scholarly journals Digital elevation model and satellite images an assessment of soil erosion potential in the Pcinja catchment

2007 ◽  
Vol 87 (2) ◽  
pp. 11-20 ◽  
Author(s):  
Ivica Milevski ◽  
Slavoljub Dragicevic ◽  
Stanimir Kostadinov
Keyword(s):  
Soil Erosion ◽  
Satellite Images ◽  
Outcome Data ◽  
Field Analysis ◽  
Vegetation Coverage ◽  
Anthropogenic Factors ◽  
Soil Composition ◽  
Digital Elevation ◽  
Left Tributary ◽  
Elevation Model

Pcinja is large left tributary of Vardar River (135 km long, 2877,3 km2 catchment?s area), which drainages surface waters from northeastern Macedonia, and small part of southeastern Serbia. Because of suitable physical-geographic factors (geology, terrain morphology, climate, hydrology, vegetation coverage, soil composition, and high human impact), some parts of the catchment?s suffer significant erosion process. For this reason, it is necessary to research properly spatial distribution of erosion, then influence of physical and anthropogenic factors for the intensity of soil erosion, related erosion landforms (with morphology, genesis, evolution, soil erosion protection etc.). Earlier researches in the area have been performed generally with combination of cartographic and classic field analysis. But in last decades, there are new possibilities available like satellite images and digital elevation models. In this work has been presented the methodology of utilization of satellite images and DEM for erosion research, with analysis and comparisons of outcome data.

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 ANALYSIS OF INFLUENCE OF TERRAIN RELIEF ROUGHNESS ON DEM ACCURACY GENERATED FROM LIDAR IN THE CZECH REPUBLIC TERRITORY

2016 ◽  
Vol XLI-B4 ◽  
pp. 25-30 ◽  
Author(s):  
M. Hubacek ◽  
V. Kovarik ◽  
V. Kratochvil
Keyword(s):  
Czech Republic ◽  
Laser Scanning ◽  
Vegetation Coverage ◽  
The Czech Republic ◽  
Digital Elevation ◽  
Lower Accuracy ◽  
Check Points ◽  
Elevation Data ◽  
Dem Accuracy ◽  
Elevation Model

Digital elevation models are today a common part of geographic information systems and derived applications. The way of their creation is varied. It depends on the extent of area, required accuracy, delivery time, financial resources and technologies available. The first model covering the whole territory of the Czech Republic was created already in the early 1980's. Currently, the 5th DEM generation is being finished. Data collection for this model was realized using the airborne laser scanning which allowed creating the DEM of a new generation having the precision up to a decimetre. Model of such a precision expands the possibilities of employing the DEM and it also offers new opportunities for the use of elevation data especially in a domain of modelling the phenomena dependent on highly accurate data. The examples are precise modelling of hydrological phenomena, studying micro-relief objects, modelling the vehicle movement, detecting and describing historical changes of a landscape, designing constructions etc. <br><br> Due to a nature of the technology used for collecting data and generating DEM, it is assumed that the resulting model achieves lower accuracy in areas covered by vegetation and in built-up areas. Therefore the verification of model accuracy was carried out in five selected areas in Moravia. The network of check points was established using a total station in each area. To determine the reference heights of check points, the known geodetic points whose heights were defined using levelling were used. Up to several thousands of points were surveyed in each area. Individual points were selected according to a different configuration of relief, different surface types, and different vegetation coverage. The sets of deviations were obtained by comparing the DEM 5G heights with reference heights which was followed by verification of tested elevation model. Results of the analysis showed that the model reaches generally higher precision than the declared one in majority of areas. This applies in particular to areas covered by vegetation. By contrast, the larger deviations occurred in relation to the slope of the terrain, in particular in the micro-relief objects. The results are presented in this article.

scholarly journals Fusion Analysis of Optical Satellite Images and Digital Elevation Model for Quantifying Volume in Debris Flow Disaster

