International Geosphere-Biosphere Programme Research Articles

Next-generation radiance unfiltering process for the Clouds and the Earth's Radiant Energy System instrument

Abstract. The filtered radiances measured by the Clouds and the Earth's Radiant Energy System (CERES) instruments are converted to shortwave (SW), longwave (LW), and window unfiltered radiances based on regressions developed from theoretical radiative transfer simulations to relate filtered and unfiltered radiances. This paper describes an update to the existing Edition 4 CERES unfiltering algorithm (Loeb et al., 2001), incorporating the most recent developments in radiative transfer modeling, ancillary input datasets, and increased computational and storage capabilities during the past 20 years. Simulations are performed with the updated Moderate Resolution Atmospheric Transmission (MODTRAN) 5.4 version. Over land and snow, the surface bidirectional reflectance distribution function (BRDF) is characterized by a kernel-based representation in the simulations, instead of the Lambertian surface used in the Edition 4 unfiltering process. Radiance unfiltering is explicitly separated into four seasonally dependent land surface groups based on the spectral radiation similarities of different surface types (defined by the International Geosphere-Biosphere Programme); over snow, it is separated into fresh snow, permanent snow, and sea ice. This differs from the Edition 4 unfiltering process where only one set of regressions was used for land and snow, respectively. The instantaneous unfiltering errors are estimated with independent test cases generated from radiative transfer simulations in which the “true” unfiltered radiances from radiative transfer simulations are compared with the unfiltered radiances calculated from the regressions. Overall, the relative errors are mostly within ±0.5 % for SW, within ±0.2 % for daytime LW, and within ±0.1 % for nighttime LW for both CERES Terra Flight Model 1 (FM1) and Aqua FM3 instruments. The unfiltered radiances are converted to fluxes and compared to CERES Edition 4 fluxes. The global mean instantaneous fluxes for Aqua FM3 are reduced by 0.34 to 0.45 W m−2 for SW and increased by 0.25 to 0.46 W m−2 for daytime LW; for Terra FM1, they are reduced by 0.24 to 0.34 W m−2 for SW and increased by 0.08 to 0.28 W m−2 for daytime LW. Nighttime LW flux differences are negligible for both instruments.

Hybrid Global Annual 1-km IGBP Land Cover Maps for the Period 2000–2020

Land cover products provide critical information for monitoring and analyzing land surface changes. However, notable disagreement and incompatible classification systems among existing land cover products bring challenges in using them. Here, we developed a hierarchical International Geosphere-Biosphere Programme (IGBP) classification system and integrated four widely used land cover products (i.e., MODIS-IGBP, ESA-CCI, GlobeLand30, and GLC_FCS30) based on their accuracy against a collection of global reference samples. We generated a hybrid global annual land cover product (HYBMAP) with ~1 km (1/120°, 30″) spatial resolution from 2000 to 2020. The HYBMAP integrates information from the four products of high- and medium-resolution and reduces the disagreement between them by up to 20.1%. The overall accuracy of the HYBMAP is 75.5%, which is higher than the best of the four products (MODIS-IGBP, 70.9%). HYBMAP also integrates the temporal change information from the four products and identifies a faster growth of built-up lands. The HYBMAP provides more consistent and reliable global land cover time series data for global change research. It is free to access at https://doi.org/10.5281/zenodo.10488191 .

