SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA
Proper management and monitoring of the ecological condition of natural feeders are crucial for both the economy and natural environments. Armenia is no exception, and addressing this issue requires comprehensive studies combining traditional methods with remote sensing technologies. Remote sensing...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1325/2023/isprs-archives-XLVIII-1-W2-2023-1325-2023.pdf |
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| author | G. Ayvazyan S. Asmaryan |
| author_facet | G. Ayvazyan S. Asmaryan |
| author_sort | G. Ayvazyan |
| collection | DOAJ |
| description | Proper management and monitoring of the ecological condition of natural feeders are crucial for both the economy and natural environments. Armenia is no exception, and addressing this issue requires comprehensive studies combining traditional methods with remote sensing technologies. Remote sensing in agriculture utilizes various sensors and technologies to collect data about crops, soil conditions, and agricultural parameters from a distance. This study focuses on the utilization of remote sensing, including satellite imagery, to assess the ecological state of grasslands and pastures in the Syunik administrative district of Armenia. Over a 22-year period (2000–2021), the study utilized Landsat series (5,7,8) multispectral optical images processed through Google Earth Engine (GEE) to analyze changes in the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation health. The results reveal favorable trends in vegetation health across the study regions, as indicated by consistently positive Z-values in the Seasonal Mann-Kendall test. While no significant trends were observed in some areas, others showed improvements in biomass conditions. This study provides valuable insights into the resilience and health of grasslands and pastures in the Sisian and Goris regions, offering a basis for targeted interventions and strategies to preserve these ecosystems for future generations. |
| first_indexed | 2024-03-08T23:33:16Z |
| format | Article |
| id | doaj.art-e4583723b17949ada54eb4cc7734af40 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-03-08T23:33:16Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-e4583723b17949ada54eb4cc7734af402023-12-14T09:25:12ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342023-12-01XLVIII-1-W2-20231325133010.5194/isprs-archives-XLVIII-1-W2-2023-1325-2023SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIAG. Ayvazyan0S. Asmaryan1Centre for Ecological-Noosphere Studies, National Academy of Sciences, Abovyan Street 68, Yerevan 0025, ArmeniaCentre for Ecological-Noosphere Studies, National Academy of Sciences, Abovyan Street 68, Yerevan 0025, ArmeniaProper management and monitoring of the ecological condition of natural feeders are crucial for both the economy and natural environments. Armenia is no exception, and addressing this issue requires comprehensive studies combining traditional methods with remote sensing technologies. Remote sensing in agriculture utilizes various sensors and technologies to collect data about crops, soil conditions, and agricultural parameters from a distance. This study focuses on the utilization of remote sensing, including satellite imagery, to assess the ecological state of grasslands and pastures in the Syunik administrative district of Armenia. Over a 22-year period (2000–2021), the study utilized Landsat series (5,7,8) multispectral optical images processed through Google Earth Engine (GEE) to analyze changes in the Normalized Difference Vegetation Index (NDVI) as an indicator of vegetation health. The results reveal favorable trends in vegetation health across the study regions, as indicated by consistently positive Z-values in the Seasonal Mann-Kendall test. While no significant trends were observed in some areas, others showed improvements in biomass conditions. This study provides valuable insights into the resilience and health of grasslands and pastures in the Sisian and Goris regions, offering a basis for targeted interventions and strategies to preserve these ecosystems for future generations.https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1325/2023/isprs-archives-XLVIII-1-W2-2023-1325-2023.pdf |
| spellingShingle | G. Ayvazyan S. Asmaryan SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA |
| title_full | SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA |
| title_fullStr | SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA |
| title_full_unstemmed | SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA |
| title_short | SATELLITE REMOTE SENSING FOR ASSESSING THE SPATIOTEMPORAL CHANGES OF THE ECOLOGICAL STATE OF THE AGRICULTURAL LANDS IN ARMENIA |
| title_sort | satellite remote sensing for assessing the spatiotemporal changes of the ecological state of the agricultural lands in armenia |
| url | https://isprs-archives.copernicus.org/articles/XLVIII-1-W2-2023/1325/2023/isprs-archives-XLVIII-1-W2-2023-1325-2023.pdf |
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