eChapters

Introduction

Goats provide multiple products like chevon, milk, skin, fibre, manure and transport. Pashmina occupies a prime position among animal fibres for its firmness, warmth, durability, lightness, softness and ability to absorb dyes and moisture compared to mohair and/or wool for being free from modulation and crimps. Pashmina is highly valued fibre for manufacturing quality apparels. It has recorded its name in the Guinness Book of World Records for being costliest cloth in the world after trade ban of most precious natural fibre Shahtoosh (King of fibre) of small Tibetan Antelope known as Chiru. In India, two recognized pashmina breeds are Changthangi and Chegu. Changthangi is native to high altitude areas (3700 to 4500m) in Ladakh region of Jammu and Kashmir reared by a pastoralist nomads Changpas whose population is 1,96,000 (LADHC, 2006). The Chegu breed is distributed in cold-arid trans-Himalayan mountain ranges from Himachal Pradesh to Uttaranchal at an altitude of more than 3000 m (Thakur et al., 2006).

Introduction

Food and nutritional security continues to be the main plank of India’s food policy despite its tremendous achievements on food production front during the last three decades. The Green Revolution helped India to overcome chronic food scarcity and made it self sufficient in food production. The per capita availability of cereals increased from 360 gms/day in 1966 to 422.4 gms/day in 2004. On the other hand, availability of pulses, the main source of protein for over- whelming vegetarian population of India, declined from 48 gms/day to 38 gms/day, which is attributed largely to diversion of land from pulses to cereals crops (Gopalan et al, 2004). The extra income generated due to Green Revolution has increased the access of rural population to a wide variety of foods, like milk, meat, eggs, fish, fruits and vegetables, which perhaps could offset the protein deficiency due to decline in per capita availability of pulses, therefore, resulting in the increase in per capita consumption of protein in rural areas. The trends in cereal consumption indicate that per capita cereal consumption has been declining in most of the states. This trend is more prominent in agriculturally developed states, like Punjab and Haryana. In these states, production and per capita consumption of milk have increased substantially.

The dietary pattern in India remains cereal based and the expenditure shares of foods of animal origin (meat, eggs and fish) and fruits, which are rich in nutrients, are trivial. More than 22 per cent of the population stays below poverty line and generally suffers from various nutritional disorders due to lower purchasing power. The nutrient rich foods like milk, meat eggs, fruits, etc. are highly responsive to income changes. Besides, choice of food and consequently the level of nutrient intake is also influenced by the other economic, social, cultural and climatic factors. Spurt in income growth and increasing consumerism in rural areas in recent years has heightened the need for understanding the food consumption pattern. Using the farm level data from three regions of Maharashtra this paper attempts to examine the pattern of consumption of nutrients by cultivators and sources of supply of different nutrients.

Introduction

The Integrated Watershed Development has come to be recognized internationally as an important holistic approach to natural resources management and poverty reduction, wherein promoting the concept of sustainable development. In the Indian context, watershed development has come to be acknowledged as key and discrete units in rural development which forms an important vehicle for achieving the objectives of increased production and availability of food, fodder and fuel restoration of agro ecological balance and in improving the livelihood status of the village communities.

In line with the above, the conceptualization of Integrated Watershed Development Project Hills-II (initiated in September 1999) has been built up on the success of IWDP Hills-I project with a laudable vision to arrest environmental decline, boost agricultural growth, and ensure better management of scarce land and water resources and reducing poverty dimensions in the Siwalik & Karewas regions, which are one of the most environmentally degraded areas in India. The project area encompasses two sub-watersheds in sub-tropical belt of Siwaliks of Jammu region and two in temperate Karewas of Kashmir valley, covering an area of 1,11,080 ha. Ramnagar and Akhnoor sub-watersheds are located in Siwalik range of Jammu region whereas the sub-watersheds of Rajwar and Rambiara are located in Karewas belt of Kashmir valley.

