TEAM 1 Progress Report I

Food Security in Relation to Earth Observation (GEOSS and COPERNICUS relevance)

This is the first progress report of the team no 1 of the Nairobi INSPIRE Hackathon 2019. The team is led by Karel Charvat.

The team includes 115 members out of which 25 are actively participating.C

The webinar of this team was organised on Monday 15th April 2019. The recording of the webinar can seen below.

We started collecting answers on a few questions. The key questions are listed below.

Why I would like work in this group?

Food security is a major challenge in Kenya and Africa at large considering the country’s economy is largely agrarian. Any unforeseen changes in weather patterns could be fatal not only to our economy but also to millions of people who rely on agriculture for employment and as a source of livelihood.

Food and nutrition security is my major areas of expertise therefore, I am always willing to participate in anything that can help to improve my knowledge in the area. Besides the major importance of food security in the development at a individual, micro and macro level, I believe that I will be more efficient in this team and I will participate significantly in the team.

Food (and water) insecurity are a consistent drivers of vulnerability in Africa. I wish to be part of the solution to food insecurity problem by collaborating with other interested experts and stakeholders.

Where Earth Observation can help to African Agriculture?

Soil management can benefit a lot from earth observation. Modelling erosion would help avert loss in soil fertility.

Near real-time crop monitoring data would be very helpful to farmers to enable them identify remedies to crop failures in good time and avoid losses.

The same data could assist government plan in advance in terms of addressing the anticipated deficit in food stock hence avert cases of food shortage.

Earth Observation will also be very important in prediction analysis in the agricultural sector. This will permit African Agriculture to be economical and technically efficient. It can also permit African countries to specialise in into different sector, therefore, develop trade agreement..

In highlighting the suitable areas for different agricultural practices and the hotspots of food insecurity. As any other thematic area, agriculture has a geographic dimension that can only be captured and revealed by accurate and dynamic earth observation data.

Earth observation can be used to assess risks/threats to sensitive ecosystems like forests and wetlands. Forests and wetlands are known contributors to food security particularly when sustainably used.

EO in particular weather data and biomass can be used to generate index based services for Banking and insurance such as Weather and Yield index (Kizito)

Ideas about potential experiments?

Sampling plots from different agro-climatic zones in Kenya and monitoring their growth using earth observation techniques together with ancillary data like weather data and biophysical data.

Also establishing crop growth scenarios under different weather events could help in projecting future yields which is very critical in the planning operations and budgeting by state agencies and county governments.

Prediction of disease susceptibility of crop using the temporal crop dynamics from earth observation data. Using historical data of crop disease and connecting them with features extracted from earth observation data for generating alert of probable crop disease.

To make some experiments only based on observation data and compare the results.

A combination of agent-based models of human activities and how these contribute to food (in)security and a dynamic changes in the environment as captured by big earth observation data.

Accurate monitoring crop phenology to aid the application of farm inputs like fertilizers, irrigation and farm management.

Assessment of hydrological flows through a combination of field observations and output from satellite image analysis workflows.

Augmenting weather and climate monitoring through the use of affordable in-situ weather sensors and remote sensed weather estimates.

Who are main target groups of farmers in your country?

In Kenya, some of the significant farmer groups include maize farmers in the rift valley region and in the western part of the country, rice farmers around lake victoria and in the Mwea scheme in the central part of the country, and sugarcane farmers in western, rift valley areas and in the coastal parts of the country

Do you have practical experience with implementation of EO in your country?

I (Parmita Ghosh) do have for my country India and Germany (I was an exchange student in Technische Universität Darmstadt, Darmstadt, Germany).

I have experience with Copernicus Data for climate monitoring (Kizito)

I have a background in applied geoinformatics and am currently using earth observation data to address water and food insecurity questions in the dryland regions of Kenya (Francis Oloo)

Can benefit small farmers from EO?

Sentinel 1, 2 has spatial resolution of 20 m so small farmers can be benefited by the products developed using images from these satellites.

Landsat can particularly be used for awareness creation on issues like land degradation and land use change and its influence on land health and the potential areas that can be used for farming.

