Mykola Lavreniuk

Mykola Lavreniuk
National Academy of Sciences of Ukraine | ISP · Space Research Institute

Master of Applied Science

About

100
Publications
64,556
Reads
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2,930
Citations
Citations since 2016
81 Research Items
2910 Citations
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600
20162017201820192020202120220100200300400500600

Publications

Publications (100)
Conference Paper
In the past few years, medium and high-resolution data became freely available for downloading. It provides great opportunity for researchers not to select between solving the task with high-resolution data on small territory or on global scale, but with low-resolution satellite images. Due to high spectral and spatial resolution of the data, Senti...
Article
Full-text available
Crop rotation is an important determining factor of crop productivity. Sustainable agriculture requires correct rules of crop rotation. Failure to comply with these rules can lead to deterioration of soil biochemical characteristics and land degradation. In Ukraine as well as in many other countries, sunflower monocropping is common practice and th...
Conference Paper
Full-text available
Based on modern satellite products Planet with high spatial resolution 3 meters, authors of this paper improved the neural network methodology for constructing land cover classification maps based on satellite data of high spatial resolution using the latest architectures of convolutional neural networks. The process of information features formati...
Article
Full-text available
Agriculture land appraisal analysis is an important component of the land market. This task is especially essential for Ukraine, which plans to lift the moratorium on land transactions and legalize farmland sales in 2021. Most post-Soviet countries adopted the notion of a soil bonitet—a quantitative score representing natural soil fertility. This s...
Chapter
Full-text available
Sustainable Development Goals (SDGs) indicators assessment is a very important task for today’s global scientific communities. Remote sensing data has been used to solve many problems in the process of ensuring sustainable land use and city’s management. One such example is assessment of SDG indicator 11.3.1: "Ratio of land consumption rate to popu...
Chapter
Full-text available
The ERA-PLANET Horizon 2020 project "The European Network for Observing our Changing Planet" is a contribution of the European Community for addressing the objectives of international agreements such as the Sustainable Development Goals (SDGs), the Paris Agreement on Climate and the Sendai Framework for Disaster Risk Reduction. One of the four stra...
Conference Paper
Illegal tree cutting is a big problem for developing countries. In Ukraine by official data, by 2019 118000 square meters of trees were cut illegally. The total losses this year due to illegal logging were 814 million of hryvna. This problem is still actual, because in Ukraine there is no tool for independent monitoring of forestry at the state lev...
Conference Paper
Ukraine is on the verge of the land market opening. This process should begin in 2020, when free sale of land will be introduced. Now, only the land lease is officially allowed. To ensure transparency, equity and reliability of this process, objective information on real land use and its history, crop development state in each vegetation season is...
Article
Full-text available
While people are aware that there is a continuing conflict in Ukraine, there is little understanding of its impact. The military conflict in South-Eastern Ukraine has been on-going since 2014, with a major socio-economic impact on the Donetsk and Luhansk regions. In this study, we quantify land cover land use changes in those regions related to cro...
Conference Paper
For evaluating how far we are from achieving the Sustainable Development Goals and how big the progress is a global indicator framework was developed by the Inter-Agency and Expert Group on Sustainable Development Goals Indicators (IAEG-SDGs). In this paper, we propose an improved methodology for calculating indicator 2.4.1 "Proportion of agricultu...
Article
For accurate crop classification, it is necessary to use time-series of high-resolution satellite data to better discriminate among certain crop types. This task brings the following challenges: a large amount of satellite data for download, Big data processing and computational resources for utilization of state-of-the-art classification approache...
Article
Free access to the paper for 50 days: https://authors.elsevier.com/a/1YvAs14ynSEen9 -------Cropland maps derived from satellite imagery have become a common source of information to estimate food production, support land use policies, and measure the environmental impacts of agriculture. Cropland classification models are typically calibrated with...
Conference Paper
Monitoring of agricultural regions is an important task. Recent trends to solve it are based on applying multi-temporal remote sensing in order to obtain reliable crop classification maps. If a radar remote sensing is used, speckle presence in the original data reduces a classification accuracy. A negative impact of speckle can be reduced by image...
Article
Full-text available
There is a growing recognition of the interdependencies among the supply systems that rely upon food, water and energy. Billions of people lack safe and sufficient access to these systems, coupled with a rapidly growing global demand and increasing resource constraints. Modeling frameworks are considered one of the few means available to understand...
Poster
Full-text available
We benchmark different training data sources in situ (IS), landcover-derived (LC) and crowd source (CS) for large-scale cropland mapping and to assess the accuracies of the cropland maps generated with these datasets and temporal features based on Landsat satellite data. Maps derived from CS dataset are usually more accurate than those from LC, whi...
Article
Full-text available
For evaluating the progresses towards achieving the Sustainable Development Goals (SDGs), a global indicator framework was developed by the UN Inter-Agency and Expert Group on Sustainable Development Goals Indicators. In this paper, we propose an improved methodology and a set of workflows for calculating SDGs indicators. The main improvements cons...
