Background and Objective: Estimating aboveground carbon (AGC) of forest is a fundamental task for sustainable management of forest ecosystems; therefore, there is a critical need for appropriate approaches for quantifying of AGC. The most commonly used approaches for es More
Background and Objective: Estimating aboveground carbon (AGC) of forest is a fundamental task for sustainable management of forest ecosystems; therefore, there is a critical need for appropriate approaches for quantifying of AGC. The most commonly used approaches for estimating include global regression models that estimate the target variable over a wide range using cost-effective auxiliary data. Traditional regression models with fixed regression coefficients at all locations do not consider heterogeneity and spatial structure in modeling. The objective of this study is estimating the AGC using Regression Kriging, Geographically Weighted Regression Kriging and Landsat 8 data and compare methods.
Material and Methodology: The study was carried out in part of Zagros Forest, in Kohgiluyeh and Boyer-Ahmad Province. Totally, 184 plots (30×30 meters) surveyed and AGC were calculated by allometric equations. 32 variables were extracted from Landsat 8 as auxiliary data in the modeling process. The assessment of accuracies of methods was evaluated by K-fold cross validation via criteria such as coefficient of variation (R2), root mean square error (RMSE).
Findings: The results showed that Geographically Weighted Regression Kriging (R 2 = 0.66, RMSE= 21) had a better performance compared to Regression Kriging.
Discussion and Conclusion: Hybrid methods with heterogeneity and spatial correlation can be a good alternative to early regression methods for estimating aboveground carbon (AGC).
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Background and Objective: Precipitation is one of the most variable climatic parameters. These changes occur both in terms of location and time in terms of the region's climate. This study was conducted to model the spatial relationships of seasonal rainfall in the nort More
Background and Objective: Precipitation is one of the most variable climatic parameters. These changes occur both in terms of location and time in terms of the region's climate. This study was conducted to model the spatial relationships of seasonal rainfall in the northeast of the country with a joint monthly statistical period of 30 years (1980-2010). Method: In order to achieve spatial variation of rainfall, new methods of spatial statistics such as spatial autocorrelation, global Moran, spatial dispersion index and geographic weight regression model (GWR) were used in GIS software. Findings: The results of this study showed that rainfall changes in northeastern Iran have a high cluster pattern or positive. The Global Moran Index for each of the four seasons and the annual sum is above 0.93, the highest Global Moran index with the value of 0032191 is for the summer season. Discussion & Conclusion: The results of the GWR model showed that rainfall in the northern parts of the study area had positive spatial auto-correlation and in the southern parts, which are mostly desert areas had negative spatial auto-correlation. Also, the results of dispersion data were the result of cluster pattern of precipitation in the northeast of the country. Based on the frequency index of clusters or the ICF, the winter season is the largest cluster with a numerical value of 2646.26 in Northeast of the country.
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During research patrol of 2001 ROPME, the physical parameters of sound velocity in the Persian Gulf were measured. The range of stations selected to measure these parameters included the entire Persian Gulf. However, these measurements were discrete from the study area. More
During research patrol of 2001 ROPME, the physical parameters of sound velocity in the Persian Gulf were measured. The range of stations selected to measure these parameters included the entire Persian Gulf. However, these measurements were discrete from the study area.In this study sound speed was spatially modeled in Persian Gulf using the geostatistical analyst Arc GIS 9.2 software to prepare continuous and high validity maps of sound speed at different depths. These smart maps can be used to predict sound speed at any spatial coordinates in the study area by clicking the mouse pointer. Moreover, analysis of these maps led us to the conclusion that sound speed was highest in the shallower central parts but lowest in the eastern and western parts of the Gulf. The reason for this is the higher temperature and salinity in the central parts and the proximity of the eastern and western parts to the low-salinity waters of the Oman Sea around the Hormuz Strait in the eastern part and Arvandrood in the western part. The deeper waters also had the maximum sound speed around the Hormuz Strait and in the southern shores of the Persian Gulf where the more saline waters of the Gulf poured into the Oman Sea.
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The absence of abnormal noise and acoustic comfort in the workplace and people's lives . No sound and acoustic comfort in the environment can harm people's mental imbalance; The main objective of this research modeling land use map locations to produce a maps of noise p More
The absence of abnormal noise and acoustic comfort in the workplace and people's lives . No sound and acoustic comfort in the environment can harm people's mental imbalance; The main objective of this research modeling land use map locations to produce a maps of noise pollution is Yasouj. This study is descriptive and analytical in nature and in terms of purpose. Library and field study, no data were collected to determine the spatial distribution of land adjacent to extract acoustic comfort Map of the location database was used. In this study, the main variable is the distance as the basis for assessing the compatibility or incompatibility of establishment is from the perspective of proximity and vicinity. To analyze the information, software (Excel and GIS) is used. The model used in the analysis (FAHP) is a survey of five experts. Data analysis showed that among the four districts, the two most contaminated area and the area in between the four lowest infection is Yasouj areas.
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