Estimating potential illegal land development in conservation areas based on a presence-only model

• Published in: Journal of environmental management Vol. 321; p. 115994
• Main Authors: Lin, Jinyao, Li, Hua, Zeng, Yijuan, He, Xiaoyu, Zhuang, Yaye, Liang, Yingran, Lu, Siyan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.11.2022
• Subjects: Conservation areas; Early warning; Environmental management; Illegal development; Presence-only model; Early warning; Illegal development; Conservation areas; Presence-only model; Environmental management
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2022.115994

Conservation areas are facing increasing threats from anthropogenic land use activities. It is important to reasonably recognize and predict suspected illegal land development in advance. However, traditional methods easily suffer from selection bias due to the lack of accurate and reliable absence data. To tackle this problem, we have presented a novel method for estimating potential illegal land development based on the presence-only maximum entropy (MAXENT) model. The principle of MAXENT can guarantee that no additional unknown information (e.g., inaccurate pseudo-absence samples) will be introduced into the estimation procedure. This method was applied to the conservation areas in a fast-growing city, and the robustness of the MAXENT models was confirmed by the high AUC scores (over 0.80). The results indicated that the proposed method performs more effectively than the presence-absence random forest model. In addition, topographic conditions and proximity to transportation networks played dominant roles in the emergence of suspected illegal land development. Moreover, the probability map generated by MAXENT suggests that a considerable amount of forest, farmland, grassland, and water bodies will face a high degree of danger. Therefore, both superior and local governments should pay much more attention to regions with a higher potential for illegal land development. In summary, our findings are expected to support decision-making in the management and assessment of conservation areas in fast-growing regions. More importantly, the proposed method can be further applied to illegal land development estimation in many other regions. •This study aims to develop a robust method for estimating illegal land development.•A unique feature of this method is that only positive training samples are needed.•Probability maps of potential illegal land development can be reasonably generated.•Topographic and transport conditions matter most to illegal land development.•This method can support decision-making in the management of conservation areas.