FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2029118156> ?p ?o ?g. }

• W2029118156 endingPage "4024" @default.
• W2029118156 startingPage "4014" @default.
• W2029118156 abstract "The objective of this paper is to investigate the sensitivity of reflectance to the variation in biochemical and biophysical variables at leaf, canopy, and regional scales using a modeling approach. The results show that, at the leaf scale, the variations in chlorophyll a+b content, the leaf structure parameter, and the water content dominate the reflectance variance in the visible light (VIS), near infrared (NIR), and short-wave infrared (SWIR) regions, respectively. At the canopy scale, the sensitivity of reflectance to variation in the leaf structure parameter is very slight. For sparse foliage cover (leaf area index ), LAI is the most important variable to the canopy reflectance. As LAI increases, the sensitivity of reflectance to variation in LAI is reduced to a very low value. Moreover, chlorophyll a+b, dry matter, and water content control the variation of canopy reflectance in the VIS, NIR, and SWIR regions, respectively. At the regional scale, the sensitivity of reflectance to variation in vegetation variables is highly influenced by the mixed pixels. Thirty-six vegetation indices (VIs) are chosen in this paper to illustrate the scale dependence of the estimation accuracy of vegetation variables. The results show that the relationships between the VIs and the variables highly depend on the observation scale. For chlorophyll a+b content estimation, transformed chlorophyll absorption in reflectance index (TCARI), Blue Green pigment Index, leaf chlorophyll index (LCI), modified Normalized Difference (mND705), and Plant Biochemical Index at the leaf scale and canopy scale of and TCARI at the canopy scale of are highly related. The correlation between the indices and chlorophyll content in the regional scale is, however, much lower. For water content estimation, disease water stress index (DSWI), leaf water vegetation index 2 (LWVI_2), moisture stress index (MSI), normalized difference infrared index (NDII), normalized difference water index (NDWI), hyperspectral perpendicular vegetation index (RVI), SWIR water stress index (SIWSI), SR water index (SRWI), and water index (WI) are good choices at the leaf scale and canopy scale of , while at the canopy scale of and the regional scale, the correlation between the indices and water content is very low. For LAI estimation, VIs, including the Greenness Index, simple ratio (SR), Normalized Difference VI, modified soil-adjusted vegetation index (MSAVI), modified triangular vegetation index 1 (MTVI1), modified triangular vegetation index 2 (MTVI2), optimized soil-adjusted vegetation index (OSAVI), modified chlorophyll absorption ratio index 1 (MCARI1), modified chlorophyll absorption ratio index 2 (MCARI2), Enhanced VI, LAI Determining Index, renormalized difference vegetation index (RDVI), Spectral Polygon VI, Wide Dynamic Range VI, and triangular vegetation index (TVI), have high correlation with LAI at the canopy scale of while a low correlation at the canopy scale of and the regional scale." @default.
• W2029118156 created "2016-06-24" @default.
• W2029118156 creator A5015096720 @default.
• W2029118156 creator A5045153029 @default.
• W2029118156 creator A5049431983 @default.
• W2029118156 creator A5053782309 @default.
• W2029118156 date "2014-07-01" @default.
• W2029118156 modified "2023-10-17" @default.
• W2029118156 title "Sensitivity Analysis of Vegetation Reflectance to Biochemical and Biophysical Variables at Leaf, Canopy, and Regional Scales" @default.
• W2029118156 cites W188908432 @default.
• W2029118156 cites W1964075913 @default.
• W2029118156 cites W1969010087 @default.
• W2029118156 cites W1977691607 @default.
• W2029118156 cites W1978160572 @default.
• W2029118156 cites W1981695237 @default.
• W2029118156 cites W1981873348 @default.
• W2029118156 cites W1984491304 @default.
• W2029118156 cites W1986786848 @default.
• W2029118156 cites W1993192512 @default.
• W2029118156 cites W1994249905 @default.
• W2029118156 cites W2000102737 @default.