Introduction

In India, per capita cereal consumption has been declining since the early seventies, despite a significant increase in per capita cereal production (Radhakrishna and Ravi, 1992 and Rao, 2000). Cereal consumption per capita per month fell from 15.35 kgs in 1970-71 to 12.70 kgs in 1999-2000 in rural area and from 11.40 kgs to 10.40 kgs in urban area during same period. It might be due to shifting of consumers’ choice from food to non-food items; from cereals to non-cereals within the food group and from course to fine cereals within the cereal group. The decline in cereal consumption has been higher in the rural area due to development of rural infrastructure and availability of job opportunities which ultimately helped in improving their level of income (Rao, 2000). Despite spectacular growth in food production during last 30 years the problem of malnutrition still persists across different regions in India because increase in food grain supply alone cannot conquer hunger and malnutrition.

The consumption pattern and nutritional status have also experienced a significant change during last two decades in Bihar. Cereal consumption per capita per month has declined from 476 gms in 1983 to 455 gms in 19992000. The situation is more alarming in poor households who constitute about half of rural population in north Bihar. There is lack of research on consumption pattern, nutrient intake and nutritional status based on household data, particularly in context of Bihar. In view of the above observations the present study is undertaken to analyze the consumption pattern and nutritional status of poor households in north Bihar.

Introduction

The right to food is the most fundamental among the human rights. Food production, distribution and consumption is an important issue for developing countries. The dimensions of food problem in Asia have been changing since the food crisis of sixties and seventies. The lesson of those years is well-learnt, and attaining self-reliance in food came to be recognized as a key goal of development. Most of the Asian countries have been suffering with many problems such as slow growth rate in cereal production, large share of agriculture in the gross domestic product, weak infrastructure, low purchasing power and massive rural poverty which had made the South Asia region as a whole food deficit (Plumb, 1998).The possibility of impending world food crisis looms largely from increasing pressure on national agricultural sector to meet the demands triggered by rising population, growth in people’s income and change in expenditure and consumption pattern (Ghosh, 2001).

Agricultural mechanization involves the design, manufacture, distribution, use and servicing of all types of agricultural tools, equipment and machines. It includes three main power sources: human, animal and mechanical with special emphasis on mechanical (tractive power).

Mechanization has been identified as one of the critical inputs for production agriculture. It may be described as an appropriate package of technology to i) ensure timely field operations to increase productivity, reduce crop losses and improve product quality, ii) increase land utilization and input use efficiency and iii) increase labour productivity through labour saving and drudgery reducing mechanical devices. The mechanization of Indian agriculture has proceeded along two-pronged approach based on improved equipment and enhanced power supply. However, compared to the mechanization of western agriculture which was motivated by the need to substitute human labour and draught animals with mechanical prime movers, the guiding principle in mechanizing Indian agriculture has been to maintain a socially desirable mix of human labour, draught animal power and mechanical power.

Classification of Materials

Broadly there are two groups of materials used for making farm machines namely metallic and non-metallic:

It is a mechanical manipulation of soil to provide favourable condition for crop production. Soil tillage consists of breaking the compact surface of earth to a certain depth and to loosen the soil mass, so as to enable the roots of the crops to penetrate and spread into the soil.

Tillage operations following primary tillage which are performed to create proper soil tilth for seeding and planting are secondary tillage. These are lighter and finer operations, performed on the soil after primary tillage operations. Secondary tillage consists of conditioning the soil to meet the different tillage objectives of the farm. These operations consume less power per unit area compared to primary tillage operations. Secondary tillage implements may be tractor drawn or bullock drawn implements.

Seeding or sowing is an art of placing seeds in the soil to have good germination in the field. A perfect seeding gives a) Correct amount of seed per unit area. b) Correct depth at which seed is placed in the soil. c) Correct spacing between row-to-row and plant-to-plant. Seed drill is a machine for placing the seeds in a continuous flow in furrows at uniform rate and at controlled depth with or without the arrangement of covering them with soil. Planter is normally used for those seeds which are larger in size and cannot be used by usual seed drills. A planter consists of: (i) hopper (ii) feed metering device (iii) knock out arrangement (iv) cut-off mechanism (v) furrow opener and (vi) other accessories. A planter has seed hopper for each row.

