About

Ranga Myneni is a Professor at Boston University in the Department of Earth & Environment. He specializes in vegetation remote sensing with satellite data and climate-vegetation interactions, contributing to research in vegetation remote sensing and climate research. His educational background includes a Ph.D. from the University of Antwerp. He is involved in teaching courses such as Natural Environments: The Atmosphere, Physical Models in Remote Sensing, and Modeling and Monitoring Terrestrial Ecosystems Processes. His work focuses on understanding terrestrial ecosystems and their interactions with climate through remote sensing technologies.

Research topics

• Ecology
• Geology
• Geography
• Environmental science
• Biology
• Climatology
• Physical geography
• Atmospheric sciences
• Forestry
• Meteorology
• Agroforestry
• Mathematics
• Algorithm
• Soil science

Selected publications

• Assessing the Direct Impact of Typhoons on Vegetation Canopy Structure and Photosynthesis

  Journal of Remote Sensing · 2025-01-01 · 7 citations

  articleOpen accessSenior author

  Typhoons are undergoing changes in frequency, intensity, and landward movement due to climate change, placing coastal vegetation ecosystems at heightened risk. These ecosystems provide critical ecological, social, and economic functions, making accurate assessment of typhoon impacts essential for effective management and disaster risk reduction. Traditional methods for assessing typhoon impacts on large-scale vegetation often compare pre- and post-typhoon satellite images. These do not account for natural variations in plant life cycles or interannual variations in environmental conditions, potentially leading to inaccurate assessments of typhoon-induced vegetation damage and recovery. This study proposes a novel framework for quantifying typhoons’ immediate and long-term impacts on vegetation canopy structure and photosynthesis. We developed random forest models based on satellite-observed leaf area index (LAI) and environmental data during typhoon-free periods to simulate LAI under non-typhoon conditions. The simulated LAI time series was then compared with the satellite-observed typhoon-affected LAI to assess the typhoon-induced canopy loss and recovery, which was then used to estimate the typhoon-caused photosynthesis loss and recovery with 2 widely used light-use efficiency models. The framework was applied to 3 super typhoons that traversed the Greater Bay Area. Typhoons Nida, Hato, and Mangkhut caused canopy losses in 76.58%, 61.25%, and 89.67% of vegetated regions, respectively, leading to direct cumulative gross primary production losses of 0.36, 0.22, and 0.50 Tg C. The proposed framework establishes a pivotal foundation for future modeling and assessment of direct vegetation damage attributed to typhoons, providing scientific support for vegetation management and disaster risk reduction in coastal areas.

  PublisherDOI

• Satellite-based evidence of recent decline in global forest recovery rate from tree mortality events

  Nature Plants · 2025-04-18 · 22 citations

  article
  PublisherDOI

• Rainfall-caused water film on canopy surface biases remotely-sensed vegetation greenness

  Remote Sensing of Environment · 2025-04-10 · 4 citations

  articleSenior author
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• Abstract CT224: Phase II open-label multi-cohort study evaluating CPI-613 (devimistat) in combination with hydroxychloroquine and 5-fluorouracil or gemcitabine in patients with advanced chemo-refractory solid tumors

