scholarly journals Mapping Mature Post-Agricultural Forests in the Polish Eastern Carpathians with Archival Remote Sensing Data

2021 ◽  
Vol 13 (10) ◽  
pp. 2018
Author(s):  
Zofia Jabs-Sobocińska ◽  
Andrzej N. Affek ◽  
Ireneusz Ewiak ◽  
Mihai Daniel Nita
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Management Practices ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Aerial Photographs ◽  
Secondary Forests ◽  
Agricultural Lands ◽  
Sensing Data ◽  
Eastern Carpathians

Post-WWII displacements in the Polish Carpathians resulted in widespread land abandonment. Most of the pre-war agricultural areas are now covered with secondary forests, which will soon reach the felling age. Mapping their exact cover is crucial to investigate succession–regeneration processes and to determine their role in the landscape, before making management decisions. Our goal was to map post-agricultural forests in the Polish Eastern Carpathians using archival remote sensing data, and to assess their connectivity with pre-displacement forests. We used German Flown Aerial Photography from 1944 to map agricultural lands and forests from before displacements, and Corona satellite images to map agricultural lands which converted into the forest as a result of this event. We classified archival images using Object-Based Image Analysis (OBIA) and compared the output with the current forest cover derived from Sentinel-2. Our results showed that mature (60–70 years old) post-agricultural forests comprise 27.6% of the total forest area, while younger post-agricultural forests comprise 9%. We also demonstrated that the secondary forests fill forest gaps more often than form isolated patches: 77.5% of patches are connected with the old-woods (forests that most likely have never been cleared for agriculture). Orthorectification and OBIA classification of German Flown Aerial Photographs and Corona satellite images made it possible to accurately determine the spatial extent of post-agricultural forest. This, in turn, paves the way for the implementation of site-specific forest management practices to support the regeneration of secondary forests and their biodiversity.

scholarly journals DETECTION AND MONITORING OF GLOBAL CHANGES AND THE EVOLUTION IN THE REGION OF BOUZINA (AURES) USING REMOTE SENSING DATA

2015 ◽  
Vol II-2/W2 ◽  
pp. 35-40
Author(s):  
M. Mekaoussi ◽  
H. Benmessaoud
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Critical Threshold ◽  
Global Changes ◽  
Vegetable Crops ◽  
Sensing Data ◽  
Intensive Exploitation ◽  
Bare Soils

The functioning of Mediterranean ecosystems to daily or interannual scale presents an ecological and socio-economic interest. The intensive exploitation of natural resources of this ecosystem by the population has now reached a critical threshold. To this is added the effect of climate change leading to a drought that occurs mainly in the southern part. This leads to accelerated degradation of the ecosystem and requires the establishment of sustainable management rules. The objective of this study is to determine the contribution of multi-date satellite images in detecting global changes and monitoring of developments in the watershed of the Aurès Bouzina center. The approach is to use satellite images Landsat at different times (1986, 2001 and 2013) and sampling work for the confrontation with the ground truth, to conduct a thematic analysis of this environment, and view the global changes that have occurred in this area. The overall reading of the results of the tracking map changes, we notice a degradation of forest cover in ascending gradient from north to south and led to the reduction of vegetation cover drills. The area of irrigated crops registered an increase of grain. In favor of bare soils and wetlands, related to the influence of rivers, as well as the emergence of forage and vegetable crops. Bare soils dominated by a sandy texture are located primarily near areas of crops due to agricultural practices based on the intensification of agriculture as well as silting soil justified by an increase in bare soil. This work is a first step to track the degradation or restoration through ecological indicators field, related to remote sensing data.

scholarly journals ASSESSMENT OF NATURAL CONDITIONS FOR THE CONSTRUCTION OF LANDFALL OF TRANSITION OF THE BOVANENKOVO-UKHTA GAS PIPELINE THROUGH THE BAIDARATSKAYA GUBA (KARA SEA) ACCORDING TO REMOTE SENSING DATA

2021 ◽  
Vol 2 (6) ◽  
pp. 59-65
Author(s):  
S.G. Mironyuk ◽  
◽  
, O.M. Kasimova ◽  
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Kara Sea ◽  
Gas Pipeline ◽  
Aerial Photographs ◽  
River Channels ◽  
Sensing Data ◽  
Landsat Satellite ◽  
Sketch Map

