Using Diurnal Variation in Backscatter to Detect Vegetation Water Stress

Steele‐Dunne, Susan; Friesen, Jan; Giesen, Nick van de

doi:10.1109/tgrs.2012.2194156

Cited by 74 publications

(59 citation statements)

References 53 publications

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“…NDII is defined similarly to the NDVI, but using the shortwave infrared reflectance (ρSWIR) as (ρNIR − ρSWIR)/(ρNIR + ρSWIR). NDII can be used to detect water shortage using the property of shortwave infrared reflectance, which is negatively related to leaf water content due to the large absorption by the leaf e.g., [57,58].…”

Section: Remote-sensing Datamentioning

confidence: 99%

Recent Drought-Induced Vitality Decline of Black Pine (Pinus nigra Arn.) in South-West Hungary—Is This Drought-Resistant Species under Threat by Climate Change?

Móricz

Garamszegi

Rasztovits

et al. 2018

Forests

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This paper analyses the recent recurring dieback and growth decline of Black pine (P. nigra Arn. var austriaca) in the Keszthely mountains of south-west Hungary, and their relations to water deficits due to droughts. These relations were studied in five stands with low soil water storage capacity for the period 1981-2016. The vitality was assessed using 60 tree-ring samples and changes in remotely sensed vegetation activity indices, i.e., the normalized difference vegetation index (NDVI) and the normalized difference infrared index (NDII). Water deficit was estimated by using meteorological drought indices such the standardized precipitation-evapotranspiration index (SPEI) and the forestry aridity index (FAI), as well as the relative extractable water (REW), calculated by the Brook90 hydrological model. Results revealed a strong dependency of annual tree ring width on the amount of water deficit as measured by all the above estimators, with the highest correlation shown by the summer REW. Droughts also showed a long-term superimposed effect on tree growth. NDII seemed to be more sensitive to drought conditions than NDVI. The robust dependency of tree growth on the summer water availability combined with the projected increasing aridity might lead to decreasing growth of Black pine in Hungary towards the end of the century. We thus argue that the suggestion by several papers that Black pine can be a possible substitute species in the Alpine and Mediterranean region in the future should be revisited.

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Section: Remote-sensing Datamentioning

confidence: 99%

Recent Drought-Induced Vitality Decline of Black Pine (Pinus nigra Arn.) in South-West Hungary—Is This Drought-Resistant Species under Threat by Climate Change?

Móricz

Garamszegi

Rasztovits

et al. 2018

Forests

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“…The integrative nature of soil moisture with a seasonal memory is a major control for evaporation, air temperature, and thereby precipitation. Current satellite sensors, on the other hand, only sense the moisture content of the top soil, or even just the vegetation (Steele-Dunne et al 2012). More monitoring networks can improve the understanding of the poorly understood land surface interactions, which is valuable for climate studies.…”

Section: June 2016mentioning

confidence: 99%

Observed Soil Moisture–Precipitation Feedback in Illinois: A Systematic Analysis over Different Scales

Duerinck

Ent

Giesen

et al. 2016

Journal of Hydrometeorology

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The lack of understanding on the soil moisture-precipitation feedback mechanisms remains a large source of uncertainty for land-atmosphere coupled models. Previous observation-based studies on the soil moistureprecipitation feedback in Illinois have shown contradictory results. This paper extends earlier research by providing a more holistic analysis considering different scales based on an 11-yr (2003-13) hourly soil moisture dataset, which makes it possible to revisit the disputed hypothesis on the correlation between warmseason soil moisture and subsequent precipitation. This study finds a strong positive correlation between late spring/early summer state-average soil moisture at the root-zone depths and subsequent state-average summer precipitation. On the daily to weekly time scale, however, no relation is found. Moreover, regional analysis suggests that precipitation variability over central Illinois can be best explained by the soil moisture variability in northwest Illinois. Using a back-trajectory method [Water Accounting Model-2 layers (WAM2layers)] from May to July, the evaporative sources of precipitation in Illinois are identified. The pattern of the source regions shows little interannual variability, while the strength of the sources changes significantly and the Gulf of Mexico contributes more during wet years. However, strong influences (teleconnections) of sea surface temperatures on the subsequent precipitation variability in Illinois are not found on a seasonal scale. The long time scale of the soil moisture-precipitation correlation and the weak influences of SSTs and climate indices may suggest that precipitation variability in spring/summer in Illinois is mostly related to continental-scale soil moisture-precipitation feedback.

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“…To test diurnal variation vegetation water status as explanation of the observed diurnal differences in radar backscatter, Steele-Dunne et al (2012) modeled the sensitivity of L-and C-band backscatter to changing vegetation water content. Using the Michigan Microwave Canopy Scattering Model (MIMICS, ), it was demonstrated that during periods of low soil moisture availability, radar backscatter is sensitive to changes in vegetation water content.…”

Section: Diurnal Variations In Backscattermentioning

confidence: 99%

“…Vegetation water stress affects diurnal variations in VWC significantly (Slayter et al, 1967;Hsiao, 1973), and recent work has hypothesized the sensitivity of radar backscatter to vegetation water stress (Friesen, 2008;Steele-Dunne et al, 2012). Due to a lack of ground data this hypothesis has not been tested thoroughly yet.…”

Section: Introductionmentioning

confidence: 99%