scholarly journals Возможность использования данных дистанционного зондирования при мониторинге водных объектов

2021 ◽  
Author(s):  
Наталья Сергеевна Решетило ◽  
Елена Павловна Хлебникова
Keyword(s):  
Erdas Imagine

В статье рассмотрены первостепенные задачи мониторинга водных объектов, цели, возможности использования данных дистанционного зондирования с применением программного комплекса Erdas Imagine 2015. Показано как с помощью данных дистанционного зондирования можно получить достоверную информацию о состоянии водных объектов, выявить и спрогнозировать неблагоприятные экологические явления, а также извлечь полезную информацию.

scholarly journals Estimation of Wheat Area using Sentinel-1 and Sentinel-2 Datasets (A Comparative Analysis)

2019 ◽  
Author(s):  
Ayesha Behzad ◽  
Muneeb Aamir ◽  
Syed Ahmed Raza ◽  
Ansab Qaiser ◽  
Syeda Yuman Fatima ◽  
...  
Keyword(s):  
Comparative Analysis ◽  
Random Forest ◽  
Water Body ◽  
Supervised Classification ◽  
Wheat Crop ◽  
Random Forest Classification ◽  
Forest Classification ◽  
Wheat Cultivation ◽  
Erdas Imagine ◽  
Sentinel 2

Wheat is the basic staple food, largely grown, widely used and highly demanded. It is used in multiple food products which are served as fundamental constituent to human body. Various regional economies are partially or fully dependent upon wheat production. Estimation of wheat area is essential to predict its contribution in regional economy. This study presents a comparative analysis of optical and active imagery for estimation of area under wheat cultivation. Sentinel-1 data was downloaded in Ground Range Detection (GRD) format and applied the Random Forest Classification using Sentinel Application Platform (SNAP) tools. We obtained a Sentinel-2 image for the month of March and applied supervised classification in Erdas Imagine 14. The random forest classification results of Sentinel-1 show that the total area under investigation was 1089km2 which was further subdivided in three classes including wheat (551km2), built-up (450 km2) and the water body (89 km2). Supervised classification results of Sentinel-2 data show that the area under wheat crop was 510 km2, however the built-up and waterbody were 477 km2, 102 km2 respectively. The integrated map of Sentinel-1 and Sentinel-2 show that the area under wheat was 531 km2 and the other features including water body and the built-up area were 95 km2 and 463 km2 respectively. We applied a Kappa coefficient to Sentinel-2, Sentinel-1 and Integrated Maps and found an accuracy of 71%, 78% and 85% respectively. We found that remotely sensed algorithms of classifications are reliable for future predictions.

scholarly journals New technology for mineral deposits prediction to identify prospective areas in the Zhezkazgan ore region

2021 ◽  
Vol 15 (2) ◽  
pp. 134-142
Author(s):  
Boris Zeylik ◽  
Yalkunzhan Arshamov ◽  
Refat Baratov ◽  
Alma Bekbotayeva
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
New Technology ◽  
Methodological Approach ◽  
Cost Savings ◽  
Remote Sensing Data ◽  
Ring Structure ◽  
Mineral Deposits ◽  
Erdas Imagine ◽  
Radar Satellite

Purpose. Exploration and predicting the prospective areas in the Zhezkazgan ore region to set up detailed prospecting and evaluation works using new integrated technologies of prediction constructions in the mineral deposits geology. Methods. An integrated methodological approach is used, including methods for deciphering the Earth’s remote sensing (ERS) data, the use of geophysical data and methods of analogy and actualism. All constructions are made in accordance with the principles of shock-explosive tectonics (SET). Prediction constructions are started with the selection of remote sensing data for the studied region and interpretation based on the processing of radar satellite images obtained from the Radarsat-1 satellite. The radar satellite images are processed in the Erdas Imagine software package. Findings. New local prospective areas have been identified, within which it is expected to discover the deposits. Their reserves are to replenish the depleted ore base in the Zhezkazgan region. Area of the gravity maximum 1 (the Near), considered to be the most promising, is located in close proximity to the city of Zhezkazgan; area of the gravity maximum 2 (the Middle); area of the gravity maximum 3 (the Distant-Tabylga); area of the gravity maximum 6 (the Central). A prospective area has been also revealed, overlaid by a loose sediment cover and located inside the Terekty ring structure, as well as the area of a thick stratum of pyritized grey sandstones, which is adjacent to the Sh-2 well drilled to the south of the Zhezkazgan field. Originality. The use of a new prediction technology, in contrast to the known ones, is conditioned by the widespread use of the latest remote information from satellite images, which increases the accuracy of identifying the prospective areas of fields. Practical implications. The new technology for predicting mineral deposits makes it possible to significantly reduce the areas exposed to priority prospecting, which provides significant cost savings.