  Cancer Research · 2025-04-25

  article

  Abstract Background: Cancer cells use TCA cycle to generate metabolites as precursors for macromolecule synthesis. Preclinical studies show preventing TCA cycle generation of metabolites decrease tumor growth. CPI-613 (Devimistat) is a non-redox-active lipoate derivative that inhibits mitochondrial TCA cycle enzymes, pyruvate dehydrogenase (PDH) and α-ketoglutarate dehydrogenase (α-KGDH), to impair cells’ ability to utilize the TCA cycle to produce metabolites for growth. As an adaptive mechanism, cancer cells induce autophagy to generate metabolites. Pre-clinical studies report anti-tumor activity when CPI-613 is combined with autophagy inhibitor, hydroxychloroquine (HCQ). Methods: We designed an investigator initiated, open-label, phase II trial for patients (pts) with advanced chemo-refractory colorectal (Cohort 1), pancreatic (Cohort 2), and solid cancers (Cohort 3, exploratory). Cohorts 1+2 received combination of 2000 mg/m2 CPI-613+2400 mg/m2 5-fluorouracil (5FU) IV over 46hrs D1+D15 on 28D cycle. Cohort 3 received 1000 mg/m2 gemcitabine (GEM) + 2000 mg/m2 CPI-613 on D1+D15. For all cohorts, HCQ was given on C1D15 at 400mg PO BID for sequential metabolic analysis. Primary endpoint in cohorts 1+2 was objective response rate (ORR), and Simon’s 2-stage design was used, requiring ≥ 1/10 ORR’s in Stage 1 to proceed to Stage 2, and ≥4/29 ORR’s at trial end to claim the therapy promising. Secondary endpoints: safety, progression-free survival (PFS), overall survival (OS). Correlative analysis: evaluate metabolic signature changes with therapy from blood done at baseline, C1D15 and C2D1. (NCT05733000) Results: Between March 2023-Sept 2024, 26 evaluable patients enrolled, median age 60; 65% female; 54% ECOG=1; 84% White. Cohorts 1 + 2 each enrolled 10 pts in Stage 1. Cohort 3 included 6 pts (3 lung, 2 biliary,1 ovarian) to date. There were no ORR’s in Cohorts 1 + 2. 1 pt in cohort 2 had 38% decrease in target lesions with equivocal new lesion confirmed on next imaging. Best response stable disease in 3(30%) and 2(20%); median PFS 2.3 and 1.7 months; median OS 5.5 and 3.1 months, in cohort 1 and 2 respectively. Overall, 22/26 (85%) pts had at least one TRAE, including 8 (31%) highest grade 3-4 and 14 (54%) highest grade 1-2 AEs. Most frequent TRAEs across patients were vomiting (46%), fatigue (38%), lymphopenia (38%), anemia (35%). Metabolic signature analysis show alteration in PDH, α-KGDH and other TCA cycle functions with therapy, with differential expression based on clinical benefit. Conclusion: To date, in all cohorts, CPI-613 + HCQ + (5FU or GEM) did not add new safety signals compared with 5FU or GEM alone. Early efficacy data suggests clinical benefit for certain patients but no ORR’s were observed in Cohorts 1 and 2, and they will not continue to Stage 2. Further subgroup efficacy, correlative analysis and updates from ongoing cohort 3 will be presented. Citation Format: Devalingam Mahalingam, Carolyn Moloney, Masha Kocherginsky, Claudie Bosc, Katrina Dobinda, Aparna Kalyan, Sheetal M. Kircher, Therese Davis Brown, Ramya Myneni, Mary F. Mulcahy, Al B. Benson, Navdeep Chandel. Phase II open-label multi-cohort study evaluating CPI-613 (devimistat) in combination with hydroxychloroquine and 5-fluorouracil or gemcitabine in patients with advanced chemo-refractory solid tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_2):Abstract nr CT224.

  PublisherDOI

• MCI GPP: ensembling a global model- and climate-independent gross primary productivity for 2001–2023

  Scientific Data · 2025-12-11

  articleOpen accessSenior author

  Gross primary productivity (GPP), the starting point of carbon entry into the land, is crucial for understanding the global carbon cycle. Previous research have debated incorporating the CO2 fertilization effect (CFE) and canopy structural traits into GPP modeling. This study systematically evaluates their influence, demonstrating that CFE improves GPP estimation accuracy and significantly alters long-term trends. Interestingly, a two-leaf model (TLM) achieved comparable accuracy to the production efficiency model (PEM). Leveraging these insights, we generated 12 distinct GPP datasets and integrated them into a novel model- and climate-independent (MCI) GPP product using random forest regression and spatio-temporal tensor models. The MCI GPP estimates average global GPP from 2001 to 2023 at 141.9 ± 4.0 Pg C yr−1, with a significant global increase of 5.7 Pg C yr−1 per decade. Validation against AmeriFlux data shows MCI GPP outperforms other global products (MOD17, GOSIF, X-Base Fluxcom), achieving an R2 of 0.72 and RMSE of 1.86 g C m−2 d−1. Available on Zenodo, this robust 0.05° monthly dataset provides a valuable resource for carbon-climate feedback studies.

  PublisherOA PDFDOI

• Vegetation greenness in 2024

  Nature Reviews Earth & Environment · 2025-04-11 · 30 citations

  review
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• Mapping Potential Forest Canopy Top Height over Eastern United States for Aid in Restoration and Silviculture Planning

  2025-11-19

  articleSenior author

  Effective, large-scale forest restoration requires quantitative, spatially explicit targets for future forest structure. This study addresses this need by developing forest type group-specific 1-km maps of potential forest canopy top height (pCTH) across the eastern United States. We introduce a novel mechanistic model grounded in water limitations, where pCTH is determined by the equilibrium between site-specific water availability and canopy transpiration demand. The model integrates topographic, climatic, and forest trait data, with key parameters calibrated for distinct forest type groups using a robust Bayesian framework with observations from the Global Ecosystem Dynamics Investigation (GEDI) sensor. Validation against independent datasets shows strong agreement, with 63% of old-forest grid cells aligning within ±20% of TreeMap height estimates. By providing a quantitative, science-based benchmark for what forests can become, this work offers actionable insights for prioritizing restoration, guiding silviculture, and advancing nature-based climate solutions.

