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Table of contents
1.
Introduction
1.1.
Further reading
2.
Smallholder agriculture
2.1.
The primary food production process
2.2.
The biophysical environment
2.3.
The socio-economic environment
2.4.
Farm practices
2.5.
The governance pyramid
2.6.
The farm inputs pyramid
2.7.
The farm outputs pyramid
2.8.
References
3.
Remote sensing technology
3.1.
Introduction
3.1.1.
Multispectral and panchromatic images
3.1.2.
Platforms and orbits
3.1.3.
Sensors
3.2.
Platforms
3.2.1.
Digital Globe
3.2.2.
RapidEye/Blackbridge
3.2.3.
Landsat
3.2.4.
SPOT
3.2.5.
PlanetLabs
3.2.6.
Other satellites and upcoming missions
3.2.7.
Sentinel satellites
3.3.
References
4.
Potential uses of remote sensing in smallholder context
4.1.
Farm characteristics
4.1.1.
Delineating farm boundaries: why is it important?
4.1.2.
Delineating farm boundaries
4.2.
Monitoring crop growth and performance
4.2.1.
Vegetation indices
4.2.2.
fCover
4.2.3.
Crop height
4.2.4.
Soil Moisture
4.3.
Crop identification
4.4.
Yield estimation
4.5.
References
5.
UAV technology
5.1.
Platforms
5.2.
Flight planning
5.2.1.
Defining the mission area
5.2.2.
Establishing ground control points
5.2.3.
Determining flight parameters
5.2.4.
UAV operation
5.3.
Images and processing routines
5.3.1.
Adding and aligning/stitching photos
5.3.2.
Point cloud generation
5.3.3.
Deriving a Digital Surface Model
5.3.4.
Generating orthophotos
5.4.
References
6.
Field data collection
6.1.
Field level surveys
6.1.1.
Farm characteristics
6.1.2.
Crop development information
6.1.3.
Biophysical characteristics
6.1.4.
Farm management practices
6.2.
Measurement equipment
6.2.1.
Locational
6.2.2.
Measuring crop growth
6.3.
Measurement protocols
6.4.
References
7.
Image analysis
7.1.
Automated image processing workflow
7.1.1.
Mosaicking
7.1.2.
Atmospheric correction
7.1.3.
Masking
7.1.4.
Geometric correction
7.1.5.
Image co-registration
7.1.6.
Extracting statistical moments
7.2.
Algorithmic approaches
7.2.1.
Classification techniques
7.2.1.1.
Unsupervised classification
7.2.1.2.
Supervised classification
7.2.2.
Classification approaches
7.2.2.1.
Pixel-based classification
7.2.2.2.
Sub-pixel classification
7.2.2.3.
Object-based image analysis
7.2.3.
Classification algorithms
7.2.3.1.
Parametric algorithms
7.2.3.2.
Non-parametric algorithms
7.3.
References
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Magazine
Table of contents
1. Introduction
Further reading
2. Smallholder agriculture
The primary food production process
The biophysical environment
The socio-economic environment
Farm practices
The governance pyramid
The farm inputs pyramid
The farm outputs pyramid
References
3. Remote sensing technology
Introduction
Multispectral and panchromatic images
Platforms and orbits
Sensors
Platforms
Digital Globe
RapidEye/Blackbridge
Landsat
SPOT
PlanetLabs
Other satellites and upcoming missions
Sentinel satellites
References
4. Potential uses of remote sensing in smallholder context
Farm characteristics
Delineating farm boundaries: why is it important?
Delineating farm boundaries
Monitoring crop growth and performance
Vegetation indices
fCover
Crop height
Soil Moisture
Crop identification
Yield estimation
References
5. UAV technology
Platforms
Flight planning
Defining the mission area
Establishing ground control points
Determining flight parameters
UAV operation
Images and processing routines
Adding and aligning/stitching photos
Point cloud generation
Deriving a Digital Surface Model
Generating orthophotos
References
6. Field data collection
Field level surveys
Farm characteristics
Crop development information
Biophysical characteristics
Farm management practices
Measurement equipment
Locational
Measuring crop growth
Measurement protocols
References
7. Image analysis
Automated image processing workflow
Mosaicking
Atmospheric correction
Masking
Geometric correction
Image co-registration
Extracting statistical moments
Algorithmic approaches
Classification techniques
Unsupervised classification
Supervised classification
Classification approaches
Pixel-based classification
Sub-pixel classification
Object-based image analysis
Classification algorithms
Parametric algorithms
Non-parametric algorithms
References
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