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Synergetic Use of Bare Soil Composite Imagery and Multitemporal Vegetation Remote Sensing for Soil Mapping (A Case Study from Samara Region’s Upland)статья
- Авторы: Chinilin Andrey V., Lozbenev Nikolay I., Shilov Pavel M., Fil Pavel P., Levchenko Ekaterina A., Kozlov Daniil N.
- Журнал: LAND
- Том: 13
- Номер: 12
- Год издания: 2024
- Первая страница: 2229
- Последняя страница: 2229
- DOI: 10.3390/land13122229
- Аннотация: This study presents an approach for predicting soil class probabilities by integratingsynthetic composite imagery of bare soil with long-term vegetation remote sensing data and soilsurvey data. The goal is to develop detailed soil maps for the agro-innovation center “Orlovka-AIC”(Samara Region), with a focus on lithological heterogeneity. Satellite data were sourced from acloud-filtered collection of Landsat 4–5 and 7 images (April–May, 1988–2010) and Landsat 8–9 images(June–August, 2012–2023). Bare soil surfaces were identified using threshold values for NDVI (<0.06),NBR2 (<0.05), and BSI (>0.10). Synthetic bare soil images were generated by calculating the medianreflectance values across available spectral bands. Following the adoption of no-till technologyin 2012, long-term average NDVI values were additionally calculated to assess the condition ofagricultural lands. Seventy-one soil sampling points within “Orlovka-AIC” were classified usingboth the Russian and WRB soil classification systems. Logistic regression was applied for pixel-basedsoil class prediction. The model achieved an overall accuracy of 0.85 and a Cohen’s Kappa coefficientof 0.67, demonstrating its reliability in distinguishing the two main soil classes: agrochernozems andagrozems. The resulting soil map provides a robust foundation for sustainable land managementpractices, including erosion prevention and land use optimization.
- Добавил в систему: Лозбенев Николай Игоревич
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | Полный текст | Chinilin_land-13-02229.pdf | 5,9 МБ | 24 декабря 2024 [NikolayLozbenev] |