Plant communities and solitary Desert Locust abundance                     in the Algerian Sahara, compared to other African countries

Mahdjoubi, Djillali; Guendouz-Benrima, Atika

doi:10.1127/phyto/2017/0124

Cited by 2 publications

(1 citation statement)

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“…Through calculation, this paper found that the red band (band 4), the near-infrared band (band 5), and shortwave infrared band 1 (band 6) were most suitable for simultaneous classification. Furthermore, vegetation is the main food source and suitable living environment for locusts [35][36][37], and NDVI is the best factor to reflect the vegetation health situation [38], so this study took NDVI as a band to be a part of the classification. In summary, the final features involved in the classification were red, nearred, shortwave infrared band 1, and NDVI.…”

Section: Habitat Classification Methodsmentioning

confidence: 99%

Study on the Forming Mechanism of the High-Density Spot of Locust Coupled with Habitat Dynamic Changes and Meteorological Conditions Based on Time-Series Remote Sensing Images

et al. 2022

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The outbreak of the Asian migratory locust (Locusta migratoria migratoria) (AML) can deal a great blow to agriculture and grassland farming. The emergence of high-density locusts facilitates the outbreak of locusts. Understanding the forming mechanism of the high-density spot of locust (HDSL) is very important for locust monitoring and control. To achieve this goal, this paper took Nong’an County, which used to form an HDSL in 2017, as the study area. Firstly, based on the habitat classification system, support vector machine (SVM), random forest (RF), and maximum likelihood (ML) methods were employed to explore the best classification method for locust habitats. Then, the optimal method was applied to monitor habitat dynamic changes from 2014 to 2017 in the HDSL in Nong’an. Finally, the HDSL forming mechanism was clarified coupled with habitat dynamic changes and meteorological data. The results showed that the SVM method was the optimal method, with an accuracy of 95.28%, which is higher than the RF and ML methods by 0.25% and 8.52%, respectively. The annual increased barren land and sufficient reeds provided adequate suitable habitats for the breeding of AML. From 2014 to 2016, the temperatures during the overwintering and hatching periods were higher than the 2010–2018 average, and the precipitation during the spawning period was lower than the 2010–2018 average. The precipitation during the growing period in 2017 was 30.8 mm less than the average from 2010 to 2018. All these characteristics were conducive to the reproduction of locusts. We concluded that the suitable habitat and meteorological conditions increased the locust quantity yearly, resulting in the formation of HDSL. These results are instrumental for monitoring potential high-risk outbreak areas, which is important to improve locust control and ensure food security.

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Section: Habitat Classification Methodsmentioning

confidence: 99%