scholarly journals Crop Classification of Satellite Imagery Using Synthetic Multitemporal and Multispectral Images in Convolutional Neural Networks

2021 ◽  
Vol 13 (17) ◽  
pp. 3378
Author(s):  
Guillermo Siesto ◽  
Marcos Fernández-Sellers ◽  
Adolfo Lozano-Tello
Keyword(s):  
Satellite Imagery ◽  
Low Cost ◽  
Time Frame ◽  
Multispectral Images ◽  
The European Union ◽  
Convolutional Network ◽  
The Common ◽  
Crop Classification ◽  
Sentinel 2

The demand for new tools for mass remote sensing of crops, combined with the open and free availability of satellite imagery, has prompted the development of new methods for crop classification. Because this classification is frequently required to be completed within a specific time frame, performance is also essential. In this work, we propose a new method that creates synthetic images by extracting satellite data at the pixel level, processing all available bands, as well as their data distributed over time considering images from multiple dates. With this approach, data from images of Sentinel-2 are used by a deep convolutional network system, which will extract the necessary information to discern between different types of crops over a year after being trained with data from previous years. Following the proposed methodology, it is possible to classify crops and distinguish between several crop classes while also being computationally low-cost. A software system that implements this method has been used in an area of Extremadura (Spain) as a complementary monitoring tool for the subsidies supported by the Common Agricultural Policy of the European Union.

scholarly journals A development of the Enhanced Built-up and Bareness Index (EBBI) based on combination of multi-resolution Landsat 8 and Sentinel 2 MSI images

2021 ◽  
Vol 62 (1) ◽  
pp. 1-9
Author(s):  
Hung Le Trinh ◽  
Ha Thu Thi Le ◽  
Loc Duc Le ◽  
Long Thanh Nguyen ◽  
Keyword(s):  
Land Cover ◽  
Satellite Imagery ◽  
Near Infrared ◽  
Urban Land ◽  
Urban Land Use ◽  
Landsat 8 ◽  
Infrared Band ◽  
Bare Land ◽  
Sentinel 2

Classification of built-up land and bare land on remote sensing images is a very difficult problem due to the complexity of the urban land cover. Several urban indices have been proposed to improve the accuracy in classifying urban land use/land cover from optical satellite imagery. This paper presents an development of the EBBI (Enhanced Built-up and Bareness Index) index based on the combination of Landsat 8 and Sentinel 2 multi-resolution satellite imagery. Near infrared band (band 8a), short wave infrared band (band 11) of Sentinel 2 MSI image and thermal infrared band (band 10) Landsat 8 image were used to calculate EBBI index. The results obtained show that the combination of Landsat 8 and Sentinel 2 satellite images improves the spatial resolution of EBBI index image, thereby improving the accuracy of classification of bare land and built-up land by about 5% compared with the case using only Landsat 8 images.

scholarly journals Effects of agricultural policy on the development of Slovenian agriculture during the transition and the process of accession to the European Union

2005 ◽  
Vol 50 (1) ◽  
pp. 75-88
Author(s):  
Tinea Volk
Keyword(s):  
Agricultural Policy ◽  
Agricultural Production ◽  
The European Union ◽  
Strategic Development ◽  
Development Goals ◽  
The Common ◽  
High Level ◽  
High Degree ◽  
The Eu

The thesis analyzes the development of agricultural policy and agriculture in Slovenia in the period from 1992 to 2002. The analysis is based on the classification of agricultural policy and its measures, standard indicators used for analysis of development of agricultural policy and agriculture, and specific methods for evaluating the efficiency of agricultural policy (evaluation methods, simulation methods). The results show that the transition in Slovenia caused no marked shocks for agricultural production. The development goals for agriculture were set forth early (in 1992) and were modeled on the EU standards, and they remained unchanged throughout the transition. A protectionist development concept of agricultural policy was adopted, which assured a relatively high level of support to agriculture. Under this concept, the agricultural policy was substantially reoriented during the transition, but this happened gradually and was reflected above all in the re-instrumentation of policy and changes of the structure of support to agriculture. Agricultural policy was relatively successful. It managed to achieve most of the strategic development goals of agriculture and a high degree of compatibility with the Common Agricultural Policy (CAP).

scholarly journals IMPROVED IN-SEASON CROP CLASSIFICATION PERFORMANCE USING ENSEMBLE LEARNING TECHNIQUE: A CASE STUDY OF LEKODA INSURANCE UNIT, UJJAIN, MADHYA PRADESH

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 477-481
Author(s):  
V. Pandey ◽  
K. K. Choudhary ◽  
C. S. Murthy ◽  
M. K. Poddar
Keyword(s):  
Ensemble Learning ◽  
Classification Performance ◽  
Agricultural Crop ◽  
Learning Techniques ◽  
Learning Technique ◽  
Multi Temporal ◽  
Crop Types ◽  
Crop Classification ◽  
Sentinel 2

