eChapters

The satellite data is available in raster format. Raster data consists of two – dimensional array of pixels or grids which stores the values representing features. All the pixels are of same size and shape with their particular coordinate location. A raster data format is shown below.

The calculation of raster data statistics is very essential before performing some geoprocessing operations. Raster data statistics involve knowing the distribution of pixel values in a band, comparing the pixel values of two bands, extracting values of all bands for a particular geographical location or point, and computing statistics like mean, median, standard deviation, etc. at pixel level across all bands of raster dataset.

In R, codes to perform raster data statistics are present in raster package. The visualisation of raster data statistics can be done by rasterVis package. So, we need to import these packages in R in order to perform this exercise.

1. Introduction
Soils stand out as an intricate and diverse ecosystem on our planet. Their significance extends beyond supplying 98.8% of the world’s food, encompassing a wide array of essential services such as carbon storage, regulation of greenhouse gas emissions, flood prevention, and offering support to burgeoning urban populations. However, it is crucial to recognize that soil is a finite natural resource. The unprecedented growth of the human population, escalating from 250 million in the year 1000 to 6.1 billion in 2000, with projections reaching 9.8 billion by 2050, along with the intensified practices of agricultural production, is exerting immense pressure on the sustainability of soils.
For long-term sustenance the concept of ‘Soil quality’ was propagated around three decades back from now in the United States of America, and further expanded to the scientists of European and Asian countries. Soil health and soil quality are two interweaving term that signifies the potentiality or capacity of soil towards mankind. These two words complement each other in such a way that one term automatically comes with another to determine both aspects i.e. agricultural sustainability and environmental quality in terms of plant, animal and human health (Haberern, 1992; Doran, 2002). Idowu et al. (2007) remarked that the term “soil quality” is more favoured by scientists, whereas “soil health” is a term favoured by farmers as it connotes a holistic approach to soil management. The inception and application of soil quality term was officially approved by Soil Science Society of America (SSSA). They defined soil quality as “The capacity of a specific kind of soil to function within natural or managed ecosystem boundaries, to sustain biological productivity, maintain environmental quality, and promote plant and animal health” as illustrated by Karlen et al. (1997). It is a complex composition of certain properties associated with physical (texture, bulk density, water holding capacity, infiltration capacity etc.), chemical (pH, EC, organic carbon, extractable macronutrient and micronutrient etc.) and biological (microbial activity and related parameters) conditions of soil (Prabha et al., 2020). There are primarily two key methodologies for assessing soil quality: the descriptive approach, which focuses on characterizing various aspects or attributes of soil quality, and the Indicative approach, which aims to identify the ability or capacity of an attribute in a desired manner. The comprehensive process of developing a soil quality index is guided by the 3-Is framework: the Identification of indicators, Interpretation, and Integration of selected soil quality indicators. It is important to note that the specific set of indicators utilized can vary between different soils, diverse agroecosystems, and from one crop to another. Additionally, climatic conditions and other abiotic factors may also significantly influence the assessment of soil quality.
The USDA has categorized soil quality indicators into four primary groups: visual, physical, chemical, and biological indicators. However, in the current context, the dominant indicators are physical, chemical, and biological. For a systematic assessment of soil quality, it is crucial to collect individual parameters and integrate them meaningfully. Consequently, integrated soil quality indicators

Abstract

Coral reefs, the marine representatives of tropical forests, coupled with the sea grasses contribute considerably to the coastal productivity. Damages to these ecosystems will immediately affect the fishery productivity of the region. Due to this, the long-term ecological impact of the recent tsunami will be a serious set back to the local, national and regional economy than the immediate losses. Andaman and Nicobar reefs represent the second largest coral reef formation next to the Great Barrier Reef and are also comparable to the coral reefs of Indonesia and Philippines in terms of diversity of species and associated floral and faunal components. The recent mega – subduction of the Indian plate below the Burmese micro – plate in Andaman – Sumatra region has not only deepened the southern and uplifted the northern group of Andaman – Nicobar islands but also created a disastrous tsunami on Dec 26, 2004. While such tectonic changes are expected to cause longterm changes in the coral reefs of Andaman, Nicobar group of islands, the tsunami has damaged the coral reefs instantaneously. However, the coral reefs of the Gulf of Mannar and Palk Bay are not much affected by the tsunami by virtue of their geographic position in the shadow region of Sri Lanka.

