Ecological Drought Monitoring of Middle Zagros Based on Landsat 7 Satellite Data and Climate Data (Case Study: Lorestan Province)

Document Type : Original Article

Authors

1 Associate Prof., Lorestan University

2 Associate Prof., Geography Dep., Faculty of Geography, Tehran University, Tehran

3 Ph.D. of Geography, Geography Dep., Faculty of Geography, Tehran University, Tehran

Abstract

Vegetation plays an important role in protecting water and soil resources, stabilizing carbon and improving air quality. In Middle Zagros, forest and pasture vegetation is very important in terms of protecting soil and water resources and sustaining economic activities. In this research, using the Google Earth Engine platform and Landsat 7 satellite images, the drought of Middle Zagros (Lorestan province) was monitored with vegetation indices NDVI, SAVI and VCI, as well as meteorological drought index SPI for the statistical period of 2020-2000. To calculate the SPI index, the precipitation data of 9 synoptic meteorological stations with appropriate spatial distribution and the length of the statistical period (2020-2000) were used, and the processing was done in DPI software. In order to calculate the plant indices, first, all the geometrically corrected satellite images of the ETM+ sensor of the Landsat satellite were called for Lorestan province for each year. At this stage, an average of 52 images were called for each year. Then the images with less than 5% cloud cover were selected and processed. The results of the VCI index showed that mainly the studied area was affected by mild drought during the statistical period of 2020-2000. The year 2008 had the highest amount of drought related to the middle class with 5880.6 hectares among the studied years. The results of the SPI index showed that there was a moderate drought in 2010, a severe drought in 2008 and 2017, a mild drought in 2006, and a severe drought in 2019. The results of NDVI and SAVI indices also show the increase of thin vegetation classes and areas without vegetation by 1.331679 and 115164 hectares, respectively, and the decrease of normal and dense vegetation by 446160.7 and 682.4 hectares respectively per year. 2008 was compared to 2006 and 2007. Based on the results of all three investigated indicators, the favorable conditions of vegetation cover and ecological threat were obtained in 2016, 2019 and 2020. The highest level of this coordination between SPI meteorological drought and vegetation indices was observed in 2008 and 2010 and to some extent in 2019. In general, the results show that the increase or decrease of vegetation can be caused by the occurrence or absence of drought, while other factors such as land use changes should also be considered.

Keywords

References

Abdollahi, L., Faraji, M., Haghizadh, A. & Dehdari, S., 2019, Investigation of Hydrological Drought Process Using Time Series Analysis and SDI Index (Case Study of Marian River Basin of Lorestan Province), Journal of Range and Watershed Managment, 72(2), PP. 477-487. In Persian. doi: 10.22059/jrwm.2019.261687.1279.
Abdollahi, A.A., Khabazi, M. & Dorani, Z., 2020, Modeling and Predicting Land Use Changes in Lahijan City With a Sustainable Development Approach, Journal of Sustainable City, 2(4), PP. 17-30. In Persian.
Aghababaei, M., Ebrahimi, A., Naghipour, A., Asadi, E. & Verrelst, J., 2021, Vegetation Types Mapping Using Multi-Temporal Landsat Images in the Google Earth Engine Platform, Remote Sens, 13(22), PP. 1-15.
Alimohammadi, A., Mousivand, A.J. & Shayan, S., 2010, Prediction of Land Use and Land Cover Changes by Using Multi-Temporal Satellite Imagery and MARKOV Chain Model, Spatial Planning, 14(367), PP. 117-130. In Persian.
Alirezaee, Z., Gandomkar, A., Khodagholi, M. & Abasi, A., 2019, Spatiotemporal Dynamics of Oak Forest of Zagros in Responce to Drought Case Study: Oak Forest of Lorestan, Iranian Journal of Forest and Range Protection Research, 17(1), PP. 107-123. In Persian. doi: 10.22092/ijfrpr.2019.119997.
Amanpour, S., Kamelifar, M. & Bahmaei, H., 2017, Analysis of Landuse Change Metropolises Using Satellite imagery Analysis in ENVI Case Study: AHVAZ METROPOLIS, Scientific – Research Quarterly Geographical Data (SEPEHR), 102, PP. 139-150. In Persian.
Areffian, A., Kayani Sadr, M., Eslamian, S. & Khosh Fetrat, A., 2020, Monitoring the Effects of Drought on Vegetation in Mountainous Areas Using MODIS Satellite Images (Case Study: Lorestan Province), Journal of Environmental Science Studies, 5(4), PP. 3183-3189. In Persian.
 