scholarly journals Land Use/Land Cover Changes in a Disturbed River Watershed Kenya

2019 ◽  
Vol 3 (2) ◽  
pp. 29
Author(s):  
Zachary Gichuru Mainuri ◽  
John M. Mironga ◽  
Samuel M. Mwonga
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Remote Sensing Image ◽  
Land Cover Changes ◽  
Land Use Land Cover ◽  
Human Needs ◽  
Observation Systems ◽  
Erdas Imagine ◽  
Remote Sensing Image Processing

Drivers of land use change were captured by the use of DPSIR model where Drivers (D) represented human needs, Pressures (P), human activities, State (S), the ecosystem, Impact (I) services from the ecosystem and Response (R), the decisions taken by land users. Land sat MSS and Land sat ETM+ (path 185, row 31) were used in this study. The Land sat ETM+ image (June 1987, May, 2000 and July, 2014) was downloaded from USGS Earth Resources Observation Systems data website. Remote sensing image processing was performed by using ERDAS Imagine 9.1. Two land use/land cover (LULC) classes were established as forest and shrub land. Severe land cover changes was found to have occurred from 1987-2000, where shrub land reduced by -19%, and forestry reduced by -72%. In 2000 – 2014 shrub land reduced by-45%, and forestry reduced by -64%. Forestry and shrub land were found to be consistently reducing.

scholarly journals Satellite image classification using proposed singular value decomposition method

2019 ◽  
Vol 13 (28) ◽  
pp. 52-67
Author(s):  
Noor Zubair Kouder
Keyword(s):  
Singular Value Decomposition ◽  
Classification Accuracy ◽  
Satellite Image ◽  
Field Work ◽  
Mean Value ◽  
Singular Value ◽  
Singular Value Decomposition Method ◽  
Erdas Imagine ◽  
Value Decomposition ◽  
Svd Method

In this work, satellite images for Razaza Lake and the surrounding areadistrict in Karbala province are classified for years 1990,1999 and2014 using two software programming (MATLAB 7.12 and ERDASimagine 2014). Proposed unsupervised and supervised method ofclassification using MATLAB software have been used; these aremean value and Singular Value Decomposition respectively. Whileunsupervised (K-Means) and supervised (Maximum likelihoodClassifier) method are utilized using ERDAS imagine, in order to getmost accurate results and then compare these results of each methodand calculate the changes that taken place in years 1999 and 2014;comparing with 1990. The results from classification indicated thatwater and hills are decreased, while vegetation, wet land and barrenland are increased for years 1999 and 2014; comparable with 1990.The classification accuracy was done by number of random pointschosen on the study area in the field work and geographical data thencompared with the classification results, the classification accuracy forthe proposed SVD method are 92.5%, 84.5% and 90% for years1990,1999,2014, respectivety, while the classification accuracies forunsupervised classification method based mean value are 92%, 87%and 91% for years 1990,1999,2014 respectivety.

scholarly journals INVESTIGATIONS ON THE BUNDLE ADJUSTMENT RESULTS FROM SFM-BASED SOFTWARE FOR MAPPING PURPOSES

2018 ◽  
Vol XLII-2 ◽  
pp. 623-628
Author(s):  
Y. A. Lumban-Gaol ◽  
A. Murtiyoso ◽  
B. H. Nugroho
Keyword(s):  
Aerial Photography ◽  
Large Scale ◽  
Bundle Adjustment ◽  
Aerial Images ◽  
Topographic Maps ◽  
Main Method ◽  
Aerial Photogrammetry ◽  
Lower Accuracy ◽  
Spatial Management ◽  
Erdas Imagine

