A Semiempirical Approach for Decomposition of Remotely Sensed Leaf Area Index Into Overstory and Understory Components Over Russian Forests

Shabanov, Nikolay V.; Барталев, С.А.; Kobayashi, Hideki; Nagai, Shin; Khovratovich, T.S.; Zharko, Vasily; Medvedev, A.A.; Telnova, Natalia

doi:10.1109/tgrs.2023.3287075

Cited by 1 publication

(2 citation statements)

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“…The IKI MODIS LAI is a cloud-and snow-screened daily composited and interpolated product at 230 m resolution from January 2001 to the present [22]. LAI (dimensionless) is defined as one-sided green leaf area per unit ground area in the broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies [23].…”

Section: Iki Modis Ndvi Evi2 Fpar and Lai Productsmentioning

confidence: 99%

“…LAI (dimensionless) is defined as one-sided green leaf area per unit ground area in the broadleaf canopies and as one-half the total needle surface area per unit ground area in coniferous canopies [23]. In this study, we utilize total forest LAI; in other words, we did not separate foliage into overstory and understory [22]. The daily LAI retrieval algorithm is an enhanced version of the NASA MODIS Collection 6 MOD15 algorithm https://lpdaac.usgs.gov/documents/624/MOD1 5_User_Guide_V6.pdf (accessed on 13 November 2023).…”

Section: Iki Modis Ndvi Evi2 Fpar and Lai Productsmentioning

confidence: 99%

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Utility of Leaf Area Index for Monitoring Phenology of Russian Forests

Shabanov,

Egorov,

Miklashevich

et al. 2023

Remote Sensing

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Retrievals of land surface phenology metrics depend on the choice of base variables selected to quantify the seasonal “greenness” profile of vegetation. Commonly used variables are vegetation indices, which curry signal not only from vegetation but also from the background of sparse foliage, they saturate over the dense foliage and are also affected by sensor bandwidth, calibration, and illumination/view geometry, thus introducing bias in the estimation of phenometrics. In this study we have intercompared the utility of LAI and other biophysical variables (FPAR) and radiometric parameters (NDVI and EVI2) for phenometrics retrievals. This study was implemented based on MODIS products at a resolution of 230 m over the entire extent of Russian forests. Free from artifacts of radiometric parameters, LAI exhibits a better utilization of its dynamic range during the course of seasonal variations and better sensitivity to the actual foliage “greenness” changes and its dependence on forest species. LAI-based retrievals feature a more conservative estimate of the duration of the growing season, including late spring (9.3 days) and earlier fall (8.9 days), compared to those retrieved using EVI2. In this study, we have tabulated typical values of the key phenometrics of 12 species in Russian forests. We have also demonstrated the presence of the latitudinal dependence of phenometrics over the extent of Russian forests.

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Section: Iki Modis Ndvi Evi2 Fpar and Lai Productsmentioning

confidence: 99%

Section: Iki Modis Ndvi Evi2 Fpar and Lai Productsmentioning

confidence: 99%