沈艳艳, 张竞成, 沈栋, 田洋洋, 黄文江, 杨小冬. 基于多源遥感信息的作物病虫害生境评价研究进展[J]. 中国生态农业学报 (中英文), 2023, 31(7): 1012−1025. DOI: 10.12357/cjea.20220930
引用本文: 沈艳艳, 张竞成, 沈栋, 田洋洋, 黄文江, 杨小冬. 基于多源遥感信息的作物病虫害生境评价研究进展[J]. 中国生态农业学报 (中英文), 2023, 31(7): 1012−1025. DOI: 10.12357/cjea.20220930
SHEN Y Y, ZHANG J C, SHEN D, TIAN Y Y, HUANG W J, YANG X D. Research progress on habitat suitability assessment of crop diseases and pests by multi-source remote sensing information[J]. Chinese Journal of Eco-Agriculture, 2023, 31(7): 1012−1025. DOI: 10.12357/cjea.20220930
Citation: SHEN Y Y, ZHANG J C, SHEN D, TIAN Y Y, HUANG W J, YANG X D. Research progress on habitat suitability assessment of crop diseases and pests by multi-source remote sensing information[J]. Chinese Journal of Eco-Agriculture, 2023, 31(7): 1012−1025. DOI: 10.12357/cjea.20220930

基于多源遥感信息的作物病虫害生境评价研究进展

Research progress on habitat suitability assessment of crop diseases and pests by multi-source remote sensing information

  • 摘要: 作物病虫害严重影响粮食产量和质量, 对农业生产造成巨大损失。开展作物病虫害生境适宜性评价能够对适合病虫害繁殖和流行的环境区域进行有效表征, 为病虫害预测提供重要信息。由于作物病虫害发生和流行受多种生境因素影响, 同时这些生境因素时空异质性高, 难以通过传统气象站点数据、人为调查等方式进行有效表征, 为病虫害生境评价带来较大的挑战。遥感技术的发展和成熟为病虫害生境信息表征带来重要机遇。多源遥感信息在时空异质信息表征方面具有天然优势, 同时能与传统气象站点数据形成信息互补, 为病虫害生境适宜性评价提供全面、丰富的信息, 支持生境适宜性评价模型的构建。本文对多源遥感信息在作物病虫害生境适宜性评价方面的研究进展进行综述, 重点分析多源遥感数据在寄主作物分布及生长状态、环境气象条件和景观等病虫害生境因子表征方面的潜力, 以及大范围生境适宜性评价涉及的统计模型、机器学习模型和生态位模型等建模方法。在此基础上, 提出基于多源遥感信息的作物病虫害生境评价模型构建的框架, 并对技术的发展趋势进行探讨, 为更加精准、科学的区域尺度病虫害防控管理提供技术支撑, 为病虫害统防统治和绿色防控提供科学指导。

     

    Abstract: Crop diseases and pests severely affect food yield and quality, causing significant losses in agricultural production. Habitat suitability assessments for crop diseases and pests can effectively characterize environmental areas that are suitable for the breeding and prevalence of pests and diseases, which can provide crucial information for disease and pest prediction. The occurrence and prevalence of crop diseases and pests are affected by habitat factors. These factors are highly spatially and temporally heterogeneous and are difficult to effectively characterize through traditional meteorological station data and human surveys. This poses a great challenge for the evaluation of pest and disease habitats. Fortunately, the development and maturity of remote sensing technologies present significant opportunities. Multi-source remote sensing information not only has natural advantages in the representation of spatiotemporal heterogeneity but can also form information complementarities with traditional meteorological station data. Therefore, it can provide comprehensive and abundant information for habitat suitability evaluation of pests and diseases and support model construction. This paper reviewed the research progress of multi-source remote sensing information in evaluating the habitat suitability for crop pests and diseases, focusing on the potential of multi-source remote sensing data for the characterization of habitat factors, such as host crop distribution and growth status, environmental and meteorological conditions, and landscape, as well as modeling methods, such as statistical, machine learning, and niche models in a wide-scale habitat suitability assessment. On this basis, this paper proposed a framework for crop disease and pest habitat evaluation model construction based on multi-source remote sensing information and discussed the development trends in technology. This study provides technical support for highly accurate and scientific regional prevention and management strategies. In addition, it provides scientific guidance for integrated control and green prevention.

     

/

返回文章
返回