Darvishi, Sh., Soleimani, K., Rashidpour, M. & 2019, Analysis of Land Use Role in the Formation of Thermal Islets of Marivan County Using Landsat Satellite Images, Geography and Development, 17(54), PP. 143-162. In Persian. doi: 10.22111/gdij.2019.4361.
Dehdari, S., Armand, N., Faraji, M., Arman, N. & Hadian, F., 2018, Land Use Change Detection of 3 and 4 Karun Dams Using Satelite Images, Journal of Range and Watershed Management, 71(1), PP. 85-96. In Persian.  doi: 10.22059/jrwm.2017.240266.1161.
Ding, Y., Xu, J., Wang, X. & Peng, X. & Cai, H., 2020, Spatial and Temporal Effects of Drought on Chinese Vegetation under Different Coverage Levels, Science of the Total Environment, 716, PP. 137-166.
Esmaeili, H., Mirmousavi, S.H. & Soheili, E., 2022, Investigation of Agricultural Drought Time Series in Darab City using Remote Sensing and Google Earth Engine System, Journal of Geography and Environmental Hazards, 10(4), PP. 175-192. In Persian. doi: 10.22067/geoeh. 2021.69186.1029.
Falahi, M., Mansouri, M.R., AliGhaderi, R. & Salehi, H., 2019, Drainage Zoning and Analysis in Lorestan Province Using Drought Indices, Geography and Human Relationships, 2(2), PP. 200-219. In Persian.
Han, Zh., Huang, Sh., Huang, Q., Bia, Q., Leng, G., Wang, H., Zhao, J., Wei, X. & Zheng, X., 2020, Effects of Vegetation Restoration on Groundwater Drought in the Loess Plateau, China, Journal of Hydrology, 591, PP. 125-566.
Hashemnia, G., Amar, T., Moulai, N. & Basit Gharashi Minabad, M., 2018, Explaining the Physical Consequences of Agricultural Land Use Changes in the Villages of Khammam District of Rasht City in the Last Two Decades, Quarterly of Geography (Regional Planing), 8(33), PP. 333-346. In Persian.
Imani, J., Ebrahimi, A., Gholonejad, B. & Tahmasebi, P., 2018, Comparison of NDVI and SAVI in Three Plant Communities with Different Sampling Intensity (Case Study: Choghakhour Lake Rangelands in Charmahal & Bakhtiri), Iranian journal of Rangeland and Desert Research, 25(1), PP. 152-169. In Persian. doi: 10.22092/ijrdr.2018. 116233.
Karimi, M., Shahedi, K., Raziei, T. & Miryaghoobzadeh, M., 2020, Analysis of Performance of Vegetation Indices on Agricultural Drought Using Remote Sensing Technique in Karkheh Basin, Iranian Journal of Remote Sensing & GIS, 11(4), PP. 29-46. In Persian. doi: 10.52547/gisj.11.4.29.
Khan, R. & Gilani, H., 2021, Global Drought Monitoring with Drought Severity Index (DSI) Using Google Earth Engine, Theoretical and Applied Climatology, 146, PP. 411-427.
Khosravi, M., Movaqqari, A. & Mansouri Daneshvar, M.R., 2013, Evaluating the PNI, RAI, SIP and SPI Indices in Mapping Drought Intensity of Iran: Comparing the Interpolation Method and Digital Elevation Model (DEM), Geography and Environmental Sustainability, 2(4), PP. 53-70. In Persian.
Khosravi, R., Hassanzadeh, R., Hossinjanizadeh, M. & Mohammadi, S., 2020, Investigating Water Body Changes Using Remote Sensing Water Indices and Google Earth Engine: Case Study of Poldokhtar Wetlands, Lorestan Province, Iranian journal of Ecohydrology, 7(1), PP. 131-146. In Persian. doi: 10.22059/ije.2020.295498.1265.
