The accuracy of large-area forest canopy cover estimation using Landsat in boreal region

Author(s):  
Hadi ◽  
Lauri Korhonen ◽  
Aarne Hovi ◽  
Petri Rönnholm ◽  
Miina Rautiainen
2021 ◽  
Vol 13 (2) ◽  
pp. 257 ◽  
Author(s):  
Shaun R. Levick ◽  
Tim Whiteside ◽  
David A. Loewensteiner ◽  
Mitchel Rudge ◽  
Renee Bartolo

Savanna ecosystems are challenging to map and monitor as their vegetation is highly dynamic in space and time. Understanding the structural diversity and biomass distribution of savanna vegetation requires high-resolution measurements over large areas and at regular time intervals. These requirements cannot currently be met through field-based inventories nor spaceborne satellite remote sensing alone. UAV-based remote sensing offers potential as an intermediate scaling tool, providing acquisition flexibility and cost-effectiveness. Yet despite the increased availability of lightweight LiDAR payloads, the suitability of UAV-based LiDAR for mapping and monitoring savanna 3D vegetation structure is not well established. We mapped a 1 ha savanna plot with terrestrial-, mobile- and UAV-based laser scanning (TLS, MLS, and ULS), in conjunction with a traditional field-based inventory (n = 572 stems > 0.03 m). We treated the TLS dataset as the gold standard against which we evaluated the degree of complementarity and divergence of structural metrics from MLS and ULS. Sensitivity analysis showed that MLS and ULS canopy height models (CHMs) did not differ significantly from TLS-derived models at spatial resolutions greater than 2 m and 4 m respectively. Statistical comparison of the resulting point clouds showed minor over- and under-estimation of woody canopy cover by MLS and ULS, respectively. Individual stem locations and DBH measurements from the field inventory were well replicated by the TLS survey (R2 = 0.89, RMSE = 0.024 m), which estimated above-ground woody biomass to be 7% greater than field-inventory estimates (44.21 Mg ha−1 vs 41.08 Mg ha−1). Stem DBH could not be reliably estimated directly from the MLS or ULS, nor indirectly through allometric scaling with crown attributes (R2 = 0.36, RMSE = 0.075 m). MLS and ULS show strong potential for providing rapid and larger area capture of savanna vegetation structure at resolutions suitable for many ecological investigations; however, our results underscore the necessity of nesting TLS sampling within these surveys to quantify uncertainty. Complementing large area MLS and ULS surveys with TLS sampling will expand our options for the calibration and validation of multiple spaceborne LiDAR, SAR, and optical missions.


Land ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 433
Author(s):  
Xiaolan Huang ◽  
Weicheng Wu ◽  
Tingting Shen ◽  
Lifeng Xie ◽  
Yaozu Qin ◽  
...  

This research was focused on estimation of tree canopy cover (CC) by multiscale remote sensing in south China. The key aim is to establish the relationship between CC and woody NDVI (NDVIW) or to build a CC-NDVIW model taking northeast Jiangxi as an example. Based on field CC measurements, this research used Google Earth as a complementary source to measure CC. In total, 63 sample plots of CC were created, among which 45 were applied for modeling and the remaining 18 were employed for verification. In order to ascertain the ratio R of NDVIW to the satellite observed NDVI, a 20-year time-series MODIS NDVI dataset was utilized for decomposition to obtain the NDVIW component, and then the ratio R was calculated with the equation R = (NDVIW/NDVI) *100%, respectively, for forest (CC >60%), medium woodland (CC = 25–60%) and sparse woodland (CC 1–25%). Landsat TM and OLI images that had been orthorectified by the provider USGS were atmospherically corrected using the COST model and used to derive NDVIL. R was multiplied for the NDVIL image to extract the woody NDVI (NDVIWL) from Landsat data for each of these plots. The 45 plots of CC data were linearly fitted to the NDVIWL, and a model with CC = 103.843 NDVIW + 6.157 (R2 = 0.881) was obtained. This equation was applied to predict CC at the 18 verification plots and a good agreement was found (R2 = 0.897). This validated CC-NDVIW model was further applied to the woody NDVI of forest, medium woodland and sparse woodland derived from Landsat data for regional CC estimation. An independent group of 24 measured plots was utilized for validation of the results, and an accuracy of 83.0% was obtained. Thence, the developed model has high predictivity and is suitable for large-scale estimation of CC using high-resolution data.


Author(s):  
Qingwang Liu ◽  
Shiming Li ◽  
Kailong Hu ◽  
Yong Pang ◽  
Zengyuan Li
Keyword(s):  

Silva Fennica ◽  
2006 ◽  
Vol 40 (4) ◽  
Author(s):  
Lauri Korhonen ◽  
Kari Korhonen ◽  
Miina Rautiainen ◽  
Pauline Stenberg

2020 ◽  
Vol 12 (11) ◽  
pp. 1820
Author(s):  
Raoul Blackman ◽  
Fei Yuan

Urban forests provide ecosystem services; tree canopy cover is the basic quantification of ecosystem services. Ground assessment of the urban forest is limited; with continued refinement, remote sensing can become an essential tool for analyzing the urban forest. This study addresses three research questions that are essential for urban forest management using remote sensing: (1) Can object-based image analysis (OBIA) and non-image classification methods (such as random point-based evaluation) accurately determine urban canopy coverage using high-spatial-resolution aerial images? (2) Is it possible to assess the impact of natural disturbances in addition to other factors (such as urban development) on urban canopy changes in the classification map created by OBIA? (3) How can we use Light Detection and Ranging (LiDAR) data and technology to extract urban canopy metrics accurately and effectively? The urban forest canopy area and location within the City of St Peter, Minnesota (MN) boundary between 1938 and 2019 were defined using both OBIA and random-point-based methods with high-spatial-resolution aerial images. Impacts of natural disasters, such as the 1998 tornado and tree diseases, on the urban canopy cover area, were examined. Finally, LiDAR data was used to determine the height, density, crown area, diameter, and volume of the urban forest canopy. Both OBIA and random-point methods gave accurate results of canopy coverages. The OBIA is relatively more time-consuming and requires specialist knowledge, whereas the random-point-based method only shows the total coverage of the classes without locational information. Canopy change caused by tornado was discernible in the canopy OBIA-based classification maps while the change due to diseases was undetectable. To accurately exact urban canopy metrics besides tree locations, dense LiDAR point cloud data collected at the leaf-on season as well as algorithms or software developed specifically for urban forest analysis using LiDAR data are needed.


