فهرست مطالب خسرو میرآخورلو

Identifying suitable land for wood cultivation is essential for future planning. However, it is a sensitive issue that needs to be addressed due to climate change and the dynamics of the issue, both biophysically, socially, and economically. To implement this project, ecological indices of Populus deltoides and Populus euramericana including temperature, precipitation, soil, and physiography were determined. Climate and temperature data were collected from meteorological stations. A climatic information layer, non-forest land layer, soil layer, and the current status of the poplar plantation layer were prepared. By AHP and layers-weighted overlay methods and intersect command, and then weighting each of these ecological indices using interpolation models (kriging), according to the ability of two Populus deltoides and Populus euramericana species to cultivate, they were classified and prioritized into areas with suitable and unsuitable potential for development of poplar cultivation. The results showed that Guilan province's poplar development potential was 63806 ha divided into two types of rainfed and rainfed with supplementary irrigation. Of these, 12335.74 ha are rainfed.

Nowadays, natural resources are exploited for the purpose of economical development in developing countries. Expansion of agricultural lands, supply of charcoal and fuel wood and wood production play an important role in forest degradation which affects biodiversity, soil conservation, the quantity and quality of water and the global climate conducted to the importance of forest conservation and reforestation. Therefore quantitative assessment of forests is required for conservation programs and forest monitoring is defined as a tool for sustainable forest management.Today, remote sensing techniques and satellite images can widely provide functional information in environmental studies. In this work, sentinel-2 satellite images with high spatial, temporal and spectral resolution were applied to determine the area, distribution and density of the Arasbaran forestsas well as other land use classes in the area.

Arasbaran area is located in Qaradagh mountainous region inthe north of East Azerbaijan province between 38°25′ 59 " N- 39°20′ 7.7 " N latitude and 46°09′ 18 " E- 47°16′ 5.3 " E longitude which covers an area of 551211 hectares and the deciduous forests of this area are known as the 11th Biosphere Reserved in Iran. The altitude varies from ca. 256 m tomore than 2000 m. the importance of the area is in having a rich flora (about 1334plant species) and unique vegetation among the vegetation of the country.
For the first time, the Sentinel-2 images with a combination of high spatial and temporal resolution were used to classify the land use of the area.The best band combination was found for bands 2, 3, 6, 12 and NDVI index. Land use classification included dense, semi -dense, sparse and very sparse forests as well as rangeland, agriculture, residential area-bare soil, garden and water was implemented using 9 different algorithms in a pilot area to find the best algorithm. 280 training sample points were collected from all different land use classes in the area.Consequently, supervised classification technique and Maximum Likelihood algorithm with the Kappa coefficient of 0.886 and anoverall accuracy of 89.6% was identified as the best classification method for the Arasbaran area.Accuracy assessment of the final map was done using ground control points and Google earth images with a total accuracy of 95%.Finally creating an error matrix with 880 ground reference test pixels revealed the accuracy indices.

The final land use map of the Arasbaran area based onthe Supervisedclassification technique and Maximum Likelihood algorithm was created.Based on the results, the accuracy assessment of the final map showed that the Kappa coefficient and the overall accuracy of the classified map were 0.88 and 89.8% respectively.The forest distribution and canopy cover density map were extracted from the land use area map. The total area of forests with a canopy cover of more than 5%, obtained 131019 ha consisting of 39% dense forest, 36% semi -dense forest, 17% sparse forest and 8% very sparse forest. In addition, the largest type of land use accounted for rangeland with 270000, forest with 131019, agriculture with 101974, residential area-bare soil with 30028, garden with 15434 and water with 2756 hectares respectively. Based on the error matrix table and correct classified points as well as total ground control points, the highest user’s and producer’s accuracy belonged to the densed forest class as well as the lowest user’s accuracy and lowest producer’s accuracy belonged to garden and agriculture classes respectively.

The results conducted supervised pixel-based image classification based on the Maximum Likelihood algorithms an acceptable method. It can be because of well -distributed training sample points, the high spatial resolution of sentinel-2 images or Environmental heterogeneity of the area. According to the results, dense forests declined(from 56910 to 50628 ha)however semi -dense and sparse forests have increased (from 35280 to 47930 ha)with respect tothe last forest survey project in the Arasbaran area in 2003.In addition, the results revealed an overlap between agriculture and garden as well as rangeland and residential area-bare soil classes because of multi culture of crops and fruit trees together as well as dried or low vegetation cover of rangelands in the area. These results can provide useful information for decision- making and sustainable forest management for reducing forest degradation and it seems to be an important next step to manage these forests based on conservation policies.

