scholarly journals USING SPATIAL DATA TO SIMULATE RAIN RUNOFF

2021 ◽  
Vol 4 (1) ◽  
pp. 167-176
Author(s):  
Olga V. Lovtskaya ◽  
Alexey V. Kudishin ◽  
Anastasiya B. Golubeva
Keyword(s):  
Grain Size ◽  
River Basin ◽  
Soil Texture ◽  
Spatial Data ◽  
Size Composition ◽  
Weather Station ◽  
Data Preparation ◽  
Morphometric Characteristics ◽  
Data Set ◽  
Soil Database

The paper presents the main stages of spatial data preparation for computer models of runoff formation by the example of the Charysh River basin. DEM was employed to construct a system of sub-basins and a hydrological graph as well as to calculate morphometric characteristics of its elements. Sources of data on vegetation and mechanical composition of soils are given Using the Harmonized World Soil Database and the soil map of Altai Krai, a map of soil texture (grain-size composition) of the Charysh River basin was created. Two ways of precipitation accounting (the weather station data; the Persiann-CDR data set) were compared. Calculations of runoff from the the Charysh catchment were made for two models.

scholarly journals Geoarchaeology of the early medieval stronghold surroundings in grzybowo near Września, Greater Poland

2019 ◽  
Vol 38 (3) ◽  
pp. 95-108
Author(s):  
Michał Marcinkowski ◽  
Małgorzata Szczepaniak
Keyword(s):  
Grain Size ◽  
Organic Matter ◽  
Calcium Carbonate ◽  
Size Composition ◽  
Flood Plain ◽  
River Channel ◽  
Archival Data ◽  
Data Set ◽  
Holocene Sediments ◽  
Radiocarbon Data

Abstract The stronghold in Grzybowo (Rabieżyce village) near Września is a remnant of medieval ring-fort. It is investigated to a considerably lower degree than similar objects from Greater Poland. The analysis of archival data shows that the stronghold is located on the edge of the flood plain of the Struga River formed by Holocene sediments, cutting into the moraine plateau. Analysis of sediments in the stronghold vicinity revealed interlayers of organic matter and sandy deposits rich in calcium carbonate with variable grain size composition, particularly west of the stronghold (i.e. in the valley floor). Moreover, radiocarbon data set showed a considerably older than Holocene age of the sediment. The analysis of the course of the contemporary river channel also allowed for stating hypotheses regarding a potentially different course of the former Struga River channel and its changes during the development of the stronghold. These assumptions were based on the analysis of the archaeological archival data, where field drawings suggest the existence of such a channel in the territory of the stronghold.

Grain size composition of broken rocks under different conditions of blasting

2019 ◽  
Vol 8 ◽  
pp. 83-94 ◽  
Author(s):  
B.R. Rakishev ◽  
◽  
A.A. Orynbay ◽  
A.M. Auezova ◽  
A.E. Kuttybaev ◽  
...  
Keyword(s):  
Grain Size ◽  
Size Composition ◽  
Grain Size Composition

ANALYSIS OF THE MODERN GRAIN-SIZE COMPOSITION VARIABILITY OF THE ANAPA BAY-BAR BEACH SEDIMENTS

2018 ◽  
Author(s):  
В. Крыленко ◽  
V. Krylenko ◽  
Р. Косьян ◽  
R. Kos'yan ◽  
М. Крыленко ◽  
...  
Keyword(s):  
Grain Size ◽  
Bottom Sediments ◽  
Size Structure ◽  
Size Composition ◽  
Potential Danger ◽  
Grain Size Composition ◽  
Beach Sediments ◽  
Sediment Particles ◽  
Sand Material

The results of realized in 2010 field researches of the spatial and time grain-size structure variability of beach and bottom sediments of the bay-bar Anapskaya southern part are presented in this paper. Irretrievable carrying out of sediment particles to depths more than 7 m intensifies with their size decrease to 0,1 mm. As over 70 % bottom and about 60 % beach sediments are presented by fractions less 0,16 mm on bay-bar Anapskaya southern part, namely at this part there is sand material massive carrying out to depth. Potential danger of the investigated site geosystem degradation is revealed.

