eChapters

Introduction

Famous French postmodern philosopher Jean Baudrillard commented on information once. “Information can tell us everything. It has all the answers. But they are answers to questions we have not asked, and which doubtless don’t even arise.” This seemingly paradox observation fits contemporary Internet age perfectly. Internet is a vast repository of information of all kinds and is bursting on its seams. The seeker needs to search with monumental grit and determination to have a full handle on the range of information available for any particular search. A search string for GIS returns more than 1185000 results, in a mere 0.26 seconds. Recommending a comprehensive resource list is not possible as new material gets continually added by way of additions and updates. However for a beginner the list given below will be handy. The flip side is GIS has innumerable resources and a broad range of content. Software vendors, organizations, individuals, universities and companies have provided a wealth of information. The readers are exhorted to make use of the materials to improve their understanding of the subject.

Abstract

Quality of water is a matter of serious concern for arid and semi arid region like Rajasthan. The study area chosen is extreme western arid part of Rajasthan state where water quality and quantity both are very important issues. Due to absence of any perennial river, scanty rainfall and scarcity of surface water resources, ground water is very deep and saline. The groundwater potability assessment was based on 1119 wells water quality data. The purposes of this investigation were (1) to provide an overview of present groundwater quality and (2) to determine spatial distribution of groundwater quality parameters which affect water potability and (3) to map groundwater potability in the study area by using GIS and Geostatistics techniques. Arc GIS 9.3 and Arc GIS Geostatistical Analyst were used for generation of various thematic maps and Arc GIS Spatial Analyst to produce the final groundwater potability map.

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

Groundwater is one of the major sources of exploitation in arid and semi -arid regions of Rajasthan. To protect groundwater, its data on spatial distribution are important along with quantity. Analysis of quality of groundwater is also very important, because the physical and chemical characteristics of groundwater determine its suitability for agricultural, industrial and domestic usages. The importance ground water increases many fold for arid tracts like Western Rajasthan. Here quality of water is also matter of serious concern. Geostatistics methods are most advanced techniques for interpolation of Groundwater quality. The present study appraises the groundwater quality of western Rajasthan for agricultural purpose with GIS technology. Kriging Raster Interpolation technique of spatial analyst module in Arc GIS software has been used to generate the spatial distribution map of ground water for agricultural purpose. In western Rajasthan only 28% (58109 km2) of ground water falls under the category of good and is suitable for agricultural use. 

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.

Abstract

The groundwater targeting in hard rock aquifer systems is complex, because of the heterogeneity of the aquifer systems. The ground water mobility and stability in such aquifer systems varies because of the lithology, folded structures, fracture density, geomorphology, slope etc., These occur in various permutations and combinations and control the overall water holding and conducting capacity in different parts of the aquifer systems. Hence, one needs to analyse all the data so as to understand and bring out precise spatial models on the groundwater probability in hard rock aquifer systems. In the present study, the authors have carried out GIS based appraisals to understand the relation between the lithology and groundwater movement in hard rock aquifer systems of parts of Central Tamil Nadu covering 1300 sq.km. In the said study, GIS images were generated on the maxima zones of various aquifer parameters such as water level, width of aquifer depletion, transmissivity, permeability, specific capacity, storage co-efficient, optimum yield and recovery rate. These were overlaid with the lithology GIS image. Such an analysis has shown that, in general, the fissile hornblende biotite gneiss appears to have some control over the groundwater systems.

Demographic explosion, environment pollution, habitat destruction, enlarging ecological footprint, widespread hunger and unsustainable lifestyles, and potential adverse changes in climate all threaten the future of human food, water, health and livelihood security systems. 2010 appears to mark the beginning of uncertain weather patterns and extreme climate behaviour. Events like temperature rise, drought, flood, coastal storms and rise in sea level are likely to present new challenges to the public, professionals and policy makers. Biodiversity has so far served as the feedstock for sustainable food and health security and can play a similar role in the development of climate-resilient farming and livelihood systems. Biodiversity is also the feedstock for the biotechnology industry. Unfortunately, genetic erosion and species extinction are now occurring at an accelerated pace due to habitat destruction, alien species invasion and spread of agricultural systems characterised by genetic homogeneity. Genetic homogeneity increases genetic vulnerability to biotic and abiotic stresses. To generate widespread interest in biodiversity conservation, the UN General Assembly has declared 2010 as the International Year of Biodiversity.

