eChapters

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

Anantapur is the driest district of Andhra Pradesh and hence, agriculture conditions are very often precarious. Groundnut grows where other crops fail and thus it is the predominant crop of Anantapur district. Groundnut is grown in about 7.5 lakh ha in Anantapur district; however the average yields are low at 500 kg ha^-1. Among various available vegetation indices, normalised difference vegetation index (NDVI) is widely used for all reasons, which is a single numerical indicator of presence and condition of green vegetation. NDVI mapping at a regional scale helps to assess the spatial changes in the vigour of green vegetation and thus occurrence of any moisture stress. Climate tools have a great role in understanding the crop performance and estimating the yields. This study was taken up by using freely available MODIS data to understand NDVI in terms of abiotic stresses over Anantapur district and linking with the actual rainfall conditions, groundnut crop acreage and production. Results indicate that low groundnut yields in general could be related to NDVI-based stress measurements and rainfall quantum and distribution in the area however, with a few exceptions. It is hoped that by combining improved practices through IWM with climate-adapted crop varieties, rainfed farmers of Anantapur district can sustain their crop production under present climate variability and become resilient to future climate change.

Keywords: Climate, MODIS, NDVI, Anantapur, Groundnut, Integrated Watershed Management

Abstract

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

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

Abstract

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 sustainable management of plant genetic resources is of great concern as increasing population and rapid technological strides are putting enormous pressure on this country’s nutritional and food security. Management of plant genetic resources at national level generates and uses enormous data and analysis of these data is crucial to the effectiveness of PGR management process and can add significantly to the value of genetic resources. A GIS is a database management system that can simultaneously handle data representing spatial objects and their attribute data. GIS allows us to view, understand, question, interpret, and visualize data in many ways that reveal relationships, patterns, and trends in the form of maps, globes, reports, and charts. It can play an important role in the management of large and complex PGR datasets. The article analyses the potential uses of GIS in plant genetic resources management in India covering various activities such as germplasm exploration and collection, characterization and evaluation, plant health management, documentation and conservation.

Key words : plant genetic resources, germplasm, conservation, documentation, DIVA-GIS,

Abstract

Geographical Information Systems (GIS) application in plant genetic resource management allow capture, manipulate, process and display of georeferenced data integrated with genetic resource database for operations such as query and statistical analysis, visualization and geographic representation. GIS based several spatial tools have been developed that model species’ ecological niches finding a relationship between crop or variety with a set of environmental parameters and useful for planning exploration, evaluation trials, in situ and ex situ conservation sites. GIS technologies have direct practical application in elucidation of genetic, ecological and geographic patterns in the distribution of crops and wild relatives; mapping of richness, diversity, distribution of useful traits and, location of areas with complementary diversity; gene bank information management and strategies for future explorations and gap analysis; selection of suitable accessions/sites for ex situ evaluation; searching germplasm for abiotic stress tolerance and developing core collections. With the increasing availability of high- speed computers and software development in the area of GIS tools specific to PGR management increasing trend in application of these is expected. Apart from ecogeographic survey for locating diversity and germplasm collection and design, management and monitoring of in situ reserves, introduction of new varieties, and development of core collection, locating gene donors for biotic and abiotic stresses are the areas to be benefited with the GIS application.

Keywords: GIS, genetic resource, distribution, diversity, core collection, gap analysis, mapping

Abstract

Agroforestry is an integrated self-sustainable land use management system that is not only capable of producing food from marginal agricultural land but also capable of maintaining and improving the quality of environment. It plays a vital role in achieving integrated rural and urban development. But reliable data on number of trees and area under agroforestry is not available as methodology for estimation of even area under agroforestry is not yet standardized. In this paper, a methodology for estimation of number of trees under agroforestry using high resolution satellite data has been proposed and estimation of number of trees as well as area under agroforestry in Ludhiana district of Punjab State has been done using the proposed methodology. Land use/land cover map of the district has also been generated using ERDAS IMAGINE software. It has been observed from the accuracy assessment that the estimates of number of trees as well as area under agroforestry obtained using the proposed methodology under this study are very reliable. Therefore, the proposed methodology may be replicated for estimating number of trees as well as area under agroforestry in other parts of the country.

