Environmental Modelling and Earth Observation

Improving our understanding of the Earth’s biosphere and atmosphere

Image courtesy of ESA

Group Overview

Our group focuses on understanding how natural and man-made changes affect the biosphere, and using satellite information to improve modelling of weather and climate.The main research themes addressed are:

· Developing new global land and atmosphere datasets from current and future satellites

· Improving monitoring of forest health and productivity

· Quantifying regional and global land-atmosphere fluxes of carbon, water and radiation

· Advancing weather forecast and climate models

Examples of recent work includes the early detection of changes in forest and ecosystem health from aircraft and satellite, offering potential to manage threats from stress related to climate change, and increasing prevalence of disease and pests.

The group works with space agencies ESA and NASA in developing new satellite methods and datasets to improve understanding of the Earth’s biosphere and atmosphere. Examples are the retrieval of global atmospheric aerosol data sets in support of the ESA Climate Change Initiative, development of techniques to obtain data on vegetation structure in support of NASA’s ICESAT-2 mission, and algorithm development for ESA TRUTHS and Fluorescence Explorer (FLEX) planned satellite missions. This research involves development of theoretical radiative transfer modelling of light interaction with vegetation and atmosphere, such as the FLIGHT model, to underpin practical advances.

Our research contributes to climate change resilience initiatives through the development of early-warning systems for wildfire. Our work makes extensive use of state-of-the-art seasonal climate forecasts data, process-based ecosystem model outputs, remotely sensed data, and machine learning algorithms. The group works with national and international agencies, such as ECMWF and UK Met Office, and has contributed to improved modelling of weather and climate by these agencies.

Associated Research Projects

Global atmospheric aerosol products under the ESA Climate Change Initiative, uptake by international weather and climate forecasting agencies (ESA, EU Copernicus, EUMETSAT)
Remote sensing for forest management: detecting forest growth, health and decline, drivers for forest models (productivity, wind risk), and observing compliance (Royal Society, DEFRA, NERC, NCEO); UK National Forest Inventory and subcompartment database update (DEFRA)
Fire risk, forest management, Panda habitat and landscape restoration assessment in China (NERC NEWTON)
Towards a Fire Early Warning System for Indonesia (ToFEWSI) (NERC NEWTON)
Global satellite-derived vegetation data sets available from https://daac.ornl.gov/ (ISLSCP FASIR NDVI and biophysical parameters), and http://www.ceda.ac.uk (ISLSCP FASIR NDVI and biophysical parameters; vegetation height) (NCEO); Producing long term Global albedo datasets used by UK Met Office and other national forecasting agencies (ESA GlobAlbedo); Development of precise surface reflectance from the proposed ESA TRUTHS Mission (ESA, NCEO, NPL); Modelling Solar Induced Fluorescence (SIF) for monitoring of forest health and productivity (FLUORFLIGHT, European Commission Marie Curie Fellowship)

Affiliated Staff

Academic staff: Rocio Hernandez-Clemente, Sietse Los Pete North (lead) Jackie Rosette (RS fellow), Allan Spessa

Postdoctoral Researchers: Iain Bye, Tadas Nikonovas, Kevin Pearson

Postgraduate students: Zach Davies, Jacob Iglhaut, Alberto Hornero, Caitlin Jones, Harry Cook

Collaborative Partners and Research Centres

European Space Agency

EUMETSAT

ECMWF

UK Met Office

NRW

Forest Research Edinburgh

National Centre for Earth Observation

Department for Environment

Food and Rural Affairs

NASA

National Physical Laboratory

US Forest Service

INRA & UFVJM Brazil

Chinese Academy of Forestry

Facilities

Fixed wing and multicopter unmanned aerial systems (UAS) with RGB, lidar and hyperspectral sensors
Field mensuration equipment including sonic vertex and LAI 2000
High-Performance computing facilities: Linux cluster and RAID storage
Sun-Induced Chlorophyll Fluorescence instrumentation: FluoWat leaf clip; FluorPen FP 110

Research News

Abrupt impacts on dryland ecosystems

Early detection of diseases in olive trees

Is the apparent greening in the Amazon during droughts an optical illusion?

