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Über dieses Buch

This book uniquely presents accurate and up-to-date information related to crops in small and fragmented agricultural lands with mixed cropping patterns. The book involves research using remote sensing (RS), Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to develop crop inventories in three growing seasons in three villages across India to inform decision makers and planners on best practices for agricultural management. The data analysis of crop details using various geospatial technologies fills in gaps in statistical agriculture research, and provides reliable, replicable and efficient methods for generating agricultural statistics. The book will be of interest to statisticians, planners and decision makers in crop management and production.

Inhaltsverzeichnis

Frontmatter

Chapter 1. Introduction

Abstract
World needs to elevate 700 million poor people living in rural area. Sustainable Development Goal emphasizes ending poverty and hunger by 2030 and the importance of agriculture in the economy, employment, food security, national self-reliance, and general well-being. Reliable information related to agriculture is at the center of everything and agricultural statistics are part of the economic profile of a village/taluk/district/state and country and are increasingly becoming important. Agriculture data includes agricultural holding by distribution, size, tenure, land use, means of production, and labor force and statistics are essential to monitor trends and estimate future prospects for agricultural commodity markets which can assist in setting policies such as price supports and strategies to promote economic growth.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 2. Crop Area Statistics

Abstract
Generation of crop statistics in India dates back to Kautilya’s Arthashastra (an ancient Indian treatise on statecraft belonging to third century BC) as well as Moghul era (sixteenth century). Currently, the crop statistics are generated based on land revenue system for major food crops and non-food crops. The data is received from the State Agricultural Statistics Authorities in various states and union territories. Methods for crop area estimation based on different sampling techniques have been successful but cost-effective methods, especially in developing or underdeveloped nations, are needed. New technologies like remote sensing, GPS, and GIS have played a major role. Crop area estimation at the national level is more established. Addressing accuracy first, it is important to address national versus small area estimation; in terms of accuracy, it seems to be a choice between accuracy and cost, assuming each has an approximate level of timeliness. Methods using satellite images have the essential component of reference of ground truths. In a mixed cropping pattern with small and fragmented holdings, the extent of ground truths was found to be inadequate, and studies indicate that manual extraction of field boundaries with thorough knowledge of the landscape provides useful results and provides control on datasets for further validation, while field inventory is done adopting an integrated approach.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 3. Procedure Adopted in Different States

Abstract
Generation of crop area statistics in Karnataka State is a collaborative process involving different departments. At state level, the Department of Economics and Statistics processes the reconciled crop area reports submitted by the districts. Primary process starts at a particular village, and the data gets aggregated at different levels of administrative hierarchy. At the village level, statistics on land use, crop area, and crops irrigated are collected through a joint field inspection by a team comprising of Village Accountant, Agricultural Assistant, and Work Inspector from the Water Resources Department. In Andhra Pradesh, Village Revenue Officer at village level is mainly responsible for the collection of land utilization and crop statistics information every season with the help of Village Revenue Assistants which is verified and compiled and monitored at Mandal level by Mandal Revenue Officer. The data are further reviewed at district level and accepted by the Directorate of Economics and Statistics at state level. In Odisha, Directorate of Economics and Statistics (DES) is responsible for collection of information on land utilization and crop statistics every year. The District Planning and Monitoring Units (DPMUs) undertake village-level surveys in approximately about 20% villages covering each Block/Mandal every year. The state has formulated EARAS (Establishment of an Agency for Reporting Agricultural Statistics) framework defining coverage of villages for every five years. Over a period of five years, all the villages in each Block/Mandal are covered through EARAS randomized sampling framework.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 4. Theme of the Crop Inventory Experiment

Abstract
Agricultural statistics should correspond to ground situations and determine the actual extent of each crop along with cultivation and other farming practices. The process should provide reliable, retraceable geographical data that are climate independent and can be applied to different agroclimatic regions. Geo-stamping approach, an integration of remote sensing, GPS, and GIS, has an inbuilt tracking of workflow of any regular data collection and reporting system and allows plot-level inventory. The process is cost-effective, and the basic reference data system can be used repeatedly without much effort. GPS-based smartphones are the best instruments that can be operated by anyone because it provides authenticity of data and captures actual ground situation.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 5. Development of a Spatial Reference (System) Database