<p><strong>Abstract.</strong> The classification of agricultural crop types is an important application of remote sensing. With the improvement in spatial, temporal and spectral resolution of satellite data, a complete seasonal crop growth profile and separability between different crop classes can be studied by using ensemble-learning techniques. This study compares the performance of Random Forest (RF), which is a decision tree based ensemble learning method and Naïve Bayes ( a probabilistic learning technique) for crop classification of <i>Lekoda</i> gram panchayat, <i>Ujjain</i> district, using multi-temporal Sentinel 2 of Rabi 2017&amp;ndash;18. The study area contains seven different classes of crop types, and in each class, we have used 65% of the ground data for training and 35% to test the classifier. The performance of RF classifier was found to be better than NB classifier. Kappa coefficient of RF classifier in mid of the crop season (December&amp;ndash;January) was found to be 0.93. This result indicates that an accurate in-season crop map of the study area can be generated through integrated use of Sentinel 2 temporal data and RF classifier.</p>

scholarly journals UAV-based training for fully fuzzy classification of Sentinel-2 fluvial scenes

2020 ◽  
Author(s):  
Patrice Carbonneau ◽  
Barbara Belletti ◽  
Marco Micotti ◽  
Andrea Casteletti ◽  
Stefano Mariani ◽  
...  
Keyword(s):  
Neural Networks ◽  
Spatial Resolution ◽  
Low Cost ◽  
Super Resolution ◽  
Training Data ◽  
Fuzzy Classification ◽  
Training Phase ◽  
Small Channels ◽  
Sentinel 2

&lt;p&gt;&lt;span&gt;In current fluvial remote sensing approaches, there exists a certain dichotomy between the analysis of small channels at local scales which is generally done with airborne data and the analysis of entire basins at regional and national scales with satellite data. &lt;/span&gt;&lt;span&gt;One possible solution to this challeng&lt;/span&gt;&lt;span&gt;e&lt;/span&gt;&lt;span&gt; is to use low-altitude imagery from low-cost UAVs to provide sub-metric scale class information which can then be used to train fuzzy classification models for entire Sentinel 2 tiles&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;The fuzzy classification approach can allow for sub-pixel information and when extended to entire Sentinel 2 tiles, the method therefore develops information at a resolution of less than 10 meters (the best spatial resolution of Sentinel 2 bands) at regional scales. &lt;/span&gt;&lt;span&gt;In &lt;/span&gt;&lt;span&gt;this&lt;/span&gt;&lt;span&gt; contribution, we present &lt;/span&gt;&lt;span&gt;such &lt;/span&gt;&lt;span&gt;a method wh&lt;/span&gt;&lt;span&gt;ere&lt;/span&gt;&lt;span&gt; UAV &lt;/span&gt;&lt;span&gt;imagery &lt;/span&gt;&lt;span&gt;is used &lt;/span&gt;&lt;span&gt;as the training data for the fully fuzzy classification of&lt;/span&gt;&lt;span&gt; Sentinel 2 imagery. &lt;/span&gt;&lt;span&gt;We partition the fluvial corridor in three simple classes: water, dry sediment and vegetation.&amp;#160; Then we manually classify the local UAV imagery into highly accurate class rasters. In order to augment the value of the Sentinel 2 data, we use an established super-resolution method that delivers 10 meter spatial resolution across all 11 Sentinel 2 bands&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;We &lt;/span&gt;&lt;span&gt;then use the sub-metric UAV classifications as training data for the 10 meter super-resolved Sentinel 2 imagery and we&lt;/span&gt;&lt;span&gt; train &lt;/span&gt;&lt;span&gt;fuzzy classification &lt;/span&gt;&lt;span&gt;models using random forests, dense neural networks and convolutional neural networks (CNN). We find that CNN architectures perform best&lt;/span&gt; &lt;span&gt;and &lt;/span&gt;&lt;span&gt;can predict class membership within a pixel of &lt;/span&gt;&lt;span&gt;a new &lt;/span&gt;&lt;span&gt;Sentinel 2 &lt;/span&gt;&lt;span&gt;tile not seen in the training phase&lt;/span&gt;&lt;span&gt; with a mean error of 0% and an RMS error of 1&lt;/span&gt;&lt;span&gt;8&lt;/span&gt;&lt;span&gt;%. Crisp class predictions derived from the fuzzy models range in accuracy from 88% to 9&lt;/span&gt;&lt;span&gt;9&lt;/span&gt;&lt;span&gt;%, &lt;/span&gt;&lt;span&gt;even in the case of tiles never seen in the training phase&lt;/span&gt;&lt;span&gt;. &lt;/span&gt;&lt;span&gt;With this approach, it is now possible to deploy a low-cost UAV in order to train a transferable CNN model that can predict &lt;/span&gt;&lt;span&gt;fuzzy classes at very large scales from freely available Sentinel 2 imagery. &lt;/span&gt; &lt;span&gt;This approach can therefore serve as the basis for multi temporal classification and change detection of the Sentinel 2 archives.&lt;/span&gt;&lt;/p&gt;

scholarly journals A Modified Fully Convolutional Network for Crack Damage Identification Compared with Conventional Methods

