FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W1595743416> ?p ?o ?g. }

• W1595743416 abstract "Great attention has been paid to biomass estimation in recent years because biomass can simply be converted to carbon storage which is very important to understand the carbon cycle in the environment. Biomass is typically defined as the oven-dry mass of the above ground portion of a group of trees in forestry (Brown, 1997, 2002; Bartolot and Wynne, 2005; Momba and Bux, 2010). However there are a few studies about below ground biomass estimation. Conventionally, it is estimated using measurements which are recorded on the ground. On the other hand, the large number of studies have confirmed that Lidar as a kind of active remote sensing system is able to estimate biomass properly (Popescu, 2007). Hence time-consuming field works can be avoided and unavailable regions become accessible using a relatively low cost and automated Lidar system. (Nelson et al., 2004; Drake et al., 2002, 2003; Popescu et al., 2003, 2004). Traditional remote sensing systems detect vegetation cover using active and passive optical imaging sensors (Moorthy et al., 2011). Passive systems depend on the variability in vegetation spectral responses from the visible and near-infrared spectral regions. Widely accepted algorithms such as the Normalized Difference Vegetation Index (NDVI) have been empirically correlated to structural parameters (Jonckheere et al., 2006; Solberg et al., 2009; Morsdorf et al., 2004, 2006) such as Leaf Area Index (LAI) of canopy-level. On the contrary to passive optical imaging sensors, which are only capable of providing detailed measurements of horizontal distributions in vegetation canopies, Lidar systems can produce more accurate data in both the horizontal and vertical dimensions (Lim et al., 2003). Lidarbased instruments from space-borne, airborne, and terrestrial platforms provide a direct means of measuring forest characteristics which were unachievable previously by passive remote sensing imagery. Developments in remote sensing technologies, in particular laser scanning techniques, have led to innovative methods and models in the estimation of forest inventories in terms of efficiency and scales (Hudak et al., 2008; Tomppo et al., 2002; Tomppo and Halme, 2004; Zhao et al., 2009; Koch, 2010; Yu et al., 2011). Lidar experiments and researches within the remote sensing community are now focusing to develop robust methodologies. These methods and models employ very precise 3D point cloud data (Omasa et al., 2007) to direct process and retrieve vegetation structural attributes which are validated by in situ measurements of vegetation biophysical parameters (Maas et al., 2008; Cote et al., 2011). Laser scanning systems have been used to extract various kinds of parameters, such as tree height, crown size, diameter at breast height (dbh), canopy density, crown volume, and tree" @default.
• W1595743416 created "2016-06-24" @default.
• W1595743416 creator A5018237987 @default.
• W1595743416 creator A5035870683 @default.
• W1595743416 date "2011-09-09" @default.
• W1595743416 modified "2023-10-18" @default.
• W1595743416 title "Lidar for Biomass Estimation" @default.
• W1595743416 cites W1241110089 @default.
• W1595743416 cites W1584015278 @default.
• W1595743416 cites W169356037 @default.
• W1595743416 cites W1966946865 @default.
• W1595743416 cites W1969245801 @default.
• W1595743416 cites W1970135336 @default.
• W1595743416 cites W1970313932 @default.
• W1595743416 cites W1970623533 @default.
• W1595743416 cites W1972508359 @default.
• W1595743416 cites W1975937257 @default.
• W1595743416 cites W1979678339 @default.
• W1595743416 cites W1980183272 @default.
• W1595743416 cites W1980316124 @default.
• W1595743416 cites W1980403882 @default.
• W1595743416 cites W1987794512 @default.
• W1595743416 cites W1990077509 @default.
• W1595743416 cites W1990763871 @default.
• W1595743416 cites W1993432662 @default.
• W1595743416 cites W1995869471 @default.
• W1595743416 cites W1995969754 @default.
• W1595743416 cites W1996263757 @default.
• W1595743416 cites W1998779060 @default.
• W1595743416 cites W2000197130 @default.
• W1595743416 cites W2003644107 @default.
• W1595743416 cites W2006750359 @default.
• W1595743416 cites W2008812878 @default.
• W1595743416 cites W2010062112 @default.
• W1595743416 cites W2012824497 @default.
• W1595743416 cites W2017658827 @default.
• W1595743416 cites W2018140562 @default.
• W1595743416 cites W2019126302 @default.
• W1595743416 cites W2023899670 @default.
• W1595743416 cites W2026227145 @default.
• W1595743416 cites W2030359906 @default.
• W1595743416 cites W2032057822 @default.
• W1595743416 cites W2040413668 @default.
• W1595743416 cites W2040943149 @default.
• W1595743416 cites W2042832944 @default.
• W1595743416 cites W2042891401 @default.
• W1595743416 cites W2050966212 @default.
• W1595743416 cites W2053241347 @default.
• W1595743416 cites W2056769281 @default.
• W1595743416 cites W2062883956 @default.
• W1595743416 cites W2067775707 @default.
• W1595743416 cites W2071635229 @default.
• W1595743416 cites W2071997121 @default.
• W1595743416 cites W2076712994 @default.
• W1595743416 cites W2078073057 @default.
• W1595743416 cites W2078925105 @default.
• W1595743416 cites W2080157231 @default.
• W1595743416 cites W2083468770 @default.
• W1595743416 cites W2086128494 @default.
• W1595743416 cites W2093082656 @default.
• W1595743416 cites W2093830434 @default.
• W1595743416 cites W2094434264 @default.
• W1595743416 cites W2094876857 @default.
• W1595743416 cites W2101343198 @default.
• W1595743416 cites W2104845516 @default.
• W1595743416 cites W2106488983 @default.
• W1595743416 cites W2112850050 @default.
• W1595743416 cites W2113488626 @default.
• W1595743416 cites W2113569325 @default.
• W1595743416 cites W2115198311 @default.
• W1595743416 cites W2116674621 @default.
• W1595743416 cites W2122296075 @default.
• W1595743416 cites W2127243393 @default.
• W1595743416 cites W2131578332 @default.
• W1595743416 cites W2132262882 @default.
• W1595743416 cites W2133014538 @default.
• W1595743416 cites W2140175581 @default.
• W1595743416 cites W2146974384 @default.
• W1595743416 cites W2150460756 @default.
• W1595743416 cites W2155698916 @default.
• W1595743416 cites W2155714399 @default.
• W1595743416 cites W2162456434 @default.
• W1595743416 cites W2164124513 @default.
• W1595743416 cites W2168178486 @default.
• W1595743416 cites W2169059815 @default.
• W1595743416 cites W2254707079 @default.
• W1595743416 cites W2273297058 @default.
• W1595743416 cites W2304374093 @default.
• W1595743416 cites W2309077524 @default.
• W1595743416 cites W2340847604 @default.
• W1595743416 cites W2581822959 @default.
• W1595743416 cites W2979676421 @default.
• W1595743416 cites W3027469538 @default.
• W1595743416 cites W359740556 @default.
• W1595743416 cites W48960425 @default.
• W1595743416 cites W600210939 @default.
• W1595743416 doi "https://doi.org/10.5772/16919" @default.
• W1595743416 hasPublicationYear "2011" @default.
• W1595743416 type Work @default.
• W1595743416 sameAs 1595743416 @default.

• next