Field Surveys
Why Is Field Survey Required?
Field surveys are essential in geography and related disciplines for collecting primary data and gaining a deeper understanding of phenomena in their real-world context. While remote sensing and existing maps provide valuable information, direct observation and data collection in the field are often indispensable.
Reasons for Conducting Field Surveys:
- Primary Data Collection: To gather original data that is not available from secondary sources (maps, reports, remote sensing). This includes direct measurements, observations, interviews, and surveys.
- Ground Truthing/Validation: To verify and validate data obtained from remote sensing imagery or existing maps. Field checks confirm the accuracy of interpretations (e.g., identifying land cover types seen in satellite images, verifying settlement locations).
- Detailed Information: To collect information on features that are too small or complex to be represented accurately on maps or captured by remote sensing (e.g., specific land use practices, local soil conditions, infrastructure details, socio-economic conditions of a community).
- Understanding Context: To understand the spatial relationships and the 'why' behind observed patterns. Field visits provide context that purely data-driven analysis might miss (e.g., understanding the reasons for settlement patterns, the impact of local traditions on land use).
- Data for Small Areas: For detailed local studies, field surveys are often more practical and provide higher resolution data than broad-area remote sensing.
- Socio-economic Data: To collect data on human populations, livelihoods, poverty, access to resources, cultural practices, and community perceptions, which often requires direct interaction.
- Environmental Monitoring: To directly measure environmental parameters (e.g., water quality, soil erosion, vegetation health) that might be indirectly inferred from remote sensing.
- Resource Assessment: For detailed assessment of resources like minerals, water bodies, or agricultural land.
In essence, field surveys bridge the gap between abstract data and the tangible reality on the ground, providing crucial primary information and validation for geographical studies.
Field Survey Procedure
A successful field survey follows a structured procedure to ensure that data is collected efficiently, accurately, and in a way that directly addresses the research objectives.
Defining The Problem
Description: Clearly identify the issue or phenomenon that the survey aims to investigate. What specific question are you trying to answer?
Process:
- Start with a broad area of interest.
- Narrow it down to a specific research question or problem statement.
- Ensure the problem is well-defined, measurable, and relevant.
Example: Investigating the causes of water scarcity in a particular region.
Objectives
Description: State precisely what the survey aims to achieve. Objectives should be specific, measurable, achievable, relevant, and time-bound (SMART).
Process:
- Break down the main problem into smaller, manageable objectives.
- What specific information needs to be collected to address the problem?
Example Objectives (for water scarcity):
- To map the availability of water sources (wells, rivers, tanks).
- To measure rainfall patterns in the region.
- To assess current water usage by households and agriculture.
- To identify the primary determinants of water scarcity (e.g., low rainfall, inefficient usage, pollution).
Scope
Description: Define the geographical boundaries, the target population or phenomena, and the timeframe of the survey.
Process:
- Geographical Area: Specify the exact region to be covered (e.g., a district, a few villages, a specific watershed).
- Target Group/Phenomena: Identify whom or what to study (e.g., households, farmers, specific land uses, types of vegetation).
- Timeframe: Set a duration for data collection and analysis.
Example Scope: To conduct a household survey in five villages of the Belgaum district, Karnataka, over a period of two months, focusing on water availability and usage patterns.
Tools And Techniques
Description: Determine the methods and equipment that will be used to collect data.
Common Tools and Techniques:
- Surveys: Questionnaires for interviews, household surveys.
- Observations: Direct visual inspection of phenomena (e.g., land use, soil conditions, vegetation health).
- Measurements: Using instruments like GPS (for location), measuring tapes, clinometers (for slope), rain gauges, water quality testing kits, soil augers.
- Sampling Techniques: Random sampling, stratified sampling, systematic sampling to select representative study units.
- Data Collection Forms: Standardized forms for recording data consistently.
- Cameras: For documenting observations and features.
- Sketching: For creating rough maps or diagrams in the field.
Compilation And Computation
Description: After collecting data in the field, it needs to be compiled, organized, cleaned, and processed.
Process:
- Data Entry: Transferring field data into a digital format (e.g., spreadsheets like Excel, databases).
- Data Cleaning: Checking for errors, inconsistencies, and missing values.
- Data Processing: Performing calculations using statistical methods (mean, median, standard deviation, correlation) or applying formulas for measurements (e.g., calculating area from contour data, converting raw instrument readings).
- Data Analysis: Analyzing the processed data to identify patterns, trends, and relationships relevant to the research objectives.
Cartographic Applications
Description: Translating the collected and processed data into maps for visual representation and analysis.
Process:
- Digitizing: Converting hand-drawn field sketches or scanned maps into digital vector or raster formats.