Strategy for Deriving Sacramento Model Parameters Using Soil Properties to Improve Its Runoff Simulation Performances

Physically-based parameter estimations are essential to improve the simulation performance of a hydrologic model and to produce physically reasonable parameters with spatial consistency. This study proposed a parameter derivation strategy to improve the Sacramento Soil Moisture Accounting (SAC-SMA) model simulation performance based on the publicly accessible Harmonized World Soil Database (HWSD). The HWSD soil properties were used to estimate the soil moisture characteristics, and the HWSD soil texture classifications and International Geosphere-Biosphere Programme (IGBP) land cover types were used to identify the Soil Conservation Service (SCS) runoff curve number (CN). After the soil moisture characteristics and CNs were identified, the major parameters of the SAC-SMA model were derived. The simulation results were evaluated using the Nash efficiency coefficient (NSEC), and Free Search (FS) algorithm was used to further adjust and calibrate the parameters. Compared with the simulation accuracy (NSEC = 0.66~0.88) and parameter transferability (NSEC = 0.22~0.83) obtained for the SAC-SMA model using directly calibrated parameters, the HWSD data-derived parameters allowed the SAC-SMA model to achieve a similar simulation accuracy (NSEC = 0.65~0.86) and a better transferability (NSEC = 0.61~0.85).

In memory of Will Steffen, 1947–2023

Will Steffen’s death has prompted the present article that attempts to summarise the many aspects of his contribution to our understanding of Earth System science, his role as an outstanding leader and communicator and the affection and respect he earned from his many colleagues, friends and associates. Personal recollections of Will from his time as Executive Director of the International Geosphere-Biosphere Programme (IGBP) and as contributor to and fellow editor of the Anthropocene Review are also included.

Comparison of Methods for Reconstructing MODIS Land Surface Temperature under Cloudy Conditions

Land surface temperature (LST) is a vital parameter associated with the land–atmosphere interface. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST product can provide precise LST with high time resolution, and is widely applied in various remote sensing temperature research. However, due to its inability to penetrate the cloud and fog, its quality is not able to meet the requirements of actual research. Hence, obtaining continuous and cloudless MODIS LST datasets remains challenging for researchers. The critical point is to reconstruct missing pixels. To compare the performance of different methods, first, three kinds of methods were used to reconstruct the missing pixels, namely, temporal, spatial, and spatiotemporal methods. The predicted values using these methods were validated by the automatic weather system data (AWS) in the Heihe river basin of China. The results demonstrated that, compared with other methods, linear temporal interpolation using Aqua data had the best performance in MODIS LST reconstruction in the Heihe river basin, with an RMSE of 7.13 K and an R2 of 0.82, and the NSE and PBias were 0.78 and −0.76%, respectively. Furthermore, the interpolation method was improved using adaptive windows and robust regression. First, the international Geosphere–Biosphere Program (IGBP) classification was employed to distinguish the different land surface types. Then, the invalid LST values were reconstructed using adjacent days’ effective LST values combined with a robust regression. Finally, a mean filter was applied to eliminate outliers. The overall results combined with ERA5 data were validated by AWS, with an RMSE of 6.96 K and an R2 of 0.79 and the NSE and PBias were 0.77 and −0.20%, respectively. The validation demonstrated that the scheme proposed in this paper is able to accurately reconstruct the missing values and improve the accuracy of the interpolation method to a certain extent when reconstructing MODIS LST.

Suitability and Sensitivity of the Potential Distribution of Cyclobalanopsis glauca Forests under Climate Change Conditions in Guizhou Province, Southwestern China

Global climate change is becoming increasingly prominent and has already begun to influence natural biological systems. Assessing the potential impact of climate change on ecosystems is an important research topic of the International Geosphere-Biosphere Programme (IGBP). Based on current distribution data, climate data, climate change scenarios (RCP8.5 scenario, 2070–2099), and application of the MaxEnt model, this study assessed suitability and sensitivity of the potential distribution of Cyclobalanopsis glauca forests under climate change conditions in Guizhou Province. The results were as follows: (1) Area under the curve values of training data and texting data indicated excellent performance of the model; (2) Compared to the current climate, areas of probability <0.4 were decreased, and the other areas presented an increasing trend under the RCP8.5 scenario; (3) Positive sensitivity areas were much larger than negative sensitivity areas under climate change. In either case, slight sensitivity areas accounted for the largest proportion; (4) The mean altitude of slight sensitivity areas measured the lowest, and highly negative sensitivity areas were the highest.