scholarly journals THE CULTURAL HERITAGE SPATIAL DATA SET OF KLAIPĖDA OLD TOWN / SAUGOMŲ KLAIPĖDOS SENAMIESČIO OBJEKTŲ ERDVINIŲ DUOMENŲ RINKINYS / НАБОР ПРОСТРАНСТВЕННЫХ ДАННЫХ ОХРАНЯЕМЫХ ОБЪЕКТОВ СТАРОГО ГОРОДА КЛАЙПЕДЫ

2012 ◽  
Vol 37 (4) ◽  
pp. 172-176
Author(s):  
Lina Kuklienė ◽  
Dainora Jankauskienė ◽  
Indrius Kuklys
Keyword(s):  
Cultural Heritage ◽  
Spatial Data ◽  
Road Construction ◽  
Heritage Management ◽  
Data Set ◽  
Management Planning ◽  
Cultural Heritage Management ◽  
Input Devices ◽  
Relevant Point ◽  
Cultural Heritage Objects

The purpose of the thesis is to analyze the main geodetic databases of Lithuania and to create a geodetic database of cultural heritage objects in Klaipėda using program ArcGIS 9.3. The problem is that the geodetic database storing graphical and attributive information about cultural heritage in Klaipeda city has not been created yet. Thus, in order to incorporate GIS technologies into the management of cultural heritage, starting the creation of such a database seems to be a relevant point. The fully completed and regularly updated geodetic database can be used for cultural heritage management, planning, design, road construction, etc. Therefore, the following objectives have been set: 1) describing geo-data collection and input devices; 2) stimulating the geodetic database that introduces information about buildings, building complexes, cemeteries, locations of archaeological and cultural heritage; 3) giving a detailed description of the database creation process; 4) analyzing the need for establishing a geodetic database of cultural heritage objects in Klaipėda. Santrauka Lietuvoje GIS pagrindu sukurta daug įvairiems tikslams skirtų georeferencinių bei teminių erdvinių duomenų rinkinių. Viena iš šių rinkinių panaudojimo sričių – valstybės registruose esančių duomenų kaupimas. Tokiu principu yra sukurta Kultūros vertybių registro duomenų bazė, kurios pagrindiniai duomenys buvo panaudoti kuriant Klaipėdos miesto kultūros paveldo objektų erdvinių duomenų rinkinį. Siekiant kuo operatyviau įtraukti GIS technologijas į kultūros paveldo objektų tvarkybą, aktualu Klaipėdoje pradėti kurti kultūros paveldo objektų erdvinių duomenų rinkinį. Nuolat atnaujinamas erdvinių duomenų rinkinys palengvins įvairių sričių specialistų atliekamus kultūros paveldo objektų administravimo, teritorijų planavimo, projektavimo, kelių tiesimo ir kitus darbus. Резюме В Литве на основе ГИС для различных целей создано множество гео-ссылок, а также тематических наборов пространственных данных. Область использования одного из множеств – сбор данных, имеющихся в государственном учете. По такому принципу создана регистрационная база культурных ценностей, основные данные которой были использованы при создании набора пространственных данных объектов культурного наследия города Клайпеды. С целью оперативно обеспечить управление объектами культурного наследия технологиями ГИС следует начать создание набора пространственных данных объектов культурного наследия в Клайпеде. Полностью заполненный и постоянно обновляемый набор пространственных данных облегчит работу специалистов в различных областях: администрировании объектов культурного наследия, планировании территорий, проектировании, строительстве дорог и других.

scholarly journals Leveraging Road Characteristics and Contributor Behaviour for Assessing Road Type Quality in OSM

2021 ◽  
Vol 10 (7) ◽  
pp. 436
Author(s):  
Amerah Alghanim ◽  
Musfira Jilani ◽  
Michela Bertolotto ◽  
Gavin McArdle
Keyword(s):  
Machine Learning ◽  
Spatial Data ◽  
Classification Accuracy ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Data Set ◽  
Semantic Inference ◽  
Road Type ◽  
The Impact

