Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index.
The Asian Migratory locust ( Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), wh...
| Publicado en: | Journal of Environmental Management Vol. 183; pp. 562 - 576 |
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| Autores principales: | , , , , , |
| Formato: | Artículo |
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Academic Press Inc.
Dec2016 Part 3
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=118569040&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 118569040 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Dec2016 Part 3 vid: 183 pid: 735 pub: Academic Press Inc. artinfo: ui: 118569040 10.1016/j.jenvman.2016.09.001 ppf: 562 ppct: 14 formats: tig: atl: Timely monitoring of Asian Migratory locust habitats in the Amudarya delta, Uzbekistan using time series of satellite remote sensing vegetation index. aug: au: Löw, Fabian Waldner, François Latchininsky, Alexandre Biradar, Chandrashekhar Bolkart, Maximilian Colditz, René R. affil: MapTailor (NGO), Rosenheim, Germany International Centre of Agricultural Research in the Dry Areas (ICARDA), Amman, Jordan Université catholique de Louvain, Earth and Life Institute, Croix du Sud, Louvain-la-Neuve, Belgium Department of Ecosystem Science and Management, University of Wyoming, Laramie, WY, 82071, USA Julius-Maximilians University, Würzburg, Germany National Commission for the Knowledge and Use of Biodiversity (CONABIO), Mexico City, DF, Mexico su: Amu Darya Migratory locust Remote-sensing images Phragmites australis Time series analysis Vegetation & climate Random forest algorithms sug: subj: Amu Darya Migratory locust Remote-sensing images Phragmites australis Time series analysis Vegetation & climate Random forest algorithms keyword: Aral Sea Land cover change Locust management MODIS Random forest Reeds Satellite earth observation Aral Sea Land cover change Locust management MODIS Random forest Reeds Satellite earth observation ab: The Asian Migratory locust ( Locusta migratoria migratoria L.) is a pest that continuously threatens crops in the Amudarya River delta near the Aral Sea in Uzbekistan, Central Asia. Its development coincides with the growing period of its main food plant, a tall reed grass (Phragmites australis), which represents the predominant vegetation in the delta and which cover vast areas of the former Aral Sea, which is desiccating since the 1960s. Current locust survey methods and control practices would tremendously benefit from accurate and timely spatially explicit information on the potential locust habitat distribution. To that aim, satellite observation from the MODIS Terra/Aqua satellites and in-situ observations were combined to monitor potential locust habitats according to their corresponding risk of infestations along the growing season. A Random Forest (RF) algorithm was applied for classifying time series of MODIS enhanced vegetation index (EVI) from 2003 to 2014 at an 8-day interval. Based on an independent ground truth data set, classification accuracies of reeds posing a medium or high risk of locust infestation exceeded 89% on average. For the 12-year period covered in this study, an average of 7504 km 2 (28% of the observed area) was flagged as potential locust habitat and 5% represents a permanent high risk of locust infestation. Results are instrumental for predicting potential locust outbreaks and developing well-targeted management plans. The method offers positive perspectives for locust management and treatment of infested sites because it is able to deliver risk maps in near real time, with an accuracy of 80% in April-May which coincides with both locust hatching and the first control surveys. Such maps could help in rapid decision-making regarding control interventions against the initial locust congregations, and thus the efficiency of survey teams and the chemical treatments could be increased, thus potentially reducing environmental pollution while avoiding areas where treatments are most likely to cause environmental degradation. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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