MODIS Vegetation Continuous Fields tree cover needs calibrating in tropical savannas

Abstract. The Moderate Resolution Imaging Spectroradiometer Vegetation Continuous Fields (MODIS VCF) Earth observation product is widely used to estimate forest cover changes and to parameterize vegetation and Earth system models and as a reference for validation or calibration where field data are limited. However, although limited independent validations of MODIS VCF have shown that MODIS VCF's accuracy decreases when estimating tree cover in sparsely vegetated areas such as tropical savannas, no study has yet assessed the impact this may have on the VCF-based tree cover data used by many in their research. Using tropical forest and savanna inventory data collected by the Tropical Biomes in Transition (TROBIT) project, we produce a series of calibration scenarios that take into account (i) the spatial disparity between the in situ plot size and the MODIS VCF pixel and (ii) the trees' spatial distribution within in situ plots. To identify if a disparity also exists in products trained using VCF, we used a similar approach to evaluate the finer-scale Landsat Tree Canopy Cover (TCC) product. For MODIS VCF, we then applied our calibrations to areas identified as forest or savanna in the International Geosphere-Biosphere Programme (IGBP) land cover mapping product. All IGBP classes identified as “savanna” show substantial increases in cover after calibration, indicating that the most recent version of MODIS VCF consistently underestimates woody cover in tropical savannas. We also found that these biases are propagated in the finer-scale Landsat TCC. Our scenarios suggest that MODIS VCF accuracy can vary substantially, with tree cover underestimation ranging from 0 % to 29 %. Models that use MODIS VCF as their benchmark could therefore be underestimating the carbon uptake in forest–savanna areas and misrepresenting forest–savanna dynamics. Because of the limited in situ plot number, our results are designed to be used as an indicator of where the product is potentially more or less reliable. Until more in situ data are available to produce more accurate calibrations, we recommend caution when using uncalibrated MODIS VCF data in tropical savannas.

Land Surface Temperature Retrieval from Fengyun-3D Medium Resolution Spectral Imager II (FY-3D MERSI-II) Data with the Improved Two-Factor Split-Window Algorithm

Land surface temperature (LST) is an essential parameter widely used in environmental studies. The Medium Resolution Spectral Imager II (MERSI-II) boarded on the second generation Chinese polar-orbiting meteorological satellite, Fengyun-3D (FY-3D), provides a new opportunity for LST retrieval at a spatial resolution of 250 m that is higher than that of the already widely used Moderate Resolution Imaging Spectrometer (MODIS) LST data of 1000 m. However, there is no operational LST product from FY-3D MERSI-II data available for free access. Therefore, in this study, we developed an improved two-factor split-window algorithm (TFSWA) of LST retrieval from this data source as it has two thermal-infrared (TIR) bands. The essential coefficients of the TFSWA algorithm have been carefully and precisely estimated for the FY-3D MERSI-II TIR thermal bands. A new approach for estimating land surface emissivity has been developed using the ASTER Global Emissivity Database (ASTER GED) and the International Geosphere-Biosphere Program (IGBP) data. A model to estimate the atmospheric water vapor content (AWVC) from the three atmospheric water vapor absorption bands (bands 16, 17, and 18) has been developed as AWVC has been recognized as the most important factor determining the variation of AT. Using MODTRAN 5.2, the equations for the AT estimate from the retrieved AWVC were established. In addition, the AT of the pixels at the far edge of FY-3D MERSI-II data may be strongly affected by the increase of the optical path. Viewing zenith angle (VZA) correction equations were proposed in the study to correct this effect on AT estimation. Field data from four stations were applied to validate the improved TFSWA in the study. Cross-validation with MODIS LST (MYD11) was also conducted to evaluate the improved TFSWA. The cross-validation result indicates that the FY-3D MERSI-II LST from the improved TFSWA are comparable with MODIS LST while the correlation coefficients between FY-3D MERSI-II LST and MODIS LST over the Mid-East China region are in the range of 0.84~0.98 for different seasons and land cover types. Validation with 318 field LST samples indicates that the average MAE and R2 of the scenes at the four stations are about 1.97 K and 0.98, respectively. Thus, it could be concluded that the improved TFSWA developed in the study can be a good algorithm for LST retrieval from FY-3D MERSI-II data with acceptable accuracy.

