Description 

Better Cotton is the world’s largest cotton sustainability programme. Our mission: to help cotton  communities survive and thrive, while protecting and restoring the environment. In difficult times, we  are meeting the challenge head on. Through our network of field-level partners we have provided  training on more sustainable farming practices to more than 2.9 million cotton farmers in 26  countries. More than a fifth of the world’s cotton is now grown under the Better Cotton Standard and  our membership network includes more than 2,400 members.  

More information about Better Cotton can be found on our website: www.bettercotton.org

Background

Development of a crop monitoring system using remote sensing and field data mapping Applications Deadline: 12 September 2025  

This work is part of a larger ISEAL funded project focusing on the Geospatial Information Technology  for Outcome Verification (GIT4OV) as a means to pave the way for improved smallholder livelihoods.  This work focuses on the integration of remote sensing and GIS technology to improve cotton  farmers efficiency, productivity and sustainability by developing the algorithms for crop detection,  crop monitoring and soil health monitoring. 

Geospatial Information Technology (GIT) combines the principles of geography with advanced  technology to collect, analyse and manage geographical data. The key components of GIT are  geographic information system (GIS), Remote Sensing (RS), Global positioning system (GPS) and  geospatial data. GIT is being used in various fields including agriculture and natural resource  management. GIT is agriculture supports precision farming, crop monitoring, crop advisory and soil  analysis for better natural resource management and conservation. 

Remote Sensing is a modern-day requirement for agriculture and management practices. Remote  sensing has its key implications in crop monitoring, precision agriculture, crop production/yield  prediction, soil analysis and weather monitoring for informed decision making for the farmers  regarding crop health, site specific fertiliser application, crop rotation and soil management, better  planning for yield and market decisions and particularly about tracking weather patterns and  predicting natural disasters allowing farmers to practice prevention and mitigation.  

Better Cotton has conducted a detailed matrix review of remote sensing technologies in agriculture and GIS approaches that are being used in agriculture globally and have also documented the best  practices and case studies from use of remote sensing and GIS applications in agriculture. The  matrix review report recommended a hybrid approach for the Better Cotton that can integrate freely  available Sentinel-2 imagery or commercial datasets for precise field boundary delineation, especially  on fragmented small farms. The review recommendation also included the use of deep learning  models to fine-tune through farmer-validated ground truthing via mobile tools such as ODK and  introducing a centralised geospatial data warehouse on Azure and a Power BI dashboard to streamline monitoring of crop health, water use, and regenerative outcomes. The scaling should  follow a pilot–scale–sustainability roadmap, culminating in a global open-source boundary repository  to drive equitable digital agriculture. Based on the recommendations of the review, Better Cotton is  looking for developing the crop monitoring system using remote sensing and field data. 

Better Cotton distinguishes farms by size to adapt sustainability requirements. Small farms (up to 20  hectares) are typically family-managed with limited hired labour, focusing on basic record-keeping and  participatory training. Medium farms (20-200 hectares) involve more structured operations, requiring  formal management systems, enhanced documentation, and broader worker engagement. Large  farms (>200 hectares) operate commercially with significant labour forces and mechanisation,  demanding rigorous compliance with all Better Cotton Principles and Criteria, including integrated  pest management, water stewardship, decent work, and biodiversity enhancement. Each category  aligns with the Better Cotton Standard System, ensuring that practices are scaled appropriately to  farm capacity while promoting continuous improvement. Criteria are adapted to reflect differences in  decision-making, resource access, and workforce dynamics, enabling inclusive and measurable  sustainability outcomes across all farm types. 

A comprehensive remote sensing system must be useful for crops detection particularly cotton in the  field with multi-temporal, openly available high-resolution, satellite imagery combined with ground truthing protocols to ensure accuracy. It should support vegetation indices, canopy cover analysis,  and phenological monitoring to detect crop health, stress, and yield potential. It must have integration  with GIS platforms to enable spatial mapping and decision support. For rangelands and forests,  biomass estimation and land cover classification are essential. The system must accommodate  diverse crop cycles, local climatic conditions, and stakeholder needs, while ensuring interoperability  with existing agricultural databases and enabling scalable, real-time monitoring for sustainable land  management.

Scope of Work & Deliverables 

Better Cotton invites qualified consultants or consulting firms to submit proposals for the  development of algorithms and integrated tools for crop detection and field data mapping. The scope  includes: 

1. Design a machine learning-based solution to automate the delineation of agricultural field  boundaries using remote sensing imagery. It must be a functional algorithm capable of  segmenting satellite imagery to generate polygonal representations of field boundaries by  integration of models fine-tuned for smallholder’s context compatible with geospatial  platforms. 

2. Designing algorithms and tools for land cover classification and biomass detection, land  conversion over time, crop detection, crop health monitoring, agriculture practices validation  (e.g. land levelling, ridge sowing, intercropping etc.) pest and disease detection, yield  estimation, soil health monitoring (e.g. soil organic matter, soil nitrogen status, moisture  contents etc.) weather conditions and farmer advisories.  

3. Integrating remote sensing data with local agricultural practices, weather patterns, and  government datasets. 

4. Develop dynamic web-based system with graphical user interface (GUI) to access the  algorithms and tools developed under scope 1, 2 and 3. 