Since its first inception, aerial photography has been used for topographic mapping. Large-scale aerial photography contributed to the creation of many of the topographic maps around the world. In Indonesia, a 2013 government directive on spatial management has re-stressed the need for topographic maps, with aerial photogrammetry providing the main method of acquisition. However, the large need to generate such maps is often limited by budgetary reasons. Today, SfM (Structure-from-Motion) offers quicker and less expensive solutions to this problem. However, considering the required precision for topographic missions, these solutions need to be assessed to see if they provide enough level of accuracy. In this paper, a popular SfM-based software Agisoft PhotoScan is used to perform bundle adjustment on a set of large-scale aerial images. The aim of the paper is to compare its bundle adjustment results with those generated by more classical photogrammetric software, namely Trimble Inpho and ERDAS IMAGINE. Furthermore, in order to provide more bundle adjustment statistics to be compared, the Damped Bundle Adjustment Toolbox (DBAT) was also used to reprocess the PhotoScan project. Results show that PhotoScan results are less stable than those generated by the two photogrammetric software programmes. This translates to lower accuracy, which may impact the final photogrammetric product.

scholarly journals A Conceptual Framework for Organisation of River Basin Developmentand Management in Nigeria

2019 ◽  
Vol 4 (6) ◽  
pp. 34-40
Author(s):  
Bukar Abba Gana ◽  
Isah Funtua Abdulkadir ◽  
Hassan Musa ◽  
Tijjani Garba
Keyword(s):  
Conceptual Framework ◽  
River Basin ◽  
Crop Production ◽  
Drainage System ◽  
Framework Analysis ◽  
Basin Development ◽  
Erdas Imagine ◽  
River Basin Development ◽  
Development And Management ◽  
Basin Area

River Basin Development Authorities (RBDAs) in Nigeria were established since 1976 and they operate mechanized and capital intensive programmes. All the 12 RBDAs operate as separate Authorities, each with separate administrative and operational autonomy, but sharing the Basin Resources of the 8 Hydrological Areas. However, their performance was generally described as disappointing. This study first reviewed the existing organization of the 12 RBDAs in Nigeria. Thereafter, one of the 8 Hydrological Areas – the Komadugu-Yobe Basin (KYB) – which is the major inland drainage system in Nigeria was purposely selected for detailed study.  Information on its major streams, tributaries and the main river; the hydrological area as well as the RBDAs sharing resources of the basin area, was gathered using ArcGIS version 10.0 and Erdas Imagine 9.2 software, as well as topographical and hydrological maps. This was processed and analyzed based on the principles of Stream Ordering and Logical Framework Analysis. The findings revealed that in establishing the RBDAs, basin-wide consideration of their sphere of operation was not taken into account. Dams were constructed before establishing the RBDAs. Runoff waters and spill ways were poorly controlled leading to flooding during rainy season and reduced water supply downstream during dry season, with serious environmental and socio-economic problems in the basin area. It was concluded that the RBDAs in Nigeria were poorly organized and have consequently failed to accelerate agricultural and rural development, and have also failed to boost food and industrial crop production as expected. The need was established for effective organization of River Basin Development and Management to improve their performance. To achieve this, a Conceptual framework for Integrated River Basin Development and Management was developed for adoption by river basin managers and other relevant stakeholders in Nigeria and around the globe to improve performance.

UAV and the comparison of image processing software

2017 ◽  
Vol 5 (1) ◽  
pp. 18-27 ◽  
Author(s):  
Dimitris Kaimaris ◽  
Petros Patias ◽  
Maria Sifnaiou
Keyword(s):  
Image Processing ◽  
Global Positioning System ◽  
Design Methodology ◽  
Surface Model ◽  
Content Type ◽  
Global Positioning ◽  
Erdas Imagine ◽  
Aerial Vehicle ◽  
Processing Software ◽  
Image Processing Software

Purpose The purpose of this paper is to discuss unmanned aerial vehicle (UAV) and the comparison of image processing software. Design/methodology/approach Images from a drone are used and processed with new digital image processing software, Imagine UAV® of Erdas imagine 2015®. The products (Digital Surface Model and ortho images) are validated with check points (CPs) measured in the field with Global Positioning System. Moreover, similar products are produced by Agisoft PhotoScan® software and are compared with both the products of Imagine UAV and the CPs. Findings The results reveal that the two software tools are almost equivalent, while the accuracies of their products are similar to the accuracies of the external orientations of drone images. Originality/value Comparison of image processing software.