Instructional guidelines based on conceptions of students and scientists about economic and population growth within planetary boundaries

The burden placed by human activities on Earth is ever-increasing. Global environmental changes have profoundly affected the Earth’s core systems and processes, thus, risking their stability. These core systems and processes are described in the planetary boundary framework. The drastic rate of environmental change over the last 200 years, which is also known as the Great Acceleration, has been depicted graphically by the International Geosphere-Biosphere Program. This study is aimed to (1) examine the conceptions of students and scientists regarding socioeconomic growth within planetary boundaries, and (2) develop instructional guidelines based on the comparison of their conceptions. Accordingly, relevant conceptions of 22 junior and 20 senior secondary school students were analyzed. Scientists’ conceptions were extracted by thoroughly analyzing nine publications, which were selected by systematic literature search. Student statements and scientific inferences were coded following established protocols. Our results indicated that junior and senior secondary school students considered global population growth to be the primary cause of global environmental changes. On the contrary, the scientists considered the quantity of natural resources consumed by rich countries in their economic pursuits as the most critical factor in environmental degradation. Based on our findings, we proposed instructional guidelines for planning lessons on changing current socioeconomic systems to enable humans to live within planetary boundaries.

Assessing and predicting soil carbon density in China using CMIP5 earth system models

Soil carbon (SC) is a key component of the carbon cycle and plays an important role in climate change; however, quantitatively assessing SC dynamics at the regional scale remains challenging. Earth system model (ESM) that considers multiple environmental factors and spatial heterogeneity has become a powerful tool to explore carbon cycle-climate feedbacks, although the performance of the ESM is diverse and highly uncertain. Thus, identifying reliable ESMs is a prerequisite for better understanding the response of SC dynamics to human activity and climate change. The 16 ESMs that participated in the fifth phase of the Coupled Model Intercomparison Project (CMIP5) were employed to evaluate the skill performance of SC density simulation by comparison with reference data from the International Geosphere-Biosphere Programme Data and Information System (IGBP-DIS). Although ESMs generally reflect spatial patterns with lower SC in northwest China and higher SC in southeast China, 11 of 16 ESMs underestimated the SC in China, and 5 of 16 ESMs overestimated the SC density as most ESMs had large discrepancies in capturing the SC density in the northern high latitudes of China and the Qinghai-Tibet Plateau. According to a series of model performance statistics, SC simulated by Institute Pierre Simon Laplace (IPSL) Coupled Model had a close spatial pattern with IGBP-DIS and showed higher skills for SC predictions in China relative to other CMIP5 ESMs. The multimodel ensemble average obtained by IPSL family ESMs showed that SC density exhibited increasing trends under both the RCP4.5 scenario and RCP8.5 scenario. The SC density increased slowly under RCP8.5 compared with that under RCP4.5 and even displayed a decreasing trend in the late 21st century. The findings of this study can provide a reference for identifying the shortcomings of SC predictions in China and guide SC parameterization improvement in ESMs.