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Meng Meng ◽  
Kun Zhu ◽  
Keqin Chen ◽  
Hang Qu
Keyword(s):  
Large Scale ◽  
Crack Detection ◽  
Damage Identification ◽  
Low Cost ◽  
Convolutional Network ◽  
Fully Convolutional Network ◽  
Concrete Crack ◽  
The Common ◽  
Underwater Structures

Large-scale structural health monitoring and damage detection of concealed underwater structures are always the urgent and state-of-art problems to be solved in the field of civil engineering. With the development of artificial intelligence especially the combination of deep learning and computer vision, greater advantages have been brought to the concrete crack detection based on convolutional neural network (CNN) over the traditional methods. However, these machine learning (ML) methods still have some defects, such as it being inaccurate or not strong, having poor generalization ability, or the accuracy still needs to be improved, and the running speed is slow. In this article, a modified fully convolutional network (FCN) with more robustness and more effectiveness is proposed, which makes it convenient and low cost for long-term structural monitoring and inspection compared with other methods. Meanwhile, to improve the accuracy of recognition and prediction, innovations were conducted in this study as follows. Moreover, differed from the common simple deconvolution, it also includes a subpixel convolution layer, which can greatly reduce the sampling time. Then, the proposed method was verified its practicability with the overall recognition accuracy reaching up to 97.92% and 12% efficiency improvement.

Philosophcal review of h. white̕s tropological theory in the context of the new philosophy of history

2020 ◽  
Vol 3 (152) ◽  
pp. 92-99
Author(s):  
S. M. Geiko ◽  
◽  
O. D. Lauta
Keyword(s):  
Modern Science ◽  
Historical Knowledge ◽  
Text Organization ◽  
The Social ◽  
History Of ◽  
Actual Material ◽  
The Common ◽  
Historical Nature ◽  
Selection Of

The article provides a philosophical analysis of the tropological theory of the history of H. White. The researcher claims that history is a specific kind of literature, and the historical works is the connection of a certain set of research and narrative operations. The first type of operation answers the question of why the event happened this way and not the other. The second operation is the social description, the narrative of events, the intellectual act of organizing the actual material. According to H. White, this is where the set of ideas and preferences of the researcher begin to work, mainly of a literary and historical nature. Explanations are the main mechanism that becomes the common thread of the narrative. The are implemented through using plot (romantic, satire, comic and tragic) and trope systems – the main stylistic forms of text organization (metaphor, metonymy, synecdoche, irony). The latter decisively influenced for result of the work historians. Historiographical style follows the tropological model, the selection of which is determined by the historian’s individual language practice. When the choice is made, the imagination is ready to create a narrative. Therefore, the historical understanding, according to H. White, can only be tropological. H. White proposes a new methodology for historical research. During the discourse, adequate speech is created to analyze historical phenomena, which the philosopher defines as prefigurative tropological movement. This is how history is revealed through the art of anthropology. Thus, H. White’s tropical history theory offers modern science f meaningful and metatheoretically significant. The structure of concepts on which the classification of historiographical styles can be based and the predictive function of philosophy regarding historical knowledge can be refined.

The Development of Slovenia in the European Union: Social Aspects

2017 ◽  
pp. 102-108
Author(s):  
Iryna Butyrska
Keyword(s):  
Negative Impact ◽  
The State ◽  
Political Regime ◽  
The European Union ◽  
National Unity ◽  
Social Sphere ◽  
Regime Stability ◽  
Number Of Factors ◽  
The Common ◽  
The Eu

The author proves that the successful stability of independent Slovenia contributed to a number of factors, existing since its being incorporated in the SFRY. The factor, uniting the state has become the common goal – the aspiration to join the EU. The process of the European integration contributed to the modernization of a number of spheres, in particular social, cultural and economic ones. The global financial and economic crisis has revealed the turmoil in the economy of the state and its leadership was forced to gradually reduce a significant part of social privileges for the population. This caused the tension in the society and reduced the level of the national unity, having a negative impact on people’s wellbeing. However, since 2014, the Prime Minister M. Cherar has been trying to restore people’s trust in the state. The situation is getting better; indicators of trust in government are increasing, which also points to state capacity and political regime stability in Slovenia. Keywords: Slovenia, state stability, social sphere, government

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