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Manipulation and Analysis01:21

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GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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Design Example: Identifying the Locations of Monuments in the Field Using Global Positioning System Device01:30

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Surveyors use Global Positioning System (GPS) technology to measure the precise location and elevation of points on Earth. In a recent survey, GPS receivers were used to determine the coordinates and elevations of two park monuments. The process involved careful mission planning, data collection, and correction to ensure accuracy. The survey began with mission planning to identify optimal satellite visibility and minimize Position Dilution of Precision (PDOP). A geodetic control point...
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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
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Levels of Use of a GIS01:29

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Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
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Selected Data About Geographic Locations01:25

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Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
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Related Experiment Video

Updated: Mar 17, 2026

Integrating Remote Sensing with Species Distribution Models; Mapping Tamarisk Invasions Using the Software for Assisted Habitat Modeling SAHM
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Targeting Villages for Rural Development Using Satellite Image Analysis.

Kush R Varshney1,2, George H Chen3, Brian Abelson1,4

  • 11 DataKind DataCorps , New York, New York.

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Summary

Satellite imagery analysis provides crucial data for rural development planning. This approach aids in targeting aid and infrastructure like solar microgrids in underserved areas.

Keywords:
data miningmachine learningpredictive analytics

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Area of Science:

  • Remote Sensing and Geospatial Analysis
  • Big Data Applications in Social Good
  • Rural Development Studies

Background:

  • Rural development planning often lacks sufficient data, especially in resource-limited regions.
  • Satellite imagery offers a scalable solution for data acquisition in remote areas.
  • Traditional data collection methods are often inadequate for the scale and scope of rural development needs.

Purpose of the Study:

  • To demonstrate the utility of satellite imagery analysis for rural development planning.
  • To explore the application of remote sensing in targeting social welfare programs.
  • To analyze the effectiveness of satellite data in infrastructure siting for remote communities.

Main Methods:

  • Utilizing satellite imagery as a form of big data for analysis.
  • Applying algorithms for estimation and inference from remotely sensed images.
  • Case study analysis of rural development projects in sub-Saharan Africa and India.

Main Results:

  • Satellite data analysis effectively informed the targeting of unconditional cash transfers in sub-Saharan Africa.
  • Remote sensing data proved valuable for the siting and planning of solar microgrids in rural India.
  • The study identified common lessons for improving rural development through data-driven approaches.

Conclusions:

  • Satellite imagery analysis is a powerful tool for informed rural development.
  • Data-driven insights from remote sensing can significantly enhance the effectiveness of social good initiatives.
  • The methodologies discussed offer a scalable framework for addressing challenges in underserved rural populations.