Keywords: Agroforestry; Estimation of number of trees, Area estimation; Remote Sensing; GIS

Abstract

Agroforestry is an ancient practice that farmers have adopted throughout the world. There are innumerable examples of traditional land use practices combining production of trees and agriculture crops on the same piece of land. In India, the organized agroforestry research began in 1979 when a Seminar on Agroforestry was organized at Imphal by the ICAR, New Delhi. As a follow up to this, ICAR launched an All India Co-ordinated Research Project on Agroforestry (AICRPAF) was started in 1983. The diagnostic survey and appraisal revealed that there are enumerable agroforestry practices prevalent in different agro- ecological zones of India occupying sizeable areas. However, spatial technologies like Geographical Information System (GIS), Remote Sensing (RS) and Geographical Positioning System (GPS) have yet to be implemented extensively in this field in India. The spatial technologies have shown great potential in natural resource management through out the world, especially in developed countries in the fields like forest cover mapping, agricultural planning, watershed management, land use planning, etc. In India the agroforestry land use occupy large areas but use of these technologies to estimate area has been initiated in year 2007 with DST sponsored project entitled ‘Spatial and Temporal analysis of agroforestry interventions in North-western India using GIS and Remote Sensing’ The area under agroforestry systems has been estimated/ mapped in two districts viz., Yamunanagar (Haryana) and Saharanpur (Uttar Pradesh), where intensive commercial agroforestry was predominant. Besides, the methodology developed as an out come of this study may be replicated for agroforestry systems existing in other parts of the country.

Keywords: Agroforestry, Geo-spatial, Mapping, Natural Resources, Remote Sensing.

Abstract

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

Abstract

Soil quality assessment has been recognized as an important step towards understanding the long term effects of land management practices within agricultural watersheds. Potential soil quality issues include continued high rates of erosion, losses of organic matter, reductions in soil fertility and productivity, as well as chemical and heavy metal contamination. This case study addressed the spatial variability of soil properties and its quality at the watershed level using geostatistical methods. Soil samples from the 0- to 20-cm depth were collected on a 100- by 100-m grid across an 88-ha watershed at Sakaliseripalli village in the Nalgonda District in Andhra Pradesh State, India. Geostatistical analysis showed that most of the soil parameters were moderately spatially dependent. An assessment framework, that included a minimum data set, linear scoring technique, and additive indices, was used to evaluate the soil quality index (SQI). Through principal component analysis, cation exchange capacity, exchangeable Na percentage, DTPA-extractable Zn, available P, available water, and dehydrogenase activity have been emerged as the most important indicators for evaluating soil quality. A kriged map of SQI was prepared for the watershed. The SQI was found to be higher in irrigated systems than under rainfed conditions. In the study, potential soil loss calculated using the Universal Soil Loss Equation and crop yield were identified as the quantifiable management goals; the results indicated that soils having higher soil quality indices were more productive and less erosion prone.

Keyword : Principal Component analysis, SQI, Watershed, Geostatistics, Potential soil loss

Abstract

Runoff from rainfall is an important component of the hydrological cycle. Estimation of runoff is critical for the design of hydrological structures and drainage systems in watersheds. Different soils, land use, and water management practices affect runoff differently. In real watersheds, land use, soils and weather conditions vary spatially over the geographical area of the watershed leading to spatial variations in runoff. Also, most watersheds form a part of larger drainage basin or a large watershed consisting of several such subwatersheds. Each subwatershed is hydrologically connected to the other subwatersheds of the basin. A comprehensive GIS based decision support system (DSS) for estimation of runoff that includes the spatial variations in rainfall and natural resources is presented. The DSS is developed as a deployable application by integrating independent GIS layers of watershed features created in ArcGIS with MapObjects in VB, for a case study watershed - the KK3 watershed in Mahbubnagar district of Andhra Pradesh, India. The DSS generates thematic maps of spatial variations in runoff on individual rainy days for the subwatersheds.

