Reconstruction of Historical Land Use and Urban Flood Simulation in Xi’an, Shannxi, China

Abstract

Reconstruction of historical land uses helps to understand patterns, drivers, and impacts of land-use change, and is essential for finding solutions to land-use sustainability. In order to analyze the relationship between land-use change and urban flooding, this study used the Classification and Regression Tree (CART) method to extract modern (2017) land-use data based on remote sensing images. Then, the Paleo-Land-Use Reconstruction (PLUR) program was used to reconstruct the land-use maps of Xi’an during the Ming (1582) and Qing (1766) dynasties by consulting and collecting records of land-use change in historical documents. Finally, the Flo-2D model was used to simulate urban flooding under different land-use scenarios. Over the past 435 years (1582–2017), the urban construction land area showed a trend of increasing, while the unused land area and water bodies were continuously decreasing. The increase in urban green space and buildings was 20.49% and 19.85% respectively, and the unused land area changed from 0.32 km2 to 0. Urban flooding in the modern land-use scenario is the most serious. In addition to the increase in impervious areas, the increase in building density and the decrease in water areas are also important factors that aggravate urban flooding. This study can provide a reference for future land-use planning and urban flooding control policy formulation and revision in the study area.

Using PLE-SEM to Quantify the Impacts of Natural and Human Factors on Vegetation Change: A Case Study of the Jialing River Basin

“…Previous studies in semiarid areas showed that rainfall had a more significant driving effect on NDVI than temperature, further supporting the view of the "short board effect." The enormous pressure of continuous population growth, the intensification of human socioeconomic activities, the development of the planting industry, and the expansion of agricultural areas in the research area has inevitably led to a continuous reduction in forest vegetation [54,55], causing damage to the environment [56]. Human activity factors had a negative impact on the direct pathway affecting the NDVI, and the impact was gradually strengthening.…”

Using geomorphologic indicators in preparation for flood zoning and flood risk maps in the Kashafroud basin, Iran

“…On the other hand, with the development of computer science, many software and numerical models have been presented for flood modeling. Among software models, HEC‐RAS (Ghimire et al, 2022; Namara et al, 2022; Sejati et al, 2022), HEC‐HMS (Altaf & Romshoo, 2022; Nadeem et al, 2022; Shah & Lone, 2022), MIKEs (Mike11, Mike21, Mike Flood, Mike Urban) (Dikici et al, 2022; Goumas et al, 2022; Li et al, 2022; Zhang et al, 2022; Zhou, Teng, et al, 2022; Zhou, Zheng, et al, 2022), Bentley Open Flow (de Andrade et al, 2022; Ellwood et al, 2022; Khakhar et al, 2022), Flo‐2D (Gerundo et al, 2022; Komolafe, 2022; Liu et al, 2022; Wang, Luo, et al, 2022), and CCHE (Lee et al, 2020; Kakati et al, 2022; Poorzaman et al, 2022) models can be mentioned. Also, the most applied numerical models include artificial neural network (Ahmad et al, 2022; Dahri et al, 2022; Wang, Yang, et al, 2022), random forest (Abedi et al, 2022; El‐Magd & Ahmed, 2022; Ha & Kang, 2022; Zhu & Zhang, 2022), and analytic hierarchy process (Bouamrane et al, 2022; Roy et al, 2023; Souissi et al, 2022; Vilasan & Kapse, 2022).…”

Quantitative Model Construction for Sustainable Security Patterns in Social–Ecological Links Using Remote Sensing and Machine Learning

“…With global warming and urbanization, the frequency of extreme natural disasters has increased, posing challenges to regional ecological security [1][2][3]. Issues such as biodiversity reduction [4,5], habitat loss [6], and eutrophication [7,8] have become prominent, thereby hindering balanced development and emphasizing the importance of planning, protecting, and governing regional ecological security patterns (ESPs) [9][10][11]. As a vital ecological barrier in China, the Qinling Mountains region plays a crucial role in protecting the environment and establishing rational ESPs [12,13].…”