Sprayer is a machine to apply fluids in the form of droplets. Sprayer is used for the following purpose.

• Application of herbicides to remove weeds.
• Application of fungicides to minimize fungus diseases.
• Application of insecticides to control insect pests.
• Application of micro nutrients on the plants.

It is the operation of cutting, picking, plucking and digging or a combination of these operations for removing the crop from under the ground or above the ground or removing the useful part or fruits from plants.

Thresher is a machine to separate grains from the harvested crop and provide clean grain without much loss and damage. During threshing, grain loss in terms of broken grain, un-threshed grain, blown grain, spilled grain etc. should be minimum. Bureau of Indian Standards has specified that the total grain loss should not be more than 5 per cent, in which broken grain should be less than 2 per cent. Clean un-bruised grain fetch good price in the market as well as it has long storage life.

It is a machine designed for harvesting, threshing, separating, cleaning and collecting grains while moving through standing crops. Bagging arrangement may be provided with a pick up attachment. The main functions of a combine are: (i) Cutting the standing crops (ii) Feeding the cut crops to threshing unit (iii) Threshing the crops (iv) Cleaning the grains from straw (v) collecting the grains in a container.

• A machine is a device which receives some sort of energy and does some work.
• A rigid link is one, which does not undergo any deformation while transmitting motion.
• A flexible link is one which is partly deformed in a manner not to affect the transmission of motion.
• A structure is an assemblage of a number of resistant bodies having no relative motion between them.
• A turning pair has a completely constrained motion.
• Cam and follower includes higher pair.
• The lower pairs are self-closed pair.

Tractor is a self-propelled power unit having wheels or tracks for operating agricultural implements and machines including trailers. Tractor engine is used as a prime mover for active tools and stationary farm machinery through power take-off shaft (PTO) or belt pulley.

Power tiller is a prime mover in which the direction of travel and its control for field operation is performed by the operator walking behind it. It is also known as hand tractor or walking type tractor. The concept of power tiller came in the world in the year 1920. Japan is the first country to use power tiller on large scale. Power tiller was first introduced in India in the year 1963. Power tiller is a walking type tractor. The operator walks behind the power tiller, holding the two handles of power tiller in his own hands. Power tiller may be called a single axle walking type tractor, though a riding seat is provided in certain designs. In agricultural applications it is often required to transmit the mechanical power from its source to the point of application. The main sources of power for agricultural machines, i.e., the diesel engine for self-propelled machines and the electrical motor for many stationary machines are primarily rotary power and are transmitted by means of belts and chains. Tractor power is utilized by traction, power-take-off drives (PTO) by fluid power.

Ergonomics (also known as Human Engineering, Human Factors or Human Ergology) is the scientific study of relationship between a person and his/her working environment. The term environment includes the tools, materials and method of work, ambient conditions and physical environment in which the work is carried out, and also the organizational factors. Ergonomics application can help in increasing the efficiency and productivity, reducing drudgery and occupational health problems, and enhancing safety of workers in various activities.

Energy is defined as the capacity of doing work and is necessary for survival. It is basic input to any society’s development and economic growth. Everything happens in the world is the expression of flow of energy from one form to other. There are different sources of energy, i.e., chemical, mechanical, fossil, nuclear and renewable energy.

The following products are obtained from refining of crude oil

For development of agricultural engineering machineries, materials and manufacturing techniques play a very important role. Functionality, efficacy, life span, economics and aesthetic of any machine or structure are affected severely by the material of fabrication process. The manufacturing processes discussed in this chapter also include the pretreatment to manufacturing and structural materials. Wood and some kind of ferrous alloys had been the choice of materials for fabrication of agricultural machines in past few centuries, whereas these materials along with mud, bamboo, some agricultural residues and some earthen materials were the materials of choice for agricultural structures. Engineering materials are available with wide range of properties and characteristics. There are many properties, which are inherent in the materials, and some of them can be changed during processing and manufacturing.