scholarly journals VARIAÇÃO DAS TEMPERATURAS E DA UMIDADE RELATIVA DO AR NO EXTREMO INVERNO E VERÃO NA CIDADE DE BARRA DO GARÇAS-MT

2020 ◽  
Vol 26 ◽  
Author(s):  
Francisco Sousa Lira ◽  
Rildo Vieira Araujo ◽  
Leonardo José De Melo ◽  
Reginaldo Brito Costa ◽  
Romario Rosa De Sousa
Keyword(s):  
Landsat 8 ◽  
Erdas Imagine

Este trabalho teve como objetivo conhecer as variações de temperaturas e umidade relativa do ar no extremo inverno e verão na cidade de Barra do Garças-MT. Quanto a metodologia utilizada, pautou-se na aquisição dos dados diários coletados a cada 30 minutos a partir de 9 termohigrômetros digitais. Foram utilizados dados diários proveniente do Banco de Dados Meteorológicos para Ensino e Pesquisa BDMEP/INMET, referentes as estações meteorológicas de Aragarças-GO, Nova Xavantina-MT, Poxoréo-MT e Jataí-GO. As imagens orbitais digitais gratuitas do município de Barra do Garças-MT, foram obtidas do satélite Landsat-8 no Serviço de Levantamento Geológico Americano (USGS), sensor OLI (Operational Land Imager) orbita 224, ponto 71, com data de passagem 13/07/2017 e 21/01/2108 e horário central 10:30 horas, banda: 10 com resolução espacial de 30 metros e banda 10 infravermelho termal. A composição colorida e as aplicações das modelagens foram realizadas no software ERDAS Imagine versão 2013. As temperaturas no mês de julho de 2017, se destacou com valores mais elevados, e a umidade relativa do ar baixa com 52%, apresentando uma insolação total de 260,1w/m², precipitação 0,0mm, e a velocidade do vento em 0,486471m/s. Já para o mês de janeiro de 2018, este apresentou valores menores de temperaturas e alta umidade relativa do ar com 81%, e insolação com uma medida de 163,9w/m², e precipitação acumulada em 255,4mm, e a velocidade do vento em 0,497845 m/s. Constatou-se uma variação de temperaturas e da umidade relativa do ar e um diagnóstico da dinâmica climática urbana.

Comparative Study of Change Detection and Urban Expansion Using Multi-Date Multi-Source Data: A Case Study of Greater Khartoum

2012 ◽  
Vol 23 (2) ◽  
pp. 139-172
Author(s):  
Abdullah Salman Alsalman Abdullah Salman Alsalman
Keyword(s):  
Image Processing ◽  
Change Detection ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Urban Expansion ◽  
Remote Sensing Data ◽  
Principal Component ◽  
Test Area ◽  
Image Differencing ◽  
Erdas Imagine

Noting that Khartoum represents the most rapidly expanding city in the Sudan and taking into account that change detection operations are seldom , the present study has been initiated to attempt to produce work that synthesizes land use/land cover (LULC) to investigate change detection using GIS, remote sensing data and digital image processing techniques; estimate, evaluate and map changes that took place in the city from 1975 to 2003. The experiment used the techniques of visual inspection, write-function-memoryinsertion, image differencing, image transformation i.e. normalized difference vegetation index (NDVI), tasseled cap, principal component analysis (PCA), post-classification comparison and GIS. The results of all these various techniques were used by the authors to study change detection of the geographic locale of the test area. Image processing and GIS techniques were performed using Intergraph Image analyst 8.4 and GeoMedia professional version 6, ERDAS Imagine 8.7, and ArcGIS 9.2. Results obtained were discussed and analyzed in a comparative manner and a conclusion regarding the best method for change detection of the test area was derived.

scholarly journals Image Processing and Data Analysis with ERDAS IMAGINE

2020 ◽  
Vol 86 (10) ◽  
pp. 597-598
Author(s):  
Stacy A.C. Nelson ◽  
Siamak Khorram ◽  
Shiloh Dorgan
Keyword(s):  
Image Processing ◽  
Data Analysis ◽  
Erdas Imagine
Sign in / Sign up

Export Citation Format

Share Document