Predicting land cover changes using a CA Markov model under different shared socioeconomic pathways in Greece

ABSTRACT Land change modeling (LCM) is a complex GIS procedure aiming at predicting land cover changes in the future, contributing thus to the design of interventions that help maintain ecosystem services and mitigate climate change impacts. In the present work, the land change model for Greece, a typical Mediterranean country, has been developed, based on historical information from remotely sensed land cover data. Land cover types based on the International Geosphere-Biosphere Program (IGBP) classification were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product, i.e. MCD12Q1, provided annually from 2001 to 2018 at a spatial resolution of 500 m. Initially, the dominant land cover changes and their driving variables for the decade of 2001 to 2011 were determined and the transition potential of land was mapped using a multi-layer perceptron (MLP) neural network. Four dominant land-cover transformations were found in Greece from 2001 to 2011, i.e. land transformation from Savannas to Woody Savannas, from Savannas to Grasslands, from Grasslands to Savannas, and from Croplands to Grasslands. Driving variables were found to be the Evidence Likelihood of Land Cover, i.e. the relative frequency with which different land cover categories occurred within the areas that transitioned, the Altitude as realized in the Digital Elevation Model of Greece from ASTER GDEM, the Distance from previously changed land and two climate variables i.e. Mean Annual Precipitation and Mean Annual Minimum Temperature. After the model was calibrated, its predictive ability was tested for land cover prediction for 2018 and was found to be 96.7%. Future land cover projections up to 2030 were developed incorporating CMIP6 climate data under two Shared Socioeconomic Pathways (SSPs), i.e SSP126 corresponding to a sustainable future and SSP585, which describes the future world based on fossil-fueled development. The results indicate that major historical land transformations in Greece, do not correspond to land degradation or desertification, as it has been reported in previous works. On the contrary, the land cover transitions indicate that the Woody Savannas gain areas constantly, whereas Grasslands and Croplands lose areas, and forested areas of all types demonstrate moderate gains. Concerning future land cover, the present work indicates that the direction of historical changes will also prevail in the next decade, with the most severe scenario, i.e. SSP585 slowing down the rate of changes and the most sustainable one, i.e. SSP126, accelerating the rate of expansion of woody vegetation land cover type.

A new net primary productivity model and new management strategy of grassland classification based on CSCS in China

The discovery of grassland field, form and biomass in China was central to the sustainable development of grassland. In this study, the realistic spatial distribution patterns of grasslands were clarified through the combination of the International Geosphere-Biosphere Program (IGBP) and the Comprehensive and Sequential Classification System (CSCS). An optimal net primary productivity (NPP) model suitable for Chinese grasslands was introduced by integrating the classification indices-based model (CIM) with the Normalised Difference Vegetation Index (NDVI), and comparing it with the standard classical model (Miami, Schuur, CIM, CASA model). Using the optimal model as the algorithm basis, the net primary production spatial pattern of grassland in China was determined. The results showed that: (1) the total area of grassland was ~374.3 × 104 km2 in 2018, mainly distributed in north-western China. Among the grassland super-class groups, Tundra and alpine steppe were largest, and Warm desert smallest; (2) the optimal modified CIM had the highest prediction efficiency, and the overall accuracy was higher than the standard classical model (Miami, Schuur, CIM, CASA model). It achieved the accurate calculation of grassland NPP in China; (3) different grassland super-class groups had different carbon fixation efficiency per unit area, resulting in huge differences in total NPP. Among the various grassland super-class groups, the temperate humid grassland, steppe, tundra and alpine steppe had high conversion efficiency per unit area of NPP, whereas that for warm desert and the savanna was low. The total NPP was 388.04 × 1012 g C/year in the study area in 2018. The results provide a basis for the rational arrangement of grassland ecological and productive functions, and are significant for developing a new strategy of grassland classification management in China.