Article
With the unprecedented availability of satellite data and the rise of global binary maps, the collection of shared reference data sets should be fostered to allow systematic product benchmarking and validation. Authoritative global reference data are generally collected by experts with regional knowledge through photo-interpretation. During the las...
Chapter
People experience the problems of air quality every day, either inside or outdoors. The best solution to mitigate the problem inside the buildings is to open opening the windows. It is not just the most efficient, but also the cheapest solution. However, opening windows might only worsen the situation in the room in the case of excess air pollutant...
Chapter
In this paper, we propose methodology for calculating indicators of sustainable development goals within the GEOEssential project, that is a part of ERA-PLANET Horizon 2020 project. We consider indicators 15.1.1 Forest area as proportion of total land area, 15.3.1 Proportion of land that is degraded over total land area, and 2.4.1. Proportion of ag...
Article
Full-text available
The issues addressed in the article relate to the development of modern technology based on open source data compatible with the Copernicus Urban Atlas service. The city atlas of Kyiv was developed within the framework of the project H2020 ERAPLANET SMURBS (SMART URBan Solutions for air quality, disasters, and city growth). Kyiv became the first ci...
Conference Paper
Full-text available
The study explores the reference information obtained by photo-interpretation of satellite images by an international team of volunteers for accurate cropland mapping over large areas based on Landsat remote sensing data and supervised classification. JECAM teams from Argentina, Belgium, Canada, China, Russia and Ukraine had arranged the crowdsourc...
Article
Full-text available
Land cover is one of the key terrestrial variables used for monitoring and as input for modelling in support of achieving the United Nations Strategical Development Goals. Global and Continental Land Cover Products (GCLCs) aim to provide the required harmonized information background across areas; thus, they are not being limited by national or oth...
Article
З появою у вільному доступі великих обсягів супутникових даних дедалі більшої актуальності набуває розвиток методів машинного навчання на підставі геопросторових даних, зокрема, супутникових. Розглянуто основні методи машинного навчання і проаналізовано особливості та результати їх застосування до класифікації земного покриву за супутниковими даним...
Article
Full-text available
Accurate classification and mapping of crops is essential for supporting sustainable land management. Such maps can be created based on satellite remote sensing; however, the selection of input data and optimal classifier algorithm still needs to be addressed especially for areas where field data is scarce. We exploited the intra-annual variation o...
Article
Full-text available
Along the season crop classification maps based on satellite data is a challenging task for countries with large diversity of agricultural crops with different phenology (crop calendars). In this paper, we investigate feasibility of delivering early and along the season crop specific maps using available free satellite data over multiple years, inc...
Chapter
Full-text available
The last several years and onwards could be called the years of Big Free Data in domain of Remote Sensing. During the 2013-2016 period, several optical and synthetic aperture radar (SAR) remote sensing satellites were launched with high spatial resolution (10-30 m), in particular Sentinel-1A/B and Sentinel-2A within the European Copernicus program...
Chapter
Full-text available
Останні кілька років можна назвати роками «Великих об’ємів даних» в дистанційному зондуванні Землі. Протягом 2013-2016 рр. були запущені декілька оптичних та радарних (SAR) супутників дистанційного зондування з високим просторовим розрізненням (10-30 м), зокрема Sentinel-1A/B та Sentinel-2A/B в межах європейської програми Copernicus [1]. Дані набор...
Conference Paper
Data provided by synthetic aperture radar (SAR) of Sentinel satellite can be useful for many applications. However, as for any SAR image, speckle noise is present in acquired images. Speckle properties are important for different operations of SAR image processing as filtering, edge detection, segmentation, classification. Thus, we first carry out...
Conference Paper
For many applied problems in agricultural monitoring and food security, it is important to provide reliable crop classification maps. In this paper, we aim to compare performance of different filters available in ESA SNAP toolbox and compare them with our approach with applying to reduce speckle in multitemporal synthetic-aperture radar (SAR) Senti...
Article
Full-text available
Deep learning (DL) is a powerful state-of-the-art technique for image processing including remote sensing (RS) images. This letter describes a multilevel DL architecture that targets land cover and crop type classification from multitemporal multisource satellite imagery. The pillars of the architecture are unsupervised neural network (NN) that is...
Article
Full-text available
Many applied problems arising in agricultural monitoring and food security require reliable crop maps at national or global scale. Large scale crop mapping requires processing and management of large amount of heterogeneous satellite imagery acquired by various sensors that consequently leads to a " Big Data " problem. The main objective of this st...
Conference Paper
Full-text available
For accurate crop classification, it is necessary to use time-series of high-resolution satellite data to better discriminate certain crop types. This task brings the following challenges: large amount of satellite data for download, Big data processing and computational resources for utilization of the state-of-the-art classification approaches. F...
Conference Paper
Full-text available
