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Spatially Explicit Large Area Biomass Estimation: Three Approaches Using Forest Inventory and Remotely Sensed Imagery in a GIS
"... Abstract: Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the a ..."
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Abstract: Forest inventory data often provide the required base data to enable the large area mapping of biomass over a range of scales. However, spatially explicit estimates of above-ground biomass (AGB) over large areas may be limited by the spatial extent of the forest inventory relative to the area of interest (i.e., inventories not spatially exhaustive), or by the omission of inventory attributes required for biomass estimation. These spatial and attributional gaps in the forest inventory may result in an underestimation of large area AGB. The continuous nature and synoptic coverage of remotely sensed data have led to their increased application for AGB estimation over large areas, although the use of these data remains challenging in complex forest environments. In this paper, we present an approach to generating spatially explicit estimates of large area AGB by integrating AGB estimates from multiple data sources; 1. using a lookup table of conversion factors applied to a non-spatially exhaustive forest inventory dataset (R 2 = 0.64; RMSE = 16.95 t/ha), 2. applying a lookup table to unique combinations of land cover and vegetation density outputs derived from remotely sensed data (R 2 = 0.52; RMSE = 19.97 t/ha), and 3. hybrid mapping by augmenting forest inventory AGB estimates with remotely sensed AGBSensors 2008, 8 530
Ground-Based Estimation of Leaf Area Index and Vertical Distribution of Leaf Area Density in a Betula ermanii Forest
"... of leaf area index and vertical distribution of leaf area density in a Betula ermanii forest. ..."
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of leaf area index and vertical distribution of leaf area density in a Betula ermanii forest.
Airborne Laser Scanning – a New Challenge for Forest Inventory and Monitoring of Forest Resources
"... Abstract- The use of the newest methods of airborne laser scanning integrated with hyper-spectral satellite systems, provides principally new opportunities for remote sensing of forest cover. High efficiency of laser scanning (up to 100 thousand measurements per second) in combination with sub-meter ..."
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Abstract- The use of the newest methods of airborne laser scanning integrated with hyper-spectral satellite systems, provides principally new opportunities for remote sensing of forest cover. High efficiency of laser scanning (up to 100 thousand measurements per second) in combination with sub-meter spatial resolution, high accuracy of a tree stands ’ structural parameters detection as well as three-dimensional visualization of the remote sensing data allows to developing effective algorithms for research of forest ecosystems ’ dynamics, guaranteeing a real time automatic extraction of forest inventory parameters. Development and application of such high-end forest monitoring methods is critical for boreal zone.
unknown title
, 2015
"... Available online xxxx Keywords: powerful means for assessing changes in forest structure following disturbance over this large forested area. king. Additionally, due the limited access to antifying the structural gh field measurement ect and describe forest ..."
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Available online xxxx Keywords: powerful means for assessing changes in forest structure following disturbance over this large forested area. king. Additionally, due the limited access to antifying the structural gh field measurement ect and describe forest
1 Stability
"... of LiDAR-derived raster canopy attributes with changing pulse repetition frequency ..."
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of LiDAR-derived raster canopy attributes with changing pulse repetition frequency
1 Mean height and variability of height derived from Lidar data and
"... The mean height and standard deviation of the height of the forest canopy, derived from lidar data show to be important variables to summarize forest structure. However lidar data has a limited spatial extent and very high economic cost. Landsat data provide useful structural information in the hori ..."
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The mean height and standard deviation of the height of the forest canopy, derived from lidar data show to be important variables to summarize forest structure. However lidar data has a limited spatial extent and very high economic cost. Landsat data provide useful structural information in the horizontal plane and have easy access. The integration of both data sources is an interesting goal for sustainable forest management. Different spectral indices (NDVI and Tasseled Cap) were obtained from 3 Landsat scenes (March 2000, June 2001 and September 2001). In addition, mean and standard deviation of lidar height werecalculated in 30x30m blocks. Correlation and forward stepwise regression analysis was applied between these two variables sets. Best correlation coefficients are achieved among mean lidar height versus NDVI and wetness for the three dates (range between 0.65 to-0.73). Others authors indicate that wetness is one of the best spectral indices to characterize forest structure. Best regression models include NDVI and wetness of June and September as dependent variables (adjusted r2: 0.55 – 0.62). These results show that lidar data can be useful for training Landsat to map forest structure but it should be interesting to optimize this approach.
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"... Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar ..."
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Investigating laser pulse penetration through a conifer canopy by integrating airborne and terrestrial lidar
