...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Environmental Management >Soil degradation index developed by multitemporal remote sensing images, climate variables, terrain and soil atributes
【24h】

Soil degradation index developed by multitemporal remote sensing images, climate variables, terrain and soil atributes

机译：多立体遥感图像，气候变量，地形和土壤对土壤开发的土壤退化指数

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Studies on soil degradation are essential for environmental preservation. Since almost 30% of the global soils are degraded, it is important to study and map them for improving their management and use. We aimed to obtain a Soil Degradation Index (SDI) based on multi-temporal satellite images associated with climate variables, land use, terrain and soil attributes. The study was conducted in a 2598 km~(-2) area in Sao Paulo State, Brazil, where 1562 soil samples (0-20 cm) were collected and analyzed by conventional methods. Spatial predictions of soil attributes such as clay, cation exchange capacity (CEC) and soil organic matter (OM) were performed using machine learning algorithms. A collection of 35-year Landsat images was used to obtain a multi-temporal bare soil image, whose spectral bands were used as soil attributes predictors. The maps of clay, CEC, climate variables, terrain attributes and land use were overlaid and the K-means clustering algorithm was applied to obtain five groups, which represented levels of soil degradation (classes from 1 to 5 representing very low to very high soil degradation). The SDI was validated using the predicted map of OM. The highest degradation level obtained in 15% of the area had the lowest OM content. Levels 1 and 4 of SDI were the most representative covering 24% and 23% of the area, respectively. Therefore, satellite images combined with environmental information significantly contributed to the SDI development, which supports decision-making on land use planning and management.
机译：对土壤退化的研究对环境保护至关重要。由于近30％的全球土壤劣化，因此研究和映射它们以改善其管理和使用非常重要。我们的目标是基于与气候变量，土地利用，地形和土壤属性相关的多时间卫星图像获得土壤退化指数（SDI）。该研究在巴西圣保罗州的2598公里（-2）区进行，其中收集了1562种土壤样品（0-20cm）并通过常规方法分析。使用机器学习算法进行粘土，阳离子交换能力（CEC）和土壤有机物质（OM）的土壤属性的空间预测。使用35年的Landsat图像的集合来获得多颞裸土壤图像，其光谱带被用作土壤属性预测因子。覆盖粘土，CEC，气候变量，地形属性和土地使用的地图，并施用K-Means聚类算法以获得五组，该群体代表土壤退化水平（从1到5的类别代表非常低到非常高的土壤降解）。使用OM的预测地图验证SDI。在该区域的15％中获得的最高退化级别具有最低的OM内容。 SDI的第1和4级分别是占地24％和23％的最具代表性。因此，与环境信息相结合的卫星图像显着促进了SDI开发，支持在土地使用规划和管理方面的决策。

著录项

  • 来源
    《Journal of Environmental Management》 |2021年第1期|111316.1-111316.9|共9页
  • 作者

    Claudia Maria Nascimento; Wanderson de Sousa Mendes; Nelida Elizabet Quinonez Silvero; Raul Roberto Poppiel; Veridiana Maria Sayao; Andre Carnieletto Dotto; Natasha Valadares dos Santos; Merilyn Taynara Accorsi Amorim; Jose A.M. Dematte;

  • 作者单位

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

    Department of Soil Science College of Agriculture 'Luiz de Queiroz' University of Sao Paulo Padua Dias Avenue 11 CP 9 Piracicaba SP 13418-900 Brazil;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Soil degradation; Remote sensing; Landsat; Land use/land cover;

    机译：土壤退化;遥感;Landsat;土地使用/陆盖;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号