scholarly journals Result of study on developing forest seed region in Mongolia

2019 ◽  
pp. 18-31
Author(s):  
Jamyansuren S ◽  
Udval B ◽  
Batkhuu N ◽  
Bat-Erdene J ◽  
Michael Fischer
Keyword(s):  
Genetic Selection ◽  
Siberian Larch ◽  
Distribution Area ◽  
Seed Region ◽  
Siberian Spruce ◽  
Seed Supply ◽  
Foreign Countries ◽  
Digital Elevation ◽  
Sparse Population ◽  
Elevation Model

In foreign countries, motor roads and railroads are usually used as borders of forest seed regions. In the case of Mongolia, this method is not suitable in view of the sparse population, large distribution area of forests and the huge territory of the country. Therefore, this study used topographical features to determine the borders of the seed regions. Satellite images in combination with Digital Elevation Model (DEM) make it possible to define rivers, streams and mountain ridges as the borders of forest seed regions. Overall, we identified 19 seed regions for Siberian larch and 12 regions for Scots pine, 9 regions for Siberian pine, 6 regions for Siberian fir and 9 seed regions for Siberian spruce forests. Due to a lack of genetic-selection studies in Mongolia, these proposed forest seed regions can be considered as a preliminary effort with an opportunity to be updated and improved based on more detailed research results. The forest seed regions and maps will play important role as fundamental material for establishing a permanent forest seed supply based on genetic-selection characteristics of the forests in different regions in Mongolia.

scholarly journals Result of study on developing forest seed region in Mongolia

2018 ◽  
pp. 5-14
Author(s):  
Jamyansuren S ◽  
Udval B ◽  
Batkhuu N ◽  
Bat-Erdene J ◽  
Michael Fischer
Keyword(s):  
Genetic Selection ◽  
Siberian Larch ◽  
The Other ◽  
Distribution Area ◽  
Seed Region ◽  
Pinus Sibirica ◽  
Scotch Pine ◽  
Siberian Fir ◽  
Siberian Spruce ◽  
Siberian Pine

In other countries, they usually use auto road and railroad as borders of the forest seed regions. In case of Mongolia, this method is not suitable since sparse population, large distribution area of forests and large territory. Therefore, we used topographical features to determine borders of the seed regions. Satellite images in combination with DEM make it possible to define rivers, streams and mountain ridges as border of forest seed regions. Species included in forest seed regions are: Siberian larch (Larix sibirica Ldb.), Dahurian larch (Larix dahurica Turcz), Chekanovskii larch (Larix chekanowski Szaf.), Scotch pine (Pinus sylvestris L.), Siberian pine (Pinus sibirica Du Tour.), Siberian spruce (Picea obovate Ldb.), and Siberian fir (Abies sibirica Ldb.).Mongolian forests are mountain forests with high altitudinal variation and have dry growth condition hence, seed quality of the main tree species is declining recently. It is required to use seeds from the same seed region. Only if this is not possible the seeds should be obtained from regions with comparable ecological conditions.Local seed is the ones collected from the forests within the border of same seed region, and seed from the other regions are the ones collected from the other seed region. Seeds collected from the plain forests can be used for almost all forest regions, however seeds collected from mountainous regions can only be used within 200-400 m limit of the original altitude.We identified 19 seed regions for Siberian larch and 12 regions for Scots pine, 9 regions for Siberian pine, 6 regions for Siberian fir and 9 seed regions for Siberian spruce forests, respectively. Due to lack of genetic-selection study in Mongolia, this proposed forest seed regions can be considered as preliminary effort and it is possible to changed and improved based on more detailed research results. These forest seed regions proposed by project team can be used as fundamental material for establishing permanent forest seed supply based on genetic-selection characteristics of the forests in different regions in Mongolia.

STUDY OF THE LANDSLIDE MORPHOLOGY BASED ON GNSS DATA AND AIRBORNE SOUNDING (ON THE EXAMPLE OF A SECTION OF THE PROTVA RIVER VALLEY)

2018 ◽  
Vol 12 (5-6) ◽  
pp. 50-57 ◽  
Author(s):  
I. S. Voskresensky ◽  
A. A. Suchilin ◽  
L. A. Ushakova ◽  
V. M. Shaforostov ◽  
A. L. Entin ◽  
...  
Keyword(s):  
Digital Elevation Model ◽  
Geodetic Network ◽  
Aerial Survey ◽  
River Valley ◽  
Ease Of Use ◽  
Digital Elevation ◽  
Loose Deposits ◽  
Positioning Method ◽  
Landslide Body ◽  
Elevation Model

To use unmanned aerial vehicles (UAVs) for obtaining digital elevation models (DEM) and digital terrain models (DTM) is currently actively practiced in scientific and practical purposes. This technology has many advantages: efficiency, ease of use, and the possibility of application on relatively small area. This allows us to perform qualitative and quantitative studies of the progress of dangerous relief-forming processes and to assess their consequences quickly. In this paper, we describe the process of obtaining a digital elevation model (DEM) of the relief of the slope located on the bank of the Protva River (Satino training site of the Faculty of Geography, Lomonosov Moscow State University). To obtain the digital elevation model, we created a temporary geodetic network. The coordinates of the points were measured by the satellite positioning method using a highprecision mobile complex. The aerial survey was carried out using an unmanned aerial vehicle from a low altitude (about 40–45 m). The processing of survey materials was performed via automatic photogrammetry (Structure-from-Motion method), and the digital elevation model of the landslide surface on the Protva River valley section was created. Remote sensing was supplemented by studying archival materials of aerial photography, as well as field survey conducted immediately after the landslide. The total amount of research results made it possible to establish the causes and character of the landslide process on the study site. According to the geomorphological conditions of formation, the landslide refers to a variety of landslideslides, which are formed when water is saturated with loose deposits. The landslide body was formed with the "collapse" of the blocks of turf and deluvial loams and their "destruction" as they shifted and accumulated at the foot of the slope.

Urban Flood Mapping

2017 ◽  
Author(s):  
Indra Riyanto ◽  
Lestari Margatama
Keyword(s):  
Natural Disasters ◽  
Satisfying Condition ◽  
Three Dimensions ◽  
Urban Flood ◽  
Digital Elevation ◽  
Elevation Data ◽  
Recent Occurrence ◽  
Elevation Model ◽  
Digital Elevation Model Data ◽  
Potential Area

The recent degradation of environment quality becomes the prime cause of the recent occurrence of natural disasters. It also contributes in the increase of the area that is prone to natural disasters. Flood history data in Jakarta shows that flood occurred mainly during rainy season around January – February each year, but the flood area varies each year. This research is intended to map the flood potential area in DKI Jakarta by segmenting the Digital Elevation Model data. The data used in this research is contour data obtained from DPP–DKI with the resolution of 1 m. The data processing involved in this research is extracting the surface elevation data from the DEM, overlaying the river map of Jakarta with the elevation data. Subsequently, the data is then segmented using watershed segmentation method. The concept of watersheds is based on visualizing an image in three dimensions: two spatial coordinates versus gray levels, in which there are two specific points; that are points belonging to a regional minimum and points at which a drop of water, if placed at the location of any of those points, would fall with certainty to a single minimum. For a particular regional minimum, the set of points satisfying the latter condition is called the catchments basin or watershed of that minimum, while the points satisfying condition form more than one minima are termed divide lines or watershed lines. The objective of this segmentation is to find the watershed lines of the DEM image. The expected result of the research is the flood potential area information, especially along the Ciliwung river in DKI Jakarta.

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