Keywords: Indian coral reefs, Tsunami effect, Coral recovery

Abstract

The mangrove wetlands form dynamic ecotones between land and sea. Mangrove wetlands are unique in terms of environment, plant and animal communities and their distribution is restricted in tropical and subtropical coastlines. They perform a number of protective and productive functions, which ensures ecological and livelihood security to the coastal communities. The role of mangroves in mitigating the impact of cyclones and storm surges is well known but only limited information is available on their role in reducing the impact of tsunami. The Pichavaram mangroves, located on the southeast coast of India in Tamil Nadu, which was hit by the 26 December 2004 tsunami, provided opportunities to understand the contribution of it in tsunami mitigation. Through a systematic field study, a comparative analysis was made on the impact of tsunami in a set of villages, one was protected by mangroves and the other lacks any vegetation surrounding it. These villages are located at more or less equal distance from the sea and situated at about same elevation. Assessment carried out with well defined indicators such as loss of lives due to forceful entry of tsunami water, damages to houses and types of houses, etc., shows that loss of lives and damage to houses were much less in the village surrounded by Pichavaram mangroves. Thus, Pichavaram mangrove wetland, which was restored with the participation of the local community, Tamil Nadu Forest Department and M.S.Swaminathan Research Foundation (MSSRF) during 1993-2004 provided great dividend during tsunami. This underlines the importance of strengthening the ecological foundation of the coastal zone with mangroves and other vegetation as one of the strategies for mitigating the impact of natural disasters in the coastal areas.

Keywords: Mangroves, Natural Disasters, Tsunami, Impact Reduction and Pichavaram.

Introduction 
Crop-weather models are sophisticated constructs, meticulously designed to replicate the dynamic and intricate interplay among atmospheric conditions, complex soil processes, nuanced plant physiology, and the decisive influence of human management interventions. The agricultural system is a prime example of a highly interconnected and non-linear system, where changes in one component can ripple through and affect many others, often with time lags and feedback loops. To truly comprehend, effectively design, rigorously develop, and clearly communicate the inner workings of such multifaceted simulations, relying solely on dense textual descriptions or abstract mathematical equations can prove daunting and often insufficient. This is precisely where relationship diagrams emerge as indispensable tools. At their core, relationship diagrams are powerful visual representations that translate the abstract scientific concepts and mathematical formulations embedded within crop-weather models into intuitive graphical formats. They are essentially the architectural blueprints and flowcharts of these complex systems, allowing us to see, rather than just read, how various components of the agricultural ecosystem interact. Imagine trying to understand the intricate wiring of a skyscraper or the precise movements of a symphony orchestra purely from a written description; diagrams provide the essential visual mapping that brings clarity and coherence to complexity. These diagrams are not mere aesthetic additions; they are fundamentally required because of the inherent complexity and interdisciplinary nature of crop modeling. They bridge critical gaps: Bridging Disciplinary Gaps: Agricultural system modeling brings together experts from diverse fields – agronomists who understand plant responses, meteorologists who provide weather insights, soil scientists who grasp soil physics and chemistry, and computer scientists who implement the models.

On August 6, 1945, the most dreadful among the weapons of mass destruction – the atom bomb – was dropped in the civilian area of Hiroshima. Three days later, another atom bomb was dropped in Nagasaki. In July 1955, Bertrand Russell and Albert Einstein issued their famous manifesto seeking the abolition of nuclear weapons and appealing to all inhabitants of Planet Earth:
 
Remember your humanity, and forget the rest. If you can do so, the way is open to a new Paradise; if you cannot, there lies before you the risk of universal death.

In 1957, the Russell-Einstein Manifesto led to the birth of the Pugwash Conferences on Science and World Affairs, an organisation devoted to the causes of ending the nuclear peril and reminding scientists of their ethical responsibility for the consequences of their discoveries, particularly in the area of nuclear threat to human survival.

