Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine
Irrigated agricultural expansion is one of the main reasons for water scarcity in the Lake Urmia basin. Although previous studies have analyzed the impact of cropland expansion on the Lake Urmia Shrinkage, there is a lack of comprehensive annual assessment of historical irrigation expansion in the L...
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| Format: | Article |
| Language: | English |
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Elsevier
2021-12-01
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| Series: | International Journal of Applied Earth Observations and Geoinformation |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0303243421003147 |
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| author | Amin Naboureh Ainong Li Hamid Ebrahimy Jinhu Bian Mohsen Azadbakht Meisam Amani Guangbin Lei Xi Nan |
| author_facet | Amin Naboureh Ainong Li Hamid Ebrahimy Jinhu Bian Mohsen Azadbakht Meisam Amani Guangbin Lei Xi Nan |
| author_sort | Amin Naboureh |
| collection | DOAJ |
| description | Irrigated agricultural expansion is one of the main reasons for water scarcity in the Lake Urmia basin. Although previous studies have analyzed the impact of cropland expansion on the Lake Urmia Shrinkage, there is a lack of comprehensive annual assessment of historical irrigation expansion in the Lake Urmia basin and its impact on water resources of this region. In this study, we developed an automatic and efficient workflow using Landsat and Gravity Recovery and Climate Experiment (GRACE) data, GRACE Follow-On (GRACE-FO) data, and a sample migration technique within the Google Earth Engine cloud computing platform to comprehensively investigate the impact of irrigated agricultural expansion on the shrinkage of Lake Urmia, as one of the most severe environmental crisis in the world. Additionally, using the global surface water data, we proposed a fully automatic procedure to obtain reference samples from water bodies. The Lake Urmia basin was first classified into the water, irrigated, and Non-Water/Irrigated classes using the random forest algorithm. The average overall accuracy of the produced annual land cover maps during 1987–2020 was 92.2%, representing the great potential of the developed method for land cover mapping. We found that the irrigated lands expanded by nearly 890 km2 during the study period. Coincident with this change, although the area of water bodies in Lake Urmia partially recovered after 2015 (reached from 1,050 km2 in 2015 to 3,370 km2 in 2020), it is currently far beyond its original condition (i.e., ∼5,400 km2, average record during 1987–2000). Moreover, the information of the Terrestrial Water Storage (TWS) from the GRACE and GRACE-FO data between 2003 and 2020 showed a dramatic decrease in TWS level (∼−11.5 cm). The findings of this research will assist the local stakeholders and authorities to better understanding the environmental costs of irrigation expansion in the Lake Urmia basin. |
| first_indexed | 2024-12-12T15:08:27Z |
| format | Article |
| id | doaj.art-be262266575f4e0d96f5697a0fb18276 |
| institution | Directory Open Access Journal |
| issn | 1569-8432 |
| language | English |
| last_indexed | 2024-12-12T15:08:27Z |
| publishDate | 2021-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | International Journal of Applied Earth Observations and Geoinformation |
| spelling | doaj.art-be262266575f4e0d96f5697a0fb182762022-12-22T00:20:41ZengElsevierInternational Journal of Applied Earth Observations and Geoinformation1569-84322021-12-01105102607Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth EngineAmin Naboureh0Ainong Li1Hamid Ebrahimy2Jinhu Bian3Mohsen Azadbakht4Meisam Amani5Guangbin Lei6Xi Nan7Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaResearch Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China; Corresponding authors.Center for Remote Sensing and GIS Research, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran; Corresponding authors.Research Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaCenter for Remote Sensing and GIS Research, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, IranWood Environment & Infrastructure Solutions, Ottawa, ON K2E 7K3, CanadaResearch Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaResearch Center for Digital Mountain and Remote Sensing Application, Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, ChinaIrrigated agricultural expansion is one of the main reasons for water scarcity in the Lake Urmia basin. Although previous studies have analyzed the impact of cropland expansion on the Lake Urmia Shrinkage, there is a lack of comprehensive annual assessment of historical irrigation expansion in the Lake Urmia basin and its impact on water resources of this region. In this study, we developed an automatic and efficient workflow using Landsat and Gravity Recovery and Climate Experiment (GRACE) data, GRACE Follow-On (GRACE-FO) data, and a sample migration technique within the Google Earth Engine cloud computing platform to comprehensively investigate the impact of irrigated agricultural expansion on the shrinkage of Lake Urmia, as one of the most severe environmental crisis in the world. Additionally, using the global surface water data, we proposed a fully automatic procedure to obtain reference samples from water bodies. The Lake Urmia basin was first classified into the water, irrigated, and Non-Water/Irrigated classes using the random forest algorithm. The average overall accuracy of the produced annual land cover maps during 1987–2020 was 92.2%, representing the great potential of the developed method for land cover mapping. We found that the irrigated lands expanded by nearly 890 km2 during the study period. Coincident with this change, although the area of water bodies in Lake Urmia partially recovered after 2015 (reached from 1,050 km2 in 2015 to 3,370 km2 in 2020), it is currently far beyond its original condition (i.e., ∼5,400 km2, average record during 1987–2000). Moreover, the information of the Terrestrial Water Storage (TWS) from the GRACE and GRACE-FO data between 2003 and 2020 showed a dramatic decrease in TWS level (∼−11.5 cm). The findings of this research will assist the local stakeholders and authorities to better understanding the environmental costs of irrigation expansion in the Lake Urmia basin.http://www.sciencedirect.com/science/article/pii/S0303243421003147Land coverIrrigation expansionsLake UrmiaGoogle Earth EngineSample migrationLandsat |
| spellingShingle | Amin Naboureh Ainong Li Hamid Ebrahimy Jinhu Bian Mohsen Azadbakht Meisam Amani Guangbin Lei Xi Nan Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine International Journal of Applied Earth Observations and Geoinformation Land cover Irrigation expansions Lake Urmia Google Earth Engine Sample migration Landsat |
| title | Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine |
| title_full | Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine |
| title_fullStr | Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine |
| title_full_unstemmed | Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine |
| title_short | Assessing the effects of irrigated agricultural expansions on Lake Urmia using multi-decadal Landsat imagery and a sample migration technique within Google Earth Engine |
| title_sort | assessing the effects of irrigated agricultural expansions on lake urmia using multi decadal landsat imagery and a sample migration technique within google earth engine |
| topic | Land cover Irrigation expansions Lake Urmia Google Earth Engine Sample migration Landsat |
| url | http://www.sciencedirect.com/science/article/pii/S0303243421003147 |
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