Estimation of Aboveground Biomass Using Manual Stereo Viewing of Digital Aerial Photographs in Tropical  Seasonal Forest

Shimizu, Katsuto; Ota, Tetsuji; Kajisa, Tsuyoshi; Mizoue, Nobuya; Yoshida, Shigejiro; Takao, Gen; Hirata, Yasumasa; Furuya, Naoyuki; Sano, Takio; Sokh, Heng; Ma, Vuthy

doi:10.3390/land3041270

Cited by 3 publications

(4 citation statements)

References 29 publications

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“…In fact, there is limited ground-based analysis on those relationships over tropical regions, but they report probability density functions with shapes similar to the ones shown in Fig. 8c and d. In particular, tropical tree height distributions are characterized by a right-skewed distribution with the peak corresponding to mid-range trees (Kent, Lindsell, Laurin, Valentini, & Coomes, 2015;Shimizu et al, 2014), which is around 10-15 m over the BCI 50ha plot according to the AMS3D (Fig. 8c).…”

Section: Distribution Of Individual Tree Sizementioning

confidence: 89%

Lidar detection of individual tree size in tropical forests

Ferraz

Saatchi

Mallet

et al. 2016

Remote Sensing of Environment

184

151

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Section: Distribution Of Individual Tree Sizementioning

confidence: 89%

Lidar detection of individual tree size in tropical forests

Ferraz

Saatchi

Mallet

et al. 2016

Remote Sensing of Environment

184

151

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“…Stereo Viewer Pro allows the user to perform stereoscopic measurements based on aerial photographs. It is an established method for measuring canopy tree height and forest cover ratio, and the validity of data using this method has been demonstrated in several studies (St-Onge et al 2004;Korpela 2004;Korpela and Tokola 2006;Shimizu et al 2014). In Stereo Viewer Pro, we measured the height of all visible vegetation in each plot (Fig.…”

Section: Remote Sensing Datamentioning

confidence: 99%

The 30-year impact of post-windthrow management on the forest regeneration process in northern Japan

Morimoto

Hotta

et al. 2023

Landscape Ecol Eng

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The frequency and intensity of typhoons are expected to increase over time due to climate change. These changes may expose forests to more windthrow in the future, and increasing the resilience of hemiboreal forests through forest management after windthrow is important. Here, we quantified forest structure recovery using aerial photos and light detection and ranging (LiDAR) data after catastrophic windthrow events. Our aims are to test the following three hypotheses: (1) forest structure will not recover within 30 years after windthrow, (2) forest recovery will be affected not only by salvaging but also pre-windthrow attributes and geographical features, and (3) various post-windthrow management including salvaging will drastically alter tree species composition and delay forest recovery. Our results revealed that hypothesis (1) and (2) were supported and (3) was partially supported. The ordination results suggested that more than 30 years were needed to recover canopy tree height after windthrow in hemiboreal forests in Hokkaido, Japan. Salvage logging did not delay natural succession, but it significantly decreased the cover ratio of conifer species sites (0.107 ± 0.023) compared with natural succession sites (0.310 ± 0.091). The higher the elevation, the steeper the site, and the higher the average canopy height before windthrow, the slower the recovery of forest stands after windthrow and salvaging. Scarification and planting after salvage logging significantly increased the number of canopy trees, but those sites differed completely in species composition from the old growth forests. Our study thus determined that the choice and intensity of post-disturbance management in hemiboreal forests should be carefully considered based on the management purpose and local characteristics.

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“…In addition to optical imagery, airborne Light Detection and Ranging (LiDAR) is another method used for monitoring forest structure dynamics and their impact on species. Although the use of LiDAR has been known to be costly (Hummel, Hudak, Uebler, Falkowski, & Megown, ), LiDAR provides more detailed information on forest structure such as tree heights (Shimizu et al., ). The three‐dimensional vegetation structure has been mapped using LiDAR data and was found to be associated with the presence and persistence of animal species in a given ecosystem (Davies & Asner, ).…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

Singh

Tokola

Hou

et al. 2017

Ecology and Evolution

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Avian species persistence in a forest patch is strongly related to the degree of isolation and size of a forest patch and the vegetation structure within a patch and its matrix are important predictors of bird habitat suitability. A combination of space‐borne optical (Landsat), ALOS‐PALSAR (radar), and airborne Light Detection and Ranging (LiDAR) data was used for assessing variation in forest structure across forest patches that had undergone different levels of forest degradation in a logged forest—agricultural landscape in Southern Laos. The efficacy of different remote sensing (RS) data sources in distinguishing forest patches that had different seizes, configurations, and vegetation structure was examined. These data were found to be sensitive to the varying levels of degradation of the different patch categories. Additionally, the role of local scale forest structure variables (characterized using the different RS data and patch area) and landscape variables (characterized by distance from different forest patches) in influencing habitat preferences of International Union for Conservation of Nature (IUCN) Red listed birds found in the study area was examined. A machine learning algorithm, MaxEnt, was used in conjunction with these data and field collected geographical locations of the avian species to identify the factors influencing habitat preference of the different bird species and their suitable habitats. Results show that distance from different forest patches played a more important role in influencing habitat suitability for the different avian species than local scale factors related to vegetation structure and health. In addition to distance from forest patches, LiDAR‐derived forest structure and Landsat‐derived spectral variables were important determinants of avian habitat preference. The models derived using MaxEnt were used to create an overall habitat suitability map (HSM) which mapped the most suitable habitat patches for sustaining all the avian species. This work also provides insight that retention of forest patches, including degraded and isolated forest patches in addition to large contiguous forest patches, can facilitate bird species retention within tropical agricultural landscapes. It also demonstrates the effective use of RS data in distinguishing between forests that have undergone varying levels of degradation and identifying the habitat preferences of different bird species. Practical conservation management planning endeavors can use such data for both landscape scale monitoring and habitat mapping.

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Estimation of Aboveground Biomass Using Manual Stereo Viewing of Digital Aerial Photographs in Tropical Seasonal Forest

Cited by 3 publications

References 29 publications

Lidar detection of individual tree size in tropical forests

Lidar detection of individual tree size in tropical forests

The 30-year impact of post-windthrow management on the forest regeneration process in northern Japan

Remote sensing‐based landscape indicators for the evaluation of threatened‐bird habitats in a tropical forest

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