فهرست مطالب shaban shataee jouibary

Planning, construction and assessment of road network are among the investigations for infrastructure development at watershed scales. The main aim of this study is assessing the road network connectivity in the Chehel-Chay Watershed, located in Golestan Province using Alpha (α), Beta (β), Gamma (γ), Eta (η), network density and detour indices in graph theory. The available road network map was extracted on 1:25,000 scale, satellite imagery and mapping by GPS. Then the values of indices were calculated for road network that located in forest and non-forest land uses as well as for the whole of the study area. Then, the calculated indices were compared with each other and also with standard index values correspondingly. In forest land use, non-forest land use and whole of the study area the value of calculated indices are: for Alpha index 0.79, 0.14, -.021, for Beta index 0.4, 0.78, 0.56, for Eta index 1.2, 0.64, 1.32, for Gamma index 0.37, 0.23, 0.19, for network density index 6.12, 27.53, 13.12, and for detour index 0.61, 0.81, 0.77, respectively. The results showed that the network connectivity in forest area is suitable but in non- forest area despite of an increase in network density, the network connectivity is inappropriate and for the whole of the study area the network connectivity is considered to be too weak. The network density in forest area is inadequate and in non-forest area network connectivity has been decreased despite of an increase in network density. However, for the whole of the study area the amount t network speed is low due to topographic status and inadequate level of network development. The analysis indicates that the available road network despite of high length of roads constructed in the area and the associated high costs and environmental impacts has not have essential efficiency to connect various land uses in the study area. It is necessary to improve road network based on principles of network connectivity, economic, social and environmental considerations as well as inhabitant's needs in future researches.

Roads induce some of the most pervasive anthropogenic alterations in watershed and source o run off. In mountain area road network despite of lower surface to total surface has impact the watershed hydrology. The aim of the current research is comparison of Chehel-chay Watershed roads whit rural road standards and runoff calculate of these roads.
The existing road network map was created on 1:25,000 scale (NCC), using satellite image and mapping by GPS using Arc GIS10.1.The technical characteristics roads i.e. traveled way, width, cut and shoulder width, cut and slop, road lengths slop and ditch were recorded and compared whit rural road standards using One-sample T- Test in SPSS. Then, the profile of roads in current and standard situation was created using Civil 3D and the run off these road calculated using length and width oo roads, run off coefficient and precipitation per m3 for existing roads per km in year.
Length and density of the road network in the study area are 337.07 km and 13.12mha-1, respectively. The results show that length slope and cut slop in high class >6 meters of asphalt roads, in gravel roads cut and shoulder width, lengths slop and cut slop in high class >6 meters and in dirt roads lengths slop and cut slop in high class >6 meters are significant different with standards. The results indicate that 43.06%, 39.02%, 33.42% pre m3/km in year the run off of existing asphalt, gravel and dirt roads, respectively more than standard situation.
The different between roads in existing and standard situation whether explain just by statistics can not realize the expert with failing to comply of standards. The difference between existing and standard situation showed that at the time of manufacture can reduce side effects caused by the construction of roads. In this research the runoff in existing situation about 39% more than standards for total roads. Estimation the run off of roads is effective criteria in order to distinguish of destructive effects of roads without consider to standards, is the main finding of current research. The different between roads in existing and standard situation whether explain just by statistics can not realize the expert with failing to comply of standards. The difference between existing and standard situation showed that at the time of manufacture can reduce side effects caused by the construction of roads. In this research the runoff in existing situation about 39% more than standards for total roads. Estimation the run off of roads is effective criteria in order to distinguish of destructive effects of roads without consider to standards, is the main finding of current research.

In this research, the possibility of application of LiDAR-derived characteristics has been studied for discrimination amongst common hornbeam (Carpinus betulus) and Persian maple (Acer velutinum) trees. LiDAR data of individual sample trees were separated in laser point clouds using their measured center coordinates and crown diameter in the field. In district 1 of Shast-Kolate Education and Research Forest in Gorgan, 80 individual A. velutinum and C. betulus tree samples were selected. The trees were either located in dominant storey or were not overlaid by adjacent tree crowns. Tree heights were measured using Vertex 1V GPS device. Crown diameter was measured in four cardinal directions using Leica Disto lasermeter. Center coordinates of the sample trees were determined using both DGPS and distance/azimuth measurement by Total Station device. Different geometrical and statistical metrics of sample trees were extracted from LiDAR data. The results of discriminant analysis suggested the height standard deviation of laser points over 80% of tree height and crown slope as the selected metrics to differentiate the tree species (accuracy=80.3%). The mean of those two metrics showed larger values for hornbeam than maple. The selected LiDAR metrics were ascribed to represent the shape and height variation of returned crown laser points. It is therefore concluded that geometrical LiDAR-derived attributes could successfully helo by differentiating between the two tested tree species.