Publications

KEY PUBLICATIONS

• Aboveground Woody Biomass Product Validation Good Practices Protocol. Version 1.0
  Duncanson, L., Armston, J., Disney, M., Avitabile, V., Barbier, N., Calders, K., Carter, S., Chave, J., Herold, M., MacBean, N., McRoberts, R., Minor, D., Paul, K., Réjou-Méchain, M., Roxburgh, S., Williams, M., Albinet, C., Baker, T., Bartholomeus, H., Bastin, J.F., Coomes, D., Crowther, T., Davies, S., de Bruin, S., De Kauwe, M., Domke, G., Dubayah, R., Falkowski, M., Fatoyinbo, L., Goetz, S., Jantz, P., Jonckheere, I., Jucker, T., Kay, H., Kellner, J., Labriere, N., Lucas, R., Mitchard, E., Morsdorf, F., Naesset, E., Park, T., Phillips, O.L., Ploton, P., Quegan, S., Saatchi, S., Schaaf, C., Schepaschenko, D., Scipal, K., Stovall, A., Thiel, C., Wulder, M.A., Camacho, F., Nickeson, J., Román, M., Margolis, H. 2021. Aboveground Woody Biomass Product Validation Good Practices Protocol. Version 1.0. In L. Duncanson, M. Disney, J. Armston, J. Nickeson, D. Minor, and F. Camacho (Eds.), Good Practicesfor Satellite Derived Land Product Validation, (p. 236): Land Product Validation Subgroup (WGCV/CEOS), doi:10.5067/doc/ceoswgcv/lpv/agb.001
  
  
• Toward REDD+ Implementation. Annual Review of Environment and Resources
  Maniatis, D., J. Scriven, I. Jonckheere, J. Laughlin and K. Todd. 2019. Toward REDD+ Implementation. Annual Review of Environment and Resources,  44:1, 373-398.
  
  
• EDITORSPECIAL ISSUE Forests-"Remote Sensing Technology Applications in Forestry and REDD+", Publication July 2019
  
  
• The role and need for space-based forest biomass-related measurements in environmental management and policy. Surveys in Geophysics
  Herold M., S. Carter, V. Avitabile, A. B. Espejo, I. Jonckheere, R. Lucas, R. E. McRoberts, E. Næsset, J. Nightingale, R. Petersen, J. Reiche, E. Romijn, A. Rosenqvist, D. M. A. Rozendaal, F. M. Seifert, M. J. Sanz and V. De Sy. 2019. The role and need for space-based forest biomass-related measurements in environmental management and policy. Surveys in Geophysics, Vol. 40, Issue 4: 757–778.
  Jonckheere, I., C. Macfarlane and J.-M. N. Walter. 2017. Image Analysis of Hemispherical Photographs. Algorithms and calculations. In: “Hemispherical Photography in Forest Science: Theory, Methods, Applications”, Edited by Prof. R. Fournier and R. Hall, University of Sherbrook, Canada, Publisher: Springer-Verlag. 
  
  
• Satellites: ambition for forest initiative
  Foody, G., F. Achard, A. Held, M. Herold, I. Jonckheere, J. Penman and M. Wulder. 2013. Satellites: ambition for forest initiative. Nature. 06/2013; 498.
  
  
• Effects of forest fragmentation on the seedling recruitment of a tropical herb: assessing seed vs safe-site limitation
  Uriarte, M., E. M. Bruna, P. Rubim, M. Anciães, and I. Jonckheere. 2010. Effects of forest fragmentation on the seedling recruitment of a tropical herb: assessing seed vs safe-site limitation. Ecology, 91(5), 1317–1328.
  
  
• Needle age-related and seasonal photosynthetic capacity variation is negligible for modelling yearly gas exchange of a temperate Scots pine forest
  Op de Beeck, M., B. Gielen, R. Samson, I. Jonckheere, I. A. Janssens, and R. Ceulemans. 2009. Needle age-related and seasonal photosynthetic capacity variation is negligible for modelling yearly gas exchange of a temperate Scots pine forest. Biogeosciences 7, 199-215.
  
  
• Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems
  Verbesselt, J., Somers B., Lhermitte S., Jonckheere I., van Aardt J., and P. Coppin. 2007. Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Rem. Sens. Environ. Vol.108 (4): 357-368. (SCI: 4.574)
  
  
• Influence of measuremental set-up of ground-based LiDAR on tree structure derivation
  Vanderzande, D., W. Hoet, I. Jonckheere, J. van Aardt, and P. Coppin. 2006. Influence of measuremental set-up of ground-based LiDAR on tree structure derivation. Agr. For. Meteorol. Vol. 141 (2-4): 147-160.
  
  
• The relevance of fractal dimension for foliage distribution quantification in forest canopies: a model approach
  Jonckheere, I., K. Nackaerts, J. van Aardt, B. Muys, and P. Coppin. 2006. The relevance of fractal dimension for foliage distribution quantification in forest canopies: a model approach. Ecol. Modell., Vol. 197(1-2): 179-195.
  
