Modification and validation of a new method to improve the accuracy of MODIS-derived dew point temperature over mainland China

References

• Ali, H., H. J. Fowler, and V. Mishra. 2018. “Global Observational Evidence of Strong Linkage Between Dew Point Temperature and Precipitation Extremes.” Geophysical Research Letters 45 (22): 12,320–12,330. https://doi.org/10.1029/2018GL080557.
   Web of Science ®Google Scholar
• Allen, R. G., L. S. Pereira, D. Raes, and M. Smith. 1998. “Crop Evapotranspiration-Guidelines for Computing Crop Water Requirements.” FAO Irrigation and Drainage Paper No. 56. FAO, Rome, Italy.
   Google Scholar
• Baghban, A., M. Bahadori, J. Rozyn, M. Lee, A. Abbas, A. Bahadori, and A. Rahimali. 2016. “Estimation of Air Dew Point Temperature Using Computational Intelligence Schemes.” Applied Thermal Engineering 93:1043–1052. https://doi.org/10.1016/j.applthermaleng.2015.10.056.
   Web of Science ®Google Scholar
• Bello P. A., A. Mailhot, and D. Paquin. 2021. “The Response of Daily and Sub-Daily Extreme Precipitations to Changes in Surface and Dew-Point Temperatures.” Journal of Geophysical Research: Atmospheres 126:e2021JD034972. https://doi.org/10.1029/2021JD034972.
   Web of Science ®Google Scholar
• Berg, A. A., J. S. Famiglietti, J. P. Walker, and P. R. Houser. 2003. “Impact of Bias Correction to Reanalysis Products on Simulations of North American Soil Moisture and Hydrological Fluxes.” Journal of Geophysical Research 108 (D16): 4490. https://doi.org/10.1029/2002JD003334.
   Web of Science ®Google Scholar
• Bisht, G., and R. L. Bras. 2010. “Estimation of Net Radiation from the MODIS Data Under All Sky Conditions: Southern Great Plains Case Study.” Remote Sensing of Environment 114:1522–1534. https://doi.org/10.1016/j.rse.2010.02.007.
   Web of Science ®Google Scholar
• Bisht, G., V. Venturini, S. Islam, and Le Jiang. 2005. “Estimation of the Net Radiation Using MODIS (Moderate Resolution Imaging Spectroradiometer) Data for Clear Sky Days.” Remote Sensing of Environment 97:52–67. https://doi.org/10.1016/j.rse.2005.03.014.
   Web of Science ®Google Scholar
• Borbas, E., et al. 2015. MODIS Atmosphere L2 Atmosphere Profile Product. NASA MODIS Adaptive Processing System, Goddard Space Flight Center, USA. https://doi.org/10.5067/MODIS/MOD07_L2.061
   Google Scholar
• Byun, K., U. W. Liaqat, and M. Choi. 2014. “Dual-Model Approaches for Evapotranspiration Analyses Over Homo- and Heterogeneous Land Surface Conditions.” Agricultural and Forest Meteorology 197:169–187. https://doi.org/10.1016/j.agrformet.2014.07.001.
   Web of Science ®Google Scholar
• Chen, H. P., W. Y. He, J. Q. Sun, and L. F. Chen. 2022. “Increases of Extreme Heat-Humidity Days Endanger Future Populations Living in China.” Environmental Research Letters 17:0064013. https://doi.org/10.1088/1748-9326/ac69fc.
   Web of Science ®Google Scholar
• Chen, Y., S. L. Liang, H. Ma, B. Li, T. He, and Q. Wang. 2021. “An all-sky 1 km Daily Land Surface air Temperature Product Over Mainland China for 2003–2019 from MODIS and Ancillary Data” Earth System Science Data 13:4241–4261. https://doi.org/10.5194/essd-13-4241-2021.
   Web of Science ®Google Scholar
• Denson, E., C. Wasko, and M. C. Pee. 2021. “Decreases in Relative Humidity Across Australia.” Environmental Research Letters 16:074023. https://doi.org/10.1088/1748-9326/ac0aca.
   Web of Science ®Google Scholar
• Dong, J. H., W. Z. Zeng, G. Q. Lei, L. F. Wu, H. Chen, J. W. Wu, J. S. Huang, T. Gaiