scholarly journals Drone based very-high resolution imagery analysed with geographic object-based image analysis: the perfect match for mapping intertidal habitats?

2017 ◽  
Author(s):  
M Diesing ◽  
S Archer ◽  
J Bremner ◽  
T Dolphin ◽  
A -L Downie ◽  
...  
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Perfect Match ◽  
Object Based Image Analysis ◽  
High Resolution Imagery ◽  
Object Based ◽  
Geographic Object ◽  
Very High Resolution Imagery ◽  
Intertidal Habitats ◽  
Very High

scholarly journals Metodologia de análise de imagens baseada em objetos geográficos (GEOBIA) utilizando RPAS (drone) com sensor RGB

Estrabão ◽  
2021 ◽  
Vol 2 ◽  
pp. 41-85
Author(s):  
Vinicius Gonçalves
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Open Source ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Geographic Object ◽  
Very High

O presente trabalho apresenta um método para o mapeamento de vegetação, por um processo de classificação por regiões geográficas, denominado GEOBIA (Geographic Object-Based Image Analysis) considerado adequado para classificar imagens de muito alta resolução (very high resolution – VHR). É possível executar o procedimento com qualquer equipamento que disponha de um sensor RGB de boa qualidade e permita execução de aplicativos para plano de voo. O método foi desenvolvido com base em softwares de código aberto (open source) para evitar custos com licenças, em todas as etapas, desde a captação das imagens, elaboração de produtos cartográficos, processamento da classificação por regiões e conclusão mediante cálculos de áreas. O estudo foi aplicado em quatro áreas de interesse, todas na região da Grande Florianópolis-SC, contendo porções do ecossistema de Formações Pioneiras - Vegetação com Influência Marinha, também denominadas áreas de restinga, cujo principal alvo da classificação foi o mapeamento das áreas invadidas por Pinus sp. O método demonstrou útil para classificação de imagens em geral, podendo ser utilizado no manejo de outras espécies vegetais exóticas, ou até em outras aplicações ambientais.

Implementing an object-based multi-index protocol for mapping surface glacier facies from Chandra-Bhaga basin, Himalaya

2019 ◽  
Vol 9 (2) ◽  
pp. 125-140
Author(s):  
Shridhar Digambar Jawak ◽  
Sagar Filipe Wankhede ◽  
Alvarinho Joaozinho Luis ◽  
Prashant Hemendra Pandit ◽  
Shubhang Kumar
Keyword(s):  
High Resolution ◽  
Mass Balance ◽  
Structural Characteristics ◽  
Multi Index ◽  
Spectral Bands ◽  
High Resolution Imagery ◽  
Object Based ◽  
Band Ratioing ◽  
Very High Resolution Imagery ◽  
Very High

Surface glacier facies are superficial expressions of a glacier that are distinguishable based on differing spectral and structural characteristics according to their age and inter-mixed impurities. Increasing bodies of literature suggest that the varying properties of surface glacier facies differentially influence the melt of the glacier, thus affecting the mass balance. Incorporating these variations into distributed mass balance modelling can improve the perceived accuracy of these models. However, detecting and subsequently mapping these facies with a high degree of accuracy is a necessary precursor to such complex modelling. The variations in the reflectance spectra of various glacier facies permit multiband imagery to exploit band ratios for their effective extraction. However, coarse and medium spatial resolution multispectral imagery can delimit the efficacy of band ratioing by muddling the minor spatial and spectral variations of a glacier. Very high-resolution imagery, on the other hand, creates distortions in the conventionally obtained information extracted through pixel-based classification. Therefore, robust and adaptable methods coupled with higher resolution data products are necessary to effectively map glacier facies. This study endeavours to identify and isolate glacier facies on two unnamed glaciers in the Chandra-Bhaga basin, Himalayas, using an established object-based multi-index protocol. Exploiting the very high resolution offered by WorldView-2 and its eight spectral bands, this study implements customized spectral index ratios via an object-based environment. Pixel-based supervised classification is also performed using three popular classifiers to comparatively gauge the classification accuracies. The object-based multi-index protocol delivered the highest overall accuracy of 86.67%. The Minimum Distance classifier yielded the lowest overall accuracy of 62.50%, whereas, the Mahalanobis Distance and Maximum Likelihood classifiers yielded overall accuracies of 77.50% and 70.84% respectively. The results outline the superiority of the object-based method for extraction of glacier facies. Forthcoming studies must refine the indices and test their applicability in wide ranging scenarios.

scholarly journals Using very high resolution (VHR) imagery within a GEOBIA framework for gully mapping: an application to the Calhoun Critical Zone Observatory