Abstract
Field crop plot boundaries can be extracted from high-resolution images with spatial resolution less than 2.5 m from satellites like Cartosat, QuickBird, etc. The village maps along with survey numbers obtained from respective states’ departments geo-referenced using control points like natural features, roads, etc. and the coordinates obtained from DGPS were used to increase the positional accuracy. Crop plots were extracted from high-resolution natural color composite images from Google Earth. A controlled mosaic of crop plots for each village developed in GIS environment was converted to geo-fenced map tile and loaded on to smartphone powered with suitable application for automatic navigation and recording the information along with photographs in the field. Farmers in each village were informed about the process and cooperation was sought. Field inventory carried out in Rabi was kept as basic reference of crop plots of different farmers. Android application was modified to reduce the mapping of plots without crops in subsequent season. The data generated in each season was systematically organized in QGIS for visualization and spatial analysis. Farmers not only cooperated but also felt that the process is useful so that they can have reference of crop area and type.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 6. Results of Field Inventory

Abstract
The three villages located in different agro-climatic regions are conspicuous with respect to sources of irrigation, cultivation practices, cropping pattern in different growing seasons. Khatijapura village in Karnataka is entirely a rainfed village with limited groundwater development. Crops are grown in both kharif and rabi seasons and to a limited extent in summer. Cropping in different seasons is practiced and characterized by small to medium holdings with few exceptions and the plots are fairly large. About 17% of the net sown area is under lease, contract farming and crop sharing practices. Daliparru village located in coastal plains of Andhra Pradesh has source of irrigation for kharif season. Characterized by small to medium holdings, village practices almost mono-cropping—paddy (irrigated) during kharif and pulses during rabi. Having more than 15% non-resident farmers, leased cultivation is predominant. During summer hardly any crops are grown. Jarasingha village, a part of interior coastal midland of Odisha is supported by an irrigation project. Characterized very small to small holdings practices cultivation in both kharif and rabi season while summer season cropping is limited to small extent and groundwater is being used as supplementing source. Crop sharing is practiced during kharif season and leasing is seen during rabi. Kharif is dominated by paddy while in rabi, it is mixed cropping. Kitchen garden practice is conspicuous of Jarasingha.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 7. Reasons for Noncultivation

Abstract
Reasons like social, economic, and natural make farmers to keep the land uncultivated. Study highlights not a single but combination of reasons in different regions. In Khatijapura, the scarcity of water and labor are important reasons for not cultivating during Kharif, while the traditional practice also appears to be the reason. In Daliparru, the intention to convert the land to non-agriculture and migration to urban area is the major reason than shortage of water for cultivation. In Jarasingha, shortage of water only appears to be the major reason for leaving the land vacant.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 8. Land Use

Abstract
Land use is the surface utilization of all developed and vacant land on a specific location, at a given time and space, and it defines the human activities which are directly related to land, making use of its resources, or having an impact on them. In that context, the emphasis is on the purpose for which the land is used, and a particular reference is made to “the management of land to meet human needs.” Detailed mapping and field authentication using geospatial tools have enabled to accurately define the current land use in three villages. Khatijapura accounts for 92.5% of the net sown area, Daliparru 84.47%, and in Jarasingha less than 50%.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 9. Repetition in Second Year

Abstract
Crop inventory experiment was continued during the second year (Rabi season of 2017–2018) to evaluate the feasibility of transferring the data to the server on real time and involving local youths in the process. Spatial reference database of crop plots and holding had hardly any changes and was conveniently used. Internet signal was fine at the village center and data could be directly transmitted to the server, and monitoring the field inventory was achieved. Crop data of Rabi season for 2 years could be conveniently compared. Local youths could comfortably handle the mobile devices and capture the data and synchronize with the server.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 10. Kitchen Garden in Jarasingha