2019 ◽  
Vol 11 (9) ◽  
pp. 1096 ◽  
Author(s):  
Hiroyuki Miura
Keyword(s):  
Debris Flow ◽  
Digital Elevation Model ◽  
Large Scale ◽  
Satellite Images ◽  
Erosion Depth ◽  
Digital Elevation ◽  
Elevation Model ◽  
Fusion Analysis ◽  
Optical Satellite Images ◽  
Debris Flow Disaster

Rapid identification of affected areas and volumes in a large-scale debris flow disaster is important for early-stage recovery and debris management planning. This study introduces a methodology for fusion analysis of optical satellite images and digital elevation model (DEM) for simplified quantification of volumes in a debris flow event. The LiDAR data, the pre- and post-event Sentinel-2 images and the pre-event DEM in Hiroshima, Japan affected by the debris flow disaster on July 2018 are analyzed in this study. Erosion depth by the debris flows is empirically modeled from the pre- and post-event LiDAR-derived DEMs. Erosion areas are detected from the change detection of the satellite images and the DEM-based debris flow propagation analysis by providing predefined sources. The volumes and their pattern are estimated from the detected erosion areas by multiplying the empirical erosion depth. The result of the volume estimations show good agreement with the LiDAR-derived volumes.

scholarly journals A Probabilistic Assessment of Soil Erosion Susceptibility in a Head Catchment of the Jemma Basin, Ethiopian Highlands

Geosciences ◽  
2020 ◽  
Vol 10 (7) ◽  
pp. 248 ◽  
Author(s):  
Mariaelena Cama ◽  
Calogero Schillaci ◽  
Jan Kropáček ◽  
Volker Hochschild ◽  
Alberto Bosino ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Erosion ◽  
Remote Sensing Data ◽  
Gully Erosion ◽  
Entropy Model ◽  
Global Issues ◽  
Susceptibility Maps ◽  
Digital Elevation ◽  
Elevation Model ◽  
Color Composite

Soil erosion represents one of the most important global issues with serious effects on agriculture and water quality, especially in developing countries, such as Ethiopia, where rapid population growth and climatic changes affect widely mountainous areas. The Meskay catchment is a head catchment of the Jemma Basin draining into the Blue Nile (Central Ethiopia) and is characterized by high relief energy. Thus, it is exposed to high degradation dynamics, especially in the lower parts of the catchment. In this study, we aim at the geomorphological assessment of soil erosion susceptibilities. First, a geomorphological map was generated based on remote sensing observations. In particular, we mapped three categories of landforms related to (i) sheet erosion, (ii) gully erosion, and (iii) badlands using a high-resolution digital elevation model (DEM). The map was validated by a detailed field survey. Subsequently, we used the three categories as dependent variables in a probabilistic modelling approach to derive the spatial distribution of the specific process susceptibilities. In this study we applied the maximum entropy model (MaxEnt). The independent variables were derived from a set of spatial attributes describing the lithology, terrain, and land cover based on remote sensing data and DEMs. As a result, we produced three separate susceptibility maps for sheet and gully erosion as well as badlands. The resulting susceptibility maps showed good to excellent prediction performance. Moreover, to explore the mutual overlap of the three susceptibility maps, we generated a combined map as a color composite where each color represents one component of water erosion. The latter map yields useful information for land-use managers and planning purposes.

scholarly journals New discoveries on astronomical orientation of Inca site in Ollantaytambo, Peru

2015 ◽  
Vol 14 (2) ◽  
pp. 37-46
Author(s):  
Karolína Hanzalová ◽  
Jaroslav Klokočník ◽  
Jan Kostelecký
Keyword(s):  
Digital Elevation Model ◽  
Satellite Images ◽  
Observation Point ◽  
Google Earth ◽  
The Sun ◽  
Winter Solstice ◽  
Machu Picchu ◽  
Digital Elevation ◽  
Elevation Model ◽  
The Temple

