Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine

Mehravar, Saeed; Amani, Meisam; Moghimi, Armin; Javan, Farzaneh Dadrass; Samadzadegan, Farhad; Ghorbanian, Arsalan; Stein, Alfred; Mohammadzadeh, Ali; Mirmazloumi, S. Mohammad

doi:10.1016/j.asr.2021.08.041

Cited by 25 publications

(4 citation statements)

References 77 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since the severe drought period from 1999 to 2001, Iran has experienced a 20-year warm and dry period (compared to 1980-2000), with a less pronounced drying trend or even a reverted trend towards wetter conditions. Mehravar et al (2021) 65 analyzed integrative drought indices for Iran from 2001 to 2020 and reported trends to wetter conditions even in most basins of Iran.…”

Section: Discussionmentioning

confidence: 99%

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Behling

Roessner

Foerster

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Iran has experienced a drastic increase in water scarcity in the last decades. The main driver has been the substantial unsustainable water consumption of the agricultural sector. This study quantifies the spatiotemporal dynamics of Iran’s hydrometeorological water availability, land cover, and vegetation growth and evaluates their interrelations with a special focus on agricultural vegetation developments. It analyzes globally available reanalysis climate data and satellite time series data and products, allowing a country-wide investigation of recent 20+ years at detailed spatial and temporal scales. The results reveal a wide-spread agricultural expansion (27,000 km$$^2$$ 2 ) and a significant cultivation intensification (48,000 km$$^2$$ 2 ). At the same time, we observe a substantial decline in total water storage that is not represented by a decrease of meteorological water input, confirming an unsustainable use of groundwater mainly for agricultural irrigation. As consequence of water scarcity, we identify agricultural areas with a loss or reduction of vegetation growth (10,000 km$$^2$$ 2 ), especially in irrigated agricultural areas under (hyper-)arid conditions. In Iran’s natural biomes, the results show declining trends in vegetation growth and land cover degradation from sparse vegetation to barren land in 40,000 km$$^2$$ 2 , mainly along the western plains and foothills of the Zagros Mountains, and at the same time wide-spread greening trends, particularly in regions of higher altitudes. Overall, the findings provide detailed insights in vegetation-related causes and consequences of Iran’s anthropogenic drought and can support sustainable management plans for Iran or other semi-arid regions worldwide, often facing similar conditions.

show abstract

Section: Discussionmentioning

confidence: 99%

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Behling

Roessner

Foerster

et al. 2022

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Overall, the processing and analyses were conducted in Google Earth Engine (GEE) through the method illustrated in Figure 2. The GEE was launched by Google in 2010 for cataloging and processing a wide variety of Earth observation data in a cost-and time-efficient manner [54][55][56][57]. This platform is precious when the objective is to process big open-access Earth observation data over a large area and within a long time [58,59].…”

Section: Data Processing Methodologymentioning

confidence: 99%

Trends of CO and NO2 Pollutants in Iran during COVID-19 Pandemic Using Timeseries Sentinel-5 Images in Google Earth Engine

et al. 2022

Self Cite

View full text Add to dashboard Cite

The first case of COVID-19 in Iran was reported on 19 February 2020, 1 month before the Nowruz holidays coincided with the global pandemic, leading to quarantine and lockdown. Many studies have shown that environmental pollutants were drastically reduced with the spread of this disease and the decline in industrial activities. Among these pollutants, nitrogen dioxide (NO2) and carbon monoxide (CO) are widely caused by anthropogenic and industrial activities. In this study, the changes in these pollutants in Iran and its four metropolises (i.e., Tehran, Mashhad, Isfahan, and Tabriz) in three periods from 11 March to 8 April 2019, 2020, and 2021 were investigated. To this end, timeseries of the Sentinel-5P TROPOMI and in situ data within the Google Earth Engine (GEE) cloud-based platform were employed. It was observed that the results of the NO2 derived from Sentinel-5P were in agreement with the in situ data acquired from ground-based stations (average correlation coefficient = 0.7). Moreover, the results showed that the concentration of NO2 and CO pollutants in 2020 (the first year of the COVID-19 pandemic) was 5% lower than in 2019, indicating the observance of quarantine rules, as well as people’s initial fear of the coronavirus. Contrarily, these pollutants in 2021 (the second year of the COVID-19 pandemic) were higher than those in 2020 by 5%, which could have been due to high vehicle traffic and a lack of serious policy- and law-making by the government to ban urban and interurban traffic. These findings are essential criteria that might be used to guide future manufacturing logistics, traffic planning and management, and environmental sustainability policies and plans. Furthermore, using the COVID-19 scenario and free satellite-derived data, it is now possible to investigate how harmful gas emissions influence air quality. These findings may also be helpful in making future strategic decisions on how to cope with the virus spread and lessen its negative social and economic consequences.

show abstract

“…Desertification, a global, regional, and local issue, has been studied using various techniques, including empirical, remote sensing, and model-based approaches [5][6][7][8]. Over the past three decades, remote sensing data has been utilized for monitoring ecosystems and natural disasters such as landscape degradation of coastal deserts [9], drought [10], and desertification [11,12]. Remote sensing collects precise data, provides rapid updates, and analyzes imagery over long periods of time, aiding in combating desertification in arid and semiarid regions and minimizing its effects.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Desertification Dynamics in Arid Coastal Areas by Integrating Remote Sensing Data and Statistical Techniques

Hasan,

Alharbi,

Alqurashi

et al. 2024

Sustainability

View full text Add to dashboard Cite

Arid coastal regions are threatened by land desertification, which poses a serious threat to desert ecosystems, urban areas, and sustainability on a local as well as global scale. The present study aims to map desertification and the degree of its severity over the Jazan province on the western coast of Saudi Arabia. This investigation was conducted through the integration of remote sensing data (2001 and 2020) and statistical techniques. A scatter diagram, Karl Pearson correlation coefficient, and significance p-value test were performed on various spectral indices and tasseled cap transformation (TCT) derivative matrices to determine the strong significant relation of the spectral indices combination. Based on these analyses, the desertification degree index (DDI) was developed using a NDVI–TCG combination. The desertification grades were mapped and categorized into five classes, namely, non-desertification, low, moderate, severe, and extreme desertification. The results indicated that the spatial distribution of desertification grades declined from west to east during the period from 2001 to 2020. The degree of desertification improved during the study period since there was a significant reduction in extremely serious desertification land by 15.5% and an increase in weak desertification land by 7.8%. The dynamic changes in the DDI classes in the Jazan province mainly involve transformation from extremely serious to serious, serious to moderate, and moderate to weak, with areas of 2268.1 km2, 1518.5 km2, and 1062.5 km2, respectively. Generally, over the 19-year period, the restoration of vegetated areas accounted for 41.99% of the total study area, while desertification degradation land represented 15.57% of the total area of the Jazan province.

show abstract

Temperature-Vegetation-soil Moisture-Precipitation Drought Index (TVMPDI); 21-year drought monitoring in Iran using satellite imagery within Google Earth Engine

Cited by 25 publications

References 77 publications

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Interrelations of vegetation growth and water scarcity in Iran revealed by satellite time series

Trends of CO and NO2 Pollutants in Iran during COVID-19 Pandemic Using Timeseries Sentinel-5 Images in Google Earth Engine

Assessment of Desertification Dynamics in Arid Coastal Areas by Integrating Remote Sensing Data and Statistical Techniques

Contact Info

Product

Resources

About