Measurement also forms a basic element of any control process. The measurement of discrepancy between the actual and desired performance of a system is central to any control process. Electronic instrumentation provides the solution to many and varied problems of measurement and control. It is often required to change or transduce a measurand into a corresponding electrical signal. The elements which changes/converts the physical variable in electrical signal are termed as sensors or transducers. For a measurement to be useful it must be reliable. That is where question of accuracy or uncertainty of a measurement arises. This may be dealt with clear understanding of measurand and measurement system.

• Spray Angle — The angle subtended at the final orifice by the edges of the spray pattern.
• Variation in discharge rate between first and last observation shall not be more than 5 percent.
• The volumetric efficiency requirement for roller vane type pump shall be minimum 80 percent.
• The volumetric efficiency of piston, plunger type pump shall be minimum 80 percent.
• If the droplet size is reduced from 2 mm to 1 mm, number of droplets produced will increase by 8 times from the same volume.

With increase in population, demand for basic needs has been steeply rising during the past decades in most of the developing countries of the world. The growing population needs food, clothing, shelter, fuel and fodder for them and their livestock. In India, 50 to 70% of the people are living in rural areas that neither have adequate land holdings nor alternate service opportunities to produce or procure these basic commodities.

The present day living demands quality life. The quality life can be maintained provided our surroundings remain intact or improved to provide means for better living. With increasing advancements in science and technology, we have manipulated our environment without paying adequate attention to consequences. The result has become so alarming that now all the countries of the world are trying to actualize the meaning and concept of sustainability. It is more so in case of agriculture as it forms core base of life supporting system.

The magnitude of manipulation varies from country to country depending upon level of development. It goes without saying that development and manipulation of environment are interrelated having positive and negative effects. To eradicate ill effects of manipulation, we need to understand the meaning of actualizing of sustainability.

Concept of sustainable agriculture is of multiple dimensions. It denotes potential of technology, fragile ecosystem, and human interference of limited natural resources. An understanding of sustainable agriculture in brief indicates:

1. Increase in production with efficient use of resources

2. Control of external inputs of synthetic nature

3. Nutrient cycle within the farm must be closed.

Technical Advisory Committee (TAC) of CGIAR reveals that sustainability is a dynamic concept that allows for changing needs of a steady increasing global population. Sustainable agriculture should involve the successful management of resources for agriculture to satisfy changing human needs while maintaining or enhancing the quality of environment and conserving natural resources.

The dictionary meaning of sustainability is to keep an effort continuously the ability to last out and keep from falling. Sustainability basically refers to the capacity to remain productive while maintaining the resource base. Locker (1988) explained the term sustainable, a time dimension and the capacity of farming system to endure indefinitely. The concept of sustainability should serve as guide to agricultural practices. It must include technology and practices that both sustain and enhance productivity to meet the increasing food demands (Rutton, 1988). In short, environmental sustainability implies that it is compatible with and supportive of the criteria like;

3.1. Brief description of the state

Odisha a coastal state of India lies in between 170 31’ to 220 27’ North latitude and 810 27’ to 870 30’ East longitude. It is bounded by West Bengal in the North East, Jharkhand in the North, Chhatisgarh in the West, Andhra Pradesh in the South and Bay of Bengal in the East. The main features of the state are given in Table 2.

This chapter “Research Methodology” deals with methods and procedures followed in conducting the study. The chapter contains three parts. The first part deals with the sampling technique and the second part covers the empirical measures of different variables and last part describes details of data collection and statistical measures used in the study.

Social research concentrates more on socio economic variables to find out effects of the events that take place in social system. The magnitude of variation in the variables assumes to bring variation on the effect. The variables relating to farmers of small farms are many and they are specific to farming system of the coastal ecosystem. Such variables were grouped under personal, social, economic, communication behaviour, marketing behaviour, farming behaviour and training. The sub variables under each heading were given in the following table.

