scholarly journals Aboveground Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data

2020 ◽  
Vol 12 (22) ◽  
pp. 3677
Author(s):  
Ho Yan Loh ◽  
Daniel James ◽  
Keiko Ioki ◽  
Wilson Vun Chiong Wong ◽  
Satoshi Tsuyuki ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Montane Forest ◽  
Tropical Montane Forest ◽  
Surface Model ◽  
Managed Forests ◽  
Mean Values ◽  
Tropical Regions ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data

Monitoring anthropogenic disturbances on aboveground biomass (AGB) of tropical montane forests is crucial, but challenging, due to a lack of historical AGB information. We examined the use of spaceborne (Shuttle Radar Topographic Mission Digital Elevation Model (SRTM) digital surface model (DSM)) and airborne (Light Detection and Ranging (LiDAR)) digital elevation data to estimate tropical montane forest AGB changes in northern Borneo between 2000 and 2012. LiDAR canopy height model (CHM) mean values were used to calibrate SRTM CHM in different pixel resolutions (1, 5, 10, and 30 m). Regression analyses between field AGB of 2012 and LiDAR CHM means at different resolutions identified the LiDAR CHM mean at 1 m resolution as the best model (modeling efficiency = 0.798; relative root mean square error = 25.81%). Using the multitemporal AGB maps, the overall mean AGB decrease was estimated at 390.50 Mg/ha, but AGB removal up to 673.30 Mg/ha was estimated in the managed forests due to timber extraction. Over the 12 years, the AGB accumulated at a rate of 10.44 Mg/ha/yr, which was attributed to natural regeneration. The annual rate in the village area was 8.31 Mg/ha/yr, which was almost 20% lower than in the managed forests (10.21 Mg/ha/yr). This study identified forestry land use, especially commercial logging, as the main driver for the AGB changes in the montane forest. As SRTM DSM data are freely available, this approach can be used to estimate baseline historical AGB information for monitoring forest AGB changes in other tropical regions.

Estimating past and future dinosaur skeletal abundances in Dinosaur Provincial Park, Alberta, Canada

2010 ◽  
Vol 47 (10) ◽  
pp. 1291-1304 ◽  
Author(s):  
Donald M. Henderson ◽  
Darren H. Tanke
Keyword(s):  
Land Surface ◽  
Red Deer ◽  
Volume Density ◽  
Mean Values ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Dinosaur Fossil ◽  
Provincial Park ◽  
Exposed Surface Area

Some 353 isolated skulls and partial to complete skeletons with known locations have been collected in ∼100 years from the 80 km2 of badlands in Dinosaur Provincial Park (DPP), Alberta, Canada. We wanted to estimate how many skeletons were lost to erosion before collection began and how many await discovery. Within the boundaries of DPP, a volume of rock 145 m thick between the surface of the down-cutting Red Deer River and the capping prairie was subdivided into 5 m thick slabs using digital elevation data with an average horizontal spatial resolution of 19 m and a vertical resolution of 1 m. The exposed surface area of each slab was calculated. Dinosaur fossil localities were determined with high-precision GPS surveys. The number of dinosaurs collected from the surface of a 5 m slab was divided by the product of the exposed area and an estimated erosional thickness of 80 cm to give a volume density of dinosaur fossils. Multiplying the volumes of rock lost from each layer by the dinosaur densities for each layer, the numbers of skeletons lost was determined. Estimates of the numbers of raisins in two loaves of raisin bread were made using a limited number of slices as a test of the method. Of the original volume of DPP, 6.58 km3 (60%) has eroded away, taking with it a mean number of 6310 hadrosaurs, 1640 ceratopsians, 1030 ankylosaurs, and 1600 theropods. The 5.02 km3 (40%) of rock remaining in the park can be expected to produce more dinosaur fossils of similar quality, with mean values of 6700 hadrosaurs, 1700 ceratopsians, 1010 ankylosaurs, and 1720 theropods. These estimates are minima as the estimation process excluded bone beds, the plethora of isolated bones littering the land surface of DPP, and the 100+ skulls and skeletons from the region that lack locality information.

scholarly journals Integration von hochauflösenden Fernerkundungs- und Geländemodelldaten für die Landschaftsvisualisierung

1997 ◽  
Vol 52 (1) ◽  
pp. 21-26
Author(s):  
P. Pirchl ◽  
P. Hirtz ◽  
M. Suter ◽  
D. Nüesch
Keyword(s):  
Land Cover ◽  
Aerial Photographs ◽  
Surface Model ◽  
Northern Switzerland ◽  
Transition Zones ◽  
Gis Tools ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Elevation Model