Keywords : GIS, GUI, Land use, Rainfall, Remote Sensing, Runoff, Soil, Sub-watershed, Watershed 228 Geospatial Technologies for Natural Resources Management

Abstract

Remotely sensed data have become the primary realistic source for natural resources and biomass estimation, since last 30 decades. A summary of earlier research on remote sensing and GIS based biomass estimation approaches and a discussion of existing issues prompting biomass estimation are very valuable for further improving biomass estimation performance with the integration of geographical information systems. This paper discusses the recently most accurately alternative research methods to integration of remote sensing and GIS applications for identification, characterization and analysis of biophysical characters. The remote sensed data and geographical information systems using the accurate assessment of natural resource and management for the enhancement of biomass production and estimation. There is not any other option for the perfectly biophysical and natural resources estimation in small to large area. The earlier research has demonstrated that biomass estimation remains a challenging task, especially in those study areas with complex forest and mixed traditional cropping systems and environmental conditions. Either optical sensor data or radar data are more suitable for forest sites with relatively simple forest stand structure than the sites with complex biophysical environments. A combination of spectral responses and image textures improves biomass estimation performance. More research expertise is needed to focus on the integration of remote sensing, GIS& GPS, the use of multisource data, and the selection of suitable variables and algorithms for biomass estimation at different scales. Understanding and identifying major uncertainties caused by different stages of the biomass estimation technique and applying strength of mind to reduce these uncertainties are critical.

Keywords : Integrating, Remote Sensing, Bio-physical, Resources, Environment

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

Traditionally remote sensing technology has been widely used in the mapping and change detection of vegetation features. Of late research has shown that remote sensing technology can be successfully employed for retrieval of biophysical parameters of vegetation, either by statistical techniques or by employing radiative transfer models (RTMs). This paper gives an introduction to leaf and canopy RTMs, especially about PROSAIL, which is the most commonly used model. It reviews different techniques for inverting RTM models, their merits and performance comparison. The main techniques briefly described are iterative optimization, look-up table, artificial neural network, genetic algorithm and support vector machine. At the end, it gives examples of applications which use canopy biophysical parameters retrieved by inverting RTM.

Keywords: Radiative transfer, PROSAIL, Inversion, Vegetation

1.0 Introduction

Accurate quantitative estimation of vegetation biophysical variables is useful for a large variety of agricultural, ecological, and meteorological applications (Houborg et al., 2007). The spatial and temporal distribution of these variables are important inputs into models quantifying the exchange of energy and matter between the land surface and the atmosphere, developing better yield prediction models and detecting abiotic stresses at regional scales. Among the many vegetation characteristics leaf area index, leaf chlorophyll content and leaf water content are of prime importance (Bacour et al., 2006; Houborg et al., 2007).

Abstract

In the present study an integrated remote sensing and Geographical Information System (GIS) based methodology is adopted for demarcating the groundwater prospective zones and identification of artificial recharge sites in the Peddavanka watershed, Andhra Pradesh. In this study Shuttle Radar Topograhic Mission (SRTM) digital elevation model (DEM) with spatial resolution of 90 m and Indian Remote Sensing Satellite (IRS-1A), Linear Imaging Self Scanner (LISS- III) satellite data along with other field and collateral data on geology and well inventory have been utilized to generating the Drainage, Slope, Lineaments and Hydro geomorphology of the study area, which are an essential prerequisites for demarcating water resources and identification of recharge sites. Spatial data integration and analyses are carried out in GIS environment.

