Conservation programmes need to know what is changing on the ground, where, and how fast. We map habitats and land cover, track change over time and build monitoring systems that show whether a programme is working.
Background
From satellite to field and back.
Our team's experience includes five years at WWF Germany, supporting international conservation programmes with GIS and remote sensing. That covered landscape-scale work in the Kavango-Zambezi Transfrontier Conservation Area (KAZA), which spans five countries in southern Africa: land cover mapping, habitat change detection with the BFAST time-series algorithm, and story maps to share the results.
Good monitoring also depends on good field data. Our team's experience also includes leading field data collection campaigns at the Institute for Environmental Research in the Amazon (IPAM) to build spatial land use models, and modelling land use change and urban growth in Accra, Ghana, at Humboldt-Universität zu Berlin.
Google Earth EngineBFASTFAO SEPALRPythonArcGISArcGIS StoryMapsQGIS
What we offer
Services in this pillar.
Mapping and monitoring for conservation programmes, from landscape-scale land cover change to the habitats and species that depend on them.
02.1
Land cover & land use mapping
Classification of land cover and land use from satellite imagery, at landscape, national or transboundary scale.
02.2
Habitat change & degradation
Time-series analysis (such as BFAST) to detect where habitats are degrading, recovering or being converted.
02.3
Biodiversity & impact metrics
Indicator frameworks and monitoring systems to measure biodiversity and ecosystem health over time.
02.4
Field data collection
Design of sampling and field campaigns, and integration of field data with remote sensing models.
02.5
Ecosystem services & climate adaptation
Spatial analysis of the benefits nature provides, and of climate impacts on key sites, to support planning.
02.6
Maps, dashboards & story maps
Clear visual products for programme teams, donors and the public.
Track record
Relevant experience.
2018 – 2023
WWF Germany
GIS and remote sensing specialist
Built automated land cover classification workflows with R, Google Earth Engine and the BFAST algorithm (via FAO SEPAL) to detect land degradation over many years.
Designed metrics-driven impact monitoring systems for international conservation programmes to track biodiversity and ecosystem health.
Built automated mapping and dashboard routines in ArcGIS, cutting map production time across several conservation teams.
Coordinated technical partnerships with the European Space Agency (ESA) and academic research institutions.
2014 – 2015
Humboldt-Universität zu Berlin
Research assistant
Modelled land use change over space and time in Accra, Ghana, within the interdisciplinary Water Power project, measuring urbanisation and its impacts on ecosystems.
2010 – 2011
IPAM, Rio Branco, Brazil
Research assistant
Led field data collection campaigns to parameterise spatial land use models in the Amazon.