It was in 1968 that the term Green Revolution was coined by Dr. William Gaud of USA to describe advances in agriculture arising from productivity improvement. Even in 1968, I concluded that if farm ecology and economics go wrong, nothing else will go right in agriculture.  I expressed my views in the following words in my lecture at the Indian Science Congress Session held at Varanasi in January 1968:

Exploitive agriculture offers great dangers if carried out with only an immediate profit or production motive. The emerging exploitive farming community in India should become aware of this. Intensive cultivation of land without conservation of soil fertility and soil structure would lead, ultimately, to the springing up of deserts. Irrigation without arrangements for drainage would result in soils getting alkaline or saline. Indiscriminate use of pesticides, fungicides and herbicides could cause adverse changes in biological balance as well as lead to an increase in the incidence of cancer and other diseases, through the toxic residues present in the grains or other edible parts. Unscientific tapping of underground water will lead to the rapid exhaustion of this wonderful capital resource left to us through ages of natural farming.

Abstract

The drainage pattern and the architecture are the reflections of not only the tectono fabric of a region, but also the active tectonic processes. From amongst many drainage patterns and anomalies, the eyed drainages, deflected drainages and the compressed meanders interpreted from satellite images for Pudukkottai region of Southern Tamil Nadu infer to reflect the active N-S block faults and NE-SW sinistral and NW-SE dextral faults related to post collision tectonic phenomena.

Introduction

The Geoscientists have long back recognized that the drainages are the reflections of the surface and subsurface lithology, structure and tectano fabric and also the active tectonic movements especially of the Quaternary period (Thornbury, 1985). Hence, the Geoscientists have all along been showing greater interest in mapping the drainage patterns. However, the mapping of the drainage patterns and detection of tectonic features there from have gained greater momentum only after the advent of modern Remote Sensing technology. Since the airborne and satellite borne spectral images have the credentials of showing the drainage pattern, the drainage anomalies and the tectonic features related to them all of which were studied in conjunction to bring out information on the geological history of the Quaternary period by many workers (Vaidyanadhan, 1971; Murthy and Sastri, 1981; Agarwal and Mitra, 1991; Ramasamy, 1991; Saravanavel and Ramasamy, 2014).

Introduction

Accuracy and uncertainty analysis is an important step in preparation of surface map through geostatistical techniques or digital soil mapping approach. It is because that we rely on a map based on how much accurate it is and the degree of uncertainty associated with the estimates while the map was prepared. Any stakeholder for a soil map especially policy makers is interested in accuracy and uncertainty of the map before taking suitable land management decisions involving soil map as an input. Again the level of accuracy and uncertainty depends on the properties for which the map has been developed. If the property of interest is sensitive to environment or human consumption, then the accuracy level should be very high while the uncertainty level should be very low e.g. heavy metal concentration in soil, quality parameters of water etc.

Introduction

Soil is one of the vital resource, and is the basis of the existence of mankind. Management of this resource including its conservation and utilization is of crucial importance. It is a base on which all life depends. In the recent past, with burgeoning populations and the national goals of seeking self-sufficiency in food and fibre production, this resource base is slowly being stripped. While natural systems often adapt to stress in a remarkable fashion, some relationships - once destroyed - can never be restored. Soil resources can be assessed and monitored through its spectral signatures gathered through remote sensing.

The term ‘remote sensing’ is commonly restricted to methods that employ electromagnetic energy (such as lights, heat, micro wave) as means of detecting and measuring target characteristics. Sensors acquire data as various earth surface features reflect or e mit electromagnetic energy (EM energy). Remote sensing is the technology that is now the principal method (tool) by which the earth’s surface and atmosphere (as targets or objects of surveillance) are being observed, measured, and interpreted from vantage points. Remote sensing of the earth traditionally has used reflected energy in the visible and infrared, and emitted energy in the thermal infrared and microwave regions to gather radiation that can be analyzed numerically or used to generate images whose tonal variations represent different intensities of photons associated with a range of wavelengths that are received at the sensor.