Kiavarz, M., Karimi Firozjaei, M. & Kalantari, M., 2018, Monitoring and Prediction of Land Use Changes and Physical Expansion of Babol City during 1985-2040 Using Multi-Temporal Landsat Imagery, Physical Sacial Planning, 5(3), PP. 32-52. In Persian. doi: 10.30473/psp.2018.5257.
Liu, Q., Zhang, S., Zhang, H., Bai, Y. & Zhang, J., 2020, Monitoring Drought Using Composite Drought Indices Based on Remote Sensing, Science of the Total Environment, 711, P. 134585.
Meng, X., Gao, X., Li, S., Li, S. & Lei, J., 2021, Monitoring Desertification in Mongolia Based on Landsat Images and Google Earth Engine from 1990 to 2020, Ecological Indicators, 129, PP. 107-908.
Mirmohammadhosseini, T.S., Ghermezcheshmeh, B., Hosseini, S. & Sharafati, A., 2021, An Assessment of the Relationships between Meteorological Drought Index and Vegetation Condition in Dry Farming in the Province of Lorestan, Watershed Management Research Journal, 34(2), PP. 77-90. In Persian. doi: 10.22092/wmej.2020. 342647.1332.
Nateghi, S., Nohegar, A., Ehsani, A. & Bazrafshan, O., 2017, Evaluating the Vegetation Changes upon Vegetation Index by Using Remote Sensing, Iranian Journal of Rangeland and Desert Research, 24(4), PP. 778-790. In Persian. doi: 10.22092/ijrdr.2017.114889.
Navidtalab, A., Askari, G., Ahmadpour, F. & Tahmasebi, M., 2020, Drought Evaluation of a Thirty-Year Period (1988–2017) in Lurestan Province Using the Percent of Normal Precipitation Index (PNI), Hydrogeomorphology, 7(24), PP. 107-125. In Persian. doi: 10.22034/hyd.2020.40496.1537.
Niazi, Y., Talebi, A., Mokhtaari, M.H. & Vazifedoust, M., 2017, Assessing the Efficiency of Vegetation Drought Index (VDI) and Temperature Drought Index (TDI) Based on Satellite Images in Central IRAN, Arid Biom Scientific and Research Journal, 7(1), PP. 79-94. In Persian.
Nikpey, H. & Momeni, M., 2019, Effect of Climatic Zoning and Altitude Zoning on the Correlation of Remote Sensing Drought Indices with Precipitation Data and Introducing Local Indicators, Iranian Journal of Remote Sensing & GIS, 11(2), PP. 47-62. In Persian. Doi: 10.52547/gisj.11.2.47.
Ozelkan, E., Chen, G. & Ustundag, B., 2016, Multiscale Object-Based Drought Monitoring and Comparison in Rainfed and Irrigated Agriculture from Landsat 8 OLI Imagery, International Journal of Applied Earth Observation and Geoinformation, 44, PP. 159-170.
Palchaudhuri, M. & Biswas, S., 2020, Application of LISS III and MODIS-Derived Vegetation Indices for Assessment of Micro-Level Agricultural Drought, The Egyptian Journal of Remote Sensing and Space Sciences, 23(2), PP. 221-229.
Rajabzadeh, F., 2017, Land Use Changes by Using RS and Markov Chain Technique in the South-West of Tehran, Journal of Water and Soil Resources Conservation, 6(2), PP. 59-72. In Persian.
Rezaei, R., Ghodosi, J., Hasani, A., Arjmandi, R. & VafaeiNejad, A., 2020, Classification and Evaluation of Land Use Changes Using Landsat Satellite Images (Case Study: Qazvin Plain Aquifer), Geographic Space, 72(20(, PP. 185-204. In Persian.
Sabzghabaei, G., Salehipour, F., Dashti, S. & Safavian, A., 2018, Land Use/Land Cover Change Modeling Using Marcov Chain and Cellular Automata (Case Study: Dezful, Iran), Journal of Geography and Environmental Hazards, 7(2), PP. 169-180. In Persian. Doi: 10.22067/geo.v7i2.64775.
