Consultant – Developing Google Earth Engine Scripts for Agricultural Monitoring – Remote At

Background:

Mercy Corps currently operates programs that aim to improve the livelihoods of farmers as well as the ecological sustainability of farming systems in over 25 countries, and in a diversity of ecological environments. Data collection that supports such activities is typically time-consuming and expensive, requiring long travel hours to reach farming locations and specialized measurement skills. Some indicators of interest are extremely difficult to measure over the entire area of operation, and in many cases Mercy Corps is not capable of monitoring such indicators despite the value they would bring to the programming.

Several departments in Mercy Corps are partnering to increase collective ability to use the freely-available data catalog and compute power hosted on Google Earth Engine to calculate indicators particularly relevant for agricultural programming. Preliminary research has been done to identify indicators that are likely calculable with relatively straightforward technical methods. The envisioned method for deployment is that Mercy Corps technical support personnel would be responsible for managing and running scripts that have been pre-developed to calculate indicators, and working with the program to provide necessary inputs to adjust the location and timeframe of the calculation. This project is intended to directly support that effort.

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Purpose / Project Description:

The goals of the project are:

1. To build reusable tools (i.e. programming scripts) for calculation of a limited set of agricultural indicators using publicly-available remote sensing data in Google Earth Engine, and
2. To document the necessary custom inputs (e.g. study area boundaries) and quality assurance steps required to ensure that the calculation results will be valid and reliable given different program locations and context.

The agricultural indicators included in this scope are:

• Soil organic matter content
  • Method: Designated proxy is the Soil Organic Carbon Index (SOCI)
• Abnormal change in canopy color
  • Method: Thresholding vegetation indices depending on crop type
• Surface water presence
  • Method: Automated Wetness Index (or NDWI if preferred)
• Soil erosion
  • Method: RUSLE model

The indicator names are expressed here in non-scientific language, with the notes intended to help demonstrate the technical approaches Mercy Corps currently believes appropriate to achieve the monitoring goal. The consultant may recommend alternative or adjusted methods of calculation if deemed appropriate. Each indicator would need to be calculable within a given administrative unit or custom polygon (i.e. plot boundary polygon). If calibration or validation data is required for any calculation, Mercy Corps shall be responsible for providing such data. Validation data may also be considered from widely authoritative sources (i.e. spectral libraries, reference endmembers). If the consultant judges that Mercy Corps programs should collect original calibration or validation data for an indicator, this shall be included in the process flow notes, as well as details on how that data should look and be collected (i.e. spot check 5 locations around a plot purported to have pest infestation to confirm the presence of pest damage in a location, data coded as no = 0, yes = 1).

Consultant Activities:

Working closely with the MEL and TSU teams, the consultant will:

1. Review the technical calculation method documentation for each indicator (compiled by Mercy Corps), and familiarize themselves with the cloud computing resources available to Mercy Corps.
2. For each indicator, create a programming script to calculate it using the Google Earth Engine data catalog and APIs, including necessary comments to explain calculation steps.
   1. Scripts are preferred to be written in Python and using the Google Earth Engine API for Python.
   2. Example data for necessary inputs such as study area location and timeframe will be provided.
3. Conduct quality assurance checks to ensure the scripts perform as expected when run from a Mercy Corps cloud computing environment.
4. Diagram and document the process flow for the calculations in the code and in a separate user document as appropriate, including all user-initiated steps and inputs.
   1. If flow is different for separate indicators, diagram notes should be provided to explain.
5. Conduct a webinar explaining the process flow and demonstrating at least one indicator calculation using the created scripts.

Consultant Deliverables:

The Consultant will deliver the following:

1. Final workplan submitted and approved.
2. Source files for each indicator calculation tool.
3. Process flow diagram(s) and associated notes and documentation.
4. Final webinar conducted.

Timeframe / Schedule:

• Projected Start Date: 1 November 2021
• Projected End Date: 15 January 2021

Start and end dates may be adjusted based on consultant availability and other factors (part-time vs full-time). Estimated LOE for this project is 40-60 full-time working days.

The Consultant will report to:

Senior Advisor, Monitoring, Evaluation, and Learning

The Consultant will work closely with:

Data Advisor, Technology for Development

Required Experience & Skills:

• 5-10 years of experience in relevant technical field (required)
• Demonstrated expertise in working with remote sensing datasets and developing geospatial analysis required.
• Statistical programming capabilities in Python or alternative programming language required.
• Experience in programming for Google Earth Engine highly preferred.
• Expertise in agricultural/ecological analysis preferred.

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