Abstract
Jarasingha village has unique feature of Kitchen Garden within settlement attached to dwelling units that supplements livelihood option for the people. Women in the households cultivate different varieties of vegetables using groundwater. Water from borewells is shared between households. Plots vary in size from 10 × 20 m to 15 × 30 m, and cumulative extent of such garden is 6.03 ha, and there is a clear shift in crops from leafy vegetables during summer to cauliflower in Kharif mostly due to local market demand. During summer, people practice organic cultivation; while in Kharif, chemical fertilizers and pesticides are used.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 11. Comparison of Area Statistics: Existing Practice vs Geospatial Technology

Abstract
Crop plots derived from satellite images correspond to shape and extent in the field and correlate with land records. Crop statistics generated using geospatial tools are authentic and accurate and traceable but do not correlate with the existing data compiled from traditional methods which have problems in terms of type, extent, and acreage. The land use details also appear to have not been updated. The methodology adopted has been able to provide reliable information on the basic production unit, reasons for not cultivation, farming infrastructure, farming practice, availability of agriculture inputs, and geographic variation of crops. Keeping in view the goal of doubling the income and improved agricultural productivity and climate resilience, geospatial tools appear to be useful for generating the reliable and real-time data. The technology can also be conveniently used for consolidating the spatial information of land records, particularly the holding information.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 12. Conclusion and Recommendations

Abstract
ICRISAT conducted the research experiment with the hypothesis that agricultural statistics should correspond to ground situations and determine the actual extent of each crop along with cultivation and other farming practices. The process should provide reliable, retraceable geographical data that are climate independent and can be applied to different agroclimatic regions. Having studied different approaches, tools, and technologies for generating crop statistics, it was decided to adopt “geo-stamping” approach with different geospatial tools. It is an integration of remote sensing, GPS, and GIS having inbuilt tracking of workflow of any regular data collection and reporting system and allowing plot-level inventory.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 13. SWOT Analysis of Geospatial Technology

Abstract
Geospatial tools are useful for generating crop statistics. Authenticity, error-free data compilation, GIS-based area computation, traceability, and estimation of area of mixed crops are the strengths of the technologies. Updation of changing field bunds through GPS, possibility of non-availability farmers, and “not for legal purpose” appear to be the weaknesses of the method advocated. Possibility of consolidation of holding level data, upgradation of skills of personnel, and need of the data in various public and private sectors are the opportunities, and the reluctance to adopt the technology and the financial allocation from the government may pose threat to useful geospatial technology adoption for agriculture statistics.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 14. Geospatial Technology Intervention: A Best Method for Crop Inventory

Abstract
Challenge of area estimation well within time growing season and documenting the area of mixed crops and measuring the extent of seasonally varying crops can be conveniently and efficiently achieved by geospatial technology. As the technology is made simple, adaptability of the technology by rural youths provides opportunity for temporal financial support and thereby scalable. Cost of generating all the related data to agricultural holdings by means of geospatial technology is less than 1% for an annual household earning. Compared to cost of gathering the agricultural statistics by employing the village accountants and the governmental overheads, the cost of data generation using geospatial tools is economical.
K. V. Raju, V. R. Hegde, Satish A. Hegde

Chapter 15. Executive Summary

Abstract
Ending poverty and hunger by 2030 being one of the core objectives of Sustainable Development Goals (World Bank 2015) speaks of doubling the income and the need for improved agricultural productivity and climate resilience, strengthened links to markets, agribusiness growth, and rural nonfarm incomes. Reliable and real time information related to agriculture is essential to address the agriculture growth in developing nations. Agricultural statistics including holding by distribution, size, tenure, land use, means of production are increasingly becoming important. The quality of available agricultural data and the methods by which such data is collected are weak in several developing countries. Geo-stamping approach i.e., the Remote Sensing (RS), Geographic information System (GIS) and Global Positioning System (GPS) intervention adopted in conformation with existing work flow for crop-area enumeration has yielded reliable results.
K. V. Raju, V. R. Hegde, Satish A. Hegde

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