Introduction

Over the past few decades, soil resources have witnessed many changes driven by demographic pressure and climate change. It is necessary to have up to date soil information to monitor the state of soils health with time. Soil resource inventory provides information about the potentialities and limitation of soils for its proper utilization. Soil survey offers an accurate and scientific inventory of different soils, their properties and extent. An in-depth knowledge of the type of soils and their spatial distribution is a prerequisite for developing rational land use planning. Remote sensing is the science of obtaining information about the earth’s surface without actually being in contact with it. On the other hand, proximal sensing refers to remotely sensed measurements that are taken at the field or laboratory level. Both these processes involve an interaction between incident radiation and the targets of interest. Fundamentally, remote sensing data products are a representation of the functional response of objects to energy sources. These are typically spectra, which are acquired as a discrete series of reflectance measurements taken at different wavelength intervals, or bands. In the shorter wavelengths of the electromagnetic spectrum (visible part), features can be detected by virtue of reflected solar energy, while in the longer wavelengths (microwave, thermal parts), sensing of emitted energy works. Conventional soil sampling, and subsequent laboratory analysis are generally time consuming and costly. In this context, remote sensing plays a crucial role for studying soil resources. The term remote sensing is generally used for airborne and space borne acquisitions, whereas proximal sensing refers to ground-based laboratory and field measurements. Advances in the quantitative disciplines like remote sensing and proximal sensing have laid the foundations for a spatial exploration of soil-system dynamics within a landscape context (Pennock and Veldkamp 2006).

Introduction

Soil is a dynamic natural body, characterized by high degree of spatial variability due to combined effect of physical, chemical or biological processes that operate with different intensities at different scales (Goovaerts 1998). Reports have shown that there is large variability in soil properties, crop yield, disease, weed etc., not only in large-sized fields (Godwin and Miller 2003,Vrindts et al. 2005), but also in small-sized fields (Bhattacharya et al. 2008). Therefore, knowledge of hydro-physical properties of soils is crucial for management practices for all kinds of agricultural practices for efficient utilization of input resources. Plant growth and development is highly related to soil hydro-physical properties, which not only depend on soil intrinsic textural and chemical characteristics (Hamza and Anderson 2005) but also on soil management.

Soil physical properties which change with the variation in soil structure include bulk density, total porosity, pore geometry (size distribution, shape, continuity and tortuosity), penetration resistance and aggregate stability, consequently affecting soil hydraulic properties such as water retention characteristics, plant available water capacity, infiltration capacity and saturated hydraulic conductivity. These soil properties are dependent on seasonal climatic conditions, management practices, crop development and biological activity (Reynolds et al. 2007). The hydro-physical properties of soils, i.e., water retention and water permeability in both saturated and unsaturated zones not only shape soil water balance but also decide the conditions for plant growth, development and yield. They also determine water availability for the plant root system and the transfer of water with chemical compounds dissolved in it into deeper layers.

Introduction

The life support systems of a country and socioeconomic development of its people largely depend on soils. The soils are the most valuable natural resources for the society. It caters the basic needs of mankind by producing food, fibre and timber. It is therefore essential to know the distribution and extent of different soils and their qualities, potentialities and constraints for sustainable utilization of this valuable natural resource (Shyampura and Sehgal 1995). Information on distribution, potential and constraints of major forest soils are essential to design most appropriate soil management systems in order to increase productivity of forests as forests also offer excellent potential for poverty reduction and rural economic growth in India. However, unlike agriculture lands forest soils usually draw less attention and are ignored in spite of the fact that they nourish the lungs of the Earth. Soil quality is the most important factor in forest management decisions. Soils will determine productivity of a particular forest and management strategy. Knowing about forest soils can serve as a basis for forest management decisions, including land acquisition, species selection for planting, site preparation requirements, watershed development, fertilization prescriptions, stand density/ composition, and harvest timing, as well as decisions affecting land ownership and use.

