[GeoNerds] Urban Growth & Food Production

Title of the Project: Urban Growth & Food Production

Challenge: Estimate land potential available for agriculture

Project idea in couple of sentences:

The problem we seek to tackle is “how urban growth is affecting food production ?”
The solution will be used by policy makers, farmers, researchers and the general public.

The story behind the project: what is the fact, news, personal experience, … that made you choose this issue to tackle?

Available datasets used:

Any data available to produce maps showing propositions of agricultural land lost as a result of urban growth.

IMG_3756

The prototype is going to be a map of Kadey departement, in Cameroon.
It will show agriculture land use has reduced over the years (period: 2013-2015) and also possibly provide projections but at the moment, data is missing to achieve this.
Comparison is being made with current OSM data.

The data that will be used is:

  • SPOT imagery
  • Administrative level data
  • Forest change
  • Vegetation
  • Land cover
  • Forest reserves
  • Community Forest
  • OSM data

Softwares used:

  • QGIS

Pitch Feedback - GeoNerds

Excellent well defined user and great hook in the pitch! Keep that, it’s excellent!
Your project is relevant because there is actual loss of land in relation to the extension of cities and this links directly with the aspect of food security.

But what is your exact deliverable? Maybe this needs a finer tuning. Try to better identify the indicators that will allow you to show food safety and production.

Which indicators or scientific data will demonstrate the impact of land loss due to urban extention on food safety/security?

To improve:
Will you have time to finish the maps?
And enough time to present the trends?
Take the micro closer so we can hear you when you pitch

Title of the Project: Urban Growth & Food Production

Challenge: Estimate land potential available for agriculture

Project Idea:

Urbanisation in Africa is on a meteoric rise and this results in the expansion of cities/urban areas. The increase urban land area reduces the land available for crop farming and also poses a threat on protected areas and biodiversity. The availability and size of farmland has a direct impact on food production level and thus, a decreasing farmland size will result in lower food production.

We, therefore, seek to estimate land potential available for agriculture which will enable city planners protect agricultural land from urban growth through sustainable zoning.

The story behind the project:
Mr. Samuel Song is a 54 year old farmer in Kadey Department (District) in Cameroon. Mr. Song has many years of experience in farming but in recent times he has been losing a lot of land to urban development. His complaints to the city authorities have proven futile and he is afraid to lose all the land available to him in the nearest future.

Available datasets used:

  1. 2000 Landsat 7 ETM+ from USGS Earth Explorer
  2. 2019 Landsat 8 (OLI_TIRS) from Remotepixel.ca
  3. Administrative data from AGDIC-Hackathon website
  4. Forest data from AGDIC-Hackathon website
  5. OSM Data (Buildings, POIs) from OpenStreetMap

Data processing:

  1. Radiometric Calibration (Conversion of Digital Number to Reflectance)
  2. Image Subset via AOI (Area of Interest)
  3. Training of Sites (Identified land cover types)
  4. Supervised classification
  5. Generation of Classification maps
  6. Generation of charts to show trends

Software used:
ENVI
QGIS
ArcMap

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THANK YOU !! <3 <3

Prototype:

The results of our analysis will be published as maps showing land use classification in 2000, 2010 and 2019. It will show agriculture land use has reduced over the years (period: 2000-2019) and the trend will be analysed and used to project agriculture land use of the future.

The prototype is going to be an automated GIS model which can be replicated and used in other jurisdictions by manually inputting Landsat imagery data.

End users:

Farmers: The output (maps) of this solution can help farmers like Mr. Song to make evidence-backed claims and demand action from city authorities to protect agricultural land.

City Planners: City planners can use this model to identify land use classification in their jurisdictions. This will help city planners to properly zone agricultural lands and prevent unauthorised conversions of such land to urban land use.

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Idea Owner: GeoNerds Team

Team Members:

  • Samuel Darkwah Manu
  • Pascalina Awelana Abadom
  • Obed Ayettey
  • Etse Lossou
  • Yvonne Apawu
  • Ransford Yeboah

Challenge relevance:
The challenge will help local authorities and spatial planners to properly zone their land area and make land available for agricultural use which cannot be easily converted to other land uses. This will result in sustainability in food production.

Final pitch

GeoNerds.pdf (2.3 MB)

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/ The process

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