A GIS for desert locust forecasting and monitoring

Healey, Richard; Robertson, Steve; Magor, J. T.; Pender, J.; Cressman, Keith

doi:10.1080/02693799608902070

Cited by 23 publications

(8 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…First of all, Healey et al [ 111 ] introduced the requirements for a GIS to support desert locust operational forecasting and monitoring. The authors underlined the importance and further implementation of weather and habitat data derived from remote sensing sources.…”

Section: Resultsmentioning

confidence: 99%

Application of Remote Sensing Data for Locust Research and Management—A Review

Klein

Oppelt

Kuenzer

2021

Insects

View full text Add to dashboard Cite

Recently, locust outbreaks around the world have destroyed agricultural and natural vegetation and caused massive damage endangering food security. Unusual heavy rainfalls in habitats of the desert locust (Schistocerca gregaria) and lack of monitoring due to political conflicts or inaccessibility of those habitats lead to massive desert locust outbreaks and swarms migrating over the Arabian Peninsula, East Africa, India and Pakistan. At the same time, swarms of the Moroccan locust (Dociostaurus maroccanus) in some Central Asian countries and swarms of the Italian locust (Calliptamus italicus) in Russia and China destroyed crops despite developed and ongoing monitoring and control measurements. These recent events underline that the risk and damage caused by locust pests is as present as ever and affects 100 million of human lives despite technical progress in locust monitoring, prediction and control approaches. Remote sensing has become one of the most important data sources in locust management. Since the 1980s, remote sensing data and applications have accompanied many locust management activities and contributed to an improved and more effective control of locust outbreaks and plagues. Recently, open-access remote sensing data archives as well as progress in cloud computing provide unprecedented opportunity for remote sensing-based locust management and research. Additionally, unmanned aerial vehicle (UAV) systems bring up new prospects for a more effective and faster locust control. Nevertheless, the full capacity of available remote sensing applications and possibilities have not been exploited yet. This review paper provides a comprehensive and quantitative overview of international research articles focusing on remote sensing application for locust management and research. We reviewed 110 articles published over the last four decades, and categorized them into different aspects and main research topics to summarize achievements and gaps for further research and application development. The results reveal a strong focus on three species—the desert locust, the migratory locust (Locusta migratoria), and the Australian plague locust (Chortoicetes terminifera)—and corresponding regions of interest. There is still a lack of international studies for other pest species such as the Italian locust, the Moroccan locust, the Central American locust (Schistocerca piceifrons), the South American locust (Schistocerca cancellata), the brown locust (Locustana pardalina) and the red locust (Nomadacris septemfasciata). In terms of applied sensors, most studies utilized Advanced Very-High-Resolution Radiometer (AVHRR), Satellite Pour l’Observation de la Terre VEGETATION (SPOT-VGT), Moderate-Resolution Imaging Spectroradiometer (MODIS) as well as Landsat data focusing mainly on vegetation monitoring or land cover mapping. Application of geomorphological metrics as well as radar-based soil moisture data is comparably rare despite previous acknowledgement of their importance for locust outbreaks. Despite great advance and usage of available remote sensing resources, we identify several gaps and potential for future research to further improve the understanding and capacities of the use of remote sensing in supporting locust outbreak- research and management.

show abstract

Section: Resultsmentioning

confidence: 99%

Application of Remote Sensing Data for Locust Research and Management—A Review

Klein

Oppelt

Kuenzer

2021

Insects

View full text Add to dashboard Cite

show abstract

“…The system operates on an UNIX-based SunSparc workstation using ArcInfo and Ingres software. Within SWARMS, data is stored in several databases and can be displayed on maps consisting of numerous thematic overlays (Healey et al, 1996).…”

Section: Data Used In Forecastingmentioning

confidence: 99%

Current methods of desert locust forecasting at FAO ¹

Cressman¹

1996

EPPO Bulletin

Self Cite

View full text Add to dashboard Cite

Desert locusts (Schistocerca gregaria) have been feared by farmers in Africa, the Near East and South‐West Asia since antiquity. Given favourable environmental conditions, locusts can rapidly breed and form highly mobile swarms which may threaten agriculture in about 60 countries covering more than 20% of the total land surface of the earth. During this century, there have been eight major plagues, the last being in 1986/1989. Periods of recession broken by the occasional relatively minor outbreak of locusts occur in between plagues. For example, there has been an outbreak of locusts in Africa since 1992 which has not reached the proportions of a true plague. FAO operates a Desert Locust Information Service to provide early warning to affected countries of potential locust invasions and advice to the international donor community. Within this service, the locust situation and environmental conditions in affected countries are monitored on a daily basis using reports from national locust survey teams, remote‐sensing imagery and meteorological data. Short and medium‐term forecasts are prepared indicating potential locust migrations and areas of breeding. These forecasts form the basis of action plans in affected countries. This paper presents a brief introduction to desert locust biology, behaviour and population dynamics and a general overview of desert locust forecasting at FAO.

show abstract

“…Among all these methods, remote soil moisture measurement is a research topic that has significant practical value. The applications of remote soil moisture measurement include monitoring plant growth [19], water resource allocation, ecosystem response to climate change [6], and prevention of floods, pests [10], sandstorms. All these applications are based on soil subsurface moisture content (SWC) detected by remote soil moisture measurement.…”

Section: Introductionmentioning

confidence: 99%

Geotechnical engineering educational modules demonstrating measurement and regulation of soil moisture

Garg

Huang

et al. 2022

Comp Applic In Engineering

View full text Add to dashboard Cite

With the rapidly changing needs of the construction industry and higher education, Conceive—Design—Implement—Operate (CDIO) educational framework is essential in delivering basics and practical aspects to undergraduate students. This study presents an attempt to explore the use of hardware and software applications for geotechnical engineering education. An example for development of hardware (Arduino UNO) and software applications (Mobile applications) for estimating soil moisture and its regulation is presented. The study provides a new learning environment, where students from civil engineering (major) can work hand to hand with that from electronics (minor) to develop applications for soil moisture measurement. A collaborative workshop is proposed and executed. The workshop includes basic concepts related to hardware (Time domain reflectometry [TDR] probe, Arduino UNO, and Water flow measurement) and software (LabVIEW and Android studio programming platforms) followed by project implementation in a group of 5–6 students. Satisfaction and comprehension were found to increase significantly for subjects (electronics and optics) to students of civil engineering background. The adopted tools represent economical means for application in conventional classrooms as well as laboratories for undergraduate students with a civil engineering background. This integration of the digital and physical world is an attempt at approaching soil mechanics mathematics from technology and arts from a scientific perspective. The examples presented in this study can be useful for developing open‐source laboratories within the framework of the undergraduate curriculum in civil engineering.

show abstract

A GIS for desert locust forecasting and monitoring

Cited by 23 publications

References 13 publications

Application of Remote Sensing Data for Locust Research and Management—A Review

Application of Remote Sensing Data for Locust Research and Management—A Review

Current methods of desert locust forecasting at FAO ¹

Geotechnical engineering educational modules demonstrating measurement and regulation of soil moisture

Contact Info

Product

Resources

About

A GIS for desert locust forecasting and monitoring

Cited by 23 publications

References 13 publications

Application of Remote Sensing Data for Locust Research and Management—A Review

Application of Remote Sensing Data for Locust Research and Management—A Review

Current methods of desert locust forecasting at FAO 1

Geotechnical engineering educational modules demonstrating measurement and regulation of soil moisture

Contact Info

Product

Resources

About

Current methods of desert locust forecasting at FAO ¹