Bilingual Publishing Group

Air Pollution Risk Assessment Using GIS and Remotely Sensed Data in Kirkuk City, Iraq DOI:  https://doi.org/10.30564/jasr.v6i3.5834 Received: 7 July 2023 | Revised: 15 August 2023 | Accepted: 22 August 2023 | Published Online: 23 August 2023 Abstract According to World Health Organization (WHO) estimates and based on a world population review, Iraq ranks tenth among the most air-polluted countries in the world. In this study, the authors tried to evaluate the outdoor air of Kirkuk City north of Iraq. The authors relied on two types of data: field measurements and remotely sensed data. Fifteen air quality points were determined in the study region representing the monthly average measurements implemented for the one-year dataset. Geographic information systems (GIS) based geo-statistic and geo-processing techniques have been applied to collected data. Spatial distribution data related to Air Quality Index (AQI), and Particulate Matter (PM10 and PM2.5) were obtained by mapping collec...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 DOI:  https://doi.org/10.30564/jees.v4i2.4687 Received: 20 March 2022 | Revised: 2 June 2022 | Accepted: 8 June 2022 | Published Online: 16 June 2022 Abstract There are rich oil and gas resources in Alberta oil sand mining area in Canada. In the 1960s, the Canadian government decided to increase the mining intensity. However, the exploitation will bring many adverse effects. In recent years, more people pay attention to the environmental protection and ecological restoration of mining areas, such as issues related to changes in vegetated lands. Thus, the authors used the Landsat-5 TM and Landsat-8 OLI remote sensing images as the basic data sources, and obtained the land cover classification maps from 1995 to 2020 by ENVI. Based on the NDVI, NDMI and RVI, three images in each period are processed and output to explore the long-term impact of exploitation. The results show that from 1995...

Use of GIS to Estimate Recharge and Identification of Potential Groundwater Recharge Zones in the Karstic Aquifers, West of Iran DOI:  https://doi.org/10.30564/agger.v4i4.5122 Received: 4 October 2022 Revised: 31 October 2022 Accepted: 5 November 2022 Published Online: 11 November 2022 Abstract Estimating and studying groundwater recharge is necessary and important for the management of water resources. The main aim of this work is to estimate the value of the annual recharge in some parts of the Kermanshah and Kurdistan province located in the west of Iran. There are many approaches available for estimation of the recharge, but RS (remote sensing) and GIS (geographic information system) have provided and combined a lot of effective spatial and temporal data of large areas within a short time. For this purpose, nine information layers including the slope, aspect of slope, lithology, lineament density, drainage density, precipitation, vegetation density, soil cover, and karst featur...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 🌏 Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 🖊️ The authors used the Landsat-5 TM and Landsat-8 OLI remote sensing images as the basic data sources, and obtained the land cover classification maps from 1995 to 2020 by ENVI. #Alberta #Oilsands #Vegetationchanges #Remotesensing #Landsat 🔗 DOI: https://doi.org/10.30564/jees.v4i2.4687 ✉ Email: jees@bilpublishing.com 👩‍💼 Managing Editor: Tina Guo

Floodplain Mapping and Risks Assessment of the Orashi River Using Remote Sensing and GIS in the Niger Delta Region, Nigeria DOI:  https://doi.org/10.30564/jgr.v4i2.3014 Abstract Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures. The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map using ArcGIS software. The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain .Incorporating the 3D slope which reveals that> 8 and <8 makes up 1.15% and 98.85% of the study area respectively confirms the area is a floodplain. Aspect indicate west-facing slope are dark blue, 3D hillshade indicate yellow is very low area and the h...

Floodplain Mapping and Risks Assessment of the Orashi River Using Remote Sensing and GIS in the Niger Delta Region, Nigeria DOI:  https://doi.org/10.30564/jgr.v4i2.3014 Abstract Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures. The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map using ArcGIS software. The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain .Incorporating the 3D slope which reveals that> 8 and <8 makes up 1.15% and 98.85% of the study area respectively confirms the area is a floodplain. Aspect indicate west-facing slope are dark blue, 3D hillshade indicate yellow is very low area and the h...