Lack of wood resources and forest degradation in the country, on the one hand, and the inability to import wood and its products to the country, on the other hand, have doubled the importance of wood supply for the country. Lack of information on the current situation (area and distribution) of poplar planting in Ardabil province is one of the main problems of wood production managers in planning and managing wood supply. In this regard, preparing the distribution map and determining the area of poplar wood cultivation can help the planners of the province in assessing the situation of poplar planting as well as issues related to the cultivation and development of wood cultivation in the region. For this purpose, Multi-temporal Sentinel-2 satellite data were used from the beginning to the end of the poplar growth period (first half of March to December 2018), at least six time periods between 30 and 40 days. After processing, interpretation, data analysis, including atmospheric correction, geometric correction, selection of appropriate bandwidth and temporal composition of images, modeling based on time series data, and model testing in pilot areas with fieldwork information (training examples) for use in the model a map of poplar areas in Ardabil provinces was extracted. The results showed that the province's poplar plantations were equivalent to 1074 hectares in 1397. According to the distribution map, most poplar parts are located in Meshgin Shahr, Ardabil, and Khalkhal. Most of the poplar planting plots of less than 0.5 hectares are strip or linearly planted in the margins of gardens and streams to transfer water to farms, which in addition to producing wood, act as windbreaks and garden fences. Evaluation of the accuracy of maps extracted from Sentinel-2 satellite data using 140 samples was randomly selected. The overall accuracy of the prepared map was 93.2%, which indicates the acceptable accuracy in distinguishing poplar crops from other forest species and fruitful in the extracted maps. The findings of this study can be valuable basic information for use in monitoring the area of poplar planning and management decisions in wood farming in the province.

. In this analytical report, in the first stage, the quantitative and qualitative status of poplar plantations, including determining the existing areas under poplar cultivation and also determining the quantitative and qualitative status of trees stand in poplar plantations provinces of the country were evaluated. Then, the scientific and technical capacities that are the result of research achievements, as well as the potentials and lands suitable for poplar cultivation were evaluated as a capacity. According to the available data in terms of quantity and quality of wood production, problems and barriers were identified and and appropriate scientific, technical, executive and extension solutions were provided. The current and future demand of industries for wood raw materials based on population growth rate and per capita wood consumption for a period of 10 years shows that wood consumption through wood cultivation is estimated at about 12 million cubic meters. The results of studies of research departments and executive organizations indicate that the current areas of poplar plantations in the country can be increased. By determining the capabilities and potentials of poplar plantations development, the annual harvest of wood can be increased. A study on the ability to produce wood for high-yield poplar clones (35-40 m3/ha/yr.) has shown that the production of required wood raw materials can be achieved with an area of 300,000 hectares, which will be achieved in a 10-year plan by planting 30,000 hectares per year.

Estimating the amount of wood produced in poplar plantations is not possible without determining the area of poplar plants. Estimating the amount of wood produced is very important for the production management of wood industry units. Industry owners need to know how much poplar wood can be extracted in the coming years. Therefore, identifying areas of poplar cultivation in Mazandaran province is one of the main objectives of the present study.

This study was conducted to estimate adult poplar cultivations area using Sentinel2 satellite in Mazandaran Province. Firstly, the general survey carried out on poplar cultivation with full canopy distribution and its cultivation area at the regarding area. Then, in the whole area, the numbers of 202 cultivated areas have randomly been mapped using Global Positioning System (GPS) as Training Samples. In the next step, the relevant images have been identified in term of time and downloaded, and also radiometric, atmospheric, and geometric corrections have been done on them. Also, banding appearance, color compositions, images mosaicking and bands calculations have been performed. The Support Vector Machine (SVM) algorithm has been used in order to extract poplar cultivation in the growth period of 2018 (March to December). Evaluation of the accuracy of the classification results of the generated maps was performed using 183 ground trust points via GPS.