From South Asia to the world: embracing the challenge of global sustainable nitrogen management

From South Asia to the world: embracing the challenge of global sustainable nitrogen management

Climatology of the Combined ASTER MODIS Emissivity over Land (CAMEL) Version 2

The Combined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) MODIS (Moderate Resolution Imaging Spectroradiometer) Emissivity over Land (CAMEL) Version 2 (V002) has been available since March 2019 from the NASA LP DAAC (Land Processes Distributed Active Archive Center) and provides global, monthly infrared land surface emissivity and uncertainty at 0.05 degrees (~5 km) resolution. A climatology of the CAMEL V002 product is now available at the same spatial, temporal, and spectral resolution, covering the CAMEL record from 2000 to 2016. Characterization of the climatology over case sites and IGBP (International Geosphere-Biosphere Programme) land cover categories shows the climatology is a stable representation of the monthly CAMEL emissivity. Time series of the monthly CAMEL V002 product show realistic seasonal changes but also reveal subtle artifacts known to be from calibration and processing errors in the MODIS MxD11 emissivity. The use of the CAMEL V002 climatology mitigates many of these time dependent errors by providing an emissivity estimate which represents the complete 16-year record. The CAMEL V002 climatology’s integration into RTTOV (Radiative Transfer for TOVS) v12 is demonstrated through the simulation of IASI (Infrared Atmospheric Sounding Interferometer) radiances. Improved stability in CAMEL Version 3 is expected in the future with the incorporation of the new MxD21 and VIIRS VNP21 emissivity products in MODIS Collection 6.1.

Vegetation Expansion on the Tibetan Plateau and Its Relationship with Climate Change

The natural shift in land cover from non-vegetated to vegetated land is termed as vegetation expansion, which has substantial impacts on regional climate conditions and land surface energy balance. Barrens dominate the northwestern Tibetan Plateau, where vegetation is predicted to expand northwestward with the ongoing climate warming. However, rare studies have confirmed such a forecast with large-scale vegetation monitoring. In this study, we used a landcover dataset, classified according to the International Geosphere–Biosphere Program criteria, to examine previous model-based predictions and the role of climate on the expansion rate across the plateau. Our results showed that shrublands, open forests, grasslands, and water bodies expanded while evergreen and deciduous broadleaf forests, croplands and barrens shrank during the period 2001–2018. Vegetation expanded by 33,566 km2 accounting for about 1.3% of the total area of this plateau and the land cover shifting from barrens to grasslands was the primary way of vegetation expansion. Spatially, the vegetation expanded northwestward to lands with colder, drier, and more radiation in the climate. Increasing precipitation positively correlated with the vegetation expansion rate for the arid and semi-arid northwest Tibetan Plateau and warming contributed to the vegetation expanding in the semi-humid southeast Tibetan Plateau. Our results verified the predictions of models and highlighted the “greening” on barrens in recent years.

Science and Diplomacy around the Earth

In this article we discuss two phases in the evolution of global environmental programs, namely the Man and Biosphere Programme and the International Geosphere-Biosphere Programme, with the aim of showing their hidden diplomatic ambitions from both US and Soviet perspectives. In the 1960s and 1970s, Soviet views on the biosphere prevailed thanks to the influence of Soviet scientists in the International Council of Scientific Unions and the United Nations Educational, Scientific and Cultural Organization. In the 1980s, the domination of this field by US scientists ushered in the establishment of Earth system science as a new research trend based on Earth observation technologies. We argue that despite the influence of Soviet ecologists in directing international coordination of research on the biosphere, Earth system science did not set in a trajectory of environmental cooperation. This outcome can be explained if we take the environmental and ecological turn that arose during the Cold War as being intertwined with political concerns and national interests in both the US and the USSR. Security, scientific diplomacy, and geopolitical issues limited East-West collaboration on the interdisciplinary study of the earth, which instead turned into a sort of cooperative antagonism. The transition from biosphere studies to Earth system science reveals a changing strategy toward environmental problems, which in turn reflects changes in Cold War policy. This essay is part of a special issue entitled Science Diplomacy, edited by Giulia Rispoli and Simone Turchetti.

