Timon Weitkamp 🥍
Timon Weitkamp

Geospatial analyst: satellite monitoring, change detection and machine learning

I’m a geospatial analyst. Since 2019 I have been turning Sentinel-1, Sentinel-2 and PlanetScope imagery into maps and monitoring products for people who are not remote sensing experts: smallholder farmers, sugar mills, government agencies and the World Bank.

I work at Resilience BV (Saterra Labs) and I’m co-founder and technical lead of SmartCane BV, a satellite monitoring service for sugarcane. From 2024 to 2026 I was also a remote sensing consultant for the World Bank’s Water Informatics Team. I have a PhD in remote sensing of irrigated agriculture from Wageningen University.

Outside work I play box lacrosse for Team Netherlands, walk my dog, build furniture and play drums.

Interests
  • Satellite monitoring
  • Map making
  • Box lacrosse
Education
  • PhD Remote sensing of irrigated agriculture

    Wageningen University

  • MSc International Land and Water Management

    Wageningen University

  • MSc Geo-Information Science

    Wageningen University

  • BSc International Land and Water Management

    Wageningen University

Featured work

SmartCane | Satellite monitoring for sugarcane

Thousands of sugarcane fields in several African countries, from 0.2-hectare smallholder plots to large estates. Growth problems, ponding and harvest timing, sent out every week by WhatsApp, SMS, PDF or API. Read more →

Mapping smallholder irrigation in Mozambique | PhD and FASIMO

Smallholder irrigation hardly shows up in official statistics. My PhD and the FASIMO programme were about mapping it from space, and about how much the method changes the map. Read more →

Tools for colleagues | Viewers, web apps, Opportunity Radar

Small web tools so colleagues who don’t use QGIS or code can still look at fields, check data and triage tenders. Read more →

All projects → · Research & publications →

Technical expertise
Sensors and data: Sentinel-1, Sentinel-2, PlanetScope, time series analysis, change detection, microwave soil moisture products • Geospatial tools: Google Earth Engine, QGIS, ArcGIS (academic use), GDAL, geopandas, R (terra, sf, tidyverse), Open Data Kit for field data • Machine learning and AI: random forest, SVM, neural networks, k-means, accuracy and transferability testing, geospatial foundation model embeddings, a self-hosted LLM chatbot • Building things: FastAPI, PostgreSQL, React, Docker, small web apps for non-technical colleagues