Recent advances in unmanned aerial vehicles (UAVs) technology, as well as the development of lightweight sensors, offers a great possibility for the measurement of different tree features with relatively low costs compared to traditional methods. In this research, the precision and accuracy of tree height measurement and estimation using imagery by a low-cost UAV were studied. For this aim, 854 images with an altitude of 100 m above the ground were taken and the images were processed and dense point cloud was extracted by applying Structure from Motion (SFM) algorithm. The study was conducted in 34. 79 ha of Sisangan forest park and 28 sample plots (30 × 30 m) were located in the field and tree heights were measured. Also, tree height was measured using the canopy height model. Linear regression was applied to estimate the actual tree heights based on CHM derived tree eights. The accuracy and precision of the estimates were assessed using relative bias and relative root mean square error. The differences between the field measured and CHM derived tree heights were statistically significant. Based on the results, the relative root means the square error of the height estimation of Buxus hyrcana, Carpinus betulus, Parrotia persica, and other species was 20. 39, 20. 39, 20. 57 and 20. 52 percent, respectively. The results showed that tree height measurement based on UAV images and methods that were applied in this research, is biased and the estimations are highly uncertain.

Forest canopy height is an important input variable to derive a set of essential parameters of forest stands, which is yet costly and time consuming when measured based on ground surveys. The satellite-based laser scanner data from ICESat-GLAS provide a 3D representation of gorund objects by measuring the distance from spacecraft to the objects on the earth surface. By means of these data, this study aims to estimate forest canopy height in a portion of mountainous Kheyroud experimental forests in north of Iran. An ICESat-GLAS dataset was analyzed. Several metrics including waveform extent, lead-edge extent and trail-edge extent were extracted from waveform data, and a terrain index was additionally calculated based on a digital elevation model at the location of all laser footprints. Forest canopy height was retrieved by calculating difference between signal begin and ground peak (direct estimation) and regression models (indirect estimation). For fitting the regression, a number of 330 highest trees were measured in 33 circular plots (70 meter diameter) which were collocated with LiDAR footprints. The directly estimated height produced 2 Ra and RMSE values of 0.56 and 10.32 m, respectively. Compared to this, regression models based on combined waveform metrics and digital elevation model provided better results. Best model fit with lowest AIC= 204.55 was achieved using waveform extent and terrain index variables (Ra2=0.82; RMSE= 6.16m). The ICESat-GLAS therefore concluded to be able to retrieve a relatively accurate estimate of maximum forest canopy height in such steep mountainous area, especially on small scales. Better results are assumed to be achieved using other statistical methods, as well as by an improved waveform processing techniques.

Knowing the forest canopy height is essential for evaluating the health and dynamics of forest ecosystems, as well as for monitoring and modeling the carbon cycle and biodiversity. However, measuring canopy height through ground surveys is costly and time-consuming. Since 2018, the ICESat-2 satellite, equipped with the ATLAS laser sensor, has enabled the direct measurement of tree height. Although ICESat-2 is specifically designed to estimate ice height, it also provides significant data on vegetation height on the Earth's surface. This study aims to investigate the ability of the ATLAS sensor to accurately estimate forest canopy height in northern Iran. For this purpose, the vegetation height data from the ATLAS sensor (ATL08) was evaluated in the Kheyroud experimental forest. To validate the accuracy of the estimated forest canopy height by ATLAS, the forest height data obtained from the satellite were compared with the maximum tree height measured in 121 plots collocated with LiDAR footprints. The estimated forest canopy height by ATLAS and the maximum measured height of trees were compared using a t-test. The RMSE, rRMSE, and R2 values were 0.87 m, 2.7%, and 0.98, respectively, indicating the high accuracy of the ATLAS sensor in forest canopy height estimation. The results of the t-test showed that the mean difference between the measured maximum height of trees in the plots and the corresponding values extracted from ICESat-2 satellite data is not statistically significant (P > 0.05). This study demonstrates that the satellite estimates forest canopy height with very good accuracy in the forests of northern Iran, with a slight overestimation in areas with low-height trees.