Abstract

The Indian Peninsula in general and its southern part in particular has been thought to be a stable shield area and hence inert to younger earth movements and seismicities. However, in addition to fast relapsing seismicities, the studies carried out by earlier workers during the past three decades indicate possible pulsatory tectonism, at least since the Jurassics. The present study is a newer attempt to identify, analyse, and spatially amalgamate a large number of anomalies visibly displayed by the tectonic, fluvial, coastal, and hydrological systems in remote sensing and ground based datasets/observations, and to finally paint a fair picture on the active tectonic scenario of South India. The study reveals that the phenomena, viz. extensive soil erosion, reservoir siltation, sediment dump into the ocean, preferential migration of rivers, restricted marine regression, shrinkage of back waters, withdrawal of creeks, fall of groundwater table, etc., indicate two E–W trending ongoing tectonic (Cymatogenic) archings along Mangalore–Chennai in the north and Cochin–Ramanathapuram in the south. Intervening these two arches, a cymatogenic deep along Ponnani–Palghat–Manamelkudi exhibiting phenomena opposite to the above is observed. In addition, the characteristic tectonic, geomorphic, and hydrological anomalies observed in 1B satellite FCC data, as well as in the field, indicate N–S trending extensional, NE–SW sinistral, and NW–SE dextral strike slip faults. These anomalies and the tectonic features deduced there upon, indicate that the southern part of the Indian Peninsula is tectonically active due to the northerly to north– north-easterly directed compressive force related to post collision tectonics. This active tectonic model visualized for South India gives a further clue that the whole Indian plate is whirling like a worm with alternate E–W arching and deepening, along with block and transform faulting from Cape Comorin in the south to the Himalayas in the north.

Introduction

The Indian Peninsular Shield in general and its southern part in particular has always been thought of as being inert to younger earth movements and related seismicities / earthquakes. For this reason, geoscientists have not shown much interest in studying the Neo-active-seismotectonics of the southern part of the Indian Peninsula, mostly restricting themselves to the western (Kutch) and central (Son-Narmada) parts of India (Auden 1949, West 1962, Choubey 1970, Biswas and Deshpande 1973, Kailasam 1975, Ghosh 1976, Pal and Bhimashankaran 1976, Crawford 1978, Dessai and Peshwa 1978, Sharma 1978, Guha and Padale 1981, Kaila et al., 1981, 1985, Murty and Mishra 1981, Powar 1981, 1993, Bhagwandas and Patel 1984, Bakliwal and Ramasamy 1987, Merh 1987, Ravishankar 1987, Amalkar 1988, Ramasamy et al. 1991, Gupta 1992, Sareen et al. 1993, Ramasamy 1995a, 1998, and many others).

Abstract

The Remote Sensing and the followed up field based investigations show that the Tamil Nadu coast, India, is facing series of geoenvironmental problems due to tectonic movements and morphodynamic processes. Such problems pose a challenge to the engineering geologists. The paper discusses such challenging engineering geological problems and plausible remedial measures.

Abstract

The ever increasing population in India and the world, impeding threats from the climate change scenario and the increasing demand for land resources from the industrial sector calls for improved resource efficiency. The production strategies are changing from input intensive to integrated resource management strategies. The shift is towards adopting the precision farming technologies like addressing the site specific variability and crop needs. Remote sensing technology coupled with GIS has been recognized as reliable tool in agriculture to guide application of fertilizer, pesticides and other farm inputs. With precision farming, technologies such as grid soil sampling, remote sensing, on- the-go sensing, and electronic yield monitoring help farmers gather very detailed information about the heterogeneous makeup of a farm field. Site specific applications means application of required input only where it is required rather than entire fields or adjusting application rates accordingly. This chapter discussed the input management based on the time of intervention - Input management prior to crop sowing, in season crop management and end of the season.

