV), almost four decades old, is a fitting example of such work.  It has helped the development of two more universities in the State, namely, West Bengal University of Animal & Fishery Sciences and the Uttar Banga Krishi Viswavidyalaya.  It is important that these three universities function like a consortium of educational institutions mandated to help in achieving agricultural advance, agrarian prosperity and rural transformation in the State.

Livestock and livelihoods are intimately related in our country.  The ownership of livestock is more egalitarian than that of land.  Similarly, West Bengal is full of fish ponds.  It is important that cultivation of crops like rice is done by adopting integrated pest management procedures, so that the water in which fish is cultivated does not get polluted with pesticides.

Introduction

Spatial variation structure of soil properties is a key input for digital soil mapping and generally determined through geostatistical techniques (Webster and Oliver 2007). In geostatistics, spatial variation is expressed by semivariogram ?(h) , which measures the average dissimilarity between data separated by a vector h. It is generally computed as half of the average squared difference between the components of data pairs:

1. Introduction
Precision farming, often referred to as precision agriculture, is an advanced agricultural management approach that leverages technology and data-driven strategies to optimize various aspects of farming operations. At its core, precision farming involves the precise measurement and control of variables like soil conditions, crop growth and environmental factors to enhance productivity, sustainability and resource efficiency. This approach encompasses use of a wide range of automated technologies, including Global Positioning System (GPS), Geographic Information Systems (GIS), remote sensing, sensor networks and automated machinery.
The significance of precision farming lies in its potential to revolutionize agriculture by addressing sustainability and conservation of resources. Precision farming is able to tailor farming practices to specific field conditions. This sitespecific management approach minimizes resource wastage, incumbent costs and environmental hazards. It enhances crop management through real-time monitoring and data analysis. By the use of GPS fitted automated machinery, drones and robotic harvesters and advanced decision support system labour costs are reduced and efficiency is increased (Gebbers and Adamchuk, 2010).By employing soil sensors, and satellite imagery, farmers can gain valuable insights of soil moisture, nutrient levels and pest infestations which helps in irrigation scheduling and adequate fertilizer application (Srinivasan et al., 2019). In contemporary agriculture, the need for sensor-based approaches in soil management has become increasingly apparent. These approaches harness cuttingedge technology and data-driven solutions to optimize soil health, crop production and resource utilization. One of the primary advantages of sensor-based approaches is their ability to monitor soil moisture levels. Soil moisture sensors, such as those based on time-domain reflectometry (TDR) or capacitance technology, provide continuous data on soil moisture content at different depths (Dzikiti et al., 2012). In addition to monitoring moisture and nutrients, sensors can assess other vital soil parameters. Soil pH sensors help maintain the optimal pH level for crop growth, as soil pH can affect nutrient availability. Compaction sensors identify areas of soil compaction, allowing for targeted tillage practices to alleviate compaction and improve root growth. These are just a few examples of how physical parameter sensors can address soil health challenges, as documented in studies by Marchetti et al. (2018) which emphasizes the role of sensors in mitigating soil erosion. Chemical parameters sensors like soil nutrient sensors, such as ion-selective electrodes, can measure key nutrients like nitrogen, phosphorus and potassium. This information enables farmers to tailor their fertilization practices with pinpoint accuracy through variable rate technology (VRT) (Zhao et al., 2018). Moreover, sensor data can be integrated with Geographic Information Systems (GIS) and global positioning systems (GPS) to create detailed soil maps, aiding in sitespecific management strategies.

Series of experiments are conducted at different locations, times, or combinations of locations and years to evaluate the spatial and temporal performance of treatments. Such experiments are especially important in forestry and agricultural research when conclusions are intended to apply across wider geographical or environmental conditions. This chapter explains combined analysis of a series of experiments after individual experiments have first been analysed according to their respective designs. Particular attention is given to testing the homogeneity of error variances, including Bartlett’s test. When variances are homogeneous, pooled analysis can assess treatment effects, location or year effects, and treatment-by-location or treatment-by-year interactions, thereby evaluating consistency of treatment responses.

India’s Northeast region — one of natural beauty and cultural richness — is both a mega-biodiversity area as well as a “hot-spot” for genetic erosion. The rural population is around 82 per cent and depends largely on agriculture and allied sectors for work and income security. The forests harbour 8000 out of the 15,000 species of flowering plants occurring in the country. Of about 1300 species of orchids reported from India, the Northeast has the highest concentration with about 700 species. The species richness is highest in Arunachal Pradesh where over 5000 flowering plants occur and the lowest in Tripura with 1600 species. Bamboo is the lifeline of the Northeast and 63 out of 136 species found in India occur in this region. Sadly, however, 25 species of bamboo fall under the rare and endangered category. The region is also home to the eri and muga silkworms. The yak and the mithun are unique animals which are threatened by the spread of non-edible invasive species like Lantana, Eupatorium and Mekenia. The cultural diversity of this region is well known, with 225 tribes out of 450 in the country living here. 

Abstract

Sabatayn basin is one of the two mature basins producing oil and gas in Yemen. Due to the recent decline in oil production, the exploration activities have been extensively concentrated mainly on these two basins (Sabatayn and Sayun-Masilah). So, this present study has been conducted to evaluate the exploration potential of the remaining trap areas within these mature basins. Fractured basement of reservoir becomes very attractive exploration target in Yemen recently, after the recent discoveries of basement fractured oil fields. As the evaluation of basement traps needs time and fund, to reduce the same, this research study uses a new technique which was devised with the help of Geoinformatics by analyzing the surface and subsurface lineaments effectively. In this study, a satellite image Enhanced Thematic Mapper (ETM+7) based analysis was conducted for extracting surface lineaments, and for the subsurface lineaments, the basement lineaments were extracted from seismic, magnetic and gravity data. An orientation analysis of these surface and subsurface linear features was performed to detect the basic structural grains of the study area. The correlation between these structural grains and subsurface oil and gas traps was performed to understand the connectivity to the reservoirs. This paper discusses in detail about the same and the importance of using surface and subsurface lineament analysis for delineating hydrocarbon reservoirs in the study area.