Introduction

High degree of spatial variability in soil properties is observed at different scales. This variability is generally originated from the combined effect of physical, chemical or biological processes operating with different intensities at different scales (Goovaerts 1998). Knowledge of this spatial variationof soil properties is important in several land management applications e.g. variable rate application of nutrient and water in agricultural production system, land suitability classifications, modeling water balance components at landscape scales, precision farming etc. The concept of ‘management zone’ was also evolved in response to this large variability with the main purpose in efficient utilization of agricultural inputs with respect to spatial variation of soils and its properties (Franzluebbers et al. 1996, Atherton et al. 1999, Malhi et al. 2001). Therefore, an appropriate understanding of spatial variation of soil properties is essential. The most important way to gather knowledge in this aspect is to prepare soil maps through spatial interpolation of point-based measurements of soil properties. Here, a case study is discussed where soil water retention at two critical levels e.g. field capacity (FC) and permanent wilting point (PWP) was spatially characterized through geostatistical approaches. Because these two soil moisture contents guide farmers to apply right amount of irrigation water at right time. The study was carried out at the experimental farm of ICAR-Indian Agricultural Research Institute, New Delhi, India (28°37′-28°39′ N, 77°8′ 30″-77°10′30″ E, 217-241 m above mean sea level). A detailed discussion of the study is available in Santra et al. (2008)

Introduction

Globally, the SOC pool of 1,550 Pg (1 Pg = 1015 g) to 1-m depth is about three times that of biotic and twice that of atmospheric pools (Post et al. 1982, Watson et al. 2000). In arid and semi-arid ecosystems, SOC contents show high degree of spatial variability due to patchiness of vegetation (Wiesmeier et al. 2009). The arid ecosystem might play a key role in mitigation of climate change effects through sequestering carbon in soils (United Nations 2011). Therefore, a suitable land use system having high C sequestration potential for arid ecosystem needs to be identified and promoted. However, the prevailing conditions of arid ecosystems normally does not support dense vegetation. Therefore, low carbon stock is expected in both above-ground vegetation and below-ground soil. Fruit trees are an integral part of arid farming system and played a significant role to improve the nutritional security and employment opportunity of farmers but also have potential role to increase carbon storage both in biomass and soil. To quickly assess the soil carbon restoration programmes, it is important to know how much soil carbon is stored in an agricultural farm through adoption of different land management practices. Therefore, reliable estimates of SOC pools are essential to establish the soil carbon sequestration programmes at different landscape scales.

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

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

Abstract

The weather or climate is a natural resource and is an important basic input in agricultural planning and strategies. Every plant process, related with growth, development and yield of a crop and each of inseason and off-season farm operations (according to World Meteorological Organization) is more than 10 per cent and can reach up to 50 per cent in smaller areas and not a surprise even if it reaches to 100 per cent on micro scale. Amongst the various weather elements, temperatures, radiation and rainfall play major role in deciding the crop growth and yield levels. Precipitation is one of the important weather factors being responsible for atmospheric and soil moisture and therefore has more agricultural importance, especially in rainfed agriculture.

Keywords: Remote sensing, weather, agroadvisory, GIS

1.0 Introduction

India receives more than 70 per cent of its annual rainfall during South West monsoon season. Indian summer monsoon rainfall shows large intra - seasonal and intra-annual variability (Parthasarathy, 1960; Alexander et al., 1978; Mooley and Parthasarathy, 1984) and also changes in space and time, intensity and distribution. Borgaonkar and Pant (2001) have reported that Indian monsoon rainfall has shown trend less nature since 17^th century based on proxy data with large inter-annual fluctuations. IPCC (2001) has reported increase in rainfall over tropical and higher latitudes and decrease in rainfall over subtropics and mid latitudes.

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

The objective of the study is to build a framework of Geo-spatial Information System for effective decision making by empowering all the stake holders with spatial and non-spatial data. The Interface of this information system is developed as a deployable windows application using Map Objects in Visual Basic programming language with MS Access database. The practical utility of the proposed information system was explained with a case study in Aquaculture. This geo-spatial information system provides required information through maps based on spatial and attribute quarries. These dynamic maps help in taking effective decisions.