  
• Derivative analysis for in situ high-dynamic range hemispherical photography and its application in forest stands
  Jonckheere, I., B. Muys, and P. Coppin. 2005. Derivative analysis for in situ high-dynamic range hemispherical photography and its application in forest stands. IEEE Geosci. and Remote Sensing Lett. Vol. 2 (3): 296-300. (SCI: 2.642)
  
  
• Review of Methods for in situ LAI Determination, Part I: Theories, sensors and hemispherical photography
  Jonckheere, I., S. Fleck, K. Nackaerts, B. Muys, P. Coppin, M. Weiss, and F. Baret. 2004. Review of Methods for in situ LAI Determination, Part I: Theories, sensors and hemispherical photography. Agr. For. Meteorol., Vol. 121 (1-2): 19-35.
  Most downloaded paper for AFM in 2004 & Top-10 most cited paper for AFM in 2001-2005
  
  
• Review of Methods for in-situ LAI determination, Part II: Estimation of LAI, errors and sampling
  Weiss, M., F. Baret, G.J. Smith, I. Jonckheere, and P. Coppin. 2004. Review of Methods for in-situ LAI determination, Part II: Estimation of LAI, errors and sampling. Agr. For. Meteorol., Vol. 121 (1-2): 36-53.
  
  
• Optimalization of in-situ LAI determination by means of hemispherical photography. Communications in agricultural and applied biological sciences
  Jonckheere, I., Muys, B., Coppin, P. 2004. Optimalization of in-situ LAI determination by means of hemispherical photography. Communications in agricultural and applied biological sciences. Vol. 69 (2): 19-22.
  
  
• Digital change detection methods in ecosystem monitoring: A review
  Coppin, P., I. Jonckheere, E. Lambin, K. Nackaerts, and B. Muys, 2004. Digital change detection methods in ecosystem monitoring: A review. Int. J. Rem. Sens., 25 (9): 1565-1596.  

Published: 11 February 2026

Abstract

The effective translation of Earth observation (EO) measurements into actionable information for agriculture and land monitoring is critical to support policy implementation on climate, environment, and sustainable development. However, this translation remains challenging, as EO evolves from an awareness-raising instrument into an operational tool for evidence-based policymaking. To address this gap, we systematically link, for the first time, European Union (EU) land-related agricultural and environmental policies to EO-derived variables that can be generated from enhanced optical satellites expected in the next decade. We present a comprehensive framework for assessing the technology readiness levels (TRLs) of EO variables used to map, monitor, and manage crop, forest, soil, mineral, and water resources, thereby facilitating policy implementation and compliance. Upcoming Copernicus Hyperspectral Imaging Mission for the Environment (CHIME), and the Sentinel-2 Next Generation (S2NG) missions, both developed by the European Space Agency (ESA), will deliver substantial technological advancements for high-level EO-based products, enabling applications such as plant nitrogen and soil organic carbon content (SOC) estimation, species identification, and water quality characterization. Realizing the full potential of CHIME and S2NG for agricultural and environmental policy implementation will require advancing current products from prototype stages (TRL 4–6) to full operational readiness (TRL 9) through robust science-policy interfaces. Within such interfaces, we recommend exploiting existing (hyperspectral) EO data and time series, strengthening in-situ observations for robust model development and validation, and testing synergies between systems. Co-design of tailored products with policymakers is then essential to refine algorithms and align EO outputs with regulatory needs and scales. Upcoming spaceborne imaging spectroscopy and enhanced multispectral data streams thus have the potential to become game-changers and indispensable tools for EU policy implementation, providing greater traceability of key environmental and agricultural processes.

Published: 13 May 2024

Abstract

A third of the world’s ecosystems are considered degraded, and there is an urgent need for protection and restoration to make the planet healthier. The Sustainable Development Goals (SDGs) target 15.3 aims at protecting and restoring the terrestrial ecosystem to achieve a land degradation-neutral world by 2030. Land restoration through inclusive and productive growth is indispensable to promote sustainable development by fostering climate change-resistant, poverty-alleviating, and environmentally protective economic growth. The SDG Indicator 15.3.1 is used to measure progress towards a land degradation-neutral world. Earth observation datasets are the primary data sources for deriving the three sub-indicators of indicator 15.3.1. It requires selecting, querying, and processing a substantial historical archive of data. To reduce the complexities, make the calculation user-friendly, and adapt it to in-country applications, a module on the FAO’s SEPAL platform has been developed in compliance with the UNCCD Good Practice Guidance (GPG v2) to derive the necessary statistics and maps for monitoring and reporting land degradation. The module uses satellite data from Landsat, Sentinel 2, and MODIS sensors for primary productivity assessment, along with other datasets enabling high-resolution to large-scale assessment of land degradation. The use of an in-country land cover transition matrix along with in-country land cover data enables a more accurate assessment of land cover changes over time. Four different case studies from Bangladesh, Nigeria, Uruguay, and Angola are presented to highlight the prospect and challenges of monitoring land degradation using various datasets, including LCML-based national land cover legend and land cover data.

Keywords: remote sensing; land cover; land cover meta language; cloud computing; sustainable land management

Dhakal, S., J.C. Minx, F.L. Toth, A. Abdel-Aziz, M.J. Figueroa Meza, K. Hubacek, I.G.C. Jonckheere, Yong-Gun Kim, G.F. Nemet, S. Pachauri, X.C. Tan, T. Wiedmann, 2022: Emissions Trends and Drivers. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. doi: 10.1017/9781009157926.004