Use of GIS to Estimate Recharge and Identification of Potential Groundwater Recharge Zones in the Karstic Aquifers, West of Iran DOI:  https://doi.org/10.30564/agger.v4i4.5122 Received: 4 October 2022 Revised: 31 October 2022 Accepted: 5 November 2022 Published Online: 11 November 2022 Abstract Estimating and studying groundwater recharge is necessary and important for the management of water resources. The main aim of this work is to estimate the value of the annual recharge in some parts of the Kermanshah and Kurdistan province located in the west of Iran. There are many approaches available for estimation of the recharge, but RS (remote sensing) and GIS (geographic information system) have provided and combined a lot of effective spatial and temporal data of large areas within a short time. For this purpose, nine information layers including the slope, aspect of slope, lithology, lineament density, drainage density, precipitation, vegetation density, soil cover, and karst featur...

Metric-based Few-shot Classification in Remote Sensing Image DOI:  https://doi.org/10.30564/aia.v4i1.4124 Abstract Target recognition based on deep learning relies on a large quantity of samples, but in some specific remote sensing scenes, the samples are very rare. Currently, few-shot learning can obtain high-performance target classification models using only a few samples, but most researches are based on the natural scene. Therefore, this paper proposes a metric-based few-shot classification technology in remote sensing. First, we constructed a dataset (RSD-FSC) for few-shot classification in remote sensing, which contained 21 classes typical target sample slices of remote sensing images. Second, based on metric learning, a k-nearest neighbor classification network is proposed, to find multiple training samples similar to the testing target, and then the similarity between the testing target and multiple similar samples is calculated to classify the testing target. Finally, the...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 DOI:  https://doi.org/10.30564/jees.v4i2.4687 Abstract There are rich oil and gas resources in Alberta oil sand mining area in Canada. Since the 1960s, the Canadian government decided to increase the mining intensity. However, the exploitation will bring many adverse effects. In recent years, more people pay attention to the environmental protection and ecological restoration of mining area, such as issues related with changes of vegetated lands. Thus, the authors used the Landsat-5 TM and Landsat-8 OLI remote sensing images as the basic data sources, and obtained the land cover classification maps from 1995 to 2020 by ENVI. Based on the NDVI, NDMI and RVI, three images in each period are processed and output to explore the long-term impact of exploitation. The results show that from 1995 to 2020, the proportion of vegetation around mining areas decreased sharply, the scale of construct...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 DOI:  https://doi.org/10.30564/jees.v4i2.4687 Keywords:  Alberta, Oil sands, Vegetation changes, Remote sensing, Landsat Abstract There are rich oil and gas resources in Alberta oil sand mining area in Canada. Since the 1960s, the Canadian government decided to increase the mining intensity. However, the exploitation will bring many adverse effects. In recent years, more people pay attention to the environmental protection and ecological restoration of mining area, such as issues related with changes of vegetated lands. Thus, the authors used the Landsat-5 TM and Landsat-8 OLI remote sensing images as the basic data sources, and obtained the land cover classification maps from 1995 to 2020 by ENVI. Based on the NDVI, NDMI and RVI, three images in each period are processed and output to explore the long-term impact of exploitation. The results show that from 1995 to 2020, the propor...

Metric-based Few-shot Classification in Remote Sensing Image DOI:  https://doi.org/10.30564/aia.v4i1.4124 Abstract Target recognition based on deep learning relies on a large quantity of samples, but in some specific remote sensing scenes, the samples are very rare. Currently, few-shot learning can obtain high-performance target classification models using only a few samples, but most researches are based on the natural scene. Therefore, this paper proposes a metric-based few-shot classification technology in remote sensing. First, we constructed a dataset (RSD-FSC) for few-shot classification in remote sensing, which contained 21 classes typical target sample slices of remote sensing images. Second, based on metric learning, a k-nearest neighbor classification network is proposed, to find multiple training samples similar to the testing target, and then the similarity between the testing target and multiple similar samples is calculated to classify the testing target. Finally, the...