The results showed that in 2018, 705 hectares of Mazandaran area are under poplar plantations, which Mahmoudabad and Neka cities with an area of 167 hectares and 33 hectares, respectively, had the highest and lowest area of poplar cultivation. Poplar cultivation area estimated in this study was excluding young poplar stands. Furthermore, the results of the accuracy assessment demonstrated that the overall accuracy is 95.35. The average area of poplar stands was 800 square meters. But the number of stands less than 500 square meters (7121 plots) includes more than 80% of the stands. Only 0.2% of the total stands (57 stands) make up more than one hectare. These 57 stands occupied about half of the province's poplar plantations.

Despite the favorable climatic conditions in Mazandaran province, the area of poplar cultivations was lower than expected. Therefore, it is suggested that in the future, the necessary measures should be taken to meet the wooden needs of Mazandaran province through wood farming.

The Lack of timely, documentary and scientific information from the current status (level and distribution) of poplar plantation of Tehran province is one of the main problems facing the managers of the wood production sector in the planning and management of wood supply in the province and the country. Preparing a map and determining the areas of poplar plantation and their distribution in Tehran province are the objectives of this study to monitor and evaluate changes of poplar plantation area in short-term periods.

The present study was conducted from April 2018 to March 2020 for 2 years in the whole of Tehran province. In this study, multi-temporal data, from the beginning to the end of the poplar growing season (second half of March to December 2018), at least 6 time periods of 30 to 40 days were used from Sentinel-2 satellite image. Then, 355 poplar plantation fields with uniformly distribution in the province were taken as a training sample for use in the SVM classifier. Post-test and calibration of SVM model based on the phenology of poplar genus and harvested field samples, poplar plantation distribution map of province was extracted.

The results showed that the total area of poplar plantation of Tehran province is 511.1 ha which covers 0.04% of the total area of province. One percent of the total poplar plantation fields were randomly selected for field control and after that, the overall mapping error obtained was calculated. In this study, the exact location and area of current poplar plantations were estimated with acceptable accuracy (96.7%). The highest level of poplar plantations was obtained in Damavand (196.8 ha), and the lowest in Varamin (0.22 ha).

Using the resulting information (distribution map and mapping poplar plantation of province), can be initiated in studies on cultivation planning and development of wood farming for the present and future of the province.

Knowledge on the area and amount of forest coverage at landscape scale can be one of the most important indicators in forest sustainable development. In this study, we used Landsat-8 full coverage imagery across the Guilan Province and the supervised classification method for forest canopy cover mapping in the summer of 2014. Field data were collected by a two-stage sampling method and 316 number of 0.5-ha plots. Subsequently, information on the types of land use and the canopy density (the ratio of the level of forest floor lightness per unit area) were recorded. With an overall accuracy of 91.8% and kappa coefficient of 0.80, results showed that 498804 ha of the total land area of Guilan Province is covered by forests, from which dense, semi-dense, and scattered forests account for about 42.1, 41.5, and 16.4% of the forested areas, respectively. This study demonstrated the negative effect of spectral similarity between farmlands with scatter and semi-dense forests in the accuracy of forest classification. This study demonstrated the proper performance of Landsat 8 data in providing thematic maps such as density and forest cover. Therefore, these data and information can be recommended for use in forest management decision-making, conservation, and restoration.

In the past decades, extensive changes have occurred especially in high-altitude and low-altitude Hyrcanian forests. Knowledge of the quantity and location of forest land use changes is the first step for forest conservation and management in Hyrcanian forests. To achieve this goal, the results of two terminated research projects, conducted at the Research Institute of Forests and Rangelands of Iran, were used to evaluate the changes in Hyrcanian forests during the 12-year period (2004-2016). The results showed that in the past 12 years, 161290 hectares of forest area (areas with tree height more than 5m and canopy cover more than 5%) were decreased. The forest cover changes in Guilan, Mazandaran and Golestan provinces were calculated to be 48543, 79558 and 33189 hectares, respectively. The rate of forest changes was estimated as 0.74 percent per year in the Hyrcanian forests of Iran.The present area of Hyrcanian forests of Iran was estimated as 1,650,495 hectares in 2016. According to the official announcement of Forests, Rangelands and Watershed Management Organization of Iran, the area of Hyrcanian Forests with a canopy cover more than 5% was reported to be 1,847,886 and 386, 073, 2 hectares in 2004 and 2015, respectively. This shows an increase of 225500 hectares of forest cover during 21 years, approximately 10738 hectares increase of forest area per year. Whereas, evidence shows that the forest cover degradation and conversion to other land uses in the Hyrcanian forests of Iran is increasing and this is an undeniable fact.

