Spatial-Temporal Simulation of Carbon Storage Based on Land Use in Yangtze River Delta under SSP-RCP Scenarios

Abstract

Land use change could affect the carbon sink of terrestrial ecosystems, implying that future carbon storage could be estimated by simulating land use patterns, which is of great significance for the ecological environment. Therefore, the patterns of future land use and carbon storage under the combination scenarios of different Shared Socioeconomic Pathway (SSP) and Representative Concentration Pathway (RCP) of the Yangtze River Delta were simulated by introducing weight matrices into the Markov model and combining the PLUS and InVEST models. The results revealed that the woodland expands greatly during 2020–2060 under the SSP1-RCP2.6 scenario, and the carbon storage of 2060 is at a high level with an estimated value of 5069.31 × 106 t and an average annual increase of 19.13 × 106 t, indicating that the SSP1-RCP2.6 scenario contributes to the improvement of carbon storage. However, the area of built-up land is increasing under the SSP5-RCP8.5 scenario, and the estimated value of carbon storage is 3836.55 × 106 t, with an average annual decrease of 11.69 × 106 t, indicating that the SSP5-RCP8.5 scenario negatively affects carbon sink. Besides, the SSP2-RCP4.5 scenario causes almost no effect on land use change and carbon storage. The above results can help policymakers manage land use patterns and choose the best development scenario.

Analyzing and Simulating the Influence of a Water Conveyance Project on Land Use Conditions in the Tarim River Region

“…The FoM, the ratio of the intersection of observed changes and simulated changes to the union of observed changes and simulated changes is, therefore, a more suitable metric for evaluating LULC modeling [66]. The FoM can be calculated as follows: FoM = Hits/(Hits + Misses + False alarms + Wrong gaining category) (8) where Hits refers to the correctness produced by observed change simulated as change, Misses refers to the mistake caused by observed change simulated as persistence, False alarms refers to the mistake caused by observed persistence simulated as change, and Wrong gaining category refers to the mistake caused by observed change simulated as the wrong gaining category. Generally speaking, three years (e.g., Year 1, Year 2, and Year 3) of LULC datasets are necessary for the validation of LULC change modeling.…”

“…Land use and land cover (LULC) change is a primary issue in global environmental change and sustainable development [1][2][3][4][5]. Land use activities will inevitably have significant influences on the planet's land surface [6][7][8][9]. Numerous environmental and social issues are associated with rapid urbanization and population growth throughout the world [10][11][12][13].…”

Land Use Change and Landscape Ecological Risk Prediction in Urumqi under the Shared Socio-Economic Pathways and the Representative Concentration Pathways (SSP-RCP) Scenarios

“…There are four typical emission pathways, namely RCP2.6, RCP4.5, RCP7.0, and RCP8.5, as well as four additional emission pathways, namely RCP1.9, RCP3.4, RCP3.4-OS, and RCP6.0, which fill the gaps between the typical pathways [23]. Referring to related studies [41], we selected three representative SSP-RCP scenarios, the meanings of which are summarized in Table 1.…”

Impact of Land Use Change on Carbon Storage Based on FLUS-InVEST Model: A Case Study of Chengdu–Chongqing Urban Agglomeration, China

“…The traditional sample land inventory method requires large amounts of labor and material resources, the time cost for updating is very high, and it is more suitable for small-scale monitoring. In contrast, remote sensing provides the possibility for largescale monitoring, and its combining with modeling techniques provides a cost-effective means of carbon assessment [13]. In addition, the InVEST model requires fewer data, ensures rapid processing, and has high accuracy.…”