Simulation of Forestland Dynamics in a Typical Deforestation and Afforestation Area under Climate Scenarios

Abstract

Forestland dynamics can affect the ecological security of a country and even the global environment, and therefore it is of great practical significance to understand the characteristics of temporal and spatial variations of forestland. Taking Jiangxi Province as the study area, this study first explored the driving mechanism of the natural environment and social economy on deforestation and afforestation using a simultaneous equation model. The results indicate that population size, topographic and geomorphologic factors, climate, and location play leading roles in influencing forestland density fluctuations. Specifically, the population size, economic development level, gross value of forestry production, climate conditions, and government policies are key influencing factors of afforestation. Deforestation is mainly influenced by agricultural population, non-agricultural economy, forestry production, forestry density, location, transportation, and climate. In addition, this study simulated the spatial distribution of land use and analyzed the spatial characteristics and variation trends of forestland area and quality under the Representative Concentration Pathways (RCPs) climate scenarios from 2010 to 2030 using the Conversion of Land Use and its Effects (CLUE) model. The results indicate that forestland declines

Scenario-Based Simulation on Dynamics of Land-Use-Land-Cover Change in Punjab Province, Pakistan

“…By analyzing, interpreting and validating, FAO in consultation with SUPARCO and Crop Reporting Services of Punjab have identified 13 main land use classes in the high resolution spatial satellite data of SPOT-5 at a scale of 1:25,000 [59]. For meeting the requirement of DLS, we prepared all land use and driving data in uniform spatial resolution and projection of 1 km × 1 km [29,60]. Subsequently, 13 land use types were reclassified into six classes [28,31,32,35] with coding 0 to 5 (Table 1) and generalized via a separate spatial representation scheme [28].For the study analysis, we adopted the land use data from 2010 to evaluate the accuracy of simulation results from the DLS model.…”

“…Natural forest includes closed forest with canopy cover more than 60% and open forest with canopy cover [59]. For meeting the requirement of DLS, we prepared all land use and driving data in uniform spatial resolution and projection of 1 km × 1 km [29,60]. Subsequently, 13 land use types were reclassified into six classes [28,31,32,35] with coding 0 to 5 (Table 1) and generalized via a separate spatial representation scheme [28].…”

Projections of Future Land Use in Bangladesh under the Background of Baseline, Ecological Protection and Economic Development

“…The DLS model is a widely practiced model of simulation of the land system [32,[37][38][39][40][41]. DLS model has two special features: firstly, it provides scenario analysis of land demand at regional level and spatial integration of land uses at pixel level.…”

Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis

“…This indicated that the north-south vegetation trend of the Yangtze River Delta before or after abrupt change was closely related to the land use type. Some studies have suggested that the increase in the vegetation of woodland in the south of the Yangtze River Delta was related to human-related policies such as ecological protection projects [61]. The urbanization in the eastern cities and the irrational human use of cropland [62][63][64] had led to a great increase in vegetation browning of cropland and built-up land.…”