The results of multi-temporal aerospace imagery of the coast of the Baydaratskaya Bay (Kara Sea) interpretation are presented. In order to draw up a sketch map for the estimated zoning of the territory according to the construction conditions of the onshore sections of the Bovanenkovo-Ukhta gas pipeline, studies were carried out. The methods, consisting of 3 stages, was used: 1) sequential of aerial photographs and satellite images interpretation of different scales; 2) spatial comparison of the obtained interpretation results with the available cartographic materials of geotechnical surveys; 3) drawing up maps and sketch maps of various contents, including the final sketch map of the estimated zoning according to the degree of favorableness of the territory for the construction of gas pipelines. Landsat satellite images (1999–2000) with a resolution of 30 m, as well as aerial photographs of 1949–1950, scale 1:60 000, covering the southern part of the coast of the Baydaratskaya Bay were used for interpretation. The retreat of the gulf coasts, changes in the configuration of the coastline, river channels in their deltaic parts, changes in the size of thermokarst lakes have been discovered over the past 50 years in the course of analysis and interpretation of Earth remote sensing data. The amount of coastal retreat varies in different parts of the coast of the Baydaratskaya Bay from 30 to 90 m, i.e. the rate of retreat of the coastline is between 0.6 and 1.8 m / year has been established. The places of development of thermokarst and polygonal wedge ice, as well as active river erosion, have been identified by deciphering signs. At the third, final stage of the studies performed, based on the analysis of natural factors that determine the patterns of distribution of the studied hazardous processes and phenomena, a schematic assessment zoning of the studied territory was carried out according to the degree of its favorableness for the construction of onshore sections of the gas pipeline. Three types of areas: unfavorable, relatively unfavorable and favorable are noted on the sketch map

scholarly journals Comparing of Landsat 8 and Sentinel 2A using Water Extraction Indexes over Volta River

2017 ◽  
Vol 10 (1) ◽  
pp. 1 ◽  
Author(s):  
Clement Kwang ◽  
Edward Matthew Osei Jnr ◽  
Adwoa Sarpong Amoah
Keyword(s):  
Remote Sensing ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Unsupervised Classification ◽  
Water Bodies ◽  
Water Extraction ◽  
Landsat 8 ◽  
Sensing Data ◽  
Optimal Classifier ◽  
Sentinel 2A

Remote sensing data are most often used in water bodies’ extraction studies and the type of remote sensing data used also play a crucial role on the accuracy of the extracted water features. The performance of the proposed water indexes among the various satellite images is not well documented in literature. The proposed water indexes were initially developed with a particular type of data and with advancement and introduction of new satellite images especially Landsat 8 and Sentinel, therefore the need to test the level of performance of these water indexes as new image datasets emerged. Landsat 8 and Sentinel 2A image of part Volta River was used. The water indexes were performed and then ISODATA unsupervised classification was done. The overall accuracy and kappa coefficient values range from 98.0% to 99.8% and 0.94 to 0.98 respectively. Most of water bodies enhancement indexes work better on Sentinel 2A than on Landsat 8. Among the Landsat based water bodies enhancement ISODATA unsupervised classification, the modified normalized water difference index (MNDWI) and normalized water difference index (NDWI) were the best classifier while for Sentinel 2A, the MNDWI and the automatic water extraction index (AWEI_nsh) were the optimal classifier. The least performed classifier for both Landsat 8 and Sentinel 2A was the automatic water extraction index (AWEI_sh). The modified normalized water difference index (MNDWI) has proved to be the universal water bodies enhancement index because of its performance on both the Landsat 8 and Sentinel 2A image.

scholarly journals Summaries of certain spatial patterns retrieved from multidate remote-sensing data

2004 ◽  
Vol 2004 (2) ◽  
pp. 287-300
Author(s):  
Hema Nair
Keyword(s):  
Remote Sensing ◽  
Genetic Algorithms ◽  
Fuzzy Logic ◽  
Spatial Patterns ◽  
Satellite Images ◽  
Remote Sensing Data ◽  
Geographic Area ◽  
Image Mining ◽  
Sensing Data

This paper presents an approach to describe patterns in remote-sensed images utilising fuzzy logic. The truth of a linguistic proposition such as “Y isF” can be determined for each pattern characterised by a tuple in the database, where Y is the pattern andFis a summary that applies to that pattern. This proposition is formulated in terms of primary quantitative measures, such as area, length, perimeter, and so forth, of the pattern. Fuzzy descriptions of linguistic summaries help to evaluate the degree to which a summary describes a pattern or object in the database. Techniques, such as clustering and genetic algorithms, are used to mine images. Image mining is a relatively new area of research. It is used to extract patterns from multidated satellite images of a geographic area.

scholarly journals Monitoring of glaciers in the Polar Urals using remote sensing Data