Keywords : DEM, Drainage, Hydrogeomorphology, Groundwater prospective zones, Remote sensing, GIS

1.0 Introduction

Groundwater is an important natural resource in arid and semi- arid regions, because most of the places surface water resources are scarce and some places it’s totally absent particularly in hard rock areas. Because in hard rock terrains availability of groundwater is of limited extent and its occurrence is essentially confined to fractured and weathered zones (Saraf and choudhury 1998, Sankar 2002). In these areas groundwater recharge depends on rainfall only. For understanding rainfall recharge mechanism and groundwater management in the watersheds level, first we have to understand the morphometric parameters in the watershed level.

Abstract

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

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

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

Abstract

Conventional wisdom holds that variability in rainfall represents a significant variability of agriculture production. But urbanization of the cities on one hand and climate change on theother hand areaffecting the agriculture. Surprisingly, there have been very few analyses exploring the link between rainfall variability and urbanization on agriculture production. Therefore an attempt is made in this paper to know the affect of rainfall variability and urbanisation on the cropping area. For this purposeNDVI analysis is carried out in the catchments of Osmansagar and Himayathsagar Reservoirs by using the medium to high spatial resolution multi spectral data provided by remote sensing satellites, such as Landsat TM, IRS-1C/1D LISS-III and IRS-P6 LISS-III has been used for the years1989, 1994, 1998, 2002 and 2008 for Kharif season, 1975, 1990, 1994, 1998, 2003 and 2008 for rabi season which is collected from NRSC (National Remote Sensing Centre). From this analysis it is found that the increment is more in rabi season compared to kharif season due to the increment of non-monsoon rainfall intensities and ground water withdrawal structures. The increased utilization of the groundwater is causing the reduction of inflows to the reservoirs in the recent years because whatever the rainfall that occurs in the catchment, first utilised for meeting the depleted soil moisture and ground water consequently reducing the surface runoff.

Keywords : Climate change, Urbanisation, Inflows, Cropping area, NDVI

Abstract

The rapid development and integration of spatial technologies viz., Geographical Information System (GIS), Remote Sensing (RS) along with Global Positioning Systems (GPS) provide functional alternatives to revolutionize the conventional entomological approaches like surveillance, spatial/temporal distribution of insect populations, pest distribution mapping and predictive modeling. Application of these technologies for insect problems is well established in the fields of forest, range land, medical and agricultural entomology elsewhere. Nevertheless, in India its field relevance in agricultural entomology is still limited owing to lack of proven field prototype studies and collaborative efforts among stakeholders. It’s time to gain real momentum to integrate these progressive technologies to formulate sustainable integrated pest management programs.

Key words: GIS, Remote Sensing, Insect Populations, Field Applications

Abstract

Carrying out effective and sustainable agriculture has become an important issue in recent years. A key to this is the usage of modern technologies for precision agriculture. Recent technological developments allowed envisioning sensor devices with distributed ambient sensory network, which could be a potential technology for monitoring various natural phenomena (weather parameters, soil moisture, etc.) at micro level. As more and more agricultural data are virtually being harvested along with the crops and are being collected/ stored in databases, the same can be used in productive decision making if appropriate data mining techniques are developed/applied. As a case study for this, an experiment was conducted with four consecutive agricultural (Kharif and Rabi) seasons in a semi-arid region of India to understand the crop-weather-environment-pest/diseases relations using wireless sensory and field-level surveillance data on closely related and interdependent pest/disease dynamics of groundnut crop. Association rule and multivariate regression mining techniques/algorithms were propose developed /tailor-made to turn the data into useful information/ knowledge/relations/trends to know crop-weather- environment-pest/disease continuum. These findings have been used for development of prediction models (cumulative and non-cumulative) followed by a web based pest/disease decision support system.

Keywords : Data Mining, Pest/Disease Management, Precession Protection, Wireless Sensor Networks

Abstract

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

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

1.0 Introduction

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

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