1.0 Introduction

Computer based information systems proved to be very efficient and effective tools for managing data and information to aid in decision making . FAO (2000) proposed agricultural knowledge and information system for rural development (AKIS/RD) to link rural people and institutions to promote mutual learning and generate , share and utilize agricultural technology , knowledge and information. This serves as vehicle for sharing ideas and principles with various stake holders addressing the problems and seeking solutions to rural development. Although the rural development planning is top-down prescriptive approach , in reality the decisions are made by the stake holders based on their perspectives, knowledge and priorities. Problems particularly related to environmental impacts are location specific and contextual. Geo-spatial technologies may serve as better vehicle to store and share all kinds of location specific data and information. The state of mapping and management of geospatial data changed during the recent years with the diffusion of modern geospatial information technologies such as GIS(Geographic information system), GPS(Global positioning system) and image analytical system for remote sensing(RS) data. Adinarayana et al., (2008) proposed a geographical information and communication technology (Geo-ICT) based information system called Grama Vikas( rural development) to assist the user in analyzing the rural information for rural development, planning . During the recent years there is a paradigm shift in GIS applications for rural development particularly in developing countries, by way of integrating top-down approach with bottom-up approach by the stake holders who stand to be affected by the decisions based on these technologies. Emerging concepts include “ community - integrated GIS”, “GIS in participatory research” and ‘participatory GIS”. (Abbot et al., 1998)

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

2.1. Open source satellite data

The satellite images have been invaluable information sources for Natural Resource Management. They provide synoptic view of the Earth periodically helping in inventory, surveying, and monitoring in agriculture, hydrology, geology, mineralogy, land cover, land use and environment. Free global satellite image data of spatial resolutions of 1m to 1 km and spectral resolution of single band to hyperspectral are available from an increasing number of sources (Table 2.1).

Coordinate Reference System (CRS) is a framework of coordinate based local, regional or global reference system used to represent the locations of geographic features. Coordinate Reference Systems (CRS) provide a standardized way to define the real-world geographic locations which further enable us to use common locations of geographic datasets for integration. The datasets from different sources and CRS are transformed to a common CRS in order to perform various integrated analytical operations like overlaying of data layers. Coordinate Reference Systems are mainly of two types:

1. Geographic Coordinate System: This is global or spherical coordinate system in which locations of features on earth are defined in terms of latitude and longitude values. Latitude and longitude are angles based on a point at the centre of the earth. In this system, locations are defined by degrees, therefore, distances cannot be measured accurately. The most common geographic coordinate system is the World Geodetic System 84 (WGS84).
2. Projected Coordinate System: In this system, locations of features are defined using cartesian x, y coordinates on a flat, two – dimensional surface. This system is based on sphere or ellipsoid projected on flat surface. Projected Coordinate System are generally referred as projec- tion. It is required for preparing maps on paper or computer screen. Un- like Geographic Coordinate System, projected coordinate system has ac- curate measurements of distance, angles and areas across the two dimen- sions. However, there is alwaystrade-offs between area, direction, shape, and distance in this system due to distortions created while representing ellipsoid or spheroid on a flat map. So, the projection type is selected based on its application. Most common projections are Universal Trans- verse Mercator (UTM), Lambert Conformal Conic and Albers Equal Area.

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.

The climate, the past weather event that existed over larger region and covering long years of more than 30 years is very important for the emergence and successful sustenance of an organism including human kind. Normally scientists talk about environment and this includes not only the soils but also the climate of the particular region. Based on this, during 1989, the Planning Commission of India divided the entire India in to 15 agro-climatic zones based on physiography and climate. This division is only for planning purposes. Subsequently under NARP, the Indian Council of Agricultural Research (ICAR), New Delhi in consultation with the Planning Commission, requested all State Agricultural Universities (SAU) to divide their State in to different sub climatic zones considering soils, temperature and other weather parameters preciously with in the major agroclimatic zone of India in which the concerned State falls. Accordingly, each SAU has divided their State into different agro-climatic sub-zones and this resulted in 129 agro-climatic sub zones in India and limited to 127 and these all fall within 15 agro climatic zones of India as done by the Planning Commission of India.

