SMARTEARTHTUNISIA: A BENCHMARK FOR MONITORING THE SDGS USING EARTH OBSERVATION DATA AND DEEP LEARNING TECHNIQUES IN TUNISIA

被引：0

作者：

Balti, Hanen ^{[1
]}

Rhif, Manel ^{[1
]}

Chouikhi, Farah ^{[1
,3
]}

Inoubli, Raja ^{[1
]}

Abidi, Azza ^{[1
]}

Jarray, Noureddine ^{[1
,3
]}

Ben Abbes, Ali ^{[1
,2
]}

Farah, Imed Riadh ^{[1
]}

机构：

[1] Natl Sch Comp Sci, RIADI Lab, Manouba 1001, Tunisia

[2] FRB, CESAB, F-34000 Montpellier, France

[3] Inst Arid Reg IRA Medenine, Medenine 4119, Tunisia

来源：

2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022) | 2022年

关键词：

SDG; Earth Observation; Deep learning; drought; climate change;

D O I：

10.1109/IGARSS46834.2022.9883449

中图分类号：

P [天文学、地球科学];

学科分类号：

07 ;

摘要：

The United Nations (UN) 2030 Agenda involves 17 major Sustainable Development Goals (SDGs). These SDGs have great implications for country-wide development and making plans in both developed and developing nations in the post-2015 period to 2030. The SDGs are a set of 17 interlinked global goals designed to be a plan to attain a better sustainable future by the combination of earth observation (EO) and artificial intelligence architecture. To attain the goal of global sustainable protection and utilization of terrestrial ecosystems, it is important to quantitatively determine the implementation of Sustainable development goal 15 (SDG-15) and goal 13 (SDG-13). In this paper, we focus on the integration of these SDGs in Tunisia as a new regional development plan. Thus, we present a complete benchmark that aims to solve the complicated analytical problems related to the sophisticated data type using Deep learning (DL) architecture.

引用

页码：7803 / 7806

页数：4

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