干旱区生态环境知识资源中心(Arid): Remote sensing-based biological and nonbiological indices for evaluating desertification in Iran: Image versus field indices

Arid

DOI	10.1002/ldr.3958
	Remote sensing-based biological and nonbiological indices for evaluating desertification in Iran: Image versus field indices
	Jafari, Reza; Abedi, Maedeh
通讯作者	Jafari, R (corresponding author), Isfahan Univ Technol, Dept Nat Resources, Esfahan 841568311, Iran.
来源期刊	LAND DEGRADATION & DEVELOPMENT
ISSN	1085-3278
EISSN	1099-145X
出版年	2021
卷号	32 期号:9 页码:2805-2822
英文摘要	Mapping and monitoring of the complex process of desertification based on ground data in broad arid and semiarid areas faces basic limitations. Therefore, the purpose of the present study was to propose a new method for mapping this phenomenon in central Iran using biological and nonbiological (BNB) indices of remote sensing products from 2003 to 2016. For this purpose, BNB indices including normalized difference vegetation index, land surface temperature, temperature vegetation dryness index, precipitation, evapotranspiration, net primary production, rain use efficiency (RUE), aridity index, and slope were extracted using MOD13A2, MOD11A2, PERSIANN-CDR, and SRTM products. After calibration and normalization of indices, they were combined using fuzzy logic and gamma operator and the combined 2003 map was validated by MEDALUS model map prepared based on ground data in 2003 using Pearson correlation and error matrix. Results showed more than 70% correlation (p < .001) as well as overall accuracy and kappa coefficient of more than 70% and 0.5 between remote sensing-based and MEDALUS-based desertification maps. According to the 2003 and 2016 maps, desertification classes including low, moderate, severe, and very severe changed from 11.9, 49.8, 34, and 4.1% to 11.11, 43.21, 40.43, and 5.24%, respectively, which indicate increasing trend of desertification in the region. The findings demonstrate the high capability of proposed method to map and monitor desertification classes. Therefore, it can be used to update existing desertification models and to report desertification condition and its positive and negative trends at local, national, and international levels.
英文关键词	arid and semiarid lands fuzzy logic land degradation MEDALUS satellite products
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000640999500001
WOS关键词	LAND-SURFACE TEMPERATURE ; VEGETATION COVER ; MEDALUS MODEL ; DEGRADATION ; SOIL ; NDVI ; CLIMATE ; ARIDITY ; AREA ; PRECIPITATION
WOS类目	Environmental Sciences ; Soil Science
WOS研究方向	Environmental Sciences & Ecology ; Agriculture
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/351081
作者单位	[Jafari, Reza; Abedi, Maedeh] Isfahan Univ Technol, Dept Nat Resources, Esfahan 841568311, Iran
推荐引用方式 GB/T 7714	Jafari, Reza,Abedi, Maedeh. Remote sensing-based biological and nonbiological indices for evaluating desertification in Iran: Image versus field indices[J],2021,32(9):2805-2822.
APA	Jafari, Reza,&Abedi, Maedeh.(2021).Remote sensing-based biological and nonbiological indices for evaluating desertification in Iran: Image versus field indices.LAND DEGRADATION & DEVELOPMENT,32(9),2805-2822.
MLA	Jafari, Reza,et al."Remote sensing-based biological and nonbiological indices for evaluating desertification in Iran: Image versus field indices".LAND DEGRADATION & DEVELOPMENT 32.9(2021):2805-2822.