The National Bureau of Soil Survey and Land Use Planning (NBSS&LUP), Nagpur not satisfied with this division, considering soils, temperature, rainfall, vegetation and all factors responsible for ecosystem (bio-climate, length of growing period, moisture index) divided the whole India in to 20 agro-eco regions by 1992 and revised preciously again by 2015 (Mandal et al., 2016) and the revised approach is being considered as scientific tool and taken for micro-level planning in India now and those are discussed at this chapter.

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).

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.

Introduction

Crop discrimination is the process of using remote-sensing technologies to identify and characterize different types of crops based on their electromagnetic behavior at different wavelengths. Each crop has a unique spectral signature that reflects its response to the incident radiation. However, the spectral signature can also vary depending on the season, the angle of the sensor, crop’s features, illumination intensity, weather phenomenon, and topography among other external factors (Parida et al., 2023).

Introduction

To address the escalating food demands of the global population, a transformation in the agricultural sector is imperative (Velten et al., 2015; Lampridi et al., 2019). The current overdependence on finite resources is leading to their overexploitation, largely due to irresponsible usage (Velten et al., 2015; Lampridi et al., 2019). By adopting a site-specific approach, farmers can apply inputs only where they are necessary in the field (Velten et al., 2015; Lampridi et al., 2019). This method can enhance output, decrease labor costs, and mitigate the environmental damage caused by excessive input use (Velten et al., 2015; Lampridi et al., 2019).

Introduction

Nanopesticides are pesticides that use nanomaterials or nanotechnology to improve their effectiveness and safety in agriculture. Nanomaterials are materials that have at least one dimension between 1 and 200 nm. Nanomaterials have different properties than their bulk counterparts, such as higher surface area, reactivity, and mobility. Nanopesticides can be formulated in various ways, such as nanosized active ingredients, molecular active ingredient nanocarrier complexes, or active ingredients encapsulated or coated by nanomaterials (Deka et al., 2021; Xu et al., 2022).

Introduction

Crop models can be broadly classified into two categories: dynamic or process-based crop simulation models (CSMs), and reduced form statistical models. Since simulation models are based on various plant-related processes, they develop or alter in tandem with plant growth (Chetty 2009); as a result, they are inherently nonlinear (Olmstead 2009). To run, calibrate, and validate, they require a significant amount of date input. However, statistical models are helpful in situations where there is a lack of data because they describe the relationships between a subset of variables while keeping the others constant. (Chetty 2009).

Introduction

The term “Remote Sensing” was coined in 1950s by Ms. Evelyn Pruitt, a geographer with the U.S. Office of Naval Research, and the term is now commonly used to describe as the science and art of identifying, observing, and measuring an object on the earth surface, without having any direct contact. This process involves the detection and measurement of radiation of different wavelengths reflected or emitted from distant objects or materials through which they may be identified and categorized by class/type, substance, and spatial distribution (National Aeronautics and Space Administration—NASA). Remote sensing technology has been widely applied in various applications such as water resources, agriculture, geological studies, forestry, land use, resource exploration, etc.

Elements of Remote Sensing

The remote sensing process involves an interaction between the incident radiation and the targets of interest, exemplified by the use of imaging systems in which the following seven elements are involved; however, remote sensing also involves sensing of emitted energy and using non-imaging sensors

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.

When ANOVA indicates significant differences among treatment means, further analysis is required to determine which particular means differ significantly. This chapter deals with post-ANOVA procedures used for detailed comparison of treatment means. It introduces methods such as critical difference, least significant difference, and multiple comparison procedures. Particular attention is given to Scheffé’s method, Newman–Keuls method, and Duncan’s New Multiple Range Test. The chapter explains the principles, calculations, and interpretation of these techniques using forestry examples, including comparisons among tree species and provenances. It also discusses considerations for selecting an appropriate multiple-range or comparison method according to the objectives and number of comparisons involved.

Abstract

Being the junction between the continental and the oceanic plates, the coastal zones are always tectonically alert and hence vested with number of aults. The study of LANDSAT ETM FCC imagery revealed one such a major fault along NNE-SSW aligned Tamil Nadu coast from Chennai in the North northeast to Cape Comorin in the South southwest. This Precambrian boundary fault shows signs of repetitive reactivation during Gondwana, Tertiary and Late Holocene periods. While in former two periods it shows indications of faulting, in the latter period, it is manifested in the form of drainage deflections indicating sinistral movements of beds. While such sinistral morphology of the fault seems to be related to the Post collision compression, the seismicities in and in its close proximities indicate the seismic significance of this fault. In the context of natural resources and disasters viz: geothermal springs, flooding and seismicities, this fault demands deeper studies.

