DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)

Remote sensing have become one of decisive technologies for detection and assessment of abiotic stress situations, such as snowstorms, forest fires, drought, frost, technogenic pollution etc. Present work is aiming at detection and assessment of abiotic stress of coniferous landscapes caused by uran...

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Main Authors: Lachezar Filchev, Eugenia Roumenina
Format: Article
Language:English
Published: Lomonosov Moscow State University 2012-03-01
Series:Geography, Environment, Sustainability
Subjects:
Online Access:https://ges.rgo.ru/jour/article/view/189
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spelling doaj-8fc47e0b29fe43c683c7fffd96386bcd2021-07-28T21:10:05ZengLomonosov Moscow State UniversityGeography, Environment, Sustainability2071-93882542-15652012-03-0151526610.24057/2071-9388-2012-5-1-52-66185DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)Lachezar FilchevEugenia RoumeninaRemote sensing have become one of decisive technologies for detection and assessment of abiotic stress situations, such as snowstorms, forest fires, drought, frost, technogenic pollution etc. Present work is aiming at detection and assessment of abiotic stress of coniferous landscapes caused by uranium mining using high resolution satellite data from Landsat. To achieve the aim, ground-based geochemical data and were coupled with the satellite data for two periods, i.e. prior and after uranium mining decommissioning, into a file geodatabase in ArcGIS/ArcInfo 9.2, where spatial analyses were carried out. As a result, weak and very weak relationships were found between the factor of technogenic pollution—Zc and vegetation indices NDVI, NDWI, MSAVI, TVI, and VCI. The TVI performs better compared to other indices in terms of separability among classes, whereas the NDVI and VCI correlate well than other indices with Zc.https://ges.rgo.ru/jour/article/view/189remote sensinghigh resolution satellite dataabiotic stressconiferous landscapesuranium mininglandsat
collection DOAJ
language English
format Article
sources DOAJ
author Lachezar Filchev
Eugenia Roumenina
spellingShingle Lachezar Filchev
Eugenia Roumenina
DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
Geography, Environment, Sustainability
remote sensing
high resolution satellite data
abiotic stress
coniferous landscapes
uranium mining
landsat
author_facet Lachezar Filchev
Eugenia Roumenina
author_sort Lachezar Filchev
title DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
title_short DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
title_full DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
title_fullStr DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
title_full_unstemmed DETECTION AND ASSESSMENT OF ABIOTIC STRESS OF CONIFEROUS LANDSCAPES CAUSED BY URANIUM MINING (USING MULTITEMPORAL HIGH RESOLUTION LANDSAT DATA)
title_sort detection and assessment of abiotic stress of coniferous landscapes caused by uranium mining (using multitemporal high resolution landsat data)
publisher Lomonosov Moscow State University
series Geography, Environment, Sustainability
issn 2071-9388
2542-1565
publishDate 2012-03-01
description Remote sensing have become one of decisive technologies for detection and assessment of abiotic stress situations, such as snowstorms, forest fires, drought, frost, technogenic pollution etc. Present work is aiming at detection and assessment of abiotic stress of coniferous landscapes caused by uranium mining using high resolution satellite data from Landsat. To achieve the aim, ground-based geochemical data and were coupled with the satellite data for two periods, i.e. prior and after uranium mining decommissioning, into a file geodatabase in ArcGIS/ArcInfo 9.2, where spatial analyses were carried out. As a result, weak and very weak relationships were found between the factor of technogenic pollution—Zc and vegetation indices NDVI, NDWI, MSAVI, TVI, and VCI. The TVI performs better compared to other indices in terms of separability among classes, whereas the NDVI and VCI correlate well than other indices with Zc.
topic remote sensing
high resolution satellite data
abiotic stress
coniferous landscapes
uranium mining
landsat
url https://ges.rgo.ru/jour/article/view/189
work_keys_str_mv AT lachezarfilchev detectionandassessmentofabioticstressofconiferouslandscapescausedbyuraniumminingusingmultitemporalhighresolutionlandsatdata
AT eugeniaroumenina detectionandassessmentofabioticstressofconiferouslandscapescausedbyuraniumminingusingmultitemporalhighresolutionlandsatdata
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