Floodplain Mapping and Risks Assessment of the Orashi River Using Remote Sensing and GIS in the Niger Delta Region, Nigeria DOI:  https://doi.org/10.30564/jgr.v4i2.3014 Abstract Residents along the shoreline of the Orashi River have yearly been displaced and recorded loss of lives,farmland,and infrastructures. The Government’s approach has been the provision of relief materials to the victims instead of implementing adequate control measures.This research employs Shuttle Radar Topographic Mission and Google Earth imagery in developing a 3D floodplain map using ArcGIS software. The result indicates the drainage system in the study area is dendritic with catchment of 79 subbasins and 76 pour point implying the area is floodplain .Incorporating the 3D slope which reveals that> 8 and <8 makes up 1.15% and 98.85% of the study area respectively confirms the area is a floodplain. Aspect indicate west-facing slope are dark blue, 3D hillshade indicate yellow is very low area and the h...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 Jixin He (College of Earth Sciences, Jilin University, Changchun, Jilin, 130061, China) Debo Chen (College of Earth Sciences, Jilin University, Changchun, Jilin, 130061, China) Ye Zhan (Aviation University Air Force, Changchun, Jilin, 130021, China) Chao Liu (College of Earth Sciences, Jilin University, Changchun, Jilin, 130061, China) Ruichen Liu (College of Earth Sciences, Jilin University, Changchun, Jilin, 130061, China) Article ID:  4687 DOI:  https://doi.org/10.30564/jees.v4i2.4687 Abstract There are rich oil and gas resources in Alberta oil sand mining area in Canada. Since the 1960s, the Canadian government decided to increase the mining intensity. However, the exploitation will bring many adverse effects. In recent years, more people pay attention to the environmental protection and ecological restoration of mining area, such as issues related with changes of vegetated lan...

Use of GIS to Estimate Recharge and Identification of Potential Groundwater Recharge Zones in the Karstic Aquifers, West of Iran DOI:  https://doi.org/10.30564/agger.v4i4.5122 Abstract Estimating and studying groundwater recharge is necessary and important for the management of water resources. The main aim of this work is to estimate the value of the annual recharge in some parts of the Kermanshah and Kurdistan province located in the west of Iran. There are many approaches available for estimation of the recharge, but RS (remote sensing) and GIS (geographic information system) have provided and combined a lot of effective spatial and temporal data of large areas within a short time. For this purpose, nine information layers including the slope, aspect of slope, lithology, lineament density, drainage density, precipitation, vegetation density, soil cover, and karst features were prepared and imported to the ArcMap software. After prepar...

Vegetation Changes in Alberta Oil Sands, Canada, Based on Remotely Sensed Data from 1995 to 2020 DOI:  https://doi.org/10.30564/jees.v4i2.4687 Abstract There are rich oil and gas resources in Alberta oil sand mining area in Canada. Since the 1960s, the Canadian government decided to increase the mining intensity. However, the exploitation will bring many adverse effects. In recent years, more people pay attention to the environmental protection and ecological restoration of mining area, such as issues related with changes of vegetated lands. Thus, the authors used the Landsat-5 TM and Landsat-8 OLI remote sensing images as the basic data sources, and obtained the land cover classification maps from 1995 to 2020 by ENVI. Based on the NDVI, NDMI and RVI, three images in each period are processed and output to explore the long-term impact of exploitation. The results show that from 1995 to 2020, the proportion of vegetation around mining areas decreased sharply, the scale of construct...

A Review of Landsat TM/ETM based Vegetation Indices as Applied to Wetland Ecosystems DOI:  https://doi.org/10.30564/jgr.v2i1.499 Abstract A review of vegetation indices as applied to Landsat-TM and ETM+ multispectral data is presented. The review focuses on indices that have been developed to produce biophysical information about vegetation biomass/greenness, moisture and pigments.In addition, a set of biomass/greenness and moisture content indices are tested in a Mediterranean semiarid wetland environment to determine their appropriateness and potential for carrying redundant information.The results indicate that most vegetation indices used for biomass/greenness mapping produce similar information and are statistically well correlated.  Keywords Greenness determination; Mediterranean wetland areas; Moisture estimation; Remote sensing; Vegetation spectral indices; Thematic Mapper sensor Full Text: PDF

  ISSN: 2630-5119(Online) Email:jasr@bilpublishing.com Online Submissions Journal of Atmospheric Science Research  publishes original research papers that offers a rapid review and publication that freely disseminates research findings in areas of Remote Sensing, Weather Extremes, Air Pollution, Satellite Meteorology and more. The Journal focuses on innovations of research methods at all stages and is committed to providing theoretical and practical experience for all those who are involved in these fields. Journal of Atmospheric Science Research  aims to discover innovative methods, theories and studies in all aspects of Atmospheric Science by publishing original articles, case studies and comprehensive reviews. The scope of the papers in this journal includes, but is not limited to: Remote Sensing Climate Dynamics Air Chemistry Hydrological Cycle Satellite Meteorology Ocean Dynamics Climate Change Weather Extremes Air Pollution Weather and Climate Prediction Climate Var...