Giant trees and climate

Recent Publications

Los, S. O., Street-Perrott, F. A., Loader, N. J., Froyd, C. A., (2021). Detection of signals linked to climate change, land-cover change and climate oscillators in Tropical Montane Cloud Forests, Remote Sensing of Environment, Special Issue: 20th Anniversary of Terra Science. 260, art. no. 112431.

Gliß, J., Mortier, A., Schulz, M., Andrews, E., Balkanski, Y., Bauer, S., Benedictow, A., Bian, H., Checa-Garcia, R., Chin, M., Ginoux, P., Griesfeller, J., Heckel, A., Kipling, Z., Kirkevåg, A., Kokkola, H., Laj, P., Sager, P., Lund, M...., & Tsyro, S. (2021). AeroCom phase III multi-model evaluation of the aerosol life cycle and optical properties using ground- and space-based remote sensing as well as surface in situ observations. Atmospheric Chemistry and Physics 21(1), 87-128.

Hornero, A., Hernández-Clemente, R., North, P.R.J., Beck, P.S.A., Boscia, D., Navas-Cortes, J.A. & Zarco-Tejada, P.J. (2020). Monitoring the incidence of Xylella fastidiosa infection in olive orchards using ground-based evaluations, airborne imaging spectroscopy and Sentinel-2 time series through 3-D radiative transfer modelling. Remote Sensing of Environment 236, 111480.

Nikonovas, T., Spessa, A., Doerr, S. H., Clay, G. D., & Mezbahuddin, S. (2020). Near-complete loss of fire-resistant primary tropical forest cover in Sumatra and Kalimantan. Communications Earth & Environment 1(1), 1-8.

Alton, P. (2020). Representativeness of global climate and vegetation by carbon-monitoring networks; implications for estimates of gross and net primary productivity at biome and global levels. Agricultural and Forest Meteorology 290(2), 10801.

Berdugo, M., Delgado-Baquerizo, M., Soliveres, S., Hernández-Clemente, R., Zhao, Y., Gaitán, J.J., Gross, N., Saiz, H., Maire, V., Lehmann, A., Rillig, M.C., Solé, R.V. & Maestre, F.T. (2020). Global ecosystem thresholds driven by aridity. Science 367, 787–790.

Zarco-Tejada, P., Camino, C., Beck, P., Calderon, R., Hornero, A., Hernandez-Clemente, R., Kattenborn, T., Montes-Borrego, M., Susca, L., Morelli, M., Gonzalez-Dugo, V., North, P., Landa, B., Boscia, D., Saponari, M., & Navas-Cortes, J. (2018). Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations. Nature Plants 4(7), 432-439.

Hernández-Clemente, R., North, P.R.J., Hornero, A. & Zarco-Tejada, P.J. (2017). Assessing the effects of forest health on sun-induced chlorophyll fluorescence using the FluorFLIGHT 3-D radiative transfer model to account for forest structure. Remote Sensing of Environment, 193, 165–179 (2017).

Rosette, J., Cook, B., Nelson, R., Huang, C., Masek, J., Tucker, C., Sun, G., Huang, C., Montesano, P., Rubio-Gil, J. & Ranson, K.J. (2015), Sensor compatibility for biomass change estimation using remote sensing datasets: part of NASA’s Carbon Monitoring System initiative. IEEE Geoscience and Remote Sensing Letters 12, 1511-1555.

Morton, D., Nagol J., Carabajal C., Rosette J., Palace M., Cook B., Vermote, E., Harding D. & North, P. (2014). Amazon forests maintain consistent canopy structure and greenness during the dry season. Nature 506, 221–224.