Mapping desertification degree and assessing its severity in Al-Ahsa Oasis, Saudi Arabia, using remote sensing-based indicators

Salih, Abdelrahim; Hassaballa, Abdalhaleem A.; Ganawa, Eltaib

doi:10.1007/s12517-021-06523-7

Cited by 10 publications

(6 citation statements)

References 35 publications

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“…Therefore, this study contributes to the body of knowledge by integrating remote sensing-derived information with expert opinions for the efficient and sustainable preservation of Al Ain oases as a case study. Moreover, in the majority of previous studies, the oases were located in rural areas [20][21][22], whereas the oases in this study are located in urban areas, and this represents a challenge for preservation. Previous studies [22,23] have demonstrated that urban and built-up areas have expanded at the expense of cultivated and bare land.…”

Section: Introductionmentioning

confidence: 86%

Integration of Analytic Hierarchy Process (AHP) and Remote Sensing to Assess Threats to Preservation of the Oases: Case of Al Ain, UAE

Yagoub,

AlSumaiti,

Tesfaldet

et al. 2023

Land

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Identifying threats to historical sites is important for formulating preventive measures to reduce their impacts. The oases in Al Ain, United Arab Emirates (UAE), are one of the historical sites and were inscribed as cultural sites in 2011 by UNESCO World Heritage Committee. This study assessed the threats to oases based on the UNESCO-listed factors affecting the outstanding universal value of the World Heritage properties. An Analytic Hierarchy Process (AHP) coupled with remote sensing was used for data collection and analysis. Expert feedback showed that water, urban expansion, soil salinity, palm disease, and the legal framework were major threats. To determine whether urban expansion influences oases preservation, remote sensing images were used to investigate land use and land cover (LULC) around the oases. The LULC change between 1972 and 2022 showed that palm trees, grass, and built-up areas increased by 59%, 76%, and 91%, respectively. The normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used to assess stress in the oases. The results indicated that oases have not been impacted by urban expansion since 1972, reflecting the UAE’s commitment to the preservation of oases. The availability of cloud-based and open-access satellite images coupled with AHP is an effective tool for understanding threats. This research aligns with UN SDG 15—“Life on Land”. The concept of this study could be used to assess threats to historical sites. It is recommended that policies for the oases’ preservation be maintained and updated to cater to issues related to population and climate change. Gray water and smart irrigation systems could be assessed as alternatives to minimize water use. Hyperspectral remote sensing is recommended for future studies related to soil salinity and palm diseases.

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Section: Introductionmentioning

confidence: 86%

Integration of Analytic Hierarchy Process (AHP) and Remote Sensing to Assess Threats to Preservation of the Oases: Case of Al Ain, UAE

Yagoub,

AlSumaiti,

Tesfaldet

et al. 2023

Land

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“…In Saudi Arabia, several causes, such as climate change, excessive groundwater use, and unsustainable farming methods, have contributed to the deterioration of soil health and desertification. The country is especially prone to these issues because of its arid climate and constrained water supplies [51][52][53][54][55][56][57].…”

Section: Importance and Challenges Of Date Palm Cultivationmentioning

confidence: 99%

Applications of AI and IoT for Advancing Date Palm Cultivation in Saudi Arabia

Mohammed,

K. Alqahtani,

Munir

et al. 2024

Internet of Things - New Insights

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Date palm cultivation is an essential part of Saudi Arabia’s economy. However, it faces several challenges: water scarcity, improper farm management, pests and diseases, inadequate farming practices, processing and marketing, and labor shortages. Artificial intelligence (AI) and the Internet of Things (IoT) can help enrich crop management, enable predictive analytics, increase efficiency, and promote sustainability in date palm cultivation. Recently, interest in this sector has begun by applying the latest precision engineering technologies integrated with AI and IoT techniques to address these challenges. This chapter aims to provide an overview of the applications of AI and IoT-based technologies, such as sensors, ML algorithms, and data analytics, and their potential benefits and challenges in supporting date palm cultivation in Saudi Arabia. Specifically, the applications of AI and IoT in smart precision irrigation, smart systems, cold storage management, pest infestation prediction, and date fruit quality optimization. In addition, the potential economic and environmental benefits of using AI and IoT in date palm cultivation in Saudi Arabia and the challenges that need to be addressed to realize these benefits fully. The chapter provides insight into the latest developments and future directions for AI and IoT in date palm cultivation, providing valuable information for researchers and policymakers.

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“…Even though Cholistan is one of the driest deserts, it has wide biodiversity because of the varied terrain in the desert comprised of trees, bushes, and a huge number of medicinal plants [14]. However, encroachment due to increased demand for agricultural land, intensive grazing, fuel-wood overcollection, frequent heat waves, and droughts is causing the severe destruction of vegetation or loss of oasis in this rainfed desert-oasis ecosystem, and the same is happening in other parts of the world [15,16]. Thus, a spatially explicit assessment of the rates and patterns of LULC changes in this area needs to be carried out for the development of informed land policy to maintain or recover the ecological integrity of this fragile ecosystem in Pakistan and others throughout the world.…”

Section: Introductionmentioning

confidence: 99%

Estimating Advance of Built-Up Area in Desert-Oasis Ecotone of Cholistan Desert Using Landsat

Ullah,

Shi,

Dasti

et al. 2023

Land

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There have been few attempts to estimate the effects of land use and land cover (LULC) on ecosystem services in desert-oasis ecotones, which are recognized as critical ecological barriers and buffers that prevent deserts from expanding into oases. This research investigated how remote sensing and geographic information technology may be used to monitor changes in LULC in the Cholistan desert and the Bahawalpur region of Pakistan between the years 2015 and 2022. The objective of this research was to identify thematic and statistical shifts in LULC in the study area due to various human interventions in the area. Landsat-8 images were processed using the maximum likelihood supervised classification technique using 500 training samples to categorize the study area into four LULC classes, i.e., desert/barren land, waterbodies, vegetation, and built-up areas, with an overall accuracy of 93% and 98% for 2015 and 2022, respectively. Results indicate a significant expansion in built-up area in 2022, which is up to 43%, agriculture and vegetation area declined by 8%, waterbodies decreased by 41%, and desert area decreased by 2% when compared with 2015. The change detection approach revealed that agricultural land was directly encroached on by rapidly increasing built-up area and urbanization as the area had an overall 19% rise in population growth within eight years with an annual growth rate of more than 3%. This study will be helpful to assess the quantity of spatial and temporal changes in the desert ecosystem, which is usually ignored by policymakers and governments due to less economic activity, although it plays a huge role in biodiversity conservation and balancing the regional ecosystem.

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Mapping desertification degree and assessing its severity in Al-Ahsa Oasis, Saudi Arabia, using remote sensing-based indicators

Cited by 10 publications

References 35 publications

Integration of Analytic Hierarchy Process (AHP) and Remote Sensing to Assess Threats to Preservation of the Oases: Case of Al Ain, UAE

Integration of Analytic Hierarchy Process (AHP) and Remote Sensing to Assess Threats to Preservation of the Oases: Case of Al Ain, UAE

Applications of AI and IoT for Advancing Date Palm Cultivation in Saudi Arabia

Estimating Advance of Built-Up Area in Desert-Oasis Ecotone of Cholistan Desert Using Landsat

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