Junteng Luo, Liang Liu, Jianghua Zheng, Jun Lin, Wanqiang Han, Yang Yan, Jianhao Li, Feifei Zhang, Zhong Liang, Qige Qi
{"title":"基于种群密度和生境适宜性的遥感与集成模型的斜体螯虾危险区识别与分类","authors":"Junteng Luo, Liang Liu, Jianghua Zheng, Jun Lin, Wanqiang Han, Yang Yan, Jianhao Li, Feifei Zhang, Zhong Liang, Qige Qi","doi":"10.1016/j.jag.2026.105498","DOIUrl":null,"url":null,"abstract":"<div><div>Locust outbreaks remain a major challenge to global ecological and environmental security. <em>Calliptamus italicus</em> is the most common migratory locust in the China-Kazakhstan border region. Although relevant countries are actively carrying out control, the excessively large control area has become an important burden. Previous studies have mapped its potential suitable areas, but most studies used only a single model and focused only on suitability changes. Limited attention has been paid to the effect of density on population distribution. This study identifies risk zones by integrating potential suitable areas with population density. It aims to enhance suitable habitat prediction and is of great significance for improving locust control. Based on five categories of Earth observation data and field-surveyed occurrence and density data, this study constructed a regional risk zoning framework using nine models, geographical detector, and path analysis. The ensemble model yielded an AUC value of 0.98, outperforming previous studies in this region. The suitable areas of <em>Calliptamus italicus</em> showed a radial spatial pattern expanding outward from highly suitable areas. Seasonal temperature and precipitation, vegetation condition, and soil texture had the highest explanatory power for regional locust density, and formed multiple impact pathways. Risk zones were distributed in the northern part of the study area and the transboundary continuous grassland belt, and gradually extended toward the central region, showing an overall banded or mosaic spatial pattern. A spatial mismatch existed between suitable areas and risk zones, highlighting the complementary value of field-measured density data in locust risk assessment. This framework helps provide a new perspective for pest management and control under climate change.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"152 ","pages":"Article 105498"},"PeriodicalIF":8.2000,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Identification and classification of risk zones for Calliptamus italicus based on remote sensing and ensemble modeling: considering population density and habitat suitability\",\"authors\":\"Junteng Luo, Liang Liu, Jianghua Zheng, Jun Lin, Wanqiang Han, Yang Yan, Jianhao Li, Feifei Zhang, Zhong Liang, Qige Qi\",\"doi\":\"10.1016/j.jag.2026.105498\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Locust outbreaks remain a major challenge to global ecological and environmental security. <em>Calliptamus italicus</em> is the most common migratory locust in the China-Kazakhstan border region. Although relevant countries are actively carrying out control, the excessively large control area has become an important burden. Previous studies have mapped its potential suitable areas, but most studies used only a single model and focused only on suitability changes. Limited attention has been paid to the effect of density on population distribution. This study identifies risk zones by integrating potential suitable areas with population density. It aims to enhance suitable habitat prediction and is of great significance for improving locust control. Based on five categories of Earth observation data and field-surveyed occurrence and density data, this study constructed a regional risk zoning framework using nine models, geographical detector, and path analysis. The ensemble model yielded an AUC value of 0.98, outperforming previous studies in this region. The suitable areas of <em>Calliptamus italicus</em> showed a radial spatial pattern expanding outward from highly suitable areas. Seasonal temperature and precipitation, vegetation condition, and soil texture had the highest explanatory power for regional locust density, and formed multiple impact pathways. Risk zones were distributed in the northern part of the study area and the transboundary continuous grassland belt, and gradually extended toward the central region, showing an overall banded or mosaic spatial pattern. A spatial mismatch existed between suitable areas and risk zones, highlighting the complementary value of field-measured density data in locust risk assessment. This framework helps provide a new perspective for pest management and control under climate change.</div></div>\",\"PeriodicalId\":73423,\"journal\":{\"name\":\"International journal of applied earth observation and geoinformation : ITC journal\",\"volume\":\"152 \",\"pages\":\"Article 105498\"},\"PeriodicalIF\":8.2000,\"publicationDate\":\"2026-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of applied earth observation and geoinformation : ITC journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1569843226004140\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2026/7/27 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843226004140","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/7/27 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Identification and classification of risk zones for Calliptamus italicus based on remote sensing and ensemble modeling: considering population density and habitat suitability
Locust outbreaks remain a major challenge to global ecological and environmental security. Calliptamus italicus is the most common migratory locust in the China-Kazakhstan border region. Although relevant countries are actively carrying out control, the excessively large control area has become an important burden. Previous studies have mapped its potential suitable areas, but most studies used only a single model and focused only on suitability changes. Limited attention has been paid to the effect of density on population distribution. This study identifies risk zones by integrating potential suitable areas with population density. It aims to enhance suitable habitat prediction and is of great significance for improving locust control. Based on five categories of Earth observation data and field-surveyed occurrence and density data, this study constructed a regional risk zoning framework using nine models, geographical detector, and path analysis. The ensemble model yielded an AUC value of 0.98, outperforming previous studies in this region. The suitable areas of Calliptamus italicus showed a radial spatial pattern expanding outward from highly suitable areas. Seasonal temperature and precipitation, vegetation condition, and soil texture had the highest explanatory power for regional locust density, and formed multiple impact pathways. Risk zones were distributed in the northern part of the study area and the transboundary continuous grassland belt, and gradually extended toward the central region, showing an overall banded or mosaic spatial pattern. A spatial mismatch existed between suitable areas and risk zones, highlighting the complementary value of field-measured density data in locust risk assessment. This framework helps provide a new perspective for pest management and control under climate change.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.