There are no globally available high resolution satellite-derived crop specific maps at present. Only coarse-resolution imagery (> 250 m spatial resolution) has been utilized to derive global cropland extent. In 2016 we are going to carry out a country level demonstration of Sentinel-2 use for crop classification in Ukraine within the ESA Sen2-Agri...
Conference Paper
Full-text available
Land cover and crop type maps are one of the most essential inputs when dealing with environmental and agriculture monitoring tasks [1]. During long time neural network (NN) approach was one of the most efficient and popular approach for most applications, including crop classification using remote sensing data, with high an overall accuracy (OA) [...
Poster
Full-text available
Due to launch of Sentinel-2 mission European Space Agency (ESA) started Sentinel-2 for Agriculture (Sen2-Agri) project coordinated by Universite catholique de Louvain (UCL). Ukraine is selected as one of 3 country level demonstration sites for benchmarking Sentinel-2 data due to wide range of main crops (both winter and summer), big fields and high...
Article
Full-text available
In this article, the state of current research in Ukraine in the field of applied problems of Earth observations is analyzed in the context of participation of Ukraine in demonstration project of European Space Agency Sentinel-2 for Agriculture (Sen2-Agri), participation in SIGMA Project of 7th Framework Programme supported by European Commission,...
Article
Ukraine is one of the most developed agricultural countries in the world. For many applications, it is extremely important to provide reliable crop maps taking into account diversity of cropping systems used in Ukraine. The use of optical imagery only is limited due to cloud cover, and previous studies showed particular difficulties in discriminati...
Article
Full-text available
Accurate cropland information is of paramount importance for crop monitoring. This study compares five existing cropland mapping methodologies over five contrasting Joint Experiment for Crop Assessment and Monitoring (JECAM) sites of medium to large average field size using the time series of 7-day 250 m Moderate Resolution Imaging Spectroradiomete...
Article
In the paper we propose the methodology for solving the large scale classification and area estimation problems in the remote sensing domain on the basis of deep learning paradigm. It is based on a hierarchical model that includes self-organizing maps (SOM) for data preprocessing and segmentation (clustering), ensemble of multi-layer perceptrons (M...
Conference Paper
Full-text available
In the paper we propose the methodology for solving the large scale classification and area estimation problems in the remote sensing domain on the basis of deep learning paradigm. It is based on a hierarchical model that includes self-organizing maps (SOM) for data preprocessing and segmentation (clustering), ensemble of multi-layer perceptrons (M...
Article
Full-text available
Many applied Earth observation problems are based on land cover and land use maps, derived from satellite data. That is why it is important to assess their accuracy. We have developed retrospective regional 30 meter resolution land cover maps for Ukraine based on Landsat data for 1990, 2000 and 2010. As there is no reference data for validating ret...
Article
Full-text available
Along the season crop classification based on satellite data is challenging task for Ukraine because of a big diversity of different agricultural crops with different phenology (crop calendars). Taking into account the availability for free of high resolution (10 to 30 meter) optical and SAR data from different satellite, the most resource consumin...
Article
Full-text available
For many applied problems in agricultural monitoring and food security, it is important to provide reliable crop classification maps. Satellite imagery is extremely valuable source of data to provide crop maps in a timely way at moderate and high spatial resolution. Information on parcel boundaries that takes into account the spatial context may im...
Conference Paper
Full-text available
During the last years satellite data with high enough spatial and temporal resolution have become available under free and open licenses. The very large volumes of these data allow providing classification maps at global, national and regional scale in operational procedures. Crop mapping and classification of agricultural crops is extremely valuab...
Conference Paper
Full-text available
A big amount and heterogeneity of free satellite data (SAR and optical) opens room for large scale land cover and land use mapping with high resolution. Large-scale mapping of land cover and land use can be considered as a problem of automated processing of big amount of geospatial data, which may contain various uncertainties (for example, clouded...
Article
Full-text available
In this article, the current state of researches held in Ukraine in the field of applied problems of Earth studies is analyzed with orientation to international cooperation and participation in European programs outlooks. The main scientific problem is the large amount of geospatial and satellite data, for processing of which, modern methods and te...
Article
Full-text available
Large-scale mapping of land cover is considered in the paper as a problem of automated processing of big geospatial data, which may contain various uncertainties. To solve it, we propose to use three different paradigms, namely, decomposition method, the method of active learning from the scope of intelligent computations, and method of satellite i...
Article
Full-text available
This article aims at the determining the economic indicators that can be estimated with inductive based approaches and deep-learning techniques with use of satellite data, and accuracy assessment of such models. Among economic indicators index of sustainable development and the degree of harmonization are considered.
Poster
Full-text available
Crop mapping and classification of agricultural crops is important task in many countries with the large agricultural areas, particularly in Ukraine. Classification maps at global, national and regional scale is an extremely valuable source of information for many applications [1]. During the last years satellite data with high enough