Organic farm produce is now gaining momentum in the world. People of high status and concerned with health hazards are interested in organic product. Since 1990, the market of organic product has grown reaching a value of Rs 55 billion in 2009 as per the Organic Monitor in the world. The demand has been reflected in increase of land under organic farming which has grown correspondingly at a rate of 8.9% per annum. At present there is approximately 37,000,000 hectare of land under organic farming worldwide. The idea has been percolated to rural areas and the farmers of all kinds are aware of organic farming. In terms of organic land, Australia leads the pack with 11.3 million hectares followed by Argentina (2.8 million hectares) and Italy with more than one million hectares. In Asia, China, India and Japan are the largest organic producers. Japan is the region’s largest market and buys majority of Asia’s production.

7.1. Sustainability in Agriculture

Sustainability essentially means meeting the needs of present generation without compromising the ability of future generation to meet their own needs. The concept used by FAO to convey the meaning of sustainability necessarily rely on management and conservation of resource base in relation to orientation of technological and institutional changes to ensure satisfaction in meeting human needs. Sustainability normally covers the meaning of conservation of natural resources. The natural resources are land, water, forest and livestock. The maintenance of these resources suffers due to low or no maintenance because of absence of infrastructure and inadequate finance. Apart from these constraints, poor management ability is also responsible for degradation of natural resources. To equip the people, in general, poor managerial ability has to be upgraded through multidisciplinary program, appropriate technology and establishment of peoples’ organizations. To work on sustainability as defined for maintenance and conservation, the people in general ought to develop a positive perception to work before the program is initiated. The perception directs action of individual in a positive manner. Therefore, it is necessary to determine the perception of people about the concept of sustainability, particularly in the field of agriculture.

8.1. Ecological Soundness

Conservation of natural resources essentially means maintenance and improvement of ecological status and not permitting them for further degradation. The natural resources are soil, water, forest, mountain and animal resources. An attempt was made to find out whether the respondents adopt certain recommendations for preservation of these natural resources irrespective of source of advice.

i. Soil Health

Soil is considered as an important ingredient of ecological soundness of an area. Adoption of soil health measures, like adding of organic manures, following of crop rotations, use of balanced chemical fertilizers, green manure and bio- fertilizers are some of the recommendations to maintain soil health. While examining the adoption of these measures, the following results were obtained.

At present producers and consumers are concerned about products and their uses. In farm sector agribusiness is gaining momentum because of marketing of farm produce and its availability to the consumers at affordable rate. Agribusiness thus has been identified as important element in improving farm business. The farm business is otherwise known as agribusiness. Agribusiness is an off farm activity mainly concerned with processing and marketing. It implies that in addition to production of farm produce farmers responsibility increases to process the out-put and its sale in the market for better price. The farmers like to approach different organizations, corporation and regulated markets. Therefore attempt has been made at government level to encourage cultivators to invest in the farm business. In order to increase the efficiency of farmers there is need of keeping the business flexible encouraging farmers to invest in farm and allied sector business.

Transfer of technology is closely associated with generation of technology and its use leading to development. Extension components contain stimulating inputs that would mobilize the practitioners to put recommendations into action. Sustainability in agriculture is very important component of present day agriculture and future aspirations. Keeping these aspects in view an attempt was made to enlist suggestions under extension approaches that would enhance sustainability in agriculture in the area under study. The suggestive extension measures to enhance sustainability in agriculture were studied under components of social structure, cooperation mechanism, evaluation technique and marketing network.

The factors affecting sustainability of agriculture under small farm production system in coastal ecosystem of Odisha was studied to ascertain the status of ecological factors and suggest means and ways to improve the situation. The response of the sample farmers and the findings of the study together led to suggest the following measures for up-gradation of ecosystem of the coastal area leading to sustainability of agriculture. Like other states, Odisha is also facing with problems of sustainability of agriculture. Our sample districts namely Puri, Khurda, Ganjam and Balasore which are situated in coastal eco-system of the state has different problems concerning to natural resources like soil, water, forest and animal wealth, etc.

The suggestions to improve the sustainability status of agriculture have been viewed from two important angles. One is adoption of technological measures to preserve natural resources and other is the policy and extension approach to educate people about the necessity of taking such measures for sustainability of agriculture and improve upon.