2020 ◽  
Vol 58 (1) ◽  
pp. 567-585 ◽  
Author(s):  
Qingwang Liu ◽  
Liyong Fu ◽  
Guangxing Wang ◽  
Shiming Li ◽  
Zengyuan Li ◽  
...  

The Condor ◽  
2003 ◽  
Vol 105 (2) ◽  
pp. 288-302 ◽  
Author(s):  
Lori A. Hennings ◽  
W. Daniel Edge

Abstract In 1999, we surveyed breeding bird and plant communities along 54 streams in the Portland, Oregon, metropolitan region to link bird community metrics with structural and spatial characteristics of urban riparian areas. Canonical correspondence analysis produced two explanatory axes relating to vegetation and road density. Total and non-native bird abundance was higher in narrow forests. Native bird abundance was greater in narrow forests surrounded by undeveloped lands; native species richness and diversity were greater in less-developed areas. Native resident and short-distance-migrant abundance was higher in narrow forests, and diversity was positively associated with developed lands. Neotropical migrant abundance, richness, and diversity were greater in open-canopied areas with fewer roads. We examined spatial relationships by regressing bird variables on satellite-derived forest canopy cover, area of undeveloped lands, and street density in a series of 50-m buffers within a 500-m radius around study sites. Non-native bird abundance decreased with increasing canopy cover within 450 m, but most other relationships were strongest at smaller scales (50–100 m). Our results suggest that increasing urban canopy cover is the most valuable land management action for conserving native breeding birds. A hierarchical scheme for Neotropical migrant conservation might include increasing forest canopy within 450 m of streams to control non-native species and cowbirds; reducing street density within a 100-m radius of streams; and conserving or planting onsite native trees and shrubs. Estructura de Comunidades Riparias de Aves en Portland, Oregon: Hábitat, Urbanización y Patrones de Escala Espacial Resumen. Censamos las comunidades de aves reproductivas y plantas a lo largo de 54 arroyos en el área metropolitana de Portland, Oregon en 1999 para conectar medidas de comunidades de aves con características estructurales y espaciales de zonas riparias urbanas. Análisis de correspondencia canónica produjeron dos ejes explicativos relacionados con la vegetación y la densidad de carreteras. La abundancia total de aves y la de aves no nativas fueron mayores en bosques estrechos. La abundancia de aves nativas fue mayor en bosques estrechos rodeados por terrenos rurales y la riqueza y diversidad de especies fueron mayores en áreas menos desarrolladas. La abundancia de residentes nativas y migratorias de corta distancia fue mayor en bosques estrechos y su diversidad estuvo asociada positivamente con terrenos desarrollados. La abundancia, riqueza y diversidad de las migratorias neotropicales fueron mayores en áreas de dosel abierto y con pocas carreteras. Examinamos las relaciones espaciales mediante regresiones entre variables de aves y la cobertura del dosel derivada de imágenes satelitales, el área de terrenos sin desarrollar y la densidad de calles en una serie de áreas de 50 m de ancho en un radio de 500 m alrededor de los sitios de estudio. La abundancia de aves no nativas disminuyó con aumentos en la cobertura del dosel hasta 450 m, pero la mayoría de las demás relaciones fueron más fuertes a escalas menores (50–100 m). Nuestros resultados sugieren que el incremento de la cobertura del dosel en áreas urbanas es la estrategia de manejo más valiosa para conservar las aves nativas que se reproducen en el área. Un esquema jerárquico para la conservación de las migratorias neotropicales podría incluir aumentar la cobertura de bosque a menos de 450 m de los arroyos para controlar a las especies no nativas y a los Molothrus, reducir la densidad de calles dentro de un radio de 100 m alrededor de los arroyos y conservar o plantar árboles y arbustos nativos.


2019 ◽  
Vol 231 ◽  
pp. 111262 ◽  
Author(s):  
Hao Tang ◽  
John Armston ◽  
Steven Hancock ◽  
Suzanne Marselis ◽  
Scott Goetz ◽  
...  
Keyword(s):  

1985 ◽  
Vol 63 (1) ◽  
pp. 15-20 ◽  
Author(s):  
B. D. Amiro ◽  
J. R. Dugle

A forest site in southeastern Manitoba has been irradiated by a point source of gamma rays continuously since 1973, and measurements have been made yearly to study the change in boreal forest canopy cover along the radiation gradient. After 10 years of chronic irradiation, a zone of total tree death has resulted from mean dose rates between 25 and 62 mGy h−1. Tree canopy cover was reduced at mean dose rates exceeding ~ 4.5 mGy h−1 and the largest reduction occurred in the first 2 years of irradiation. The temporal responses of seven woody species to gamma radiation are presented. Bebb's willow, trembling aspen, speckled alder, and paper birch were less sensitive to radiation than black spruce, balsam fir, and jack pine. The results confirm that gymnosperms are more sensitive to gamma rays than angiosperms.


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