Volunteered Geographic Information (VGI) is often collected by non-expert users. This raises concerns about the quality and veracity of such data. There has been much effort to understand and quantify the quality of VGI. Extrinsic measures which compare VGI to authoritative data sources such as National Mapping Agencies are common but the cost and slow update frequency of such data hinder the task. On the other hand, intrinsic measures which compare the data to heuristics or models built from the VGI data are becoming increasingly popular. Supervised machine learning techniques are particularly suitable for intrinsic measures of quality where they can infer and predict the properties of spatial data. In this article we are interested in assessing the quality of semantic information, such as the road type, associated with data in OpenStreetMap (OSM). We have developed a machine learning approach which utilises new intrinsic input features collected from the VGI dataset. Specifically, using our proposed novel approach we obtained an average classification accuracy of 84.12%. This result outperforms existing techniques on the same semantic inference task. The trustworthiness of the data used for developing and training machine learning models is important. To address this issue we have also developed a new measure for this using direct and indirect characteristics of OSM data such as its edit history along with an assessment of the users who contributed the data. An evaluation of the impact of data determined to be trustworthy within the machine learning model shows that the trusted data collected with the new approach improves the prediction accuracy of our machine learning technique. Specifically, our results demonstrate that the classification accuracy of our developed model is 87.75% when applied to a trusted dataset and 57.98% when applied to an untrusted dataset. Consequently, such results can be used to assess the quality of OSM and suggest improvements to the data set.

A generally applicable pedotransfer function that estimates field capacity and permanent wilting point from soil texture and bulk density

2008 ◽  
Vol 88 (5) ◽  
pp. 761-774 ◽  
Author(s):  
J. A. P. Pollacco
Keyword(s):  
Organic Matter ◽  
Soil Moisture ◽  
Bulk Density ◽  
Soil Texture ◽  
The United States ◽  
Pedotransfer Functions ◽  
Pedotransfer Function ◽  
Data Set ◽  
Wide Range ◽  
Fitting Parameters

Hydrological models require the determination of fitting parameters that are tedious and time consuming to acquire. A rapid alternative method of estimating the fitting parameters is to use pedotransfer functions. This paper proposes a reliable method to estimate soil moisture at -33 and -1500 kPa from soil texture and bulk density. This method reduces the saturated moisture content by multiplying it with two non-linear functions depending on sand and clay contents. The novel pedotransfer function has no restrictions on the range of the texture predictors and gives reasonable predictions for soils with bulk density that varies from 0.25 to 2.16 g cm-3. These pedotransfer functions require only five parameters for each pressure head. It is generally accepted that the introduction of organic matter as a predictor improves the outcomes; however it was found by using a porosity based pedotransfer model, using organic matter as a predictor only modestly improves the accuracy. The model was developed employing 18 559 samples from the IGBP-DIS soil data set for pedotransfer function development (Data and Information System of the International Geosphere Biosphere Programme) database that embodies all major soils across the United States of America. The function is reliable and performs well for a wide range of soils occurring in very dry to very wet climates. Climatical grouping of the IGBP-DIS soils was proposed (aquic, tropical, cryic, aridic), but the results show that only tropical soils require specific grouping. Among many other different non-climatical soil groups tested, only humic and vitric soils were found to require specific grouping. The reliability of the pedotransfer function was further demonstrated with an independent database from Northern Italy having heterogeneous soils, and was found to be comparable or better than the accuracy of other pedotransfer functions found in the literature. Key words: Pedotransfer functions, soil moisture, soil texture, bulk density, organic matter, grouping

scholarly journals Mapping the Soil Texture in the Heihe River Basin Based on Fuzzy Logic and Data Fusion

2017 ◽  
Vol 9 (7) ◽  
pp. 1246 ◽  
Author(s):  
Ling Lu ◽  
Chao Liu ◽  
Xin Li ◽  
Youhua Ran
Keyword(s):  
Fuzzy Logic ◽  
Data Fusion ◽  
River Basin ◽  
Soil Texture ◽  
Heihe River Basin ◽  
Heihe River ◽  
The Heihe River Basin
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