The study entitled “sustainability of small farms in coastal ecosystem” was conceived out of consideration of continuous degradation of natural resources- base consisting of soil, water, forest, maintain and animal wealth of the state. With broad objective of investigation into the status of sustainability of agriculture in the state, the specific analysis like socio-economic and farming related situations, perception about sustainability of agriculture in terms of ecological soundness, economic viability, social accessibility, humaneness and adaptability, development of sustainable agriculture index, adoption of sustainable measures, extension components and suggestions and strategy to maintain sustainability were taken into consideration. The organic farming and agri-business opportunities for sustainable agriculture were also studied.

The study was conducted in the state of Odisha covering the districts of Puri, Khurda, Ganjam and Balasore. Altogether four blocks each of one district and eight villages two from each block were selected for the purpose of the study. As much as 200 respondents who were within definition of small and marginal farmers were selected for interview. The respondents randomly so selected were personally interviewed by the author through an interview schedule developed on the basis of objectives stated earlier. The secured data were processed statistically to reveal the relevant findings as per the need of the study. From the relevant findings of the study the conclusions have been summarized below.

Introduction

Geostatistics is a branch of statistics that deals with the analysis and modelling of geo-referenced data. Its main aims are to quantify spatial variability and to create maps from point observations. Of course there is much more to geostatistics than just that and indeed some of the other uses of geostatistics are addressed in this chapter too, but the emphasis is on the assessment of spatial variability and geostatistical interpolation.

The first step of geostatistical interpolation is to quantify the spatial correlation structure of the variable of interest. This can be done by examining the observations and how these vary in space. Next spatial interpolation makes use of the quantified spatial correlation to derive optimal predictions at unobserved locations and create a map. The interpolation error is quantified as well, which helps to design optimal spatial sampling schemes that balance data collection costs and map accuracy. All this will be explained in this chapter, but in order to do so we first need to explain the statistical theory that underlies geostatistical interpolation followed by representation of the spatial correlation structure, the basics of geostatistical interpolation (‘kriging’), kriging extensions and spatial stochastic simulation.

Introduction

A complex spatial soil properties pattern is directly controlled by soil internal factors and anthropogenic impacts.Hartemink et al. (2001) elaborate a strong decline in mineralogy, morphology and genesis of soil research than strong increase in pedometrics applications during 1967 to 2001. Hartemink and McBratney (2008) identified this change as “soil science renaissance”. Basically, the soil science deeply rooted in agriculture, geology, and chemistry but the paradigm has been shifted from classification and inventorization to quantification of soil patterns in spatial as well as temporal patterns and their impact on the ecosystem health and hydrological cycle. The environmental keen approach explains that soil is in the center of the ecosystem and highly interacting with the biotic and abiotic factors of the ecosystem and a complex pattern and process has been co-evolved with the time.

The arid region in India is spread over in 38.7 million hectare land. Out of the total 31.7 m hectare lies in hot arid region and remaining 7 m hectare comes under cold arid region. The hot arid region occupies major part of northwestern India (28.7 m ha) and a small pocket (3.13 mha) in southern India. The north western arid region occurs between 22°30’ and 32°05’ N latitude and 68°05’ to 75°45’ E, covering western part of Rajasthan, north western Gujarat and south western parts of Haryana and Punjab. About 62% area of arid region falls in western Rajasthan and 20% in Gujarat. Haryana and Punjab together constitute 7% area of arid region. The state wise distribution of arid region is shown in Table 3.1. Further our discussion is based on the majority area of arid region, belonging to Rajasthan, Gujarat, Punjab and Haryana.

Soil sampling is an integral and essential component of soil fertility evaluation and nutrient management research. The effectiveness of soil sampling is a prerequisite for soil testing to achieve its goals for efficient nutrient management and plant nutrition for improved yield and quality. The underlying basis for soil sampling is that a soil sample taken represents the “population” which may be a plot, field or a watershed. It further implies that nutrient status of the representative soil sample(s) determined in a laboratory would reflect nutrient status of a plot, field or watershed and is of interest for correcting nutrient disorders in the field or watershed.