• W2029118156 cites W2002934707 @default.
• W2029118156 cites W2012686349 @default.
• W2029118156 cites W2014897524 @default.
• W2029118156 cites W2014955600 @default.
• W2029118156 cites W2019965926 @default.
• W2029118156 cites W2020052620 @default.
• W2029118156 cites W2022900594 @default.
• W2029118156 cites W2024039740 @default.
• W2029118156 cites W2024700522 @default.
• W2029118156 cites W2025199302 @default.
• W2029118156 cites W2025757188 @default.
• W2029118156 cites W2025967407 @default.
• W2029118156 cites W2030078894 @default.
• W2029118156 cites W2030233869 @default.
• W2029118156 cites W2036003376 @default.
• W2029118156 cites W2049398443 @default.
• W2029118156 cites W2051128904 @default.
• W2029118156 cites W2051563170 @default.
• W2029118156 cites W2055737779 @default.
• W2029118156 cites W2056352756 @default.
• W2029118156 cites W2057106400 @default.
• W2029118156 cites W2059501000 @default.
• W2029118156 cites W2064632414 @default.
• W2029118156 cites W2066612219 @default.
• W2029118156 cites W2066724429 @default.
• W2029118156 cites W2068068744 @default.
• W2029118156 cites W2071471925 @default.
• W2029118156 cites W2077993284 @default.
• W2029118156 cites W2080808068 @default.
• W2029118156 cites W2089441588 @default.
• W2029118156 cites W2100096075 @default.
• W2029118156 cites W2107030334 @default.
• W2029118156 cites W2109030838 @default.
• W2029118156 cites W2109404357 @default.
• W2029118156 cites W2111947859 @default.
• W2029118156 cites W2113410727 @default.
• W2029118156 cites W2115539456 @default.
• W2029118156 cites W2116876595 @default.
• W2029118156 cites W2118791227 @default.
• W2029118156 cites W2130995459 @default.
• W2029118156 cites W2131126673 @default.
• W2029118156 cites W2132299303 @default.
• W2029118156 cites W2135178273 @default.
• W2029118156 cites W2142412570 @default.
• W2029118156 cites W2151868609 @default.
• W2029118156 cites W2153398128 @default.
• W2029118156 cites W2157760685 @default.
• W2029118156 cites W2158036720 @default.
• W2029118156 cites W2161815745 @default.
• W2029118156 cites W2163410149 @default.
• W2029118156 cites W2166665947 @default.
• W2029118156 cites W2167799103 @default.
• W2029118156 cites W2167869331 @default.
• W2029118156 cites W2171063647 @default.
• W2029118156 cites W51106753 @default.
• W2029118156 cites W52417668 @default.
• W2029118156 doi "https://doi.org/10.1109/tgrs.2013.2278838" @default.
• W2029118156 hasPublicationYear "2014" @default.
• W2029118156 type Work @default.
• W2029118156 sameAs 2029118156 @default.
• W2029118156 citedByCount "125" @default.
• W2029118156 countsByYear W20291181562014 @default.
• W2029118156 countsByYear W20291181562015 @default.
• W2029118156 countsByYear W20291181562016 @default.
• W2029118156 countsByYear W20291181562017 @default.
• W2029118156 countsByYear W20291181562018 @default.
• W2029118156 countsByYear W20291181562019 @default.
• W2029118156 countsByYear W20291181562020 @default.
• W2029118156 countsByYear W20291181562021 @default.
• W2029118156 countsByYear W20291181562022 @default.
• W2029118156 countsByYear W20291181562023 @default.
• W2029118156 crossrefType "journal-article" @default.
• W2029118156 hasAuthorship W2029118156A5015096720 @default.
• W2029118156 hasAuthorship W2029118156A5045153029 @default.
• W2029118156 hasAuthorship W2029118156A5049431983 @default.
• W2029118156 hasAuthorship W2029118156A5053782309 @default.
• W2029118156 hasConcept C101000010 @default.

• next