2Extended Abstract Background: The height of trees is among the important components in the field of forest inventory and measurement. Over successive decades, estimating tree height has been a major concern in forest statistics and measurement. The height variable is used in estimating tree volume, classifying stand productivity, and estimating growth rates of trees. It is also one of the important variables in calculating biomass. Another essential characteristic at the individual tree level is canopy diameter, which plays a role in modeling and practical attribute estimation, such as forest canopy cover percentage, leaf area index, and biomass. Until now, the devices and tools introduced in forestry science have only been able to measure a specific component, e.g. tree height, and the need for different tools or techniques arises for measuring canopy diameter. The approach of this research not only leads to the development and use of software capable of measuring the mentioned components but also enables the recording of inventory in designed forms, recording of geographic coordinates of tree bases, storing images taken from the trees, and ultimately creating a data archive from the study area. To achieve these goals, the design and development of a software (application) called HCP, which stands for H: Height, C: Canopy, and P: Pixel, based on the Android operating system, will be considered the essence and necessity of this research. Methods: In this research, the HCP software based on the Android platform was designed and developed according to the devices with the Android operating system and with the Java language. HCP has three parts: database, image processing, and information display. Its user interface was presented in six activity pages, including Set Image, Set Data, Set View, Set Reference, Set Pin, and Set Final, with a SQL database structure. The entire coding, execution, debugging, and testing process was carried out based on API 27 (Application Program Interface) associated with the Android SDK (Software Development Kit), in the Android Studio development environment (IntelliJ). The initial testing process was also carried out with real images stored or produced by the device camera used. A total of 150 trees from Persian Oak species (Quercus brantii Lindl) were selected and their height and canopy diameter were measured to conduct tests and compare the measured height data using Vertex and HCP methods, as well as the measured canopy diameter data using laser meter and HCP. Descriptive indices independent of the distribution type, including the first quartile, median, third quartile, minimum, and maximum, were calculated for the height and canopy diameter components measured by the four methods mentioned above. The Shapiro-Wilk test was used to examine the distribution of the difference in the height and canopy diameter of all trees. Paired t-test was used to evaluate the accuracy of HCP.  The HCP error was evaluated by the root mean square error (RMSE) and the Index of Disagreement, which is the result of dividing the absolute value of the difference of the estimated component from the actual value by the actual value. The accuracy of HCP was evaluated using linear correlation and the Index of Agreement. To further investigate the dispersion of the error distribution and to examine the accuracy and precision, the data were grouped into three levels: total trees, 75 tallest trees in terms of height (wider in terms of canopy diameter), and 75 smallest trees in terms of height (canopy diameter). All results were obtained using the R statistical software. Results: The result of the paired t-test at a 95% confidence level indicates no significant difference between the measured heights using the Vertex and HCP methods, as well as no significant differences between the canopy diameter measurements using the laser meter and HCP. The RMSE values were calculated as 0.07 and 0.065 meters for the height and canopy diameter, respectively. The values of the linear correlation coefficient and the index of agreement were reported as 0.999 for both the height and canopy diameter measured with the mentioned methods. The disagreement percentages were calculated as 1.068 and 0.963 for the height and canopy diameter, respectively. Conclusion: Modern methods of measuring tree height need to be improved before they can be widely used in forests, and once the shortcomings are addressed, a new chapter will open in measuring forest components, such as the canopy diameter and tree height. The following seven steps outline the general steps for measuring canopy diameter and tree height by using HCP photography. Finally, based on the examination of accuracy, precision, and error assessment test results, HCP can be introduced as an alternative method for measuring the height and canopy diameter of trees. Step 1: Design and develop HCP (other items include defining Java class file functions to determine tree number, recording time and date of photography, calculating the time difference between images, spatial positioning, copying the original image file to internal memory, resizing images for re-matching, and providing output in csv and zip format). Step 2: Taking pictures of the target tree (neighboring trees) and index. Step 3: Defining and determining the numerical value of the index used in the image. Step 4: Determining the lower points (tree trunk and index), upper points (tree tip and index), and the canopy diameter on the image. Step 5: Correcting all measured components, and Step 6: Starting and performing processing by HCP. Step 7: Automatically measuring all defined components for the target tree (neighboring trees), generating output file, and saving all information related to each image.

