A Landscape-Based Habitat Suitability Model (LHS Model) for Oriental Migratory Locust Area Extraction at Large Scales: A Case Study along the Middle and Lower Reaches of the Yellow River

Remote Sensing

Naichen Xing¹  Yu Ren²  Jing Wang³  Longlong Zhao⁴  Yanru Huang⁵  Yingying Dong⁵  Wenjiang Huang⁵  Ruiqi Sun⁵  Huiqin Ma⁵  Yun Geng⁵  Anting Guo⁵ 

[1] China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China;College of Urban and Environmental Sciences, Peking University, Beijing 100871, China;National Engineering Research Center for Agro-Ecological Big Data Analysis & Application, Anhui University, Hefei 230601, China;Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China;State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;

关键词: locust area extraction;    remote sensing;    landscape structure;    degree-day model;    land cover change;   

DOI  :  10.3390/rs14051058

来源: DOAJ

【 摘 要 】

The Oriental migratory locust is a destructive agricultural pest in China. Large-scale locust area (the area possessing suitable breeding habitat for locusts and has locust infestation) extraction and its evolution analysis are essential for locust ecological control. Existing methods seldom consider the spatial differences in the locust development and habitat landscape structures in large areas. To analyze these effects, our study proposed a landscape-based habitat suitability model (LHS model) for large-scale locust area extraction based on remote sensing data, taking the middle and lower reaches of the Yellow River (MLYR) as an example. Firstly, the DD model was used to simulate locust development and obtain habitat factors of the corresponding dates; secondly, the patch distribution of different land cover classes and their adjacent landscape characteristics were analyzed to determine the landscape-based factors memberships; finally, the habitat suitability index was calculated by combining the factors memberships and weights to extract the locust area. Compared with the patch-based model using moving windows (patch based-analytic hierarchy process model, R² = 0.77), the LHS model accuracy improved significantly (R² = 0.83). Our results showed that the LHS model has a better application prospect in large-scale locust area extraction. By analyzing the locust areas evolution along the MLYR extracted using the LHS model, we found human activities were the main factors affecting the locust areas evolution from 2016 to 2020, including: (1) planting the plants that locusts do not like and urbanization caused the decrease of the locust area; (2) the wetland protection policies may cause the increase of the locust area. The model and research results help locust control and prevention to realize the sustainable development of agriculture.

【 授权许可】

Unknown