Introduction

The coastal regions in general form the junction between the continental and oceanic plates. Hence, the coastal regions are always tectonically active and thus vested with coast parallel, tangential and conjugate faults depending upon the tectonic history of the area. In the Indian subcontinent too, all along the 9000 km long east and west coast margins, number of major faults were mapped by the earlier workers. Significantly, Vardarajan and Ganju (1989) have brought out a comprehensive picture on the lineaments of the entire coastal zone of India using Landsat images. Vemban et al. (1977) earlier inferred faults along certain segments of east coast of Tamil Nadu and observed them to be lithological contacts and also seismogenic in nature. Raiverman et al. (1966) have again inferred earlier a N-S curvilinear fault in Thanjavur deltaic region and attributed it to post drift kinematics of the Indian plate. Ramasamy (1989) has brought out the morphotectonic and morphodynamic model of the east and west coasts of India on the basis of tectonic and geomorphic signatures using Landsat satellite images. Ramasamy (2006) developed a first time comprehensive model on the active tectonics of the Indian Peninsular and in which he brought out detailed information on the varied geomorphic, tectonic and hydrological anomalies and inferred them to be related to the whirling and fracturing of the Indian plate due to the still prevailing N–S to NNE – SSw compressive force which originally drifted the Indian plate to the present position after the breakup of the Gondwana land.

Abstract

Landslides have become a fast spreading epidemic in the mountain belts around the world. As both the natural geosystem and the triggering parameters this phenomenon, the scientists & technocrats from all over the world have started studying it using varying parameters and multivariate advanced scientific tools. In this connection the present study lays an emphasis on the need for giving deserving importance to one of the important geosystem parameters, namely the geomorphology in Landslide Vulnerability Mapping. The same has been accomplished by taking the Nilgiri Mountains of Western Ghats, South India as the test site.

Introduction

Landslides are the most commonly witnessed geohazards in mountainous systems of all over the world causing greater and recurring loss to Man, his properties and to his various developmental programmes. As these landslides mostly occur after heavy rainfalls, it was considered as the most important triggering parameter for the landslides. In indian subcontinent, the landslides of Himalayan region while were inferred to be predominately due to Active tectonics (1,2,3,4,5,6,7,8,9,10) landslides of Westernghats of Maharastra were explained to be the effect of extensive weathering and the rock falls from the cliff and the summit zone (11,12) but in contrast, the landslides of Nilgiri mountains have been attributed to deforestation, direct entry of rain water into the soil system and the resultant pore pressure increase (13,14,15,16,17,18,19,20,21) but the studies carried out (22) in the Nilgiri Mountains indicated that various geosystem parameters viz: Lithology, Structure, Geomorphology, Slope etc., occur in various permutations and combinations and assign different landslide vulnerability grades to the land systems and when such vulnerable zones are interfered by the triggering parameters, the landslides occur.

The term hydrogeomorphology can be divided into three terms hydro- means water including both surface and groundwater; geo- means the earth and morphology- is the surface expression of the features in the form of landforms. This means that the hydrogeomorphology is dealing with the aspects of water, rocks and earth’s morphological features (land). Of these water and land are most important natural resources for human beings.

Water is synonymous with life. This is a natural resource and an absolute necessity for the survival of the living beings. Human beings have an organic relationship with water. For living and livelihood, human beings solely depend upon the availability of water. They have an inalienable right on water. This is a community resource and cannot be made a tradable commodity, violating normative law of nature. Water is among the most precious gifts of nature to mankind. Most of the ancient towns of the world grew on the banks of the river, and some of the ancient civilizations are known by the names of rivers. Rivers have always been important sources of drinking water and the means of sustaining human, animal and plant life. Whenever one is dealing with water resources development and utilization, it has to be kept in mind that not only quantity of water but also quality of water is very important. The well being and development of our society is dependent on the availability of water.