- Georeferencing: Assigning real-world coordinates to collected data points (e.g., GPS coordinates of wells or observation sites).
- Creating Thematic Maps: Using GIS software to create maps showing the distribution of phenomena based on field data (e.g., a map of water source locations, a map showing levels of poverty in different areas).
- Overlay Analysis: Combining different data layers (e.g., soil maps with land-use maps) to understand relationships.
Presentations
Description: Communicating the findings of the field survey effectively to the intended audience.
Methods:
- Reports: Detailed written reports documenting the methodology, findings, analysis, and conclusions.
- Presentations: Using slides (like PowerPoint or Google Slides) to present key findings, including maps, graphs, charts, and photographs.
- Discussions: Engaging with stakeholders to explain the results and implications.
Field Survey: Case Studies
Field surveys are crucial for understanding complex geographical and socio-economic issues. Case studies illustrate the application of survey methodologies in real-world scenarios.
Field Study Of Poverty: Extent, Determinants And Consequences
Objective: To understand the nature, causes, and impacts of poverty in a specific region.
Procedure:
- Defining the Problem: Poverty exists in the region, but its extent, underlying causes, and effects on the local population need to be quantified and understood.
- Objectives:
- To identify households below the poverty line using standard criteria (e.g., income, access to basic amenities).
- To determine key determinants of poverty (e.g., lack of education, unemployment, poor health, natural resource dependency, historical factors).
- To assess the consequences of poverty (e.g., malnutrition, limited access to healthcare and education, social exclusion).
- Scope: A specific district or a set of villages within a region known to have poverty issues. Target population: Households, community members, local leaders.
- Tools and Techniques:
- Household Surveys: Using structured questionnaires to collect data on income, expenditure, employment status, education levels, health status, asset ownership, housing conditions, access to services (water, sanitation, electricity).
- Participatory Rural Appraisal (PRA): Methods like focus group discussions, semi-structured interviews, social mapping, and resource mapping with community members to understand their perspectives on poverty, its causes, and effects.
- Observation: Direct observation of living conditions and community infrastructure.
- Secondary Data: Using census data, government reports, and NGO data for context and comparison.
- Compilation and Computation:
- Data entry into spreadsheets or databases.
- Calculating poverty incidence (percentage of people below poverty line), poverty gap.
- Statistical analysis to identify correlations between poverty and determinants (e.g., education level and income).
- Cartographic Applications:
- Creating maps showing the spatial distribution of poverty levels (e.g., poverty intensity by village or block using choropleth maps).
- Mapping access to basic amenities (water, sanitation, schools) in relation to poverty levels.
- Presentations: Reporting findings with data-backed conclusions and maps to policymakers, NGOs, and the community, suggesting potential interventions.
Field Study Of Droughts : A Study Of Belgaum District, Karnataka
Objective: To analyze the spatial extent, causes, impacts, and coping mechanisms related to droughts in a specific district.
Procedure:
- Defining the Problem: The Belgaum district experiences recurring droughts, affecting agriculture and livelihoods, but a detailed understanding of its spatial and temporal characteristics is needed.
- Objectives:
- To map drought-prone areas within the district based on rainfall data and water availability.
- To identify the primary causes of drought in the region (e.g., erratic monsoon, low rainfall, high evaporation, groundwater depletion).
- To assess the impacts of drought on agriculture, livestock, water resources, and the local economy.
- To document the coping mechanisms adopted by farmers and the community.
- Scope: Belgaum district, Karnataka. Target phenomena: Rainfall patterns, water sources (rivers, reservoirs, wells), agricultural land use, crop conditions, and community observations.
- Tools and Techniques:
- Rainfall Data Collection: Using data from meteorological stations and installing rain gauges in selected areas if necessary.
- Water Resource Assessment: Measuring water levels in wells and reservoirs, observing river flow.
- Field Observations: Assessing crop conditions (wilting, yield reduction), livestock health, soil moisture.
- Interviews: Talking to farmers, local officials, and community members about their experiences with drought, its impacts, and their coping strategies.
- Secondary Data: Rainfall data from IMD, agricultural statistics, previous drought reports.
- Remote Sensing Data: Analyzing satellite imagery (e.g., NDVI for vegetation health) can complement field observations.
- Compilation and Computation:
- Analyzing rainfall data to determine drought severity indices (e.g., Standardized Precipitation Index - SPI).
- Quantifying crop losses.
- Analyzing survey data on water usage and coping mechanisms.
- Cartographic Applications:
- Creating drought vulnerability maps based on rainfall, water availability, and agricultural dependence.
- Mapping the spatial extent of drought impacts on crops and water bodies.
- Presentations: Reporting findings to local government bodies and disaster management authorities to inform drought mitigation and preparedness strategies.