The tool, called the Grassland Ecosystem Monitoring Index, or GEMI, was developed and evaluated by Avijit Ghosh of ICAR-Indian Grassland and Fodder Research Institute and colleagues, with results published in the journal Smart Agricultural Technology. Rather than relying on the familiar Normalized Difference Vegetation Index, the workhorse of vegetation monitoring that is notorious for saturating in dense canopies and being distorted by dust, haze, and bright soils, GEMI fuses two less celebrated spectral measures with a topographic variable: the Advanced Vegetation Index, the Green Leaf Index, and elevation derived from shuttle radar topography data.

The choice of ingredients is deliberate. AVI blends near-infrared and red reflectance in a cube-root transformation that dampens atmospheric scattering, making it more stable under the dusty, thin-cloud conditions that plague semi-arid rangelands. GLI, built entirely from red, green, and blue bands, excels at separating sparse green canopy from bright soil backgrounds, a persistent headache in landscapes where vegetation cover is patchy and soil noise is high. Because GLI depends only on visible bands, it could even be replicated with low-cost drones or standard digital cameras. Elevation, meanwhile, acts as a proxy for the climatic and hydrological gradients that govern productivity, moisture, and carbon cycling across terrain.

To build and test the index, the team selected the Amrit Mahal Kaval grasslands of Karnataka, a roughly 13,738-hectare semi-arid expanse where mean annual rainfall of 518 millimetres falls far short of the 1,307 millimetres lost to evaporation. Between July and December 2024, spanning the peak monsoon growing season, the researchers sampled 220 stratified random plots, each separated by at least five kilometres and fenced against grazing. They harvested and dried above-ground biomass across four campaigns, analysed soil organic carbon by wet oxidation, measured basal soil respiration through laboratory incubation, and estimated carrying capacity assuming 30 kilograms of green fodder per adult cattle unit per day.

Satellite data filled in the rest. Landsat 8 imagery was composited into cloud-free seasonal medians, Sentinel-5P TROPOMI supplied column-averaged methane and carbon monoxide concentrations, MODIS products yielded net primary productivity, and the Universal Soil Loss Equation provided erosion estimates. The researchers then regressed GEMI against all nine service parameters, from forage yield and soil moisture to methane, carbon monoxide, erosion, soil organic carbon, net primary productivity, microbial respiration, and carrying capacity.

The results were striking. GEMI explained seventy-five percent of the variation in vegetation moisture, the strongest single association, and achieved an R-squared of 0.61 for net primary productivity, 0.52 for methane, and 0.53 for carbon monoxide. For above-ground biomass, soil organic carbon, erosion, microbial respiration, and carrying capacity, the index captured between roughly twenty-nine and thirty-nine percent of the variance, all statistically significant. Crucially, when the team pitted GEMI against NDVI, EVI, SAVI, and even the raw AVI-plus-GLI combination, the composite index outperformed every rival across all nine parameters. Where NDVI could explain only about nine percent of variation in forage biomass, GEMI managed nearly thirty-nine percent.

Robustness testing added weight to the claims. A Monte Carlo uncertainty analysis with ten thousand iterations showed the index converging on a stable mean of about 0.38 with a standard deviation of roughly 0.22, while Sobol global sensitivity analysis ranked GLI as the dominant driver, followed by AVI and then elevation, with interactions between inputs accounting for barely two percent of output variance. The near-additive behaviour means managers can interpret changes in GEMI by looking at individual inputs directly, a practical advantage for operational monitoring. On the ground, forty-four percent of the grassland scored in the good range of 0.4 to 0.8, a third was moderate, seventeen percent fell into the degraded category below 0.1, and only six percent reached the very good class above 0.8, a spatial fingerprint the authors say can pinpoint degradation hotspots for timely restoration.