Abstract. This paper presents experiments for realistic landscape visualization using high resolution digital aerial photographs and elevation modeis. The natural environment of a river in northern Switzerland is visualized. Photogrammetrically measured digital elevation data and ortho-rectified remote sensing imagery (Landsat Thematic Mapper/TM and aerial photographs) are combined to compute realistic 3D views of the landscape. To renderthe landscape more realistically, the digital elevation model (DEM) is transformed to a digital surface model (DSM), representing the surface and including objects like forests or bushes. For this transformation land cover information and GIS tools were used. Unnaturally looking vertical borders between different land cover classes were suppressed by interpolating transition zones. Additionally, 3D objects (trees) are used in the foreground to increase the realism of the views.

scholarly journals Landslides across the USA: occurrence, susceptibility, and data limitations

Landslides ◽  
2020 ◽  
Vol 17 (10) ◽  
pp. 2271-2285 ◽  
Author(s):  
Benjamin B. Mirus ◽  
Eric S. Jones ◽  
Rex L. Baum ◽  
Jonathan W. Godt ◽  
Stephen Slaughter ◽  
...  
Keyword(s):  
The United States ◽  
National Scale ◽  
Landslide Occurrence ◽  
Process Understanding ◽  
Digital Elevation ◽  
Data Limitations ◽  
Elevation Data ◽  
The Usa ◽  
Digital Elevation Data ◽  
Landslide Mapping

Abstract Detailed information about landslide occurrence is the foundation for advancing process understanding, susceptibility mapping, and risk reduction. Despite the recent revolution in digital elevation data and remote sensing technologies, landslide mapping remains resource intensive. Consequently, a modern, comprehensive map of landslide occurrence across the United States (USA) has not been compiled. As a first step toward this goal, we present a national-scale compilation of existing, publicly available landslide inventories. This geodatabase can be downloaded in its entirety or viewed through an online, searchable map, with parsimonious attributes and direct links to the contributing sources with additional details. The mapped spatial pattern and concentration of landslides are consistent with prior characterization of susceptibility within the conterminous USA, with some notable exceptions on the West Coast. Although the database is evolving and known to be incomplete in many regions, it confirms that landslides do occur across the country, thus highlighting the importance of our national-scale assessment. The map illustrates regions where high-quality mapping has occurred and, in contrast, where additional resources could improve confidence in landslide characterization. For example, borders between states and other jurisdictions are quite apparent, indicating the variation in approaches to data collection by different agencies and disparity between the resources dedicated to landslide characterization. Further investigations are needed to better assess susceptibility and to determine whether regions with high relief and steep topography, but without mapped landslides, require further landslide inventory mapping. Overall, this map provides a new resource for accessing information about known landslides across the USA.

scholarly journals Environmental classification of administrative units of the Ukrainian Carpathians

2014 ◽  
pp. 245-253
Author(s):  
Ivan Kruhlov
Keyword(s):  
Cluster Analysis ◽  
Standard Deviation ◽  
Satellite Images ◽  
Environmental Classification ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Administrative Units ◽  
Elevation Model

Boundaries of 43 administrative units (raions and oblast towns) were digitized and manually rectified using official schemes and satellite images. SRTM digital elevation data were used to calculate mean relative elevation and its standard deviation for each unit, as well as to delineate altitudinal bioclimatic belts and their portions within the units. These parameters were used to classify the units via agglomerative cluster analysis into nine environmental classes. Key words: cluster analysis, digital elevation model, geoecosystem, geo-spatial analysis.

scholarly journals Retrieval of similar topographic areas.

2016 ◽  
Vol 47 (1) ◽  
pp. 275
Author(s):  
E. Kokinou ◽  
C. Panagiotakis ◽  
Th. Kinigopoulos
Keyword(s):  
Image Processing ◽  
High Efficiency ◽  
Automatic Extraction ◽  
Local Minima ◽  
Initial Model ◽  
Area Of Interest ◽  
Digital Elevation ◽  
Elevation Data ◽  
Digital Elevation Data ◽  
Step Number

Image processing and understanding and further pattern recognition comprises a precious tool for the automatic extraction of information using digital topography. The aim of this work is the retrieval of areas with similar topography using digital elevation data. It can be applied to geomorphology, forestry, regional and urban planning, and many other applications for analyzing and managing natural resources. In specifics, the user selects the area of interest, navigating overhead a high resolution elevation image and determines two (3) parameters (step, number of local minima and display scale). Furthermore the regions with similar relief to the initial model are determined. Experimental results show high efficiency of the proposed scheme.

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