Keywords : Management zones, soil variability and Remote Sensing

Abstract

The development index and the developmental planning of a Country/Nation mostly depend on its natural resources potential including water resources. The fast emerging Remote Sensing and GIS technology has substantially reduced the problems of water resources management including groundwater. The groundwater is distinctly controlled by western crystallines, central Tertiary sandstone and eastern Quaternary sediments in Pudukkottai district. While the groundwater behavior in crystallines is dominantly controlled by secondary porosity, in Tertiary formations and Quaternary sediments, it is controlled primarily by the primary porosity and by secondary porosities also if these are structurally deformed.

Abstract

Remote Sensing (RS) and Geographic Information System (GIS) have emerged as potential tools for competent planning and administration of water resources. In this study, a new methodology is proposed to delineate groundwater target zones using integrated RS, GIS and Analytical Hierarchy Process (AHP) method. The developed methodology is confirmed by a case study in Karur district of Tamil Nadu, Southern India. Seven thematic layers, viz., Lithology, Lineament Density, Geomorphology, Slope, Post– Monsoon Water Level, Drainage Density and Land use / Land cover were considered in this study. Selected seven thematic layers and their features were assigned suitable weights on the Saaty’s scale according to their virtual significance in groundwater incidence. The assigned weights of the thematic layers and their features were then normalized by using AHP. Finally, the selected seven thematic maps were incorporated by weighted linear combination method in a GIS environment to produce a groundwater target map.

Abstract

Remote sensing and Geographic Information System (GIS) are integrated system in providing precise information on nature, extent and spatial distribution of land resources to assess their potential and limitations for planning, monitoring and management towards sustainable development. The use of remote sensing and GIS provide immense opportunities in the field of large-scale mapping, generate and update of existing geographical databases for decision making in site- specific management and development of land resources. Integration of remote sensing and GIS includes the use of each technology to benefit the other, as well as the application of both the technologies for geospatial modelling and decision support. Remote sensing and GIS integration has clearly benefited from advances in computing and Global Positioning System (GPS) technologies, including innovations in use of decision tree algorithms and neural networks. The generated precise spatial database in GIS on land resources, socio-economic and contemporary technologies could be effectively used to develop GIS based Spatial Decision Support Systems (SDSS) for sustainable management of land resources. In this article an attempt has been made to provide an overview on the remote sensing and GIS technologies as a special decision support tools in inventory, characterization and management of land resources particularly in digital terrain analysis, geomorphological mapping, hydrological applications, soil resource inventory, assessment of soil loss, land degradation and soil fertility, soil-site suitability and watershed prioritization.

Abstract

Food security to the increasing population on one side and the increasing export of food grains on the other side has lead to the immediate attention on to raise the food production in our country. The decreasing land availability for agriculture due to the increased degraded lands and use of agricultural lands for non agricultural purposes has still worsened the situation. In order to match with the food requirement from decreasing agricultural lands, Indian agriculture has been pushed towards indiscriminate use of farm inputs exploiting the non renewable natural resources without any concern to the environmental ill effects leading to further degrading of the situation. Even though the concept of sustainability is age old, the importance is felt recently. Sustainable use of resources at farm level can magnify the effect of conserving non renewable resources and reducing ill effects on the environment at state level and to the country. Sustained farm production is a key to manage our resources and environment. Adoption of new information technologies with the conventional agronomic practices to increase farm production is made inevitable due to our past experience. The advancement in the technology tools like Remote Sensing, Geographic Information System, Global Positioning System and Decision Support Systems have paved way for better and effective management of crop production at farm level. 46 Geospatial Technologies for Natural Resources Management

A systematic approach of management involving advanced technologies and conventional agronomic practices through understanding the factors like soil variability, weather parameters and crops that contribute for the sustainable farm production is need of the hour. The spatial and temporal variability of the farm production parameters are to be studied and mapped in relation to historical data of the farm for successful site specific management. Site specific management tools may improve decisions related to site conditions, thereby reducing the aspect of uncertainty in the management system. This approach of farm management using advanced technologies viz., Remote Sensing, Geographic Information System, Global Positioning System, Variable rate technology, crop production modeling and Decision Support System can enable sustainable farm production with beneficial effect on the environment in future.