2020 ◽  
Vol 217 ◽  
pp. 04003
Author(s):  
Natalia Martynova ◽  
Valentina Budarova ◽  
Artem Sheremetinsky ◽  
Nikita Mezentsev
Keyword(s):  
Remote Sensing ◽  
Technological Progress ◽  
Satellite Images ◽  
Research Question ◽  
Remote Sensing Data ◽  
Field Work ◽  
Sources Of Information ◽  
Sensing Data ◽  
Polar Urals ◽  
The Polar Urals

The development of technological progress provides more opportunities for indirect monitoring of changes in the environment. Remote sensing is one of The most accessible and reliable sources of information. In this work, we used satellite images from the Landsat family. The theoretical justification of the research question is given. The research methodology was developed. Collection and processing of satellite images for various time periods. A series of schematic maps based on remote sensing Data has been created. As a result of digitization of satellite images, 9 glacier contours were obtained by year. We determined the area of the Romantics glacier and found that it lost at least 60% of its original area. These studies were used to build a series of cartographic schemes that clearly show the reduction of the glacier area. It is concluded that the use of remote sensing allows you to solve problems, monitoring the object. The use of this method allows not only to save time for field work, but also material costs for expedition equipment and various equipment. This method can be tested on any objects.

scholarly journals Estimation of forest cover restoration damaged by Siberian silkmoth using remote sensing data and maps

2019 ◽  
Vol 75 ◽  
pp. 02005
Author(s):  
Elena Fedotova
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Tree Species ◽  
Forest Cover ◽  
Remote Sensing Data ◽  
Deciduous Forests ◽  
Sensing Data ◽  
Current State

The current state of the land cover has been estimated in the territories where in different years (1885, 1955, 1995) the forests were damaged by Siberian silkmoth. Dark-needle taiga is restored through the change of tree species. In 20 years in areas of dark-needle taiga there are graminoid communities, in 60 years we have deciduous forests there, and in 130 - dark needle forests, but not everywhere.

scholarly journals Sentinel-1 and -2 Based near Real Time Inland Excess Water Mapping for Optimized Water Management

2020 ◽  
Vol 12 (7) ◽  
pp. 2854 ◽  
Author(s):  
Boudewijn van Leeuwen ◽  
Zalán Tobak ◽  
Ferenc Kovács
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Remote Sensing Data ◽  
Weather Conditions ◽  
Human Interaction ◽  
Aerial Photographs ◽  
Sensing Data ◽  
Weather Patterns ◽  
Excess Water ◽  
Frequent Monitoring

Changing climate is expected to cause more extreme weather patterns in many parts of the world. In the Carpathian Basin, it is expected that the frequency of intensive precipitation will increase causing inland excess water (IEW) in parts of the plains more frequently, while currently the phenomenon already causes great damage. This research presents and validates a new methodology to determine the extent of these floods using a combination of passive and active remote sensing data. The method can be used to monitor IEW over large areas in a fully automated way based on freely available Sentinel-1 and Sentinel-2 remote sensing imagery. The method is validated for two IEW periods in 2016 and 2018 using high-resolution optical satellite data and aerial photographs. Compared to earlier remote sensing data-based methods, our method can be applied under unfavorite weather conditions, does not need human interaction and gives accurate results for inundations larger than 1000 m2. The overall accuracy of the classification exceeds 99%; however, smaller IEW patches are underestimated due to the spatial resolution of the input data. Knowledge on the location and duration of the inundations helps to take operational measures against the water but is also required to determine the possibilities for storage of water for dry periods. The frequent monitoring of the floods supports sustainable water management in the area better than the methods currently employed.

scholarly journals Methods of calculating landslide volume using remote sensing data

2020 ◽  
Vol 149 ◽  
pp. 02009
Author(s):  
Maira Razakova ◽  
Alexandr Kuzmin ◽  
Igor Fedorov ◽  
Rustam Yergaliev ◽  
Zharas Ainakulov
Keyword(s):  
Remote Sensing ◽  
Sea Level ◽  
Remote Sensing Data ◽  
Field Studies ◽  
Aerial Photographs ◽  
Field Observations ◽  
Sensing Data ◽  
Quantitative Estimates ◽  
Landslide Volume ◽  
Engineering Protection

The paper considers the issues of calculating the volume of the landslide from remote sensing data. The main methods of obtaining information during research are field observations. The most important results of field studies are quantitative estimates, such as the volume of the embankment resulting from a landslide, morphometric indicators, etc. The study of a remote and remote object was carried out by remote methods using aerial photographs in the Ile Alatau foothills at 1,600 meters above sea level. The obtained materials from the mudflow survey will be useful in developing solutions to mitigate the effects of disasters and in the design of measures for engineering protection from landslides.

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