Remote sensing and aerial photographs are used to produce medium to small scale images. However, for detailed information especially to estimate rangeland vegetation canopy cover there is a need to larger scale images. It is therefore necessary to study the technical applicability of different devices such as short range light airplanes, kites, gliders and balloons. In this research, we focused on suitable flight height for rangeland vegetation canopy cover estimation using large scale balloon images in Incheh Broon area where we conducted field tests in September 2010. The balloons ascended to heights of 5, 10, 25, 50 and 100 m and higher. Using the taken images, vegetation canopy covers were estimated and compared with those obtained from field measurements. Results show that there is no significant difference between field and image estimation of canopy cover for heights lower than 100 m. We therefore suggest using balloon images acquired from up to 100 m height for estimating rangeland vegetation canopy cover.

The thermal characteristics of an area are not affected lonely by climatic conditions and its seasonal changes,other factors such as urban geometry, vegetation and aquatic elements can be effective in improving thermal comfort. Improving thermal comfort is one of the important goals in designing urban open spaces. The heat island is an effective factor in the thermal comfort of the urban sub-climate and the vegetation is also effective in controlling the heat island. One of the effective solutions in controlling the heat island of open spaces is to be aware of the different characteristics of different vegetation that control the impact of this phenomenon. The aim of this study was to investigate the impact and importance of vegetation and their height in the topography of the site, as one of the most widely used and effective tools in designing the quality of thermal comfort in designing part of the urban open space of Nazhvan Park in the west of the city. Isfahan and provide an optimal model of vegetation height in topography. Data collection method, field, analytical and quantitative, with comparative analysis method of proposed design options using simulation in ENVI-met software (4. 4. 4) in nine different vegetation patterns With a fixed plant type in ten different points of the site on June 15, 2017, and the criteria for measuring thermal comfort at the site are: air temperature, relative humidity, air flow and average radiant temperature and the index used in This study is PMV, which is one of the most comprehensive methods for estimating thermal comfort. The results indicate that a large number of trees, on the one hand, and higher trees on the other, as well as changes in topographic height, are very effective in changing and improving thermal comfort.

Measurements of production and utilization of key range plant species are of utmost important tools for making range management decisions specially for stocking rate determination. A study was conducted to examine the relationships of production and utilization of Agropyron cristatumand Stipa barbata, as key grasses in Chaharbagh region of Golestan province, with some dimensional parameters. For this purpose, plants height, basal diameter and canopy diameter and their dry weights were measured. Primarily, correlation matrices and Pearson correlation coefficient were used to assess the relationships of these three dimensional variables with production. The three variables were then evaluated for predicting production by using best subset and stepwise regression approaches. Utilization was assessed based on percentage of height removed in relation to percentage weight removed. Results showed that basal and canopy diameters could usefully predict the production of the two grasses. Finally, because of subjectivity of canopy diameter measurements and its weak role in explaining production variations, just basal diameter was considered in models, having linear relationship with production and the coefficient of determinations were calculated to be 72.4 and 71 for A. cristatum and S. barbata, respectively. Therefore, dimension analysis is an appropriate approach to estimate the production and utilization of range key grasses.