Introdoction: The Qeshm Island Mangrove forests are located at southern coast of Iran, near the highest latitude of Mangrove in Southeast of Asia. Due to the importance of all aspects of mangrove forest and to prompte it as one of the most significant world ecosystems the ever increasing destruction of thease natural resources, it is essential to preserve, restore and develop thease forest in Iran.
Material & In this study, mangrove forest areas were determined for 1988, 1998 and 2008; then, the changes were detected by comparing satellite data related to two periods of 1988-1998 and 1998-2008 in the northwest of Qeshm Island.
Result & diction: The results showed that over the past two decades, significant changes have occurred in this area. In the first period, the total forest area increased from 5160.52 ha in 1988 into 5308.32 ha in 1998, i. e., the forest area had developed 181.7 ha (about 5/3%) during 10 years. In other words, the annual average growth rate of these forests was 0.35 percent, equivalent to 18.7 ha per year during that 10 year period. In the second period, the forest area of developed from 5308.32 ha in 1998 into 5512.7 ha in 2008, i. e., the forest area has been developed 204.4 ha, (3.8 %) in the second period 10 year. In other words, the annual average growth rate of the forest 0.38 percent (20.4 ha) per year during the second period. In this study,the main factor for the development of area has been causes natural regeneration and in cases of Afforestation mangrove forests in these areas.

This research aimed to study a number of water and soil properties of Avicennia marina mangroves to determine the potentially expandable mangrove stands. To this aim, A. marina stands located in Laft (Qeshm Island) and Khamir regions were selected. A total of 116 soils and 379 water samples were randomly collected along 9 transects in three districts: forest with regeneration, forest without regeneration and marginal lands (lands without forest). Water and soil parameters were measured to estimate the vegetative requirements of the forests, and results were statistically analyzed. The results of soil samples showed that Electrical Conductivity (EC), PH, Na+ and silt in both mangroves with regeneration and mangroves without regeneration were significantly (p<%5) less than those of marginal lands. However, organic carbon, available phosphorus and sand in both mangrove classes were significantly (p<%5) higher than those measured at marginal lands. The results of water analysis did not show any statistically significant differences in a number of parameters including EC, PH, Ca++, Mg++, Na+ and K+ between the three investigated areas. Since regeneration within the stands could be considered as an indicator of optimum vegetative conditions, the results obtained across the regeneration areas can be used as an index for development of A. marina stands.

Mangroves are one of the most important and valuable ecosystems throughout the world. Overexploitations of mangroves by local communities due to their diverse characteristics have caused severe degradation of these ecosystems. This process can be found in mangroves of Iran, so protection and development of them is essential. In this research, we will try to indentify the best sites for development of mangroves in Holor region of Qeshm Island with an area of about 300 hectare. Firstly, the most important parameters in growth of mangroves have determined that were as follows: tidal sites, soil pH, soil electrical conductivity, soil texture, soil saturation percent, soil Sodium absorption ratio and proportion of soil Mg and Na. Sixteen soil samples were obtained using a systematic-random sampling network and their physiochemical variables were measured in laboratory. Geographical Information System and satellite images of IRS were used to provide the map layers of soil variables. Layers were overlapped and the final map of suitable sites for development of mangroves was obtained. Based on results, 13.67 ha (4.56 %) of the total area were capable for development of mangroves which could be considered in afforestation plans.

Estimation and mapping of forest resources is a prerequisite for research, management, and planning. In this study, we applied kriging geostatistical interpolation for estimation and mapping of forest stock attributes in a natural, uneven-aged and unmanaged forest in the Caspian region of northern Iran. The elevation across the 516-ha study area ranged from 1100 to 1450 m a.s.l. Field sampling was performed using 1000 m2 circular sample plots in a 75 m × 200 m systematic grid. Total numbers of 309 plots were sampled. Experimental variograms were fitted for stem basal area (BA), volume stock (V) and stem density (N) using geo-referenced plots. The variograms of BA and V exhibited no spatial autocorrelation, except for the stratified data based on diameter classes and tree species. The N showed yet a medium spatial structure which was fitted by a spherical model. The stem density was estimated by ordinary block kriging. The cross-validated results showed high estimation accuracy. The applied geostatistical methods were concluded to be advantageous for accurately capture the spatial variability of stem density which was reflected in the stem density maps. The methods can be applied to similar unmanaged, uneven-aged stands in the north of Iran, and thereby support the estimation of forest growing stock.

