scholarly journals Feature points-based image registration between satellite imagery and aerial images of agricultural land

2020 ◽  
Vol 28 (3) ◽  
pp. 1458-1473
Author(s):  
Mohsin ABBAS ◽  
Sajid SALEEM ◽  
Fazli SUBHAN ◽  
Abdul BAIS
Keyword(s):  
Image Registration ◽  
Satellite Imagery ◽  
Agricultural Land ◽  
Aerial Images ◽  
Feature Points

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals LARGE SCALE CITY MAPPING USING SATELLITE IMAGERY / KOSMINIŲ NUOTRAUKŲ IŠ GOOGLE EARTH, TAIKOMŲ MIESTAMS KARTOGRAFUOTI STAMBIUOJU MASTELIU, REKTIFIKAVIMAS / РЕКТИФИКАЦИЯ КОСМИЧЕСКИХ СНИМКОВ ИЗ GOOGLE EARTH ДЛЯ КРУПНОМАСШТАБНОГО КАРТОГРАФИРОВАНИЯ ГОРОДОВ

2012 ◽  
Vol 37 (4) ◽  
pp. 168-171 ◽  
Author(s):  
Birutė Ruzgienė ◽  
Qian Yi Xiang ◽  
Silvija Gečytė
Keyword(s):  
Satellite Imagery ◽  
Large Scale ◽  
Modern Technology ◽  
Google Earth ◽  
Aerial Images ◽  
Control Points ◽  
Image Rectification ◽  
Image Deformation ◽  
Map Construction ◽  
Short Period

The rectification of high resolution digital aerial images or satellite imagery employed for large scale city mapping is modern technology that needs well distributed and accurately defined control points. Digital satellite imagery, obtained using widely known software Google Earth, can be applied for accurate city map construction. The method of five control points is suggested for imagery rectification introducing the algorithm offered by Prof. Ruan Wei (tong ji University, Shanghai). Image rectification software created on the basis of the above suggested algorithm can correct image deformation with required accuracy, is reliable and keeps advantages in flexibility. Experimental research on testing the applied technology has been executed using GeoEye imagery with Google Earth builder over the city of Vilnius. Orthophoto maps at the scales of 1:1000 and 1:500 are generated referring to the methodology of five control points. Reference data and rectification results are checked comparing with those received from processing digital aerial images using a digital photogrammetry approach. The image rectification process applying the investigated method takes a short period of time (about 4-5 minutes) and uses only five control points. The accuracy of the created models satisfies requirements for large scale mapping. Santrauka Didelės skiriamosios gebos skaitmeninių nuotraukų ir kosminių nuotraukų rektifikavimas miestams kartografuoti stambiuoju masteliu yra nauja technologija. Tai atliekant būtini tikslūs ir aiškiai matomi kontroliniai taškai. Skaitmeninės kosminės nuotraukos, gautos taikant plačiai žinomą programinį paketą Google Earth, gali būti naudojamos miestams kartografuoti dideliu tikslumu. Siūloma nuotraukas rektifikuoti Penkių kontrolinių taskų metodu pagal prof. Ruan Wei (Tong Ji universitetas, Šanchajus) algoritmą. Moksliniam eksperimentui pasirinkta Vilniaus GeoEye nuotrauka iš Google Earth. 1:1000 ir 1:500 mastelio ortofotografiniai žemėlapiai sudaromi Penkių kontrolinių taškų metodu. Rektifikavimo duomenys lyginami su skaitmeninių nuotraukų apdorojimo rezultatais, gautais skaitmeninės fotogrametrijos metodu. Nuotraukų rektifikavimas Penkių kontrolinių taskų metodu atitinka kartografavimo stambiuoju masteliu reikalavimus, sumažėja laiko sąnaudos. Резюме Ректификация цифровых и космических снимков высокой резолюции для крупномасштабного картографирования является новой технологией, требующей точных и четких контрольных точек. Цифровые космические снимки, полученные с использованием широкоизвестного программного пакета Google Earth, могут применяться для точного картографирования городов. Для ректификации снимков предложен метод пяти контрольных точек с применением алгоритма проф. Ruan Wei (Университет Tong Ji, Шанхай). Для научного эксперимента использован снимок города Вильнюса GeoEye из Google Earth. Ортофотографические карты в масштабе 1:1000 и 1:500 генерируются с применением метода пяти контрольных точек. Полученные результаты и данные ректификации сравниваются с результатами цифровых снимков, полученных с применением метода цифровой фотограмметрии. Ректификация снимков с применением метода пяти контрольных точек уменьшает временные расходы и удовлетворяет требования, предъявляемые к крупномасштабному картографированию.

scholarly journals The Mapping of Land Use Using Object-Based Image Analysis (OBIA) in Klaten Regency