While most recent investigation in satellite- based remotely sensed data has concentrated upon the biophysical characteristics of overstory vegetation for large area, little attention has been given to the reflectance contribution of their associated understory, versus overstory plantation reflectance to the recorded pixel value. In this research, shrubs and herbs were considered as consistent backgrounds which have an inverse effect, in contrast to plantation overstory, to the recorded pixel value in terms of their surfaceexposure to satellite sensors. Given the fact that planted tree crown closure is correlated with their height and diameter at breast height (DBH) in the early stages of the plantation, it is expected that a relationship exists between tree canopy closure, height, DBH and their associated reflectance values. The proposed concept was tested in a case study for a Jack Pine (pinus banksina) plantation using Landsat Thematic Mapper (T. M.). The crown width height, and DBH of planted trees were measured in an area of 30m X 30m, for every 2-year age interval from 1 to 21 years. Other understory natural regeneration within a 2m radius was recorded. Crown closure, mean height, and DBH of each plot (with shrub and herb understory of more than 60%) were plotted against their associated Digital Numbers (DN(s)) for 6 T. M. bands (1, 2, 3, 4, 5 and 7). The visible region of the spectrum (bands 1, 2 and 3) showed a narrow range of reflectance and was not suitable for this purpose. Band 4 revealed a greater range of DN(s) than bands 1, 2 and 3. A strong inverse linear relationship between DN(s) and their associated canopy closure, height, and DBH were found in band 5 as r2 = 0.863, 0.941, 0.873 respectively. Band 7 showed a stronger relationship with canopy closure (r2 = 0. 81) than did the other T. M. bands (except band 5). Overall, the results of this study have shown the importance of T. M. band 5 for estimating DBH and the height of plantations based on the contrast between reflectance of the overstory and understory.

Mangrove forests are known as important sea carbon ecosystems because they play an important role in carbon sequestration among coastal ecosystems. This coastal ecosystem has 10 to 50 times more carbon sequestration capacity compared to terrestrial ecosystems, and among the most productive systems, they can effectively reduce climate change. Therefore, an accurate estimation of the biomass of mangrove forests is a necessity. Meanwhile, the evaluation of the terrestrial carbon storage in mangrove forests relies on the accurate measurement of tree biomass, which is traditionally time-consuming and expensive. In this study, height and crown diameter was estimated by using UAV equipped with an RGB sensor,following sampling and measuring soil carbon in three forest sites of Sirik, Qeshm, and Khamir, the carbon storage in trees and soil was investigated. Orthophoto mosaic and dense point cloud were created based on structure from motion algorithm. Crown diameters were extracted from orthophotos. The canopy height model was extracted by subtracting the digital surface model and digital terrain model which were derived from point cloud. Tree heights were extracted from the canopy height model following imaging in November 2021. Considering that there was no significant difference between the measured variables on the ground and the extracted variables from the UAV images, the data obtained from the UAV images and allometric equations were used to estimate the aboveground carbon storage. After estimating the biomass according to the two variables of crown diameter and tree height, the carbon storage on land obtained from the information extracted from UAV images in the three sites of Sirik, Khamir, and Qeshm was obtained at 11. 63, 7. 97, and 9. 87 t/ha respectively. The soil carbon was also measured at two depths of 0 to 15 cm and 15 to 30 cm using the Walkley-Black method, and the values were shown as 67. 98, 81. 9, 85 t/ha, and 187. 2, 133. 53, and 113. 7 for Sirik, Khamir, and Qeshm sites. This research shows that UAV data has a high ability to estimate the variables related to individual trees in forest areas with difficult traffic conditions, and subsequently to estimate the height and crown diameter variables, estimate the forest stock and carbon storage based on the mentioned variables. It can be achieved in relatively homogeneous mangrove forests. Especially because these ecosystems are environments that are often inaccessible or difficult to work in.

Forest Canopy Density Mapper is a method based on spectral indexes integration in forest canopy density classification. In this paper, a data integration procedure is used to improve the result. In this respect, SFIM method and spectral response algorithm is utilized without a bad effect on the spectral and radiometric properties of bands. In the following, Landsat images of Hyrcanian forests in the north of Iran were used to implement the conventional and improved methods. Also, the ground measurements including grass-land, thin forest, semi-dense forest and forest is utilized for evaluation. The result shows that the forest canopy density model is inefficient in the thin and semi-dense forests. Alternatively, the results in the dense forest and grass land is reliable. Additionally, the improvement of the proposed method in these two areas is clearly seen. It seems that a high resolution image should be used to improve the accuracy of the forest density classification in the semi-dense and thin forests.