Background and objective:In recent years, the importance of modeling and predicting land-use/land-cover (LULC) changes for regional planning and environmental management has grown significantly. This study aims to discover and predict LULC changes in the South Pars' special economic zone over a 20-year period.Materials and methods:In this study, geographic information system (GIS) and a remote sensing technique (RS) were used to classify satellite imagery and the land change modeler (LCM) for monitoring LULC changes. The CA-Markov model was also used to predict LULC changes. The input data of our model were satellite images from TM sensor (Thematic Mapper) for 1998, and 2008 and OLI sensor (Operation Land Imager) for 2018, and this led us to predict LULC changes for 2028.Results and conclusion:Monitoring the results indicated that the area of the built-up areas was increased by 21.2533 km2 (0.81%) during this period, and the largest reduction area was related to the Bare land with 15,298 KM2 (-1.174%). prediction of LULC changes for 2028 revealed that the area of the Built-up areas is doubled and its area will reach 48.65 KM2 (56%). Water bodies and bare land areas will decrease by 113.13 km2 (-19%) to 165.96 km2 (-12%) respectively. Vegetation cover will increase to 23.24 km2 (65%). These results showed that the study area is susceptible to changes due to environmental and human factors that should be considered in urban and environmental planning. Manuscript profile

Background and objective:Detailed evaluation of biomass using Remote Sensing and Geographic Information systems is very important to manage the forest and its role as a carbon source and climate change. Ground sensing data have made a big change in compiling and exploiting information about forest biomass, But non-local equations and the use of different radar and optical images, and also huge expenses have caused ambiguities in the accurate estimation of biomass. This study aims to investigate the capabilities of different remote sensing data for modeling and estimating forest biomass.Materials and methods:Today, by using the conducted research and also by examining the conducted methods, it is possible to have an accurate assessment of biomass estimation, which brings the lowest cost and the highest efficiency. In this study, the challenges of the forest biome were investigated by reading numerous domestic and international articles and also with the opinion of natural resources experts in Iran.Results and conclusion:After reviewing the opinions of experts, all the solutions and challenges of the existing methods for estimating and modeling the forest biomass, it was concluded that to increase the accuracy and reduce the costs, the use of remote sensing capabilities can be useful in the assessment of the forest biomass. Decision makers and managers, especially in the natural resources area, can use remote sensing capabilities to prevent crises and monitor forests.Materials and methods: Today, by using the conducted research and also by examining the conducted methods, it is possible to have an accurate assessment of biomass estimation, which brings the lowest cost and the highest efficiency. In this study, the challenges of the forest biome were investigated by reading numerous domestic and international articles and also with the opinion of natural resources experts in Iran.Results and conclusion: After reviewing the opinions of experts, all the solutions and challenges of the existing methods for estimating and modeling the forest biomass, it was concluded that to increase the accuracy and reduce the costs, the use of remote sensing capabilities can be useful in the assessment of the forest biomass. Decision makers and managers, especially in the natural resources area, can use remote sensing capabilities to prevent crises and monitor forests. Manuscript profile