Sniego dangos rodiklių tyrimas nuotoliniais metodais lyguminėse teritorijose

2021 ◽  
Author(s):  
◽  
Justinas Kilpys
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Remote Sensing Methods

Determination of snow cover characteristics in flat land areas using remote sensing methods

scholarly journals TECHNOLOGY FOR MONITORING CAPITAL CONSTRUCTION OBJECTS AT THE LIFE CYCLE STAGES BY REMOTE SENSING METHODS USING UNMANNED AIRCRAFT (DRONES) BASED ON HIGH PRECISION DIGITAL MODEL

2021 ◽  
Vol 9 (3) ◽  
pp. 51-55
Author(s):  
Lyubov' Adamcevich ◽  
Pavel Vorob'ev ◽  
Egor Zheleznov
Keyword(s):  
Remote Sensing ◽  
Unmanned Aircraft ◽  
Information Modeling ◽  
Technical Solution ◽  
System A ◽  
Assessment Design ◽  
Life Cycle Stages ◽  
Capital Construction ◽  
Remote Sensing Methods

In modern construction at the stages of investment assessment, design, construction and operation of capital construction facilities with the implemented information modeling system, a serious problem is the harmonization of data collected from the construction site on the geometric parameters of the facility and territory being built. The article presents a comprehensive scientific and technical solution in the field of diagnostics of buildings and structures, monitoring the progress of construction, as well as automated determination of the volume of construction work performed using remote sensing technologies using unmanned aerial vehicles and information modeling (BIM technologies).

scholarly journals Remote Sensing Methods in the Identification of Oil Contaminations / Možnosti Využití Vybraných Metod Dpz Pro Identifikaci Ropných Kontaminací (Starých Ekologických Zátěží)

2012 ◽  
Vol 58 (1) ◽  
pp. 24-33 ◽  
Author(s):  
Eva Smejkalová ◽  
Petr Bujok
Keyword(s):  
Remote Sensing ◽  
Data Analysis ◽  
In Situ Measurements ◽  
Oil Wells ◽  
Digital Data ◽  
Ecological Hazards ◽  
Remote Sensing Methods

Abstract The article deals with the possibilities of using remote sensing methods for analysis, observation and identification of old ecological hazards caused by petroleum contaminations from insufficiently plugged and abandoned oil wells in the area of Hodonín. It is focused on the description and determination of areas of interests, remote sensing approaches to the problems of petroleum substance detection and establishing the methodology of an acquired data analysis. Moreover, proper methods, algorithms and satellite digital data parameters for this aim are discussed. The article also describes in-situ measurements, technical instruments and further research advancements. Finally, the proposals of the results evaluation, interpretation and complex comparisons with the results of past and future researches in the area of Nesyt - Hodonín are specified.

scholarly journals CHOICE OF CRITERION FOR DETERMINATION OF COASTAL LINE BY REMOTE SENSING METHODS

2018 ◽  
pp. 107-112
Author(s):  
Latifa Dzhafaraga Abdullaeva ◽  
Hikmat Hamid oglu Asadov
Keyword(s):  
Remote Sensing ◽  
Type Criterion ◽  
Remote Sensing Methods ◽  
Channel Type

Feasibility of using multi-channel methods has been grounded; the results of three channel method have been analyzed on the basis of measurements data of B1, B2, B3 channels of SPOT XS and X1hardware. A certain three-channel criterion for detecting coastal line is transformed into an index-channel type criterion. It has been shown analytically that the considered criterion possesses more sensitivity in regard of variations of B1/RED than of variations of NDVI. It has been graphically presented that sensitivity of used criterion in regard of S1/RED is at least two times more than in regard of NDVI. This fact testifies non-correctness of NDVI utilization for determination of coastal lines.