Surface wind gust prediction over Incheon international airport using the unified model

The unified model (Version: UM10.4) wind gust prediction system using rose nesting suite at 300 m resolution over the Incheon international airport (IIA) is carried out, and the prediction results of multiple domain nesting with input initial and lateral boundary conditions from the Korea meteorological administration (KMA) operational global data assimilation and prediction system (GDAPS) are compared with the operational local data assimilation and prediction system and the observed automated weather stations (AWS) dataset. The 300 m nested prediction system over the IIA is built from the 17 km GDAPS output in KMA; it is downscaled with a multiple nesting domains to 300 m resolution from the GDAPS, here after called as IIA-300 m. The model results are validated against the AWS to see the accuracy of the IIA-300 m model’s skill in predicting the wind gust over the IIA. The nesting suite is run with the default ancillary files created by the central ancillary program 9.0 (CAP 9.0) as well as modified ancillary files created by modifying the land points over IIA region using an ancillary editor. The UM model wind prediction is done with both ancillary files to see the improvements achieved by adding additional land points over the IIA domain. Further the vegetation fraction from the international geosphere-biosphere program (IGBP) data classified as 9 tiles in the ancillary file is replaced by the environmental-geographic information system (E-GIS) data to see the effect on the UM model’s wind gust predictions. The prediction of two wind gust events on 30-August-2016 and 02-October-2016 reveals only modest improvements in the prediction with respect to AWS observations, even after the modification of ancillaries with land points over the IIA domain, and only minor improvements are noted for the vegetation fraction replacement from IGBP to E-GIS vegetation dataset over the Incheon International Airport and exhibited only a marginal wind speed decrease due to warming up of the land part, particularly on the peripheries of the IIA-domain.

ASLO 2020 Award Winners

<scp>ASLO</scp> 2020 Award Winners

Applicability of MODIS land cover and Enhanced Vegetation Index (EVI) for the assessment of spatial and temporal changes in strength of vegetation in tropical rainforest region of Borneo

Rainforests in the equatorial tropical regions are facing severe changes in strength and distribution due to natural and anthropogenic activities. Climate change causes major issues in vegetation characteristics whereas logging and developmental activities destruct the natural characteristics of terrain and vegetation. In the present research, MODIS vegetation cover type and vegetation indices (Enhanced Vegetation Index –EVI) data were interpreted to assess the decade (2008–2017) variation in vegetation types and strength characteristics in the Baram River Basin (BRB) in Borneo. International Geosphere-Biosphere Programme (IGBP) based classification identified ten land cover types in the BRB and the mean EVI in most periods varies between −0.30 and greater than 0.80. Results showed spatial and temporal variation in the area covered by individual land cover during the period of analysis and the fluctuation in mean EVI values indicates variation in strength characteristics of land cover types in the region. Statistical analysis showed a significant correlation (r > 0.50) of mean EVI values between consecutive years of analysis. Though the IGBP classification scheme could not categorise the most dominant land use activities in the BRB i.e. logging and oil palm plantations, the findings of the present research validate the use of MODIS data in equatorial tropical rainforest regions for characterising the regional scale vegetation dynamics.

The emergence and evolution of Earth System Science

Earth System Science (ESS) is a rapidly emerging transdisciplinary endeavour aimed at understanding the structure and functioning of the Earth as a complex, adaptive system. Here, we discuss the emergence and evolution of ESS, outlining the importance of these developments in advancing our understanding of global change. Inspired by early work on biosphere–geosphere interactions and by novel perspectives such as the Gaia hypothesis, ESS emerged in the 1980s following demands for a new ‘science of the Earth’. The International Geosphere-Biosphere Programme soon followed, leading to an unprecedented level of international commitment and disciplinary integration. ESS has produced new concepts and frameworks central to the global-change discourse, including the Anthropocene, tipping elements and planetary boundaries. Moving forward, the grand challenge for ESS is to achieve a deep integration of biophysical processes and human dynamics to build a truly unified understanding of the Earth System. Earth System Science (ESS) has emerged as a powerful tool to investigate and understand global change. This Perspective outlines the history of ESS and advocates for the full integration of human and biogeophysical dynamics necessary to build a truly unified ESS effort.