On Friday 19th, we organised  teleconference with participation of 12 people. The main conclusion are next

Jiri will prepare infrastructure for experimentation. This will be done with Team 5

Jiri will download examples of Sentinel Data from Region

Other data will be downloaded on demand. There is expected also cooperation with team 3, 5 and 6.

In cooperation with team 3 we will tested different OS software. See the candidate.

  1. Orfeo ToolBox – Orfeo ToolBox,
  2. https://github.com/sentinel-hub/eo-learn,
  3. ESA SNAP software (http://step.esa.int/main/download/)
  4. QGIS – (Kizito)

For next communication will be organised Skype communication for the group.

TEAM 2 Progress Report I

Climatic Services for Africa

This is the first progress report of the team no 2 of the Nairobi INSPIRE Hackathon 2019. The team is led by Karel Jedlicka.

There are in total 83 team members registered, 11 of them are actively collaborating and contributing. The active members are from: Czechia (3x), Switzerland (2x), Zimbabwe (1x), Uganda (1x), Nigeria (1x) and Kenya (3x).

The team is currently working on a use case: a farmer uses meteorological data to plan maize planting and cultivation.

  • The farmer sends a field position to the climate service
  • The service returns
    • Growth plan – a time interval when to start planting to maximize yield
    • Nitrogen plan – a time interval when to insert nitrogen fertilisation to maximize its effect
    • Insect pests alert – alert when a risk of insect pest attack is high

The team has defined the concept, team assigned roles and answered open questions. The implementation will take part during the second half of April 2019.

Climate data for maize cultivation – more granular GRID for temperatures?

Here you can see the recording of the webinar taken a couple of week ago:

TEAM 9 Progress Report I

Open Transport Map (OTM) Applications for Africa

This is the first progress report of the team no 9 of the Nairobi INSPIRE Hackathon 2019. The team is led by Daniel Beran.

Team:

  • active team members: Daniel Beran, Jan Bohm, František Kolovský, Jan Sháněl
  • team members that have filled the Google Document but were not present for initial Skype call: Antoine KANTIZA, Candido B. Balaba, Jr., Laura Mugeha, Davince Koyo

Work:

  • We have acquired OSM data and preselected those layers that could be usable for traffic modelling.
  • We are discussing setting of parameters in transforming OSM data into traffic generators.

Plan for next week (15-21/04/2019):

  • Skype telco with all team members on on Tuesday 16th of April, at 1 p.m. CEST
    • Assigning unassigned work within our team: e.g. traffic generators, calibration data
  • Prepare traffic network and traffic generators from OSM data.
  • Moving prepared traffic data to STM developers.

Webinar from last week:


TEAM 7 Progress Report I

Smart Points of Interest – Publication of Open Data in Africa as 5-star Linked Open Data

This is the first progress report of the team no 7 of the Nairobi INSPIRE Hackathon 2019. The team is led by Otakar Cerba.

The goal of this team is to publish selected spatial open data from Kenya and other African countries as 5-star Linked Open Data (LOD). The datasets will be transformed and integrated into the Smart Points of Interest (SPOI) data model. The data model for the SPOI was designed during the SDI4Apps project and provides a universal exchange approach to publish point based data in RDF format according to the the linked open data (LOD) principles.

Team 7 Smart Points of Interest – Publication of Open Data in Africa as 5-star Linked Open Data performed the following activities in the past weeks:

  • Webinar (Friday 5 April, 10am) – during the webinar the Smart Points of Interest (SPOI) and initial statements of the team were introduced.
  • Shared folder development – the folder contains presentations about SPOI in general, SPOI in Kenya, SPOI data model and Team 7 ideas; there are also shared documents to add new ideas or comments to Team 7 activity and new data resources for transformation to SPOI.
  • Ideas collection
    • To find relevant open data resource for SPOI,
    • To design and realize harmonization processes of existing data to SPOI
    • To discuss future development of SPOI Ontology
    • To find business opportunities for SPOI, to define benefits of using SPOI (and 5-star LOD in general) for real GIT solutions
    • Landing pages for Kenya
    • Search for Web pages in Kenya
  • Data resources collection – Health Facilities in Kenya and data resources from Team 2

The Team 7 has registered 29 participants (2 from Asia, 8 from Europe and 19 from Africa). Twelve participants were registered to the webinar, but only four participated actively. An overview of the countries represented in this team is shown below.