2019 ◽  
Vol 22 (1) ◽  
pp. 219-234 ◽  
Author(s):  
A. Francipane ◽  
G. Cipolla ◽  
A. Maltese ◽  
G. La Loggia ◽  
L. V. Noto
Keyword(s):  
High Resolution ◽  
Critical Zone ◽  
Soil Productivity ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Critical Zone Observatory ◽  
Geographic Object ◽  
Widespread Availability ◽  
New Methodologies ◽  
Very High

Abstract Gully erosion is a form of accelerated erosion that may affect soil productivity, restrict land use, and lead to an increase of risk to infrastructure. An accurate mapping of these landforms can be difficult because of the presence of dense canopy and/or the wide spatial extent of some gullies. Even where possible, mapping of gullies through conventional field surveying can be an intensive and expensive activity. The recent widespread availability of very high resolution (VHR) imagery has led to a remarkable growth in the availability of terrain information, thus providing a basis for the development of new methodologies for analyzing Earth's surfaces. This work aims to develop a geographic object-based image analysis to detect and map gullies based on VHR imagery. A 1-meter resolution LIDAR DEM is used to identify gullies. The tool has been calibrated for two relatively large gullies surveyed in the Calhoun Critical Zone Observatory (CCZO) area in the southeastern United States. The developed procedure has been applied and tested on a greater area, corresponding to the Holcombe's Branch watershed within the CCZO. Results have been compared to previous works conducted over the same area, demonstrating the consistency of the developed procedure.

scholarly journals Rural Road Extraction using Object Based Image Analysis (OBIA): A case study from Assam, India

2019 ◽  
Vol 1 ◽  
pp. 1-8
Author(s):  
Ankita Medhi ◽  
Ashis Kumar Saha
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Rural Areas ◽  
Extraction Methods ◽  
Rural Roads ◽  
Object Based Image Analysis ◽  
Rural Road ◽  
Object Based ◽  
The Status ◽  
Very High

<p><strong>Abstract.</strong> Rural roads in India have been considered as significant component for overall rural development. In India, the status of rural road connectivity is not up to the mark in some of the states. For providing better connectivity in the rural areas the information on roads are considered important. Detailed mapping of the roads can be useful for planning further road connectivity and proving access to facilities in the rural areas. For detailed mapping of roads higher resolution satellite imageries are required. Object based Image Analysis (OBIA) has emerged as a promising map analysis approach using high and very high resolution imageries. Feature extraction is one of the important aspect in OBIA extracting features such as roads, buildings, water bodies and other important features of interest from the high resolution imageries. In the present study, an attempt has been made to extract rural roads of Titabor in Jorhat district of Assam (India). Various OBIA based extraction methods have been used for extracting roads using high &amp; very high resolution Resourcesat-II (5.8&amp;thinsp;m) and Kompsat imagery (2.8&amp;thinsp;m MS &amp;amp; 0.7&amp;thinsp;m PAN). The results have been compared and relative advantages were evaluated.</p>

scholarly journals Comparison of pixel to pixel and object-based image analysis with using WorldView-2 satellite images of Yangiobod village of Syrdarya province

2020 ◽  
Vol 26 (2) ◽  
pp. 313-321
Author(s):  
Aybek Arifjanov ◽  
Shamshodbek Akmalov ◽  
Tursunoy Apakhodjaeva ◽  
Dilmira Tojikhodjaeva
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Field Experiments ◽  
Global Analysis ◽  
Satellite Image ◽  
Advantages And Disadvantages ◽  
Object Based Image Analysis ◽  
Object Based ◽  
Image Capturing ◽  
Very High

Currently, more than 300 satellites have been launched into space and providing us with information about the Earth and processes which happens in there. Those information is very useful in all branches. These satellites started to modify and modernize year by year. Especially after 2000, satellites of very high resolution were launched into space. These satellites are sending information with very high resolution. To improve the speed and accuracy of the analysis of these images, scientists have developed a number of methods and programs. As a result, users often find face to difficulties with knowing which method or program is most effective. In this article, analyzed many researches and scientific studies and analyzed WorldView-2 (WV2) images of the Syrdarya Province based on field experiments and outlined the advantages and disadvantages of the method and tool. WV2 images are very important and provide much relevant data for all image analysis. VHR of these images can increase the quality and possibilities of all analysis. But usage of these images globally has not developed because of their costs. Square of satellite image capturing is very little for global analysis. to do global analysis we need 100 s of this image. That is why scientists use this data more often for correlation or creating general methods. That is why it has not been used for regional and global analysis. In our research, we used GEOBIA’s eCognition software. The accuracy of this program is 95 %. In arid regions like Uzbekistan, we recommend optimal software, analyse steps and data.

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