The mechanistic story behind the numbers is equally telling. Plots with greener canopies showed soil erosion reductions of up to eighty percent, soil organic carbon gains of up to seventy percent, and microbial respiration increases of roughly twenty-five percent compared with sparser sites. Elevation behaved as a genuine topographic constraint: below about 835 metres and above about 920 metres, ecosystem performance declined, so the index credits only the optimal altitudinal band. This inclusion of terrain explains much of GEMI’s edge, because erosion, productivity, and carbon storage depend not just on vegetation greenness but on slope, temperature, and moisture regimes that no spectral index alone can capture.

The authors are candid about limits: GEMI has so far been validated in a single semi-arid grassland during one growing season, and calibration coefficients may need adjustment before extrapolation to regions with different soils, rainfall regimes, or species composition. Multi-year evaluation and independent validation with external field data are the stated next steps. Still, the implications are considerable. For countries where field surveys are unaffordable and ecosystem service monitoring has largely stalled, a freely computable index built from open Landsat, MODIS, and Sentinel data offers a way to track fodder supply, grazing pressure, carbon sequestration, air quality, and soil health in one number, and to do so repeatedly, cheaply, and across entire landscapes.

Subject of Research: Development and evaluation of a remote sensing-based composite index for monitoring multiple grassland ecosystem services in semi-arid regions

Article Title: Development and evaluation of remote sensing-based grassland ecosystem monitoring tool for predicting provisioning, regulating, and supporting services in semi-arid regions

Article References: Ghosh, A., Das, B., Satpute, A. N., Haque, M. A., Singh, A. K., Chakroborty, A., Shukla, A. K., Biradar, N., Gupta, A. K., & Mukherjee, S. (2026). Development and evaluation of remote sensing-based grassland ecosystem monitoring tool for predicting provisioning, regulating, and supporting services in semi-arid regions. Smart Agricultural Technology, 15, Article 102556. https://doi.org/10.1016/j.atech.2026.102556

Image Credits: AI Generated

DOI: 10.1016/j.atech.2026.102556

Keywords: grasslands, remote sensing, ecosystem services, GEMI, vegetation indices, soil organic carbon, soil erosion, carrying capacity, semi-arid regions, Landsat 8, Sentinel-5P, net primary productivity

The study is the first of its kind to demonstrate that satellite-observed chlorophyll fluorescence can flag physiological stress in forests well before trees begin to die at a scale large enough to assess entire landscapes. Lead author Lewis Kunik, who recently completed his doctorate at the University of Utah under the joint supervision of atmospheric sciences professor John Lin and biology professor David Bowling, said he is not aware of any other tool capable of detecting this type of signal before mortality becomes obvious across such broad areas. The implications extend beyond forestry: as disturbances intensify across the American West, understanding how they impair forests’ ability to absorb and store carbon from the atmosphere has become one of the most urgent questions in Earth system science.

The technology behind the discovery exploits a quirk of plant physiology. When a leaf’s chlorophyll molecules absorb sunlight, most of that energy drives photosynthesis, the process by which plants convert light into chemical energy. But a small fraction of the absorbed radiation is re-emitted at longer, red wavelengths—a phenomenon known as fluorescence. Several next-generation satellites now carry instruments sensitive enough to detect this faint glow from orbit. Crucially, the strength of the signal tracks how efficiently plants are using the light they absorb. When trees become stressed, they absorb more light than they can put to work, their photosynthetic machinery becomes less efficient, and their red glow dims.

That dimming matters especially for Western forests, which are dominated by evergreens such as pines, spruces and firs. Conventional satellite monitoring of forest health relies on signals like greenness and canopy structure, which work reasonably well for deciduous vegetation that wilts or drops its leaves under stress. Evergreens, however, can hold onto their needles even while photosynthetically dormant, whether during winter or under severe stress, which makes them difficult to assess with traditional metrics. By tracking SIF relative to the amount of light absorbed over time, the researchers could identify subtle physiological changes in evergreen canopies that greenness-based indices simply miss.