2020 ◽  
Vol 202 ◽  
pp. 06036
Author(s):  
Nurhadi Bashit ◽  
Novia Sari Ristianti ◽  
Yudi Eko Windarto ◽  
Desyta Ulfiana
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Image Analysis ◽  
Satellite Imagery ◽  
Agricultural Land ◽  
Scale Parameter ◽  
Land Use Classification ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Sentinel 2

Klaten Regency is one of the regencies in Central Java Province that has an increasing population every year. This can cause an increase in built-up land for human activities. The built-up land needs to be monitored so that the construction is in accordance with the regional development plan so that it does not cause problems such as the occurrence of critical land. Therefore, it is necessary to monitor land use regularly. One method for monitoring land use is the remote sensing method. The remote sensing method is much more efficient in mapping land use because without having to survey the field. The remote sensing method utilizes satellite imagery data that can be processed for land use classification. This study uses the sentinel 2 satellite image data with the Object-Based Image Analysis (OBIA) algorithm to obtain land use classification. Sentinel 2 satellite imagery is a medium resolution image category with a spatial resolution of 10 meters. The land use classification can be used to see the distribution of built-up land in Klaten Regency without having to conduct a field survey. The results of the study obtained a segmentation scale parameter value of 60 and a merge scale parameter value of 85. The classification results obtained by 5 types of land use with OBIA. Agricultural land use dominates with an area of 50% of the total area.

New evidence of glacier surges in the Central Andes of Argentina and Chile

2018 ◽  
Vol 42 (6) ◽  
pp. 792-825 ◽  
Author(s):  
Daniel Falaschi ◽  
Tobias Bolch ◽  
Maria Gabriela Lenzano ◽  
Takeo Tadono ◽  
Andrés Lo Vecchio ◽  
...  
Keyword(s):  
Satellite Imagery ◽  
Remote Sensing Data ◽  
Central Andes ◽  
Aerial Images ◽  
Mountain Ranges ◽  
The Andes ◽  
Digital Elevation ◽  
Heterogeneous Behavior ◽  
Elevation Changes ◽  
Glacier Surges

In contrast to the large surge-type glacier clusters widely known for several mountain ranges around the world, the presence of surging glaciers in the Andes has been historically seen as marginal. The improved availability of satellite imagery during the last years facilitates investigating of glaciers in more detail even in remote areas. The purpose of the study was therefore to revisit existing information about surge-type glaciers for the Central Andes of Argentina and Chile (32° 40′–34° 20′ S), to identify and characterize possible further surge-type glaciers, providing new insights into the mass balance and evolution of the velocity of selected glaciers during the surge phase. Based on the analysis of 1962–2015 satellite imagery, historical aerial images, differencing of digital elevation models and a literature survey, we identified 21 surge-type glaciers in the study area. Eleven surge events and six possible surge-type glaciers were identified and described for the first time. The estimation of annual elevation changes of these glaciers for the 2000–2011 period, which encompasses the latest surge events in the region, showed heterogeneous behavior with strongly negative to positive surface elevation change patterns (−1.1 to +1.0 m yr−1). Additionally, we calculated maximum surface velocities of 3±1.9 m d−1 and 3.1±1.1 m d−1 for two of the glaciers during the latest identifiable surge events of 1985–1987 and 2003–2007. Within this glacier cluster, highly variable advance rates (0.01–1 km yr−1) and dissimilar surface velocities at the surge peak (3–35 m d−1) were observed. In comparison with other clusters worldwide, surge-type glaciers in the Central Andes are on average smaller and show minor absolute advances. Generally low velocities and the heterogeneous duration of the surge cycles are common between them and glaciers in the Karakorum, a region with similar climatic characteristics and many known surge-type glaciers. As a definitive assertion concerning the underlying surge mechanism of surges in the Central Andes could not be drawn based on the remote sensing data, this opens more detailed research avenues for surge-type glaciers in the region.

A New Algorithm of Image Registration Based on Contour Feature

2014 ◽  
Vol 912-914 ◽  
pp. 1092-1097
Author(s):  
Fu Hua Song ◽  
Peng Hui Li ◽  
Jian Ran Deng
Keyword(s):  
Image Registration ◽  
Rotation Angle ◽  
Closed Contour ◽  
Feature Points ◽  
Registration Algorithm ◽  
Image Registration Algorithm ◽  
Contour Feature ◽  
Circular Correlation ◽  
Open Contour ◽  
Calculated Amount

Image registration is an important task in image processing. In this paper, a new and fast contour-based image registration algorithm is proposed. In this algorithm, we fetch contour points and calculate the normal angles firstly, then figure out the histogram of the contour-feature points. By computing circular correlation of the histogram, the rotation angle can be gained. As the rotation angle is obtained, it vastly simplifies the complexity of estimating other registration parameters and reduces the calculated amount, thus achieving a fast image registration algorithm. This algorithm has the invariance of rotation, translation and scale, and it has high robustness for either open contour or closed contour.

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