<p>This paper deals with astronomical orientation of Incas objects in Ollantaytambo, which is located about 35 km southeast from Machu Picchu, about 40 km northwest from Cusco, and lies in the Urubamba valley. Everybody writing about Ollantaytambo, shoud read Protzen. (1)  He devoted his monograph to description and interpretation of that locality. Book of Salazar and Salazar (2) deals, among others, with the orientation of objects in Ollantaytambo with respect to the cardinal direction. Zawaski and Malville (3) documented astronomical context of major monuments of nine sites in Peru, including Ollantaytambo. We tested astronomical orientation in these places and confirm or disprove hypothesis about purpose of Incas objects. For assessment orientation of objects we used our measurements and also satellite images on Google Earth and digital elevation model from ASTER. The satellite images were used to estimate the astronomical-solar-solstice orientation, together with terrestrial images from Salazar and Salazar (2). The digital elevation model is useful in the mountains, where we need the actual horizon for a calculation of sunset and sunrise on specific days (solstices), which were for Incas people very important. We tested which astronomical phenomenon is connected with objects in Ollantaytambo. First, we focused on Temple of the Sun, also known the Wall of six monoliths.  We tested winter solstice sunrise and the rides of the Pleiades for the epochs 2000, 1500 and 1000 A.D. According with our results the Temple isn´t connected neither with winter solstice sunrise nor with the Pleiades. Then we tested also winter solstice sunset. We tried to use the line from an observation point near ruins of the Temple of Sun, to west-north, in direction to sunset. The astronomical azimuth from this point was about 5° less then we need. From this results we found, that is possible to find another observation point. By Salazar and Salazar (2) we found observation point at the corner (east rectangle) of the pyramid by <em>Pacaritanpu,</em> down by the riverside. There is a line connecting the east rectangular “platform” at the river, going along the Inca road up to vicinity of the Temple of the Sun and then in the direction to the Inca face. Using a digital elevation model we found the astronomical azimuth, which is needed for confirm astronomical orientation of the Temple. So, finally we are able to demonstrate a possibility of the solar-solstice orientation in Ollantaytambo.</p>

The Coupling Relationship between Forest Vegetation and Terrain of Daliuta Mine

2014 ◽  
Vol 641-642 ◽  
pp. 1191-1194 ◽  
Author(s):  
Dong Wen Liu ◽  
Zhi Yong Qiao ◽  
Ting Ting Wei ◽  
Shu Jiang ◽  
Ya Kai Chen ◽  
...  
Keyword(s):  
Digital Terrain Model ◽  
Vegetation Coverage ◽  
Terrain Model ◽  
Digital Terrain ◽  
Digital Elevation ◽  
Object Use ◽  
Trend Data ◽  
Elevation Model ◽  
Digital Elevation Model Data ◽  
Evolution Trend

Taking Daliuta mine as research object, use its 2002, 2011 two same period Landsat TM/ ETM and remote sensing image as the data source, use pixel dichotomy to get its vegetation coverage evolution trend data; Use DEM digital elevation model data in the region to generate digital terrain model based on ArcGIS, and make overlay analysis with the vegetation coverage evolution trend data to study the relationship between the vegetation coverage and terrain factor of the mine area. The results showed that: From 2002 to 2011, the vegetation coverage evolution trend of Daliuta mining mainly moderate improvement and significantly improvement, and concentrated in middle altitude, low slope, sunny area.

Soil Erosion Research Based on RS and USLE in Great Khinggan

2013 ◽  
Vol 864-867 ◽  
pp. 2799-2803
Author(s):  
Wei Li ◽  
Wen Yi Fan ◽  
Xue Gang Mao ◽  
Lin Zhao
Keyword(s):  
Soil Erosion ◽  
Water Conservation ◽  
Grid Cell ◽  
Strength Distribution ◽  
Space Distribution ◽  
Digital Elevation ◽  
Erosion Area ◽  
Elevation Model ◽  
Volume Estimates ◽  
Cell Data

