干旱区生态环境知识资源中心(Arid): Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security

Arid

DOI	10.3390/agronomy13051281
	Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security
	El Behairy, Radwa A.; El Arwash, Hasnaa M.; El Baroudy, Ahmed A.; Ibrahim, Mahmoud M.; Mohamed, Elsayed Said; Rebouh, Nazih Y.; Shokr, Mohamed S.
通讯作者	Shokr, MS
来源期刊	AGRONOMY-BASEL
EISSN	2073-4395
出版年	2023
卷号	13 期号:5
英文摘要	Developing countries all over the world face numerous difficulties with regard to food security. The purpose of this research is to develop a new approach for evaluating wheat's suitability for cultivation. To this end, geographical information systems (GIS) and fuzzy inference systems (FIS) are used as the most appropriate artificial intelligence (AI) tools. Outcomes of investigations carried out in the western Nile Delta, Egypt. The fuzzy inference system used was Mamdani type. The membership functions used in this work are sigmoidal, Gaussian, and zmf membership. The inputs in this research are chemical, physical, and fertility soil indices. To predict the final soil suitability using FIS, it is required to implement 81 IF-THEN rules that were written by some experts. The obtained results show the effectiveness of FIS in predicting the wheat crop's suitability compared to conventional methods. The research region is split into four classes: around 241.3 km(2) is highly suitable for wheat growth, and 224 km(2) is defined as having moderate suitability. The third soil suitability class (low), which comprises 252.73 km(2), is larger than the unsuitable class, which comprises 40 km(2). The method given here can be easily applied again in an arid region. Decision-makers may benefit from the research's quantitative findings.
英文关键词	wheat cultivation crop suitability fuzzy inference system GIS drylands
类型	Article
语种	英语
开放获取类型	gold
收录类别	SCI-E
WOS记录号	WOS:000995477100001
WOS关键词	FUZZY INFERENCE SYSTEM ; HARVESTING STRUCTURES ; SPATIAL-DISTRIBUTION ; SEMIARID REGIONS ; SOIL PROPERTIES ; RIVER-BASIN ; SCS-CN ; WATER ; MANAGEMENT ; SITES
WOS类目	Agronomy ; Plant Sciences
WOS研究方向	Agriculture ; Plant Sciences
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/395205
推荐引用方式 GB/T 7714	El Behairy, Radwa A.,El Arwash, Hasnaa M.,El Baroudy, Ahmed A.,et al. Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security[J],2023,13(5).
APA	El Behairy, Radwa A..,El Arwash, Hasnaa M..,El Baroudy, Ahmed A..,Ibrahim, Mahmoud M..,Mohamed, Elsayed Said.,...&Shokr, Mohamed S..(2023).Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security.AGRONOMY-BASEL,13(5).
MLA	El Behairy, Radwa A.,et al."Artificial Intelligence Integrated GIS for Land Suitability Assessment of Wheat Crop Growth in Arid Zones to Sustain Food Security".AGRONOMY-BASEL 13.5(2023).