Simulation of citrus production space based on MaxEnt

Abstract

Crop production space is the most important part of land use system, and spatial simulation has always been the key task of land science. Crop production space is affected by many factors on different spatio-temporal scales, which leads to the complexity of simulation models. The existing simulation models also have the limitations of lack of human factors, large simulation area and excessive reliance on expert experience. Sichuan Province is a typical area of Citrus spatial expansion in China, so it is of great practical significance to carry out spatial regulation. From the comprehensive perspective of nature and humanity, this research uses MaxEnt, ArcGIS, Orcale, SQL to design a spatial regulation method (CSSM) for citrus, predict the citrus production space in Sichuan Province in 2025, and put forward regulation suggestions. The results showed that the citrus spatial simulation method better reflects the comprehensive effect of natural and human factors on crop space, and realizes the research on the regulation of single crop production space. The dominant environmental variables affecting citrus production in Sichuan are input of production factors, society, climate and terrain. Human activities play a leading role. The suitable environment for citrus production in Sichuan is: elevation ≤500m, annual average temperature ≥16.5 °C, aspect are northeast, southwest and northwest, supported by preferential policies, the input of Citrus fertilizer in the county is ≥ 500t, the input of Citrus labor in the county is ≥ 5,000, the input of Citrus pesticide in the county is ≥ 12.5t, and the technical progress represented by unit yield is 750–7000 t/km2. The suitable space for citrus production in Sichuan are mainly located in Zigong, Nanchong, Ziyang, Neijiang, Meishan, Leshan, Yibin and Luzhou. The government should choose a positive low growth scenario to stabilize the citrus area in Sichuan at 3533 km2 in 2025, and form a major citrus production area in Meishan, Ziyang, Neijiang, Chengdu, Nanchong and Yibin.

Response of Camellia sinensis var.assamica suitable areas to climate change—Evidence from Yunnan province (China)

“…The AUC value ranges from 0 to 1, with a larger value representing the higher accuracy of the simulation (Wang et al., 2017). The results show that (Bai et al., 2018; Ding et al., 2019; Lin, Xu et al., 2019; Tan & Zuo, 2018) the AUC < 0.6 indicates the failure of a prediction, 0.7 > AUC ≥ 0.6 indicates a poor prediction, 0.8 > AUC ≥ 0.7 indicates a general prediction, 0.9 > AUC ≥ 0.8 indicates a good prediction, and 1.0 > AUC ≥ 0.9 indicates an excellent prediction (the AUC of 1.0 indicates the perfect prediction).…”

Exploring the characteristics and driving forces of orchard expansion in ecological fragile region: A case study of three typical counties in the Loess Plateau

“…Much work so far in terms of orchard expansion can be divided into three aspects: 1) identification of orchard expansions (Dong et al, 2013;Jason et al, 2017;Sun et al, 2017;Kaspar and Jefferson, 2018;Lin et al, 2022). Depending on multiple spectral indices and phenological information, much attention has been paid to identifying the expansion of different orchards.…”