  PublisherDOI

• Mapping Potential Forest Canopy Top Height over Eastern United States for Aid in Restoration and Silviculture Planning

  2025-11-10

  articleOpen accessSenior author

  Effective, large-scale forest restoration requires quantitative, spatially explicit targets for future forest structure. This study addresses this need by developing forest type group-specific 1-km maps of potential forest canopy top height (pCTH) across the eastern United States. We introduce a novel mechanistic model grounded in water limitations, where pCTH is determined by the equilibrium between site-specific water availability and canopy transpiration demand. The model integrates topographic, climatic, and forest trait data, with key parameters calibrated for distinct forest type groups using a robust Bayesian framework with observations from the Global Ecosystem Dynamics Investigation (GEDI) sensor. Validation against independent datasets shows strong agreement, with 63% of old-forest grid cells aligning within ±20% of TreeMap height estimates. By providing a quantitative, science-based benchmark for what forests can become, this work offers actionable insights for prioritizing restoration, guiding silviculture, and advancing nature-based climate solutions.

  PublisherOA PDFDOI

• HiQ-FPAR: A High-Quality and Value-added MODIS Global FPAR Product from 2000 to 2023

  Scientific Data · 2025-01-15 · 3 citations

  articleOpen accessSenior author

  The Fraction of Absorbed Photosynthetically Active Radiation (FPAR) is essential for assessing vegetation's photosynthetic efficiency and ecosystem energy balance. While the MODIS FPAR product provides valuable global data, its reliability is compromised by noise, particularly under poor observation conditions like cloud cover. To solve this problem, we developed the Spatio-Temporal Information Composition Algorithm (STICA), which enhances MODIS FPAR by integrating quality control, spatio-temporal correlations, and original FPAR values, resulting in the High-Quality FPAR (HiQ-FPAR) product. HiQ-FPAR shows superior accuracy compared to MODIS FPAR and Sensor-Independent FPAR (SI-FPAR), with RMSE values of 0.130, 0.154, and 0.146, respectively, and R² values of 0.722, 0.630, and 0.717. Additionally, HiQ-FPAR exhibits smoother time series in 52.1% of global areas, compared to 44.2% for MODIS. Available on Google Earth Engine and Zenodo, the HiQ-FPAR dataset offers 500 m and 5 km resolution at an 8-day interval from 2000 to 2023, supporting a wide range of FPAR applications.

  PublisherOA PDFDOI

• Precipitation leads the long-term vegetation increase in the conterminous United States drylands

  Environmental Research Letters · 2025-02-24 · 8 citations

  articleOpen accessSenior author

  Abstract Drylands, encompassing over 40% of the conterminous United States (CONUS), are crucial to the global carbon cycle and highly susceptible to climate change. However, Earth system models offer conflicting projections of future drought and vegetation activity in North America, and in-depth analyses of the long-term changes in greenness and its relationship with underlying climate drivers, considering both spatial and temporal variations at the ecosystem scale, are lacking. This study analyzes 20 year (2001–2020) MODIS normalized difference vegetation index (NDVI) observations to assess greenness trends in CONUS drylands and their relationship with climate drivers at 1 km spatial resolution. Results indicate a large scale and systematic greening trend, particularly in the northern Great Plains (NGP) region. Using an empirical linear attribution approach and empirical orthogonal function analysis, we uncover varied relationships between greenness trends and climate drivers, particularly highlighting the dominant role of increased precipitation in driving the observed greening. Trend analysis reveals that while rain use efficiency (RUE) remains stable in most areas, increases in the NGP region suggest potential CO 2 fertilization effects, while decreases in southern states correlate with rising temperatures. We also develop an efficiency-based model featuring RUE which successfully reproduces historical NDVI, re-confirming the dominant influence of precipitation in local greenness interannual variability. However, CMIP6 projections for 2021–2040 under the ‘Regional Rivalry’ scenario (SSP370) paint a worrying picture, with projected browning in the NGP region and states near the 42°N latitude, contrasting recent greening trends. This potential reversal underscores the vulnerability of these ecosystems to future climate change, highlighting the need to consider both historical trends and future climate projections when assessing the resilience of drylands ecosystems. Overall, our work re-emphasizes the significance of water availability to drylands vegetation growth and contributes to a more comprehensive understanding of carbon-water cycling in arid and semi-arid regions.

  PublisherDOI

Frequent coauthors

• Philippe Ciais

  Laboratoire des Sciences du Climat et de l'Environnement

  192 shared

• Yuri Knyazikhin

  183 shared

• Shilong Piao

  127 shared

• Ramakrishna Nemani

  94 shared

• Compton J. Tucker

  Goddard Space Flight Center

  76 shared

• Zaichun Zhu

  Ministry of Natural Resources

  75 shared

• Kai Yan

  72 shared

• Sangram Ganguly

  Ames Research Center

  71 shared

Labs

• Vegetation Remote Sensing & Climate ResearchPI

Education

• Ph.D.

  University of Antwerp