Geospatial Developer (Consultant) – Thailand 6 views

A. Organization Introduction:

ADPC is an autonomous international organization established for scientific, educational, developmental, and humanitarian purposes with a vision of safer communities and sustainable development through disaster risk reduction and climate resilience in Asia and the Pacific. Established in 1986 as a technical capacity building center, ADPC has grown and expanded its role to be for scientific, educational, developmental and humanitarian purposes. ADPC employs a wide range of professional expertise typically required for Disaster Risk Reduction (DRR) and Climate Resilience (CR) in an effective manner. ADPC develops and implements cross-sectoral projects/programs on the strategic themes of risk governance, urban resilience, climate resilience, health risk management, preparedness for response and resilient recovery. Our strategic themes are complemented and underpinned by the cross-cutting themes of gender and diversity, regional and transboundary cooperation as well as poverty and livelihoods.

Through its work, ADPC supports the implementation of the Sendai Framework for Disaster Risk Reduction 2015–2030, the Sustainable Development Goals (SDGs), the New Urban Agenda, the United Nations Framework Convention on Climate Change, the agenda defined at the World Humanitarian Summit in 2016, and other relevant international frameworks.

For details, please refer to ADPC website at http://www.adpc.net/.

B. Department Introduction

The Risk Analytics and Climate Services Department is a multi-disciplinary team of experts committed to providing innovative, science-based solutions for actions to adapt to climate change and mitigate the impacts of disasters. The innovations include uses of geospatial technology, satellite data, numerical models, cloud computing, and artificial intelligence for assessing vulnerability and risk, generating climate data, developing early warning systems, forecasting possible climate impact, and informing anticipatory actions. These lead to risk-informed developments in the sectors such as agriculture, transportation, water resources, energy, communications and health.

The department also applies advanced geoinformatics and climate analytics to address water and food security issues by assessing water availability and water-use efficiency, groundwater monitoring, assessing drought risks, and optimizing agricultural productivity, hence ensuring sustainable water and food systems in vulnerable regions. The department promotes Nature-Based Solutions by leveraging ecosystem services such as wetland restoration, agroforestry, and green-gray infrastructure to reduce disaster risks and build climate resilience. Lastly, the department produces risk analytics and integrates them into urban plans and engineering designs of critical infrastructures, hence improving their resilience to disasters and climate change. With a commitment to science-based approach, the department envisions empowering stakeholders to reduce risks, adapt to climate change, and build more resilient communities and ecosystems.

C. Statement of Intent

Under the Development of a Landslide Disaster Decision Support System (DSS) for Thailand (DMRLS), ADPC is supporting the Department of Mineral Resources (DMR), Thailand, to develop a national-scale Landslide Disaster Decision Support System (DSS). The DSS aims to improve landslide risk assessment, rainfall-trigger thresholds, early warning, and decision-making for landslide risk reduction in Thailand.

To support technical implementation, ADPC seeks to recruit a Geospatial Developer (Consultant) to work closely with the core technical team and provide hands-on support in GIS analysis, data processing, coding, and model implementation, particularly for landslide susceptibility and Flash Flood Alert System (FFAS)-related workflows.

D. Scope of Work

The Geospatial Developer will provide technical and programming support to the DMRLS team, translating conceptual methods, equations, and modeling logic into operational geospatial and analytical workflows. The consultant will support data preparation, model coding, automation, and troubleshooting across landslide susceptibility and FFAS-related components.

E. Expected Outputs:

The consultant is expected to deliver the following outputs:

1. Cleaned, structured, and well-documented geospatial and non-spatial datasets supporting landslide susceptibility and FFAS modeling.
2. Python-based scripts or tools supporting landslide susceptibility modeling and related analyses.
3. Code support for implementing model logic, equations, and workflows developed by the technical team.
4. Organized data management structure and basic documentation for reproducibility.
5. Technical support inputs to improve model performance, efficiency, and reliability.

F. Responsibilities and Tasks:

The Geospatial Developer will undertake the following tasks:

• Support GIS-based data processing and analysis, including terrain, land use, rainfall, geological, and hydrological datasets.
• Develop and maintain Python scripts for data cleaning, transformation, spatial analysis, and model execution.
• Translate conceptual methods, equations, or modeling logic (e.g. landslide susceptibility methods, SALAD, FFAS-related workflows) into functional code.
• Support integration of multiple datasets, including large or complex datasets, ensuring consistency and quality.
• Assist in debugging, optimizing, and improving existing scripts or workflows developed by the team.
• Organize data repositories, file structures, and metadata to support efficient team collaboration.
• Provide on-demand technical support to the team during model development and testing phases.
• Document scripts, assumptions, and workflows in a clear and practical manner.

G. Working Principles:

• The consultant will report to the DMRLS Project Manager.
• The consultant will work closely with ADPC’s Geospatial Analysts.
• Regular coordination meetings (online or in-person) will be held as required.
• The role requires flexibility to provide technical support as needs arise during model development.

H. Qualifications:

• Background in GIS, Geospatial Science, Environmental Science, Engineering, Data Science, Computer Science, or a related technical field.
• Practical experience in GIS and spatial data analysis (e.g. QGIS, ArcGIS, or similar tools).
• Working knowledge of Python for data analysis and geospatial processing (e.g. NumPy, Pandas, GeoPandas, Rasterio, GDAL, or similar libraries).
• Ability to translate methods, equations, or conceptual models into code-based workflows.
• Experience handling, cleaning, and organizing large or complex datasets is an advantage.
• Familiarity with landslide susceptibility, hydrological, flood, or hazard-related modeling is an asset but not mandatory.
• Strong problem-solving skills and ability to work collaboratively as a technical support role within a multidisciplinary team.
• Good communication skills in English.

(Formal degree level or seniority is flexible; demonstrated technical skills and hands-on ability are more important.)

1. Duty Station: ADPC Head office, Bangkok, Thailand

J. Duration: The contract will be for a period of 3 months between February 2026 – April 2026.

K. Itinerary: Any official travel required during the contract period must be approved in advance by the Director of ACS. Approved travel expenses will be covered by ADPC in accordance with its travel policy and will be reimbursed separately from the consultant’s remuneration.

L. Condition of payment:

The consultancy shall be output-based, with payments made upon satisfactory completion and acceptance of agreed deliverables by ADPC and the DMRLS Project Manager.

The total consultancy fee is USD 12,000 for the full duration of the assignment. Payments will be made in two (2) instalments, linked to the delivery of outputs as outlined in Section E:

Payment Schedule

Payment Round 1 – 50% (USD 6,000)
Paid upon satisfactory completion and acceptance of the following outputs:

• Output 1: Cleaned, structured, and well-documented geospatial and non-spatial datasets supporting landslide susceptibility and FFAS modeling
• Output 2: Python-based scripts or tools supporting landslide susceptibility modeling and related spatial analyses
• Output 3: Code implementation of agreed model logic, equations, or workflows developed by the technical team

Payment Round 2 – 50% (USD 6,000)
Paid upon satisfactory completion and acceptance of the following outputs:

• Output 4: Organized data management structure with basic documentation to support reproducibility and team collaboration
• Output 5: Technical support inputs to improve model performance, efficiency, reliability, and troubleshooting during DSS development

Payments will be transferred to the consultant’s designated bank account. No additional compensation shall be provided unless prior written approval for supplementary expenses is obtained from the designated authority. The consultant shall bear any applicable bank charges. All payments are inclusive of income tax and VAT, for which the consultant is solely responsible for declaration and settlement in accordance with relevant tax regulations.