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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Lomonosov Moscow State University
2012-03-01
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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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