Fully Convolutional Neural Networks for Mapping Oil Palm Plantations in Kalimantan
This research is motivated by the global warming problem, which is likely influenced by human activity. Fast-growing oil palm plantations in the tropical belt of Africa, Southeast Asia and parts of Brazil lead to significant loss of rainforest and contribute to the global warming by the corresponding decrease of carbon dioxide absorption. We propose a novel approach to monitoring of the development of such plantations based on an application of state-of-the-art Fully Convolutional Neural Networks (FCNs) to solve Semantic Segmentation Problem for Landsat imagery.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (ISPRS Archives) is the series of peer-reviewed proceedings published by the International Society of Photogrammetry and Remote Sensing (ISPRS). In the early years of the Society, Archive Volumes were published independent of Congress or Technical Commission Symposia.
For the first time spatio-temporal characteristics of air pollution by sulfur dioxide (SO2), nitrogen dioxide (NO2), carbon dioxide (CO2), carbon monoxide (CO) and aerosol over Ukraine and Europe are established. It was shown that moderate risks of air pollution by sulfur dioxide of eastern and western parts of Ukraine relate as 2:1. It was shown that values of moderate and high risks of European areas most polluted by aerosol (except the north of Italy) and Ukraine (Kyiv, Donetsk and Odessa regions) are approximately related as 1:1. Moderate levels of risks for Kiev, Donetsk and Odessa regions relate to moderate risk levels of other Ukrainian regions as 1.8:1. The maximum risk value of moderate pollution by nitrogen dioxide of the atmosphere of Europe and Ukraine relate as 3:1. The analysis of concentration dynamics of carbon dioxide for atmosphere of the whole earth for the last 8 years (2004–2011) revealed the increase for more than 20 ppm. It is shown that the atmosphere of Ukraine exposed to the same level of carbon monoxide pollution, as the atmosphere of other European countries.
Worth of wetland sites lies in their ecological importance. They enhance ecosystem via provision of ecological services like improving water quality, groundwater infiltration, flood risk reduction and biodiversity regulation. Like other parts of the world Pakistan is also facing wetlands degradation. Ecological and economic significance of wetlands was recognized officially in 1971 as Pakistan became signatory of Ramsar wetland convention. Wetlands provide habitat to species of ecological and economic importance. Despite being recognized for international importance, Ramsar figures state that almost half of Pakistan’s wetlands are at moderate or prominent level threat. Wetlands ecosystems are deteriorating at a rapid rate, if uncontrolled this trend may lead to substantial losses. Therefore, management of these resources demands regular monitoring. Present study is dedicated to assessing levels of change overtime in three distinct types of wetlands in Pakistan i.e. Indus delta a coastal wetland, Uchhali complex an inland wetland which are both protected sites while another site Nurri Lagoon which is not sheltered under any category of protected areas. Remotely sensed data has remarkable applications in change detection. Multitemporal Landsat images were used to map changes occurring from 2006 to 2016. Results reveal that wetland area has considerably decreased for all types. Both protected sites have experienced degradation though impact is comparatively lesser than unprotected Nurri lagoon. Significance of protection strategies cannot be denied, it is recommended that mere declaration of a site protected area is not sufficient. It is equally important to control non-point pollutants and ensuring the compliance of conservation strategy.
The archives of measurements at a network of stations of Roshydromet stocks of available water capacity and satellite measurements of relative soil moisture topsoil according with the instrument ASCAT (MetOp satellites) were used. The estimation of the statistical structure of the fields of available water capacity in the upper 10- and 20-cm soil layers, correlations were found between the data of remote sensing (RS) data and agrometeorological stations. Developed procedure for automated pre-control ground-based measurements. The algorithm is statistically optimal transform of remote sensing data in estimating the amount of moisture in the upper soil layer.
To date, all remote sensing data are represented and stored as temporal sequences of separate “snapshots” – rasters or grids. This makes impossible to quickly obtain a time series of a variable values for the full available period for a region of a coordinate grid. Trend research – one of the most important topics in Earth science – becomes extremely complex and time consuming. This paper proposes an alternative data representation and corresponding storage technique. The data are represented as a collection of individual time series, one per each grid cell or raster pixel. New storage layout enables any time series to be always readily accessible. This approach considerably facilitates the application of existing time series techniques to remote sensing, climate reanalysis and similar data as well as provides new research and development opportunities not available before.
This 2-volume set constitutes the refereed proceedings of the 9th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2019, held in Madrid, Spain, in July 2019.
The 99 papers in these volumes were carefully reviewed and selected from 137 submissions. They are organized in topical sections named:
Part I: best ranked papers; machine learning; pattern recognition; image processing and representation.
Part II: biometrics; handwriting and document analysis; other applications.
The article analyzes the near-Earth space as a future habitat for humankind. This article investigates the factors affecting the location in this environment. We estimate the boundaries of space and related space. The article highlights the main features of the near-Earth space as a human-friendly environment.
For the first time, using satellite Earth remote sensing data, the maps of air pollution risks by nitrogen dioxide (NO2) over the territory of Europe with spatial resolution of 0.25º×0.25º (approximately 27.5 km × 18 km for the 48º latitude) were created. The suggested risk calculation technique is simple yet delivers extensive understanding of typical air pollution character. It is shown that the highest risks of air pollution by nitrogen dioxide in Europe are observed over Germany, Belgium, Netherlands and southern part of the North Sea as well as over large cities.