干旱区生态环境知识资源中心(Arid): Assessing soil productivity potential in arid region using remote sensing vegetation indices

Arid

DOI	10.1016/j.jaridenv.2024.105166
	Assessing soil productivity potential in arid region using remote sensing vegetation indices
	Fadl, Mohamed E.; AbdelRahman, Mohamed A. E.; El-Desoky, Ahmed I.; Sayed, Yasser A.
通讯作者	AbdelRahman, MAE
来源期刊	JOURNAL OF ARID ENVIRONMENTS
ISSN	0140-1963
EISSN	1095-922X
出版年	2024
卷号	222
英文摘要	Remote sensing techniques offer practical benefits, particularly in sensitive ecosystems or areas with limited accessibility. However, field surveys allow for more accurate and detailed information about soil properties and productivity. Therefore, it is often recommended to combine remote sensing techniques with field surveys in order to obtain comprehensive and reliable results. The underlying basis of this study involves analyzing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Soil Adjusted Vegetation Index (SAVI), as indicators of soil productivity. By utilizing biomass density as an additional indicator, the study aims to provide valuable insights into the productivity potential of agricultural areas. The results demonstrate a positive association between the Soil Productivity Rating (SPR) and wheat yield values for the year 2022, as evidenced by a coefficient of determination (r 2 ) value of 0.8214. This value indicates a moderately strong correlation between the SPR classes and wheat yields. Throughout the Ripening period, the NDVI and EVI indices exhibited a relatively strong correlation coefficient (r 2 = 0.987 and 0.873, respectively). On the other hand, the SAVI index displayed moderate to strong accuracy in estimating crop yield, with a coefficient of determination (r 2 ) ranging from 0.819 to 0.908. These results suggest that the NDVI index serves as the most dependable predictor of yield during all vegetation periods. This study provides a comprehensive understanding of soil productivity, but further research using controlled trial patterns with differential reference plants is needed for validation and improvement.
英文关键词	Remote sensing soil productivity rating SAVI NDVI EVI
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:001241649400001
WOS关键词	PRECISION AGRICULTURE ; SPECTRAL REFLECTANCE ; CHLOROPHYLL CONTENT ; ORGANIC-MATTER ; TIME-SERIES ; WHEAT ; PREDICTION ; MANAGEMENT ; FERTILITY ; NUTRIENT
WOS类目	Ecology ; Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/404350
推荐引用方式 GB/T 7714	Fadl, Mohamed E.,AbdelRahman, Mohamed A. E.,El-Desoky, Ahmed I.,et al. Assessing soil productivity potential in arid region using remote sensing vegetation indices[J],2024,222.
APA	Fadl, Mohamed E.,AbdelRahman, Mohamed A. E.,El-Desoky, Ahmed I.,&Sayed, Yasser A..(2024).Assessing soil productivity potential in arid region using remote sensing vegetation indices.JOURNAL OF ARID ENVIRONMENTS,222.
MLA	Fadl, Mohamed E.,et al."Assessing soil productivity potential in arid region using remote sensing vegetation indices".JOURNAL OF ARID ENVIRONMENTS 222(2024).