To test the approach, the team used SIF observations from TROPOMI, an instrument aboard the European Sentinel-5P satellite chosen for its wide coverage and frequent sampling. They compared changes in fluorescence patterns across forests in the American West that later suffered wildfire- or insect-driven tree mortality against nearby control areas with similar biogeographic characteristics that experienced little mortality from wildfire or bark beetles between 2011 and 2023. In forests destined for bark-beetle die-offs, the researchers detected a significant decline in SIF roughly two years before the USDA Forest Service’s aerial detection surveys recorded any mortality. Drought alone could not explain the signal: while nearby healthy forests experienced comparable levels of drought, their SIF decline was 10 to 20 percent less severe than the decline observed in the forests later infested by beetles.

Interpreting SIF is far from straightforward, and the researchers were careful to account for the many factors that can influence it, including drought, insect infestation, canopy dieback, shifts in the seasonal timing of growth, reduced sunlight and changes in the mix of plants growing from the forest floor to the top of the canopy. The complexity of forest ecosystems makes year-to-year changes in fluorescence difficult to attribute to any single cause. In this case, however, the analysis revealed a clear and consistent pattern, and the findings suggest that SIF can serve as an early warning of forest stress that precedes widespread mortality rather than merely accompanying it.

Because bark-beetle impacts are notoriously difficult to quantify, the team validated their method using wildfire mortality as a kind of testbed, where the severity of vegetation loss can be estimated with well-established tools. They found that SIF declines scaled proportionally with the amount of vegetation lost to fire, and that wildfire’s effects on forest productivity are more predictable than beetle-driven mortality. There was also far more fire-affected land available to study. Testing the method on wildfires, Kunik explained, really helped build confidence in the bark-beetle assessment. The researchers were additionally able to use SIF to monitor how ecosystems recovered from wildfire, highlighting the technology’s potential for tracking how disturbances alter forest productivity and carbon cycling over time.

That carbon dimension is central to why the work has attracted attention beyond the forestry community. Forests store enormous quantities of carbon, and disturbances that weaken their photosynthetic capacity can tip regional carbon balances. Kunik noted that SIF is an emerging tool that Earth scientists can use to reveal the fingerprint of plant carbon dioxide uptake at regional or global scales. Drought, wildfire and bark beetle outbreaks can weaken a forest’s ability to absorb carbon and may release the carbon stored in trees, and tracking these changes will help scientists determine whether such disturbances are turning Western forests from carbon absorbers into carbon sources.

The study also benchmarked SIF against other widely used remote-sensing measures of forest health and vegetation productivity, including land surface temperature and vegetation indices such as the Normalized Difference Vegetation Index. SIF proved more sensitive to bark-beetle mortality than any of the other canopy products tested, showed stress-related declines earlier, and flagged trouble roughly two years before aerial surveys detected mortality. Co-author John Lin said the results are exciting because they demonstrate SIF’s potential to provide forest-health information over large spatial regions, and pointed to future satellites such as the European Space Agency’s FLEX mission, which will deliver fluorescence measurements at much higher spatial resolution and extend the growing SIF record.

The project began through conversations with USDA Forest Service collaborators who have long sought an early warning system to support forest management. What they want, Kunik said, is to know as soon as possible when forests may cross a threshold of stress that leaves them vulnerable to pests, pathogens or other drought-related impacts. The technology is not yet able to predict whether or exactly where mortality will occur from SIF observations alone, and the ultimate goal is not to forecast the fate of individual trees. Rather, the approach could identify areas of concern early enough for land managers to investigate on the ground, mobilize crews, allocate funding or otherwise prepare before mortality becomes widespread—a shift from reacting to die-offs after the fact toward anticipating them while intervention is still possible.

Subject of Research: Satellite observations of solar-induced chlorophyll fluorescence as an early warning of bark-beetle and wildfire tree mortality in Western U.S. forests

Article Title: Satellites spot forest stress two years before bark beetle die-offs become apparent

Article References: Satellites spot forest stress two years before bark beetle die-offs become apparent. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: solar-induced fluorescence, bark beetles, forest mortality, remote sensing, TROPOMI, Sentinel-5P, wildfire, drought stress, carbon cycling, evergreen forests, USDA Forest Service, aerial detection surveys