Keywords : Remote sensing, GIS, Sustainable Farm production, Site Specific Management

Abstract

The southern part of the Indian Peninsula has long been regarded as a stable area free from Pleistocene tectonics as it represents the Precambrian shield region. But the frequent earth tremors even up to a magnitude of 6.5 (Richter scale) which occurred in Tamil Nadu have started encouraging the geologists to think that it could possibly be a seismic prone zone. In addition, images acquired by the polar orbiting satellites offered valuable information on the fracture systems and fluvial anomalies suggesting possible Pleistocene tectonism in South India. Hence, a study has been undertaken to evaluate the signatures of Pleistocene tectonism in South India using IRS-lA, LISS-1 FCC imagery (Indian Remote Sensing Satellite lA, Linear Imaging Self Scanning 1, False Colour Composite) involving band 2, 3 and 4 under blue, green and red bands respectively.

The study has brought out a series of E-W trending cymatogenic arches and N-S trending extension, NE-SW trending sinistral, NW-SE trending dextral and E-W trending release fractures with characteristic signatures supporting Pleistocene tectonism in Tamil Nadu and Kerala.

On the basis of such morphotectonic features, a Pleistocene tectonic model has been presented with a N-S trending greatest principal stress and an E-W oriented least principal stress related to the movement of the Indian plate towards the Tibetan plate. Based on the model developed for Tamil Nadu and Kerala, a series of E-W trending cymatogenic arches and deeps have been proposed for Cochin- Rameswaram in the south to the Himalayas in the north. Further studies for seismotectonics, geothermal resources and hydrocarbon search have also been suggested along such arches and deeps.

Abstract

The art of remote sensing has opened up many vistas in the study of river migration as satellite photographs, both in their normal and digitally enhanced modes, vividly show the rivers and their migratory signatures. The rivers migrate for various reasons amongst which tectonic movement is one of the main causes. In the present study an attempt has been made to exhibit the palaeochannel network of the rivers of Western India and integrate them with lineament fabric, so as to understand the Quaternary tectonics of the region. The study has shown that Western India shows considerable signs of Quaternary tectonics.

Abstract

The art of remote sensing has opened up many vistas in the study of river migration as satellite photographs, both in their normal and digitally enhanced modes, vividly show the rivers and their migratory signatures. The rivers migrate for various reasons amongst which tectonic movement is one of the main causes. In the present study an attempt has been made to exhibit the palaeochannel network of the rivers of Western India and integrate them with lineament fabric, so as to understand the Quaternary tectonics of the region. The study has shown that Western India shows considerable signs of Quaternary tectonics.

Remote Sensing in Mineral Exploration

Remote sensing is a powerful tool used in mineral exploration to study and identify minerals and mineral deposits from a distance. This technology allows geologists to gather information about the Earth's surface and subsurface without having to physically access the site. Here are some ways remote sensing is used in mineral exploration:

Mapping Geology: Remote sensing can be used to map geology by identifying surface features associated with mineral deposits. Geologists use images collected by remote sensing satellites and aircraft to create detailed maps of the geology and topography of a region. These maps can help identify areas that are likely to contain mineral deposits.

Mineral Identification: Remote sensing can help identify specific minerals by analyzing the reflectance or absorption patterns of light. Different minerals have unique spectral signatures that can be detected by remote sensing instruments. By analyzing these signatures, geologists can identify the type and abundance of minerals present in an area.

Remote Sensing in Oil Exploration

Remote sensing plays a significant role in the oil exploration industry. It refers to the use of sensors and instruments to gather information about the Earth's surface and its environment from a distance. This information can be used to locate and evaluate oil and gas deposits.

There are different remote sensing techniques used in oil exploration, including

Seismic surveys: This technique involves creating sound waves underground and recording their reflection to determine the subsurface structure. It is commonly used in oil exploration to locate potential oil and gas deposits.

Magnetic surveys: This technique uses a magnetometer to measure the magnetic field of the Earth's surface. Magnetic anomalies can indicate the presence of underground geological structures that may contain oil or gas deposits.

Gravity surveys: This technique involves measuring variations in the Earth's gravitational field, which can indicate the presence of underground geological structures.