Uses 2011 years TM/ETM images classification were land uses/cover type figure, combination Great Khinggan area digital elevation model (DEM), and soil type distribution figure and research regional rainfall information, we got all factors values of space distribution in the USLE model, got soil erosion volume estimates data and soil erosion strength distribution figure based on grid cell data. Result indicate that the micro-absolute percentage of erosion throughout the study area, with increasing slope, area of erosion and erosion gradually reduce trend increases with the elevation increases, reduced erosion area after, generally good soil and water conservation in the region.

scholarly journals Monitoring Deformasi Gunung Merapi Menggunakan Citra Sentinel-1A Dengan Menggunakan Metode DInSAR (Studi Kasus: Gunung Merapi, Jawa Tengah)

2020 ◽  
Vol 4 (1) ◽  
pp. 14-23
Author(s):  
Rian Nurtyawan ◽  
Lady Suci Utami
Keyword(s):  
Digital Elevation Model ◽  
Volcanic Activity ◽  
Satellite Images ◽  
Disaster Mitigation ◽  
Deformation Method ◽  
Differential Interferometry ◽  
Digital Elevation ◽  
Image Pairs ◽  
Elevation Model ◽  
Deformation Map

ABSTRAKIndonesia mempunyai 127 gunung api aktif yang tersebar dari Sabang sampai Merauke. Oleh karena itu, perlu adanya pemantauan aktivitas gunung api yang dapat digunakan untuk acuan mitigasi bencana. Pada penelitian ini menggunakan metode deformasi, metode deformasi merupakan perubahan bentuk, posisi, dan dimensi dari suatu benda. Tujuan dari pemantauan deformasi ini untuk mengetahui perubahan gunung api yang disebabkan oleh aktivitas gunung api. Pemantauan aktivitas gunung api metode deformasi dilakukan dengan menggunakan citra Sentinel-1A yang diolah dengan teknologi Differential Interferometry SAR (DInSAR). Dalam penelitian ini dilakukan pengolahan dengan teknologi DInSAR metode two-pass dari empat buah citra satelit sentinel-1A 10 Januari 2018, 27 Februari 2018, 10 Mei 2018 dan 22 Januari 2019 serta data Digital Elevation Model (DEM) SRTM dengan ketelitian 30 meter .Hasil dari penelitian ini yaitu peta deformasi pra 1 erupsi yang diolah dari pasangan citra 10 Januari 2018 dengan citra 27 Februari 2018 yang menghasilkan deflasi sebesar -0,12 meter, dan peta deformasi pra 2 erupsi yang diolah dari pasangan citra 27 Februari 2018 dan 10 Mei 2018 menghasilkan deflasi sebesar -0,27 meter serta peta pasca erupsi yang diolah dari pasangan citra 10 Mei 3018 dan 22 Januari 2019 menghasilkan deflasi sebesar -0,194 meter.Kata kunci: Deformasi, Gunung Merapi, Sentinel-1A, DInSAR. ABSTRACT Indonesia has 127 active volcanoes spread over from Sabang to Merauke. Therefore, it is necessary to monitor volcanic activity that can be used as a reference for disaster mitigation. In this study, deformation method was used to reflect a change in the shape, position, and dimensions of an object. The purpose of monitoring this deformation is to find out volcanic changes caused by volcanic activity. Monitoring the volcanic activity of the deformation method is carried out using Sentinel-1A images processed with Differential Interferometry SAR (DInSAR) technology. In this research, two-pass method of DInSAR technology was processed using four sentinel-1A satellite images on January 10, 2018, February 27, 2018, May 10, 2018 and January 22, 2019 and SRTM Digital Elevation Model (DEM) data with 30 meters accuracy. This research processed pre-eruption deformation map from the 10 January 2018 imagery pair with the 27 February 2018 image which resulted in a deflation of 0.12 meters. Pre- eruption 2 deformation map was processed from the 27 February 2018 and 10 May 2018 image pairs and resulted in a deflation of 0.27 meters while post-eruption map processed from the 10 May 3018 and 22 January 2019 image pairs resulted in deflation of 0.194 meters.Keywords: Deformation, Merapi Mountain, Sentinel-1A, DinSAR.

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