Spatial Information Research

This study is aimed to identify potential ecotourism sites using Geographic Information System and Multi-criteria Decision Analysis in Adiracha district of Sheka Zone, south-western Ethiopia. Landsat ETM Image and STRM data of 2016 with 30 m resolution and topographic map of Ethiopia were used in this study. Ecotourism potential site selection criteria were designed based on 26 stakeholder’s opinions. The final suitability map of ecotourism has been realized by applying an integrated weighted overlay technique of Geographic Information System. The suitability map was categorized into four classes as Suitable, Moderately Suitable, Less Suitable, and Not Suitable. The study attempts to indicate the level of ecotourism suitability at different location in the study area. The outcome of this research is useful to understand the spatial information of Sheka district that can be used for policy makers. This study can be also used as a basis for assessing ecotourism site suitability in other regions.

Jefferson County in Texas has experienced devastating storms in recent years resulting in billions of dollars in damages. The county has gone through temporal milestones in terms of population growth and industrial development. Many studies have shown that urban development increases the risk of flooding by decreasing the soil infiltration capacity. The current study focuses on estimating the extent to which the urban development in the county has led to increased imperviousness using a combination of historical and current spatial data. Rational runoff coefficients of the County were estimated and compared at three different times over a span of 120 years. A land survey map for 1898, an aerial imagery map for 1966 and a land parcel map for 2019 were obtained from various sources. The three maps available, each in different format, were analyzed to determine the land use and land cover type for the respective years. The runoff coefficient increased by 21% from 1898 to 1966 and remained the same from 1966 till 2019. The estimates are in correlation with industrial and population growth patterns of the county. These preliminary spatial analyses are useful in estimating the contributions of recent major flooding from overall development, or if they may be more impacted from other factors such as changes in weather patterns.

Saffron (Crocus sativus L.) is the most expensive medicinal crop in the world. This crop plays a specific role in the economy and social life of Southern and Central Khorasan provinces. Its production has been recently popularized in the northwestern regions of Iran. Accordingly, the present study evaluates the climatic conditions for saffron production in Western Azerbaijan Province based on a ten-year statistics of 2005–2014. To this end, 10 meteorological stations were selected across the province and were modeled and subjected to spatial analysis of data in Arc GIS Software Package. Using optimum climatic conditions for each growth stage of saffron, the data layers were classified and the weight value of each zone was specified and the final map that showed the climatic potential for saffron growing based on the analytic hierarchy process. The results showed that the role of each individual climatic variable including precipitation, temperature, and number of sunny hours varied with the growth stage as well as the slope map and the land use in different regions of West Azerbaijan Province. Of 37,113.4 km2 of lands excluding Lake Urmia, 16.70% is highly limited, 70.30% is moderately limited, 11.16% is lowly limited and 1.84% is unlimited.

There are major gaps remaining in understanding of species distribution and how relationships between biodiversity, environment and scales change over space and time. This review explores the significance, challenges, future directions, and the potential contribution of Earth Observations based Essential Biodiversity Variables (EBVs) to enhance our understanding of biodiversity. Integrating EBVs with Remote Sensing of Earth Observations (RS-EO) is found to be an effective approach to quantify and monitor changes in biodiversity over space and time. Species serves as the fundamental taxonomic units of biodiversity and are the focal points of conservation policies. Prioritizing the utilization of species-level metrics and their seamless integration into the EBV framework is crucial. The current study has contributed 11 potential EBVs to the existing knowledge base. Integrating multiple data sources and methodologies is essential for overcoming the constraints and obtaining a more comprehensive understanding of biodiversity patterns. This synergy offers a holistic approach for monitoring, assessing, and managing biodiversity, to contribute significantly to global conservation efforts and sustainable development goals.

The growth of an urban city is determined by the efficiency of its transport network structure. Existing road networks in many of the urban cities in India are unable to meet the increasing travel demand. The demand can be met only through the effective utilization of existing road networks, for which proper connectivity, high accessibility, and effective network morphology are necessary. In many metropolitan cities, the transport network is rapidly expanding at the center while the peripheral growth of the city is ignored. A structural-parameter-based evaluation of the transport network is necessary for acquiring a clear understanding of the existing road network of a city. While the evaluation of the structural parameters of the transport network is a challenging task, understanding the interrelationship among the parameters is no less challenging. Each parameter should be examined by considering the relationship with the other parameters to devise effective strategies for improving the efficiency of an existing transportation system. This study analyzed the relationship between connectivity, accessibility, spatial pattern, and development for the existing transport network of Hyderabad city, India. The results show a strong correlation between these parameters. The use of GIS in this study simplified the analysis. The obtained results would be useful to the concerned urban transportation planning authorities for effective decision-making and policy implementations.

Pre harvest prediction of sugarcane and sugar production is essential for obtaining the objectives of the national food security mission. Traditional field experimentation results are not reliable and are biased. Improvement in the accuracy and timeliness of crop yield estimation by blending of ancillary data and remotely sensed data in the temporal domain is indispensable. Ratoon sugarcane and planted sugarcane are the two prevalent agricultural practices in India. Ratoon sugarcane crop is suitable both from economic and production consideration. Identification of ratoon sugarcane and monitoring of its growth has been poorly studied. The objective of this study is to extract the information related to the ratoon sugarcane using remote sensing data. The present study proposed NDVIT, an index based on temporal values of NDVI data of Landsat 8 for monitoring and discrimination of ratoon sugarcane. This index has been found to provide 91% accuracy when tested on the ground in the Himalayan foothills region of Uttarakhand. Study indicated that the best period for discrimination of ratoon sugarcane crop is during the first week of April and last week of August to the end of September. This matches with the start of tillering stage and during the period of grand growth stage of the sugarcane.

Climate change is a genuine issue threatening the presence of species and livelihoods, consequently causing the vulnerability. Agricultural vulnerability is seriously undermined by regular disasters, caused by climate change. Therefore, researchers and policymakers are showing their interest in the effect of climate change on agricultural vulnerability through publishing research works. This study aims to perform a bibliometric analysis of climate change-induced agricultural vulnerability using the Web of Science and Scopus databases, and PRISMA method. The study highlights the current trend, hot-spot area, and their development through a literature dataset taken into consideration from 2010 to 2021. The outcome showed that the USA, UK, Australia, and China are the countries with high publications potentials. Consequently, there has been a significant increase (R2 = 0.90) in highlighted research area (2010–2021). The findings revealed that climate change and agricultural vulnerability research expanded gradually into different subject categories. The most frequent keywords were ‘climate change,’ ‘vulnerability,’ ‘adaptation,’ and ‘agriculture.’ The result showed that five clusters displayed the co-occurrences of term map. With the help of each clustering group, development of the respective research field can be smartly analyzed. Based on the findings, several research gaps are identified and offer opportunities for further studies.