This study was aimed to assess the applicability of LANDSAT ETM+ satellite images for estimating vegetation production and cover. The images were digitized using topographic maps and geometrized in 1:25000 scales. Required processes such as spectral ratio measurement and vegetation indices were applied on the images. Collection was carried out for vegetation cover and production in various vegetation types in homogeneous units. Sampling points'' locations were recorded with GPS. Sampling method was random-systematic in such a way that in each unit، a circle with 20 meters radius was considered. One and 9 sampling plots were placed on the centre and on the perimeter، respectively. The plot size was 1m * 1m. In each plot، vegetation percentage was estimated and the production was calculated using double sampling method. Then، DN values for each sampling unit (9 pixels for one unit) were elicited in respect to primary bands'' images، vegetation indices and spectral ratios. Correlation and regression analyses between geo-information and satellite information (Digital numbers) were carried out. Results revealed that 7th and 5th Bands and IR1، MIRV2 and VNIR2 indices had a significant correlation with production and given parameter could be estimated through regression models. Likewise، RA، IR1 and TVI indices had a significant correlation with vegetation percentage and this parameter could be estimated through regression models.

This research was conducted to produce the map of vegetation cover percentage of Sorkh Abad rangelands with an area of 21717 hectares by using IRS-Liss III data. Images of IRS-LissIII were geo-referenced by digital topographic maps with a scale of 1:25000. Due to mountainous condition, for obtaining the high accuracy at the geometric correction process, elevation corrections were done on the images. In this study, in addition to main bands, vegetation indices, ratios and principle component analysis also were used.For field data collection, systematic random sampling method was employed. In each vegetation type, one key area was selected. In each key area, four vertical and horizontal transects with 100m length were established. Then along the each transect vegetation cover percentage was estimated in ten plots of 1m2. In the next step, correlation between vegetation indices, ratios and the field data was calculated. Then the indices that had stronger correlation with field data were used for classification with higher accuracy. Among the vegetation indices, RVI (0/74%) and NDVI (0/704%) had shown the highest correlation. Based on the obtained results, we may generally conclude that IRS-LissIII images have a good capability for cover percentage mapping in the study area.

To investigate capability of IRS LISS III data for rangelands separation and land usemapping, images of Sorkh Abad area, Mazandaran province related to May 3rd 2007 wereanalyzed. There was not any radiometric noise in the images. Multispectral images were georeferenced to panchromatic band using fifteen control points (accuracy: 0.5 pixel). For image enhancement different image processing techniques such as false color composite (FCC), image ratio, principal component analysis (PCA) and vegetation index were carried out. Pixel base supervised classification was done by maximum likelihood and minimum distance algorithms. Accuracy assessment of maps was done based on ground truth map and error matrix. According to the results accuracy of land use map was 88.53%. Also accuracy of maximum likelihood algorithm (87.05%) was higher than minimum distance algorithm (82.56%). Finally it can be revealed that Liss III images have good potential for land use mapping in the study area.

Range management needs to accessing data by fast and suitable methods for planning. Satellite data and geographic information systems (GIS) can be used for planning and integrating field and remotely sensed data. Landuse map is one of the most important information in range management plans. This requires overlaying, retrieve and analysis detailed information about the rangelands in GIS. Land use map provided using Landsat7 ETM data (15 Apr. 2004) for the study area (middle catchment’s of Taleghan) in the Tehran province. Based on histogram of bands and statistical analysis, bands 4, 3, 2 were selected for color composite in unsupervised classification method. We identified 4 classes land use type of study area in the fieldwork. Ground data was collected using systematic with random start point, from 86 plots (250*250m), using unsupervised map as a primary map. Overall, with combining the ETM data and the field data using supervised classification method, boundary of the landuse types were put in four classes (Rangeland, Farm land, Dry farming and Bare soil). The classification accuracy assessment showed that the overall accuracy 70.64 percent and accuracy rates of the rangeland, farm land, rain fed carping and bare soil were 81, 54, 61, and 81 percent, respectively. So it is possible to use Landsat 7 ETM+ data for landuse mapping which is essential in range management and range suitability classification.