5. Delivering a training module on Web-GIS application use in the field. 

6. Creating farmer-friendly guidelines for interpreting localised data and applying insights. 

The consultant/firm will develop a robust crop monitoring system integrating remote sensing and  field data mapping to enhance agricultural decision-making, outcome verification and sustainability  outcomes. The consultant/firm will be designing system architecture, identifying appropriate satellite  datasets and ground-truthing protocols, and establishing data validation mechanisms. The system  will monitor crop growth/health, stress indicators, and yield forecasts across designated pilot regions (Pakistan, India, Mozambique). It must align with stakeholder needs, support real-time updates, and  ensure interoperability with existing agricultural platforms. The consultant/firm will conduct  stakeholder consultations, propose user-friendly visualisation tools, and prepare training materials for  system adoption. Deliverables include a detailed implementation plan, technical manual, and a pilot tested monitoring dashboard. 

Regions/Countries: Pakistan, India, Mozambique and Australia, but scalable to other cotton growing  regions/Better Cotton working location. 

IT requirements: 

• The newly developed system including the technology stack must be compatible with Better  Cotton’s existing IT systems (can be further discussed at inception stage). 

• The newly developed system must be access based and must have user  permissions/restriction like super admin, global login, country login to access the specific  country data only. The system must be capable of storing the farmers data in country specific  locations to ensure data protection, security and compliance with legal requirements. 

• The proposed system must incorporate robust web security protocols and must comply with  established security standards. 

• The deployment should ensure scalability, security, and minimal disruption. 

1. Purpose of the Assignment  

The purpose of this assignment is to develop a crop monitoring system using remote sensing and field  data mapping that leverages remote sensing and field data mapping to enhance agricultural decision making. The system will enable timely detection of crop types, health status, and yield estimates, while  also supporting environmental monitoring and farmer advisories to promote sustainable and climate resilient farming practices and regenerative outcomes verification using the real time data. 

2. Methodology  

Better Cotton expects the consultant/firm to develop a methodology based on the purpose and scope  of work of the assignment. The consultant/firm should also provide justification for proposing a  particular approach and methodology with detailed discussion in their proposal. The final decision on  the approach and methodology to be used will be done during inception meeting in consultation with  the Better Cotton team. The proposed methodology for developing the remote sensing system must  be aligned with IT requirements mentioned above. 

3. Deliverables  

Better Cotton is expecting the following deliverables to be completed by the consultant/firm.  

1. Inception Report: The consultant/firm must deliver an inception report detailing the proposed  methodology, implementation timeframe, cost-benefit analysis, risk assessment, and  mitigation strategies. This report will serve as the foundational blueprint to ensure clarity and  alignment across stakeholders. 

2. Remote Sensing Module: A functional remote sensing module should be developed to analyse satellite imagery and other spatial data for crop detection, yield estimation, land cover  changes, and environmental monitoring. The module must integrate seamlessly with existing  geospatial systems. 

3. Web GIS Module: The GIS module must enable interactive mapping, data visualisation, and  spatial analysis. It should support functionalities like field boundary delineation and overlaying  multiple environmental datasets to guide data-driven decisions at farm and landscape levels. 

4. Farmer Advisories Module: The consultant/firm should design an intuitive module for  delivering personalised advisories to farmers. It should use field data, crop health insights, and  seasonal forecasts to generate recommendations on sustainable practices, pest control,  irrigation, and climate resilience. 

5. Draft and Final Modules: Initial drafts of each technical module must be submitted for Better  Cotton review and feedback. Final versions should incorporate revisions based on validation  results and user/field testing, ensuring each module is functional, user-friendly, and  contextually relevant. 

6. System Deployment, Source Code, Manual and Guidelines: The final system must be  deployed within the Better Cotton’s Azure-based infrastructure. The consultant/firm must also  provide a comprehensive operational manual, source code, and user guidelines to support  onboarding, troubleshooting, and long-term maintenance. 

High-level Timeline

Applications Deadline: 12 September 2025  

Required Skills & Knowledge 

In addition to skills, competencies, and expertise, we will consider value for money and demonstrable  commitment to the field of sustainability to evaluate applications. 

Getting to know you

Application Requirements 

Please note that we have changed our RFP submission protocol, and this is now in two phases:  

• Phase 1: Initial details will be submitted on the form found in this link.  

• Phase 2: You will receive an email with live links to upload relevant documents (please check your Spam and Junk folders).  

Proposals sent to respond to this Request for Proposals must include the following: 

• A succinct, well-documented Technical Proposal that includes: 

o Understanding of the assignment including a summary of tasks and main objectives o The proposed approach and methodology including working approach and justification  for the working approach and methodology. 

o Activities and their corresponding timeline. 

o A clear description of the project team members with details of their relevant. experience and their CVs. If any external experts will be engaged, share their profiles as  well. 

o At least three references from similar work conducted by the consultant/firm.

• At least one sample of previous relevant work (the contents of which will remain confidential  and will be used for the sole purpose of evaluating the submission and link of online  platform if publicly available). 

• A Financial Proposal: please provide a detailed budget including the time allocated for each  activity and the daily rates per person. Please note that ALL costs must be included in the  detailed budget including expenses, traveling costs, and taxes. Value for money is highly  appreciated and preferred. 

• Be capable of full invoicing and delivery before 30/03/2026. 

Evaluation Criteria 

Proposals will be evaluated based on the following criteria: 

Technical Evaluation Criteria 

• Demonstrated understanding of this RFP. 

• Quality and clarity of the proposal. 

• Relevant professional experience of the proposed consultant(s)/firm. 

• Quality and relevance of the sample work submitted. 

Financial Evaluation Criteria 

• Quality and clarity of budget provided, and level of detail included. 

• Value for money. 

We thank all applicants for their interest. However, only shortlisted applicants will be contacted.    

Better Cotton is committed to good practice and transparency in the management of natural, human  and financial resources. All applications will be reviewed under the principles and subject to Better  Cotton’s policies on equal opportunity, non-discrimination, anti-bribery & corruption and conflict of  interest.