Safarianzengir, V., Fatahi, A., Sobhani, B. & Amiri Doumari, S., 2022, Temporal and Spatial Analysis and Monitoring of Drought (Meteorology) and Its Impacts on Environment Changes in Iran, Atmospheric Science Letters, 23(5), PP. 1-15.
Salajegheh, A., Razavizadeh, S., Khorasani, N., Hamidifar, M. & Salajegheh, S., 2011, Land Use Changes and Its Effects on Water Quality (Case Study: Karkheh Watershed), Journal of Environmental Studies, 37(58), PP. 81-86. In Persian.
Shabani, M., Darvishan, S. & Solaimani, K., 2019, Investigating the Effects of Land Use Change on Spatiotemporal Patterns of Land Surface Temperature and Thermal Islands (Case Study: Saqqez County), Geography and Environmental Planning, 30(1), PP. 37-54. In Persian. doi: 10.22108/gep.2019.115781.1127.
Shanani Hoveyzeh, S.M. & Zarei, H., 2017, Investigation of Land Use Changes during the Past Two Last Decades (Case Study: Abolabas Basin), Jwmr, 7(14), PP. 244-237. In Persian.
Tonini, F., Lasinio, G. & Hochmair, H., 2012, Mapping Return Levels of Absolute NDVI Variations for the Assessment of Drought Risk in Ethiopia, International Journal of Applied Earth Observation and Geoinformation, 18, PP. 564-572.
Vallejo-Villalta, I., Rodríguez-Navas, E. & Márquez-Pérez, J., 2019, Mapping Forest Fire Risk at a Local Scale—A Case Study in Andalusia (Spain), Environments, 6, PP. 1-22.
Venkatapaa, M., Saski, Han, P. & Abe, I., 2021, Impacts of Droughts and Floods on Croplands and Crop Production in Southeast Asia-An Application of Google Earth Engine, Science of the Total Environment, 795, PP. 148-829.
Xie, F. & Fan, H., 2021, Deriving Drought Indices from MODIS Vegetation Indices (NDVI/EVI) and Land Surface Temperature (LST): Is Data Reconstruction Necessary?, International Journal of Applied Earth Observations and Geoinf, 101, PP. 1-16.
Xiong, Y., Xu, W., Lu, N., Huang, Sh., Wu, C., Wang, L., Dai, F. & Kou, W., 2021, Assessment of Spatial–Temporal Changes of Ecological Environment Quality Based on RSEI and GEE: A Case Study in Erhai Lake Basin, Yunnan province, China, Ecological Indicators, 125, P. 107518.
Zhang, A. & Jia, G., 2013, Monitoring Meteorological Drought in Semiarid Regions Using Multi-Sensor Microwave Remote Sensing Data, Remote Sensing of Environment, 134, PP. 12-23.
Zhang, L., Jiao, W., Zhang, H., Huang, CH. & Tong, Q., 2017, Studying Drought Phenomena in the Continental United States in 2011 and 2012 Using Various Drought Indices, Remote Sensing of Environment, 190, PP. 96-106.
Zhao, X., Xia, H. Liu, B. & Jiao, W., 2022, Spatiotemporal Comparison of Drought in Shaanxi–Gansu–Ningxia from 2003 to 2020 Using Various Drought Indices in Google Earth Engine, Remote Sens, 14(7), PP.1-20.
Zhong, Sh., Ziheng, S. & Di, L., 2021, Characteristics of Vegetation Response to Drought in the CONUS Based on Long-Term Remote Sensing and Meteorological Data, Ecological Indicators, 127, PP.107-767.
Iranian Journal of Remote Sensing & GIS
Volume 15, Issue 3 - Serial Number 59
September 2023
Pages 125-142

Files

Share

How to cite

Statistics