CONSULTANCY: GEO Land Degradation Neutrality – Reprocessing geospatial land productivity dynamics datasets for SDG 15.3.1
JOB DETAIL
DUTY STATION
Geneva, Switzerland
COMMENCEMENT OF DUTY
1 June 2024
or as soon as possible thereafterNATURE OF APPOINTMENT
Variable (depending on needs of Department/Division)
6 months
Organizational Unit
Group on Earth Observations Secretariat
WMO is committed to achieving diversity and a balanced workforce. Applications are welcome from qualified women and men, including those with disabilities. The statutory retirement age after 1 January 2014 is 65. For external applicants, only those who are expected to complete the term of appointment will normally be considered.DUTIES AND RESPONSIBILITIES
Follow the requirements of the SDG 15.3.1 Good Practice Guidance (version 2) of the UNCCD;
The method for assessing LPD in the LDN framework is to calculate an annual integral derived from remote sensing vegetation indices. Hence, all good observations within a given year are required, allowing to plot a curve of vegetation response over the year or growing season and then estimate the average NDVI/EVI2/MSAVI value for each pixel. Therefore, an approach such as a median/geomedian annual mosaic does not suffice for deriving LPD, as they would represent an average of the level of productivity over a certain period;
Produce annual LPD geospatial layers at 30-meter spatial resolution by computing annual integral layers based on vegetation indices of interest (VIs: NDVI, EVI2, MSAVI) derived exclusively from good observations/non-cloudy pixels for each given year from 2000 until 2023 respectively for one SIDS in the Pacific (proposed example: Fiji) and for one SIDS in the Caribbean (e.g. St. Lucia or Barbados). Final AOI shall be chosen in consultation with GEO-LDN leads group. Annual integrals of VIs are computed as the annual average value for each VIs, for simplicity of interpretation of results.
The LPD annual layers are produced based on the following three vegetation indices:
o Normalized Difference Vegetation Index – NDVI = (NIR-Red) / (NIR+Red);
o 2-band Enhanced Vegetation Index – EVI2 = 2.5 * (NIR-Red) / (NIR + 2.4 * Red +1);
o Modified Soil Adjusted Vegetation Index – MSAVI = [2*NIR + 1 – sqrt((2*NIR+1)^2 – 8*(NIR-Red))] / 2.
| QUALIFICATIONS | ||
| Education University degree in computer science, geomatics, geography or similar |
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| Experience The contractor should have at least 10 years of experience in all of the areas of expertise outlined in the Accountabilities/Responsibilities section of this TOR, more specifically in the use of following technologies: Proven experience cloud-based computing of remote sensing datasets, open data cubes and associated Jupyter notebooks. Prior experience working with cloud-native geospatial platforms such as Digital Earth Africa and/or Digital Earth PacificOther requirements Previous work experience with the Group on Earth Observations (GEO) or the Committee on Earth Observation Satellites (CEOS) is an asset in order to understand the complex requirements of Earth Observation datasets for global environmental monitoring. |
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| Languages Excellent knowledge of English (both oral and written). Knowledge of other official languages of WMO would be an advantage. (Note: The official languages of the Organization are Arabic, Chinese, English, French, Russian and Spanish.) |
Additional Information:
Only applicants in whom GEO has a further interest will be contacted.
Shortlisted candidates may be required to sit a written assessment and/or an interview.
Focal point email for additional information: [email protected] of issue of vacancy notice:
