Low integrity is a challenge for any organization. However, most organizations emphasize integrity without explaining what is required of an individual with high integrity. Exhibiting high integrity is necessary for academics; yet, the level of academic integrity remains unclear. Therefore, the purpose of this study is to examine the integrity level of academicians in a Malaysian public university. This paper shares the findings on the level of integrity of academics based on a questionnaire completed by 213 academicians. Data were collected by survey questionnaire and was analyzed using descriptive and inferential statistics. An overall mean score of 9.45 from a possible 10.0 indicated a high level of integrity among academics. The self-evaluation results by academics also demonstrated that they have attained integrity at a high level for their generic task, teaching and learning, research and publications and service for community with a mean score between 9.36 and 9.49. The value with the highest mean score was for “service to community”, whereas the lowest was for “research and publication”. These findings show that the university has successfully instilled values of integrity among academicians. Nevertheless, the university must continue to enhance academic integrity by exploring religiosity. Using Google Scholar, a literature search identified an Islam-based academic integrity model to explain the quantitative findings. Finally, a mixed method approach and involving all universities in Malaysia are recommended to further the findings of this study.

UAVs, also known as unmanned aerial vehicles, have emerged as an efficient and flexible system for offering a rapid and cost-effective solution. In recent years, large-scale mapping using UAV photogrammetry has gained significant popularity and has been widely adopted in academia as well as the private sector. This study aims to investigate the technical aspects of this field, provide insights into the procedural steps involved, and present a case study conducted in Cesme, Izmir. The findings derived from the case study are thoroughly discussed, and the potential applications of UAV photogrammetry in large-scale mapping are examined. The study area is divided into 12 blocks. The flight plans and the distribution of ground control point (GCP) locations were determined based on these blocks. As a result of the data processing procedure, average GCP positional errors ranging from 1 to 18 cm have been obtained for the blocks.

Identify and diagnosis of homogenous units and separating them and eventually planning separately for each unit are considered the most principled way to manage units of forests and creating these trustable maps of forest’s types, plays important role in making optimum decisions for managing forest ecosystems in wide areas. Field method of circulation forest and Parcel explore to determine type of forest require to spend cost and much time. In recent years, providing these maps by using digital classification of remote sensing’s data has been noticed. The important tip to create these units is scale of map. To manage more accurate, it needs larger scale and more accurate maps. Purpose of this research is comparing observed classification of methods to recognize and determine type of forest by using data of Land Cover of Modis satellite with 1 kilometer resolution and on images of OLI sensor of LANDSAT satellite with 30 kilometers resolution by using vegetation indicators and also timely PCA and to create larger scale, better and more accurate resolution maps of homogenous units of forest. Eventually by using of verification, the best method was obtained to classify forest in Golestan province’s forest located on north-east of country.

Every year, hundreds of fires occur in the forests and rangelands across the world and damage thousands hectare of trees, shrubs, and plants which cause environmental and economic damages. This study aims to establish a real time forest fire alert system for better forest management and monitoring in Golestan Province. In this study, in order to prepare fire hazard maps, the required layers were produced based on fire data in Golestan forests and MODIS sensor data. At first, the natural fire data was divided into two categories of training and test samples randomly. Then, the vegetation moisture stresses and greenness were considered using six indexes of NDVI, MSI, WDVI, OSAVI, GVMI and NDWI in natural fire area of training category on the day before fire occurrence and a long period of 15 years, and the risk threshold of the parameters was considered in addition to selecting the best spectral index of vegetation. Finally, the model output was validated for fire occurrences of the test category. The results showed the possibility of prediction of fire site before occurrence of fire with more than 80 percent accuracy.

This study analyzes the impact of a high-speed rail line on tax revenues and on the economy of affected regions within the country. The economic impact of infrastructure investment can be induced by changes in tax revenues when the infrastructure is in operation. Accurate regional GDP data are not necessarily available in many Asian countries. However, tax data can be collected. Therefore, this study uses tax revenue dates in order to estimate spillover effects of infrastructure investment. The Kyushu high-speed rail line was constructed in 1991 and was completed in 2003. In 2004, the rail line started operating from Kagoshima to Kumamoto. The entire line was opened in 2011. We estimated its impact in the Kyushu region of Japan by using the differencein- difference method, and compared the tax revenues of regions along the high-speed railway line with other regions that were not affected by the railway line. Our findings show a positive impact on the region’s tax revenue following the connection of the Kyushu rapid train with large cities, such as Osaka and Tokyo. Tax revenue in the region significantly increased during construction in 1991–2003, and dropped after the start of operations in 2004–2010. The rapid train’s impact on the neighboring prefectures of Kyushu is positive. However, in 2004–2013, its impact on tax revenue in places farther from the rapid train was observed to be lower. When the Kyushu railway line was connected to the existing high-speed railway line of Sanyo, the situation changed. The study finds statistically significant and economically growing impact on tax revenue after it was completed and connected to other large cities, such as Osaka and Tokyo. Tax revenues in the regions close to the high-speed train is higher than in adjacent regions. The difference-in-difference coefficient methods reveal that corporate tax revenue was lower than personal income tax revenue during construction. However, the difference in corporate tax revenues rose after connectivity with large cities was completed. Public–private partnership (PPP) has been promoted in many Asian countries. However, PPP-infrastructure in India failed in many cases due to the low rate of return from infrastructure investment. This study shows that an increase of tax revenues is significant in the case of the Kyushu rapid train in Japan. If half of the incremental tax revenues were returned to private investors in infrastructure, the rate of return from infrastructure investment would significantly rise for long period of time. It would attract stable and long-term private investors, such as pension funds and insurance funds into infrastructure investment. The last section of the paper will address how incremental tax revenues created by the spillover effects of infrastructure will improve the performance of private investors in infrastructure investment.

The main purpose of this study is to investigate the effect of environmental transformational leadership on organizational citizenship behavior through the mediating role of perceived meaningful work in Tehran District 22 Municipality. The study population in this study is the employees of the municipal district of District 22 of Tehran. The number is about 400 people, and the sample size was obtained according to Cochran’s 196 formula. The research method in the present study is applied in terms of purpose and descriptive in terms of implementation method. The Kolmogorov-Smirnov test was used to test the normality of the data, which proved with 95% confidence that the variables had an abnormal distribution. Therefore, due to the abnormality of the data distribution, Pls software was used to analyze the data. The results showed that environmental transformational leadership has an effect on organizational citizenship behaviors.