scholarly journals Geographic Distribution of Desert Locusts in Africa, Asia and Europe Using Multiple Sources of Remote-Sensing Data

2020 ◽  
Vol 12 (21) ◽  
pp. 3593
Author(s):  
Chaoliang Chen ◽  
Jing Qian ◽  
Xi Chen ◽  
Zengyun Hu ◽  
Jiayu Sun ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Logistic Regression ◽  
Regression Model ◽  
Geographic Distribution ◽  
Logistic Regression Model ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Desert Locust ◽  
Sensing Data ◽  
Potential Habitats

In history, every occurrence of a desert locust plague has brought a devastating blow to local agriculture. Analyses of the potential geographic distribution and migration paths of desert locusts can be used to better monitor and provide early warnings about desert locust outbreaks. By using environmental data from multiple remote-sensing data sources, we simulate the potential habitats of desert locusts in Africa, Asia and Europe in this study using a logistic regression model that was developed based on desert locust monitoring records. The logistic regression model showed high accuracy, with an average training area under the curve (AUC) value of 0.84 and a kappa coefficient of 0.75. Our analysis indicated that the temperature and leaf area index (LAI) play important roles in shaping the spatial distribution of desert locusts. A model analysis based on data for six environmental variables over the past 15 years predicted that the potential habitats of desert locust present a periodic movement pattern between 40°N and 30°S latitude. The area of the potential desert locust habitat reached a maximum in July, with a suitable area exceeding 2.77 × 107 km2 and located entirely between 0°N and 40°N in Asia-Europe and Africa. In December, the potential distribution of desert locusts reached its minimum area at 0.68 × 107 km2 and was located between 30°N and 30°S in Asia and Africa. According to the model estimates, desert locust-prone areas are distributed in northern Ethiopia, South Sudan, northwestern Kenya, the southern Arabian Peninsula, the border area between India and Pakistan, and the southern Indian Peninsula. In addition, desert locusts were predicted to migrate from east to west between these areas and in Africa between 10°N and 17°N. Countries in these areas should closely monitor desert locust populations and respond rapidly.

scholarly journals Surge potential and drainage-basin characteristics in East Greenland

2003 ◽  
Vol 36 ◽  
pp. 142-148 ◽  
Author(s):  
Hester Jiskoot ◽  
Tavi Murray ◽  
Adrian Luckman
Keyword(s):  
Remote Sensing ◽  
Drainage Basin ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Glacier Inventory ◽  
East Greenland ◽  
Sensing Data ◽  
Logistic Analysis ◽  
Geological Conditions ◽  
Multivariate Logistic Analysis

AbstractWe introduce a new glacier inventory of central East Greenland and use the collected data to test proposed theories on surging. The glacier inventory contains 259 glaciers, of which 10 have observed surges and a further 61 are inferred surge-type. The total glaciated area is 5.5×103 km2. The inventory was created from a combination of remote-sensing data and maps, and some 24 glacial and geological inventory parameters were collected for each glacier. A multivariate logistic analysis is used to test which combination of glacial and environmental data is conducive to surging behaviour in East Greenland. Three different models suggest that glaciers with a large complexity, low slope and oriented in a broad arc from northeast to south are most likely to be of surge type. Geological conditions, and hence substrate character, appeared not to be related to surge potential. On the basis of these results and the surge dynamics in this region, we suggest a hydrologically controlled surge mechanism operates in central East Greenland.

scholarly journals Environmental Quality Assessment of Urban Ecology based on Spatial Heterogeneity and Remote Sensing Imagery

2019 ◽  
Author(s):  
Iswari Nur Hidayati ◽  
R Suharyadi ◽  
Projo Danoedoro
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Heterogeneity ◽  
Urban Ecology ◽  
Vegetation Cover ◽  
Land Use Changes ◽  
Remote Sensing Data ◽  
Environmental Data ◽  
Ecological Index ◽  
Sensing Data

The phenomenon of urban ecology is very comprehensive, for example, rapid land-use changes, decrease in vegetation cover, dynamic urban climate, high population density, and lack of urban green space. Temporal resolution and spatial resolution of remote sensing data are fundamental requirements for spatial heterogeneity research. Remote sensing data is very effective and efficient for measuring, mapping, monitoring, and modeling spatial heterogeneity in urban areas. The advantage of remote sensing data is that it can be processed by visual and digital analysis, index transformation, image enhancement, and digital classification. Therefore, various information related to the quality of urban ecology can be processed quickly and accurately. This study integrates urban ecological, environmental data such as vegetation, built-up land, climate, and soil moisture based on spectral image response. The combination of various indices obtained from spatial data, thematic data, and spatial heterogeneity analysis can provide information related to urban ecological status. The results of this study can measure the pressure of environment caused by human activities such as urbanization, vegetation cover and agriculture land decreases, and urban micro-climate phenomenon. Using the same data source indicators, this method is comparable at different spatiotemporal scales and can avoid the variations or errors in weight definitions caused by individual characteristics. Land use changes can be seen from the results of the ecological index. Change is influenced by human behavior in the environment. In 2002, the ecological index illustrated that regions with low ecology still spread. Whereas in 2017, good and bad ecological indices are clustered.

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

Insects ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 233 ◽  
Author(s):  
Igor Klein ◽  
Natascha Oppelt ◽  
Claudia Kuenzer
Keyword(s):  
Remote Sensing ◽  
Remote Sensing Data ◽  
Effective Control ◽  
Nomadacris Septemfasciata ◽  
Pest Species ◽  
Desert Locust ◽  
Red Locust ◽  
Migratory Locust ◽  
Sensing Data ◽  
And Control

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.

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