Remote Sensing of Savannas and Woodlands II

Dear Colleagues,

Savannas, woodlands, and other tree-grass ecosystems comprise nearly 1/6th of Earth’s surface in a wide range of climates while being biodiversity hotspots. These transitory landscapes play a dominant role in global biogeochemical cycles, and are one of the most sensitive to global climate change. Indeed, these issues, combined with increasing pressures from agricultural land conversion, livestock grazing, and wildfires, require better characterization of these ecosystems. Especially, the performance of traditional remote sensing algorithms and physical modeling tend to have greater uncertainties in these landscapes due to the poor representation of both (i) the vertical multiple-layered vegetation strata (i.e., overstory with tree/shrub canopies over a herbaceous understory) and (ii) the openness of the horizontally distributed high vegetation, causing inherent pixel heterogeneity at the conventional satellite scale (e.g., >10 m). Besides, these vegetation types have distinct physiological, structural, and phenological traits that need to be better discriminated for better monitoring.

This Special Issue aims to gather papers focused on novel methodological advances to improve the characterization of savannas and woodlands integrating remote sensing. The main focus, but not limited, is towards the use of multispectral/hyperspectral and thermal infrared data to tackle the (i) vertical and (ii) horizontal variability of these ecosystems. This includes exploring sensor synergies at different spatial, spectral and temporal scales, and understanding the 3D architecture of these open forests.

Potential topics for this special issue can cover the following themes:

• Estimation of vegetation functional/structural/spectral traits, and non-photosynthetic vegetation,
• Ecological diversity, phenology, species classification,
• Processing of mixed pixels from empirical, physics-based and hybrid approaches,
• Energy balance modeling, water balance modeling, and water stress quantification, biogeochemical modeling,
• Inversion of radiative transfer modeling (1D vs. 3D)
• Sensor fusion (VSWIR, TIR, SIF,  LiDAR, Microwave)
• New hyperspectral (PRISMA, ENMAP, CHIME, SBG, ...) and TIR missions (SBG, ECOSTRESS, LSTM, TRISHNA, ...)

Dr. Karine Adeline
Dr. Ana Andreu
Dr. Vicente Burchard-Levine
Guest Editors

Manuscript Submission Information

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• savannas and woodlands
• functional traits and diversity
• evapotranspiration and water stress
• radiative transfer modeling
• energy/water balance modeling
• pixel unmixing
• imaging spectroscopy
• thermal infrared