The most important factor that influences the effectiveness of soil sampling is soil heterogeneity. However, in a relatively homogenous group of fields or plots, a small number of samples may be sufficient to represent the population to a more heterogenous group of fields that would require more number of samples to represent the soil population. Whenever, soil samples to be taken in field following points needs to be kept in mind.

Introduction

R is one of the most popular platforms for data analysis and visualization currently available. It is free, open-source software, with versions for Windows, Mac OS X, and Linux operating systems. R is a language and environment for statistical computing and graphics, similar to the S language originally developed at Bell Labs. It’s an open source solution to data analysis that’s supported by a large and active worldwide research community. But there are many popular statistical and graphing packages available e.g. Microsoft Excel, SAS, IBM SPSS, Stata, and Minitab etc., however R has many interesting features so why it is mostly followed by researchers and academicians. Few of the major features of R are given below:

Introduction

Spatial data is different from a non-spatial data in the sense that it always has a spatial reference system which is nothing but a pair of coordinate values and a system of reference for these coordinates. For example, the locations of benchmark soil series of India can be defined as pairs of longitude and latitude in decimal degree values with respect to the prime meridian at Greenwich and zero latitude at the equator. The World Geodetic System (WGS84) is a frequently used system of reference on the Earth. The different types of spatial data are: (i) point, which is a single point location, such as a GPS reading or a geocoded address (ii) line, which is defined as a set of ordered points, connected by straight line segments (iii) polygon, an area, marked by one or more enclosing lines, possibly containing holes and (iv) grid, a collection of points or rectangular cells, organised in a regular lattice. Among the above said spatial data, the first three are vector data models and represent entities as exactly as possible, while the fourth data model is a raster data model, representing continuous surfaces by using a regular tessellation. In this chapter, we discuss how a spatial data can be handled in R. There are several packages available in R in which spatial data analysis can be handled e.g. sp, rgdal, raster etc. All the contributed packages for spatial data analysis in R address two broad areas: moving spatial data into and out of R, and analysing spatial data in R. In the following section, the sp package for spatial data handling is briefly discussed.

Introduction

The first step of geostatistical analysis in R is the creation of dataset which is acceptable in R environment by using the data collected from field survey or laboratory experiments. Different type of data is collected during experiments e.g. sand content, silt content, organic carbon content, geographical location of data points, soil type, land use type etc. Here, we will discuss how these data are converted into a acceptable dataset format for R environment and how we manage these data. In R this task is performed in two steps. First, a data structure is created to hold the data and second is the entering or exporting the data into data structure.

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:

Introduction

In geographical location, the observations taken in proximity tend to be more alike than observations made at points that are far apart-that is, the values tend to be correlated. An area of study that takes this sort of spatial consideration into account is called geostatistics. A primary motivation for sampling is to make meaningful estimates of values at nearby positions in space and time. When values are assumed independent, the best estimate for an unmeasured point will be the mean. However, for correlated values nearby values are estimated by interpolation. The simplest interpolation scheme is a nearest neighbor estimate for which the unknown values are based on the closest measured location. Inverse distance is another sort of interpolation technique where weights are estimated based on the inverse distance squared. Kriging is a geostatistical interpolation technique that considers both the distance and the degree of variation between known data points when estimating values in unknown areas.

It makes the best use of existing knowledge by taking account of the way that a property varies in space through the variogram model. In its original formulation a kriged estimate at a place was simply a linear sum or weighted average of the data in its neighbourhood. Weights are based on the distance between the measured points, the prediction locations, and the overall spatial arrangement among the measured points. Since then kriging has been elaborated to tackle increasingly complex problems in mining, petroleum engineering, pollution control and abatement, and public health. The term is now generic, embracing several distinct kinds of kriging, both linear and non-linear.

