| Autor: |
Petre Bretcan, Daniel Dunea, Gabriel Vintescu, Danut Tanislav, Martina Zelenakova, Laurențiu Predescu, Gheorghe Șerban, Dariusz Borowiak, Ioan Rus, Daniel Andrei Sabău, Oana Mititelu-Ionuș, Maria Hueci, Alexandru Moreanu, Eduardt Samoila, Huu Duy Nguyen, Loredana Neagu Frasin, Ioana-Alexandra Mirea, Răzvan-Cristian Muntean |
| Rok vydání: |
2022 |
| Předmět: |
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| Zdroj: |
Water; Volume 14; Issue 12; Pages: 1858 |
| ISSN: |
2073-4441 |
| DOI: |
10.3390/w14121858 |
| Popis: |
In recent years, the accelerated development of the remote sensing domain and the improvement of the resolution and frequency of satellite images allowed the increase in the accuracy of the evaluation of morphometric characteristics and the spatiotemporal distribution of pit lakes, including the small ones. Our study quantitatively analyzes small-scale pit lakes in the piedmont and subsidence plains from contact with the Getic and Curvature Subcarpathians from Romania using the normalized difference water index (NDWI) and data series, with different resolutions, from Landsat 8, Google Earth, and Sentinel 2A. The problems encountered in extracting the contours of the gravel pit lakes were determined by the different resolution of the images, the uneven quality of the images exported from Google Earth, and an additional challenge was given by the diversity of the analyzed land surfaces, the land use, and the optical properties of the lakes. A comparison of the obtained NDWI values using data series from Sentinel 2A and Landsat 8 highlighted the importance of resolution and also showed a larger spectral difference between the identified water bodies and the surrounding land in favor of Sentinel 2A. Regarding the vegetation-derived indices, superior leaf area index (1.8–3) was recorded in low-lying plains and mixed areas (tall shrubs, wetlands, etc.) because the river banks have increased moisture that supports taller species with denser foliage and the sparsely vegetated areas are located in agricultural crops and in/near villages. Changes in vegetation richness and abundance can be spatiotemporally monitored using indices derived from the spectral bands of satellite imagery. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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