Determination of Hydrothermal Alteration Zones Using Remote Sensing Methods in Tirka Area, Toroud, NE Iran

2019 ◽  
Vol 47 (11) ◽  
pp. 1817-1830 ◽  
Author(s):  
Mina Zamyad ◽  
Peyman Afzal ◽  
Mohsen Pourkermani ◽  
Reza Nouri ◽  
Mohammad Reza Jafari
Keyword(s):  
Remote Sensing ◽  
Hydrothermal Alteration ◽  
Alteration Zones ◽  
Hydrothermal Alteration Zones ◽  
Remote Sensing Methods ◽  
Ne Iran

scholarly journals Application of remote sensing methods and GIS technologies for the classification of lands in the Pushkin district of St. Petersburg

2021 ◽  
pp. 84-102
Author(s):  
Т.К. Фан ◽  
Ч.Т. Нгуен ◽  
А.С. Алексеев ◽  
А.В. Любимов ◽  
В.Л. Сергеева ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Forest Inventory ◽  
Likelihood Method ◽  
Landsat 8 ◽  
Automated Classification ◽  
Gis Technologies ◽  
Remote Sensing Methods ◽  
Selection Of

ГИС-технологии и методы автоматизированной классификации материалов ДЗЗ активно используются во многих странах при проведении работ по инвентаризации лесов, проектированию использования лесов и изучению их состояния и характеристик. Задачи исследования состояли в разработке методики и проведении автоматизированной классификации категорий земель крупной административно-территориальной единицы на основе дистанционных методов и ГИС-технологий. Объектом исследования служила территория Пушкинского района Санкт-Петербурга. На территории Пушкинского района расположено значительное количество зелёных насаждений (парки, скверы, сады, лесополосы), часть из которых включена в список памятников, охраняемых ЮНЕСКО. Также на территории района расположены промышленные предприятия, крупные производственные зоны, развито сельское хозяйство. В качестве исходных материалов дистанционного зондирования использовались спутниковые изображения Landsat-8. Использовался также набор карт на изучаемую территорию. Программными средствами для сбора, представления и обработки данных служили ГИС Arcgis и Mapinfo, и программы ENVI и Trimble eCognition. Наземные работы по отбору эталонных (тренировочных) участков включали выбор участка на местности, фотографирование, определение координат. Классификация снимка Landsat осуществлялась по результатам двух основных операций – автоматизированного дешифрирования методом максимального правдоподобия и определения вегетационных индексов классов представленных категорий земель. После наземной верификации результатов классификации и выполнения операций обработки и агрегирования была сформирована итоговая тематическая карта классов категорий земель Пушкинского района и получены итоговые таблицы распределения площадей по муниципальным образованиям. Представленная методика, связанная с обработкой и интерпретацией материалов дистанционного зондирования средствами ГИС-технологий, может рассматриваться в качестве современного инструмента ландшафтного анализа, государственной (национальной) инвентаризации лесов, различных видов мониторинга. GIS technologies and methods of automated classification of remote sensing data are actively used in many countries in forest inventory, forest management planning and assessment of the state and characteristics of forests. The objectives of the study were to develop a methodology and conduct an automated classification of land categories for a large administrative-territorial unit based of remote sensing methods and GIS-technologies. The object of the study was the territory of the Pushkin district of St. Petersburg. On the territory of the Pushkin district are located a significant number of green zones (parks, squares, gardens, forest belts), some of which are included in the list of monuments protected by UNESCO. Also on the territory of the district are located industrial enterprises, large industrial zones, agriculture is developed. Lansat-8 satellite images and a set of maps for the study area were used as initial materials. GIS ArcGIS and MapInfo, programs ENVI and Trimble eCognition were used to collect, visualize and process data. Field work on the selection of reference (training) samples included the selection of sample plots in nature, photography, and determination of coordinates. The Landsat images were classified according to the results of two main operations – automated interpretation by the maximum likelihood method and determination of the vegetation indices of the land categories classes. After performing field verification, as well as performing processing and aggregation operations, the final thematic map of the classes of land categories in the Pushkin region was formed and the final tables of the distribution of areas by municipalities were obtained. The presented methodology, associated with the processing and interpretation of remote sensing materials by means of GIS technologies, can be considered as a modern tool for landscape analysis, state (national) forest inventory, and various types of territory monitoring.

Application of Remote Sensing in Agriculture

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Production ◽  
Satellite Images ◽  
Crop Yields ◽  
Spatial Scales ◽  
Strong Relationship ◽  
Physical Parameters ◽  
Agricultural Crop ◽  
Remote Sensing Methods

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.

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