AbdelRahman, M. A. (2023). An overview of land degradation, desertification and sustainable land management using GIS and remote sensing applications. Rendiconti Lincei.
Scienze Fisiche e Naturali, 34(3), 767-808.
https://doi.org/10.1007/s12210-023-01155-3
Ahmadaali, K., Eskandari Damaneh, H., Ababaei, B., & Eskandari Damaneh, H. (2021). Impacts of droughts on rainfall use efficiency in different climatic zones and land uses in Iran.
Arabian Journal of Geosciences, 14, 1-15.
https://doi.org/10.1007/s12517-020-06389-1
Asefjah, B., Esmaeilpour, Y., Bazrafshan, O., Keshtkar, A., & Zamani, H. (2022). Land degradation trend in the climatic types of Fars province using remote sensing and climatic variables.
Iranian journal of Ecohydrology, 9(4), 833-851.
10.22059/ije.2023.353644.1707. ]In Persian[
Ayele, G. T., Tebeje, A. K., Demissie, S. S., Belete, M. A., Jemberrie, M. A., Teshome, W. M., ... & Teshale, E. Z. (2018). Time series land cover mapping and change detection analysis using geographic information system and remote sensing, Northern Ethiopia.
Air, Soil and Water Research, 11, 1178622117751603.
doi.org/10.1177/1178622117751603
Badapalli, P. K., Kottala, R. B., Madiga, R., & Mesa, R. (2021). Land suitability analysis and water resources for agriculture in semi-arid regions of Andhra Pradesh, South India using remote sensing and GIS techniques. International Journal of Energy and Water Resources, 1-16.
Bhuiyan, C. (2008). Desert vegetation during droughts: response and sensitivity. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 37, 907-912.
Chang, J., Liu, Q., Wang, S., & Huang, C. (2022). Vegetation Dynamics and Their Influencing Factors in China from 1998 to 2019.
Remote Sensing, 14(14), 3390.
doi.org/10.3390/rs14143390
Derakhshandeh, A., Khoorani, A., & Rezazadeh, M. (2023b). Trend analysis of precipitation in Iran based on MERRA2.
Journal of the Earth and Space Physics, 49(3), 669-683.
10.22059/jesphys.2023.350125.1007465] In Persian[
Eskandari Damaneh H, Eskandari Damaneh H, Khosravi H, Gilevari A, Adeli Sardooei M. (2021b). A survey on the effect of drought on environmental indices derived from the MODIS data over the 2001-2019 period (Case study: Rangelands of Isfahan province) Journal of Rangeland.476-460(3)15] In Persian[
Eskandari Damaneh, H., Gholami, H., Mahdavi, R., Khoorani, A., & Li, J. (2022). Evaluation of land degradation trend using satellite imagery and climatic data (Case study: Fars province). Desert Ecosystem Engineering, 8(24), 49-64.] In Persian[
Eskandari Damaneh, H., Gholami, H., Mahdavi, R., Khoorani, A., & Li, J. (2021c). Monitoring Land Degradation and Desertification in the Arid and Semi-arid Regions with an Emphasis in Response to Gross Primary Production Relative to the Climatic Variables during the 2001-2017 in the Province of Fars. Watershed Management Research Journal, 34(1), 41-58.] In Persian[
Eskandari Damaneh, H., Gholami, H., Mahdavi, R., Khoorani, A., & Li, J. (2021d). Assessing the land degradation using water use efficiency (WUE) and drought indices (case study: Fars province). Journal of Range and Watershed Managment, 74(1), 103-120.] In Persian[
Ge, W., Deng, L., Wang, F., & J. Han, 2021. Quantifying the contributions of human activities and climate change to vegetation net primary productivity dynamics in China from 2001 to 2016.
Science of the Total Environment, 773: 145648.
doi.org/10.1016/j.scitotenv.2021.145648
Georganos, S., Abdi, A. M., Tenenbaum, D. E., & Kalogirou, S. (2017). Examining the NDVI-rainfall relationship in the semi-arid Sahel using geographically weighted regression.
Journal of Arid Environments, 146, 64-74.
doi.org/10.1016/j.jaridenv.2017.06.004
Ghafarian Malamiri, H. R., & Zare Khormizi, H. (2020). Investigating vegetation changes in Iran using NDVI time series of NOAA-AVHRR sensor and Harmonic ANalysis of Time Series (HANTS).
Scientific-Research Quarterly of Geographical Data (SEPEHR), 29(113), 141-158.
doi.org/10.22131/sepehr.2020.40476] In Persian [
Ghorbanian, A., Mohammadzadeh, A., & Jamali, S. (2022). Linear and non-linear vegetation trend analysis throughout Iran using two decades of MODIS NDVI imagery.
Remote Sensing, 14(15), 3683.
doi.org/10.3390/rs14153683
Gohain, K. J., Mohammad, P., & Goswami, A. (2021). Assessing the impact of land use land cover changes on land surface temperature over Pune city, India.
Quaternary International, 575, 259-269.
doi.org/10.1016/j.quaint.2020.04.052
Hemati, S., Nasiri, B., & Karampoor, M. (2020). Determination of soil temperature change trend in different climates of Kermanshah Province. Iranian Journal of Soil and Water Research, 51(10), 2641-26. ] In Persian[
Jiang, W., Yuan, L., Wang, W., Cao, R., Zhang, Y., & Shen, W. (2015). Spatio-temporal analysis of vegetation variation in the Yellow River Basin.
Ecological Indicators, 51, 117-126.
doi.org/10.1016/j.ecolind.2014.07.031
Kang, J., Zhang, Y., & Biswas, A. (2021). Land degradation and development processes and their response to climate change and human activity in China from 1982 to 2015.
