Spatiotemporal monitoring of grasshopper habitats using multi-source data: Combined with landscape and spatial heterogeneity

• Published in: International journal of applied earth observation and geoinformation Vol. 130; p. 103838
• Main Authors: Guo, Jing, Huang, Wenjiang, Dong, Yingying, Lin, Kejian, Zhou, Yantao, Wang, Ning, Hua, Rui, Hao, Zhuoqing, Ding, Xiaolong, Zhao, Fei
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.06.2024; Elsevier
• Subjects: animal husbandry; autocorrelation; confidence interval; eggs; grasshoppers; Grassland; Habitat monitoring; habitats; instars; landscapes; meteorology; Pest; principal component analysis; regression analysis; Remote sensing; soil temperature; soil water; spatial data; spatial variation; Spatiotemporal characteristics; sustainable development; topography; vegetation; Nfvc; Grassland; GYRATE; HAA; OMinT; D2; Remote sensing; Pest; SST; OLS; Spatiotemporal characteristics; N1SM; Habitat monitoring; L-GWLR; SP

•Grasshoppers can induce several environmental problems.•Monitoring indicators are established from multi-source factors.•The occurrence of grasshoppers exhibits a certain spatial autocorrelation.•A landscape-based geographically weighted logistic regression model is proposed.•The performance of the...