Introduction

Spatial datasets always exhibit two common features (i) the occurrence of a few very large concentrations (hot-spots) and (ii) the presence of data below the detection limit (black spots). Extreme values can strongly affect the characterization of spatial patterns, and subsequently the prediction. Several approaches exist to handle strongly positively skewed histograms (Saito and Goovaerts 2000). One common approach is to first transform the data (e.g. normal, Box Cox or lognormal), perform the analysis in the transformed space, and back-transform the resulting estimates. Such transform, however, does not solve problems created by the presence of numerous black spot data, since either it yields a spike of similar transformed values or, in the case of the normal-score transform, it requires a necessarily subjective ordering of all equally-valued observations. Moreover, except for the normal score transform (Deutsch and Journel 1998), it does not guarantee the normality of the transformed histogram, which is required to compute confidence intervals for the estimates. Last, the back-transform of estimated moments is not straightforward and can introduce bias if not done properly (Saito and Goovaerts 2000); for example, lognormal kriging estimates cannot simply be exponentiated. Another way to attenuate the impact of extreme values is to use more robust statistics and estimators. The non-parametric approach of indicator kriging (IK) falls within that category (Journel 1983, Goovaerts 2001). The basic idea is to discretize the range of variation of the environmental attribute by a set of thresholds (e.g. deciles of sample histogram, detection limit, regulatory threshold) and to transform each observation into a vector of indicators of non-exceedence of each threshold. Kriging is then applied to the set of indicators and estimated values are assembled to form a conditional cumulative distribution function (ccdf). The mean or median of the probability distribution can be used as an estimate of the concentration of the material in question (Barabas et al. 2001, Cattle et al. 2002, Goovaerts et al. 2005).

Introduction

Quantum Geographical Information System (QGIS) is an open source GIS environment. The software package is available freely in web https://www.qgis.org/en/site/forusers/download.html) and can be installed in a variety of computer platform e.g. Windows, Linux, Mac OS X, Android etc. Latest information on QGIS is available inhttp://www.qgis.org/en/site/. Basically, the QGIS GUI is divided into five areas: (i) Menu Bar, (ii) Tool Bar (iii) Map Legend, (iv) Map View and (v) Status Bar. QGIS allows users to define a global and project-wise coordinate reference system (CRS) for layers without a pre-defined CRS. It also allows the user to define custom coordinate reference systems and supports on-the-fly (OTF) projection of vector and raster layers. All of these features allow the user to display layers with different CRSs and have them overlay properly. QGIS has support for approximately 2,700 known CRSs. Definitions for each CRS are stored in a SQLite database that is installed with QGIS. The CRSs available in QGIS are based on those defined by the European Petroleum Search Group (EPSG) and the Institute Geographique National de France (IGNF) and are largely abstracted from the spatial reference tables used in Geospatial Data Abstraction Library (GDAL). For Post GIS layers, QGIS use the spatial reference identifier that was specified when the layer was created. For data supported by OGR, QGIS relies on the presence of a recognized means of specifying the CRS. In the following sections, few basic GIS analysis using example spatial data from arid western India is discussed. However, readers are advised to go through different tools and functions available in QGIS after installation of the system in personal computers.

Introduction

GIS (Geographical Information System) based mapping takes cogence of three major geometrical dimensions, point, line and polygons and in GIS these three features correlate their relationship through a concept called Topology. Among the various applications where covariate processing requires specific attention, the landuse/ land cover and Digital Elevation Models/surfaces or terrains are the major area of interest. Use and processing of data for these covariates carries importance as accuracy of both these aspects would influence the derivatives extracted out of them further. For example, if landuse is improperly defined, the site for which planning is proposed may not sustain, similarly, point data/elevation data in case of DEMs would decide the exact topography of any landforms for their further utilization. For their use in GIS, while DEMs depend upon point data, the landuse/ land cover will be taken care by polygons. For the purpose of the study, we are going to discuss about these two covariates in the following paragraphs.

Generally, Covariate (covariable) (koh-vair-iãt) in statistics is defined as a continuous variable that is not part of the main experimental manipulation but has an effect on the dependent variable. In other words, as per ANCOVA (Analysis of covariance) definition: a covariate is a control variable.