Evaluation for Damaged Degree of Vegetation by Forest Fire Using LiDAR and Digital Aerial Photograph

The amount of vegetation physically damaged by forest fire can be evaluated using lidar (Light Detection And Ranging) data because the loss of canopy height and width by forest fire can be relevant to the number of points transmitted to the ground through the canopy of the damaged forest. On the other hand, the biological damage of vegetation caused by forest fire can be obtained from the Normalized Difference Vegetation Index (NDVI), which determines the vegetation vitality. In this study, the degree of physical damage from the lidar data was classified into serious physical damage (SPD) and light physical damage (LPD). The degree of biological damage using NDVI was likewise classified into serious biological damage (SBD) and light biological damage (LBD). Finally, the damaged area was graded into four categories: (a) SPD and SBD, (b) LPD and SBD, (c) SPD and LBD, and (d) LPD and LBD. The accuracy assessment for the area classified into four grades showed an overall accuracy of 0.74, and a kappa value of 0.61 which provides improvement over previous works

Application of the Savitzky-Golay Filter to Land Cover Classification Using Temporal MODIS Vegetation Indices

In this study, the Savitzky-Golay filter was applied to smooth observed unnatural variations in the temporal profiles of the Normalized Difference Vegetation Index (NDVI} and the Enhanced Vegetation Index {EVI} time series from the MODerate Resolution Imaging Spectroradiometer (MODIS}. We computed two sets of land cover classifications based 011 the NDVI and EVI time series before and after applying the Savitzky-Golay filter. The resulting classification from the filtered versions of the vegetation indices showed a substantial improvement in accuracy when compared to the classifications from the unfiltered versions. The classification by the EVIsg had the highest K (0.72} for all classes compared to those of the EVI (0.67}, NDVI (0.63}, and NDV/sg (0.62). Therefore, we conclude that the EVIsg is best suited for land cover classification compared to the other data sets in this study

Forest Cover Classification by Optimal Segmentation of High Resolution Satellite Imagery

This study investigated whether high-resolution satellite imagery is suitable for preparing a detailed digital forest cover map that discriminates forest cover at the tree species level. First, we tried to find an optimal process for segmenting the high-resolution images using a region-growing method with the scale, color and shape factors in Definiens® Professional 5.0. The image was classified by a traditional, pixel-based, maximum likelihood classification approach using the spectral information of the pixels. The pixels in each segment were reclassified using a segment-based classification (SBC) with a majority rule. Segmentation with strongly weighted color was less sensitive to the scale parameter and led to optimal forest cover segmentation and classification. The pixel-based classification (PBC) suffered from the “salt-and-pepper effect” and performed poorly in the classification of forest cover types, whereas the SBC helped to attenuate the effect and notably improved the classification accuracy. As a whole, SBC proved to be more suitable for classifying and delineating forest cover using high-resolution satellite images

Estimating Crown Variables of Individual Trees Using Airborne and Terrestrial Laser Scanners

In this study, individual tree height (TH), crown base height (CBH), crown area (CA) and crown volume (CV), which were considered as essential parameters for individual stem volume and biomass estimation, were estimated by both an airborne laser scanner (ALS) and a terrestrial laser scanner (TLS). These ALS- and TLS-derived tree parameters were compared because TLS has been introduced as an instrument to measure objects more precisely. ALS-estimated TH was extracted from the highest value within a crown boundary delineated with the crown height model (CHM). The ALS-derived CBH of individual trees was estimated by k-means clustering method using the ALS data within the boundary. The ALS-derived CA was calculated simply with the crown boundary, after which CV was computed automatically using the crown geometric volume (CGV). On the other hand, all TLS-derived parameters were detected manually and precisely except the TLS-derived CGV. As a result, the ALS-extracted TH, CA, and CGV values were underestimated whereas CBH was overestimated when compared with the TLS-derived parameters. The coefficients of determination (R2) from the regression analysis between the ALS and TLS estimations were approximately 0.94, 0.75, 0.69 and 0.58, and root mean square errors (RMSEs) were approximately 0.0184 m, 0.4929 m, 2.3216 m2 and 13.2087 m3 for TH, CBH, CA and CGV, respectively. Thereby, the error rate decreased to 0.0089, 0.0727 and 0.0875 for TH, CA and CGV via the combination of ALS and TLS data

Development of plasma sources and diagnostics for the simulation of fusion edge plasmas

© 2022, The Korean Physical Society.Although the research on divertors and scrape-off layers (SOLs) has been not as focused on as the recent success of the Korean fusion program, a few linear plasma devices have been developed for simulating divertor and SOL plasmas: (1) diversified plasma simulator (DiPS), a versatile linear machine, has been developed for simulations of divertor and space plasmas with various electric probes, such as single, triple, and Mach Probes and gridded energy analyzer. DiPS consists of two major parts: a divertor plasma simulator with a LaB 6 DC plasma source and a space plasma simulator with a helicon RF plasma source, (2) divertor plasma simulator-1 (DiPS-1) is a part of DiPS with only a LaB 6 cathode, where a low-power laser-induced fluorescence (LIF) is added and more electric probe diagnostics are augmented; it is dedicated only for fusion edge and divertor plasmas, (3) Divertor Plasma Simulator-2 (DiPS-2) has been modified from the DiPS-1 by adding a magnetic nozzle with a limiter structure and by removing the helicon source and space chamber. DiPS-2 is a linear plasma device with a 4-inch LaB 6 cathode, the same as DiPS-1, and it is focused on the development of various diagnostics, such as those used for LIF and laser Thomson scattering (LTS) along with various electric probes, on the divertor and scrape-off plasmas and on the plasma-material interaction (PMI) research, such as that of tungsten and graphite as plasma-facing components (PFCs), (4) A Multi-Purpose Plasma (MP 2) device is a renovation of the Hanbit mirror device [Kwon et al., Nucl. Fusion 43, 686 (2003)] with the installation of two plasma sources: LaB 6 (DC) and helicon (RF) plasma sources. A honeycomb-like large-area LaB 6 (HLA-LaB 6) cathode has been developed for the divertor plasma simulation to improve the resistance against the thermal shock fragility for large (8-inch) and high density plasma generation, (5) DiPS-2 has been augmented by adding another cylindrical device, called the Dust interaction with Surfaces Chamber (DiSC) for the generation and diagnostics of dusts. This combined system (DiPS-2+DiSC) has added two more diagnostics: Laser Photo-Detachment (LPD) for dust density and laser Mie Scattering (LMS) for dust size. Moreover, dusts or negative ions have been analyzed by using electric probes and capacitive diagram gauges in Transport and Removal of Dusts (TReD) device.N