Remote Sensing, 13(17), 3516.
doi.org/10.3390/rs13173516
Karimi, A., & Ghajari, Y. E. (2022). Improving land surface temperature prediction using spatiotemporal factors through a genetic-based selection procedure (Case Study: Tehran, Iran).
Advances in Space Research, 69(9), 3258-3267.
doi.org/10.1016/j.asr.2022.02.004
karimi, N., & Namdari, S. (2019). Estimation of severity and extent of desertification in Iran using Landsat satellite images and spectral mixture analyses methods between 1984 and 2015. Iranian Journal of Range and Desert Research, 26(2), 500-515.] In Persian[
Kavian, A., Mohammadi, M., Gholami, L., & Rodrigo-Comino, J. (2018). Assessment of the spatiotemporal effects of land use changes on runoff and nitrate loads in the Talar River.
Water, 10(4), 445.
doi.org/10.3390/w10040445
Kendall, M.G., 1975. Rank Correlation Methods, Oxford University Press New York.
Kim, D., Kim, J., Jeong, J., & Choi, M. (2019). Estimation of health benefits from air quality improvement using the MODIS AOD dataset in Seoul, Korea.
Environmental research, 173, 452-461.
doi.org/10.1016/j.envres.2019.03.042
Kumar, B. P., Babu, K. R., Anusha, B. N., & Rajasekhar, M. (2022). Geo-environmental monitoring and assessment of land degradation and desertification in the semi-arid regions using Landsat 8 OLI/TIRS, LST, and NDVI approach.
Environmental Challenges, 8, 100578.
doi.org/10.1016/j.envc.2022.100578
Li, X., Liang, H., & Cheng, W. (2020). Spatio-Temporal Variation in AOD and Correlation Analysis with PAR and NPP in China from 2001 to 2017.
Remote Sensing, 12(6), 976.
doi.org/10.3390/rs12060976
Mann, H. B. (1945). Nonparametric tests against trend. Econometrica: Journal of the econometric society, 245-259.
Mohammadi, A., Ghazavi, R., Mirzaei, R., & Naseri, H. (2019). Investigation of the vegetation Cover Pattern Change Using MODIS Images and its Relation with Rainfall distribution.
Journal of Range and Watershed Managment, 72(3), 843-852.
https://doi.org/10.22059/jrwm.2019.280679.1381]In Persian[
Owen, T. W., Carlson, T. N., & Gillies, R. R. (1998). An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization.
International journal of remote sensing, 19(9), 1663-1681.
doi.org/10.1080/014311698215171
Ranjbar, A., Valia, A., Mokarramb, M., & Taripanahc, F. (2020). Analyzing of the spatio-temporal changes of vegetation and its response to environmental factors in north of Fars province, Iran. Iranian Journal of Remote Sensing & GIS, 11(4), 61-82. ]In Persian[
Rezaee, A., Amirtaimoori, S., & Mohammadzadeh, S. (2024). Investigation of the climatic variables' impact on the agricultural sector economic rent in Iran (Case study: irrigated barley). Journal of Natural Environment, 77(1), 123-132. ]In Persian[
Schulze, K., Malek, Ž., & Verburg, P. H. (2021). How will land degradation neutrality change future land system patterns? A scenario simulation study. Environmental Science & Policy, 124, 254-266.
doi.org/10.1016/j.envsci.2021.06.024
Sen, P. K. (1968). Estimates of the regression coefficient based on Kendall's tau. Journal of the American statistical association, 63(324), 1379-1389.
silakhori, E., ownegh, M., & soleimani sardo, M. (2019). Assessment of Risk and Hazard desertification using Topsis-GIS method (Case Study: Bashtin, Sabzevar, Razavi province). Journal of Arid Regions Geographic Studies, 10(35), 44-59. ]In Persian[
Sims, N. C., England, J. R., Newnham, G. J., Alexander, S., Green, C., Minelli, S., & Held, A. (2019). Developing good practice guidance for estimating land degradation in the context of the United Nations Sustainable Development Goals.
Environmental Science & Policy, 92, 349-355.
https://doi.org/10.1016/j.envsci.2018.10.014
Sulla-Menashe, D., & Friedl, M. A. (2018). User guide to collection 6 MODIS Land cover (MCD12Q1) product. NASA EOSDIS Land Processes DAAC: Sioux Falls, SD, USA, 2018.
Sun, W., Song, X., Mu, X., Gao, P., Wang, F., & Zhao, G. (2015). Spatiotemporal vegetation cover variations associated with climate change and ecological restoration in the Loess Plateau.
Agricultural and Forest Meteorology, 209, 87-99.
doi.org/10.1016/j.agrformet.2015.05.002
Theil, H. (1950). A rank-invariant method of linear and polynomial regression analysis. Indagationes mathematicae, 12(85), 173.
Ullah, W., Ahmad, K., Ullah, S., Tahir, A. A., Javed, M. F., Nazir, A., ... & Mohamed, A. (2023). Analysis of the relationship among land surface temperature (LST), land use land cover (LULC), and normalized difference vegetation index (NDVI) with topographic elements in the lower Himalayan region. Heliyon, 9(2).
Xu, Y., Dai, Q. Y., Lu, Y. G., Zhao, C., Huang, W. T., Xu, M., & Feng, Y. X. (2023). Identification of ecologically sensitive zones affected by climate change and anthropogenic activities in Southwest China through a NDVI-based spatial-temporal model.
Ecological Indicators, 158, 111482.
doi.org/10.1016/j.ecolind.2023.111482
Yang, C., Li, Q., Chen, J., Wang, J., Shi, T., Hu, Z., ... & Wu, G. (2020). Spatiotemporal characteristics of land degradation in the Fuxian Lake Basin, China: Past and future.
Land Degradation & Development, 31(16), 2446-2460.
doi.org/10.1002/ldr.3622