Results 71 to 80 of about 1,323 (182)

Divergent Responses of Multi-frequency Vegetation Optical Depth Products to Climate Variations in China

open access: yesJournal of Remote Sensing
Vegetation optical depth (VOD) has been widely assessed for satellite monitoring of vegetation carbon and water status under different environmental conditions.
Mingzhu He   +7 more
doaj   +1 more source

Relationship between vegetation microwave optical depth and cross-polarized backscatter from multiyear Aquarius observations [PDF]

open access: yes, 2017
Soil moisture retrieval algorithms based on passive microwave remote sensing observations need to account for vegetation attenuation and emission, which is generally parameterized as vegetation optical depth (VOD).
Entekhabi, Dara   +6 more
core   +1 more source

Deforestation Increases Vegetation Vulnerability to Drought Across Biomes

open access: yesGlobal Biogeochemical Cycles, Volume 39, Issue 5, May 2025.
Abstract Land use and land cover changes have altered terrestrial ecosystem carbon storage, but their impacts on ecosystem sensitivity to drought and temperature fluctuations have not been evaluated spatially over the globe. We estimate drought and temperature sensitivities of ecosystems using vegetation greenness from satellite observations and ...
Chenwei Xiao   +9 more
wiley   +1 more source

SMOS-based algorithm to predict potential fire propagation in Europe [PDF]

open access: yes, 2019
Desarrollo de un algoritmo de predicción de riesgo de incendios utilizando los datos de humedad del satélite SMOS y de temperatura superficial del ...
Castela Espinha, Afonso
core   +1 more source

African dryland ecosystem changes controlled by soil water [PDF]

open access: yes, 2019
Monitoring long‐term vegetation dynamics in African drylands is of great importance for both ecosystem degradation studies and carbon‐cycle modelling. Here, we exploited the complementary use of optical and passive microwave satellite data— normalized ...
Adeel Z.   +6 more
core   +1 more source

Can Large‐Scale Satellite Products Track the Effects of Atmospheric Dryness and Soil Water Deficit on Ecosystem Productivity Under Droughts?

open access: yesGeophysical Research Letters, Volume 52, Issue 8, 28 April 2025.
Abstract Drought stress, characterized by increased vapor pressure deficit (VPD) and soil water content (SWC) deficit, significantly impacts ecosystem productivity (GPP). Accurately assessing these factors in satellite remote sensing (RS) GPP products is crucial for understanding the large‐scale ecological consequences of drought. However, the accuracy
Xiaorong Wang   +8 more
wiley   +1 more source

Temperature Is Likely an Important Omission in Interpreting Vegetation Optical Depth

open access: yesGeophysical Research Letters
Vegetation optical depth (VOD) satellite microwave retrievals provide significant insights into vegetation water content and responses to hydroclimatic changes. While VOD variations are commonly linked to dry biomass and live fuel moisture content (LFMC),
Meng Zhao   +3 more
doaj   +1 more source

Response of vegetation optical depth across multiple microwave frequencies to global vegetation dynamics

open access: yesGIScience & Remote Sensing
The multi-frequency Vegetation Optical Depth (VOD), retrieved from microwave measurements, is crucial for monitoring vegetation water status and biomass at regional to global scales.
Runsheng Jing   +20 more
doaj   +1 more source

Retrieval of the vegetation optical depth (VOD) from the radar satellites ASCAT and Sentinel-1

open access: yes, 2023
Microwave remote sensing offers a valuable alternative to optical remote sensing for monitoring vegetation because of its ability to operate in cloudy conditions and penetrate dense vegetation. Vegetation optical depth (VOD) is a microwave-based vegetation index used for monitoring the vegetation water content and the biomass.
openaire   +1 more source

Global hydro-climatic biomes identified via multitask learning [PDF]

open access: yes, 2018
The most widely used global land cover and climate classifications are based on vegetation characteristics and/or climatic conditions derived from observational data.
Demuzere, Matthias   +4 more
core   +2 more sources

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