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 tectonics of the geological past from Archaeozoic to early part of Cenozoic era has been studied due to their penetrative documentation in the form of folds and faults. But the tectonic history of the latter part of the Cenozoic era (i.e Pleistocene period) has remained a matter of conjecture owing to the poor response of the rocks to Pleistocene movements. In the present study the authors presented a model for the Pleistocene earth movements of South India through the study of river migration, coast line changes and lineament fabric derived from the space borne photographs.

In the area of study, the northerly migration of Paleru and Pennar and southerly shift of Palar, Ponnaiyar and Cauvery rivers, marine regressions restricted within this segment and the closely spaced crest line fractures suggest a lineament controlled E-W trending Quaternary upwarping along Mangalore-Madras alignment. Similar E-W cymatogeny is inferred in the southern tip of the Peninsular India on the basis of once again such observations. Such E-W trending Pleistocene arching phenomenon suggests a N-S oriented regional compression which could be related to the collision of Indian plate with Tibetan plate.

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.

Introduction

All spatial data stored in a GIS are associated with a map projection, either implicitly (so-called “unprojected” data stored with raw longitude, latitude coordinates) or explicitly (where the data have been transformed into a known map projection). Map projections are a particularly important feature of spatial data because they introduce error and distortion, since a sphere cannot be transformed to a plane without some stretching and twisting of the sphere’s surface.

The typical GIS package supports anywhere from 5 to 50 map projection types, and most projections may be modified or customized by varying their parameters. This flexibility is important for two reasons First, in order to use two or more layers together in a GIS for visualization or analysis, all data must be projected in the same way. Second, certain types of analyses, such as the measurement of area, are only valid when using certain types of projections (and conversely, are completely wrong when using an inappropriate projection).

Abstract
 
The definition of what drought is and what drought is not, has profound implications for the environment and all segments of society, yet it may be different for each. Many attempts have been made to develop a comprehensive and meaningful definition. A generic definition provides a starting point:  Drought is a persistent and abnormal moisture deficiency having adverse impacts on vegetation, animals, and people. The public perceives “drought” as a serious departure from normal water conditions, a departure that requires a public response to reduce negative impacts. About two thirds of the geographic area of India receives low rainfall (less than 1000 mm), which is also characterized by uneven and erratic distributions.

Abstract

Groundwater flow modeling in hydrological sciences is one of the main tools used to assess the resource potential in terms of quantity and to predict the future impacts under different stresses/scenarios. This case study is prepared to present the  groundwater flow model for the Osian-Mandore pilot area with 12 villages of Mandore Block and 21 village of Osian Block in Jodhpur district of Rajasthan. The spatial model parameters and spatio-temporal fluxes were acquired and processed using remote sensing, GIS and Groundwater flow modeling interfaces. MODFLOW software was used to model the groundwater flow system in three interfaces PMWIN 5.3.0, Groundwater Modeling System and Visual MODFLOW. 

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.

Abstract

The strenuous field trekking, inaccessibility, perception of geology only within the visibility range of the eyes etc. have remained matters of major constraints in the past in field based geological mapping. The remote sensing technology not only eradicated these but also provided lot many newer vistas in the field of geology. In addition, the application of such unique technology has brought out a hierarchy of newer concepts in the field of geology. The paper narrates the newer knowledge gathered on the geology of South India in the post remote sensing Era.

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

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.

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.

During the last 21 years, the scientists and scholars of the M.S. Swaminathan Research Foundation (MSSRF) have been working on the design and implementation of projects which could have a large extrapolation domain in respect of imparting a pro-nature, pro-poor, pro-women and pro-sustainable livelihood orientation to technology development and dissemination. I would like to write about a few of the MSSRF initiatives, which have now become state, national and global programmes.

Mahila Kisan Sashaktikaran Pariyojana: Strengthening the role of women in agriculture

MSSRF initiated the Mahila Kisan Sashaktikaran Pariyojana in the Vidarbha region of Maharashtra in 2007 for empowering women farmers, including the widows of farmers who had committed suicide, in areas related to enhancing the productivity, profitability and sustainability of small-scale rain-fed farming. The empowerment measures incorporated access to technology, credit, inputs and market.