For studying and differentiation of geomorphological units in part of Hableh-Rood drainage basin, Enhancement Tematic Mapper (ETM+) Landsat data with the bound combination of 7, 4, and 1 in red, green and blue colors were used. For image enhancement, stretching and filtering methods used. For Facies analysis and differentiation and interpretation of photomorphic units, geology, topography, vegetation and land use maps, arial photography along with other data and field controls were used. Also for image processing, Ilwis software was used. According to the result, 44 photomorphic units were differentiated; of whose 2 are agriculture land, 3 alluvial trasses, 3 intermountain, 28 mountains and 8 hills area. The regarded scale for displaying image or among of image magnification on monitor for interpretation, units play important role in differentiates and interpretation phenomenal. The best differentiation of photomorphic units was obtained with the scale of 1:50000. This study has shown the potential of Landsat data for differentiation of land phenomenal and different facies of arid region and quick access to unit in geomorphological map.

We compared land use maps of 1988 and 2004 of northern mountainous forests of Iran that have been extracted from landsat images in 15 years period and investigated on boundary changes and calculated deforestation areas as well. This information is essential for afforestation and forest extension in the deforestation areas of upper border of the mountainous forests. For this reason, we used landsat TM and ETM+ images in 1988 and 2004 for providing land use maps and also collected information from 2960 sample plot (90×90m) using systematic random sampling. Based on extracted maps, 121528 ha of northern mountainous forests of Iran has been deforested in 15 years period. The deforestation area were estimated 8101 ha per year. It is 0.45 percent of the northern forests. The percentage of deforestation area in terms of provinces (Guilan, Mazandran and Golestan) were estimated 1182, 4647 and 2272 ha per year or annually 0.21%, 0.49% and 0.69%, respectively. The results showed that the maximum deforestation percentage occurred in the Golestan and the minimum in the Guilan province.

The country of Iran is situated in an arid and semi-arid zone, with an average precipitation of about 250 mm per year. Hormozgan province in southern Iran, is one of the most arid parts of Iran with an average annual rainfall of only 170mm. The study area is located in the Zagros and Makran geological zones.. In the study area the oldest formations are of Palaeozoic age. Another characteristic of the Zagros zone are diapirs. Diapirs rise up from the deepest part of sedimentary rocks, and after cutting through the upper layers, they may appear at the surface, which seriously affect groundwater quality and land use. Desertification; in Iran has occurred from Neosene and Quaternary. Geological formation have important effect on salinisation and desertification. Thus, the geographical investigation of desert area is very important. This investigation is based on GIS method Applications, geological map (1:250000) and supported by, fieldwork. At the first, prepared and digitizing of geological maps by Ilwis program and was carefully checked and corrected where possible. The next step prepared evaporation formation and Quaternary maps and its overlying. Prepared cross map of Quaternary and Hydrographic network and determination of primary and secondary deserts area. The final step was prepared a cross map of primary and secondary desert area map and checked by fieldwork. To comparison between units of desert area map, can be result, more than 78 percent of study area is situated in the deserts area.

For sustainable management of the Caspian Forests of Iran, a most appropriate and fastest method of data collection and combination is essential. Combination of Satellite digital data with field data, using Geographic Information Systems, (GIS) could be applied to obtain accurate information for multiple decision making which is influenced by different factors. In this study eight senses of Landsat 7ETM+ data accosted from Caspian Forests of Iran, June and July 2000, were used. Based on OIF index and statistical analysis of the ETM data, color composite 3,4 and 5 were selected for unsupervised classification. The ground observation information were collected from 3860 plots(30*30), using unsupervised map as a primary map. Overall, combining the ETM and the ground data throw the field information, using the supervised classification method, boundary of the Caspian Forests of Iran were achieved in six classes (Dense forest, Sparse forest, Rangeland, Farm land, Water and Bare soil). The classification accuracy assessment showed that the accuracy rates of the dense forest, sparse forast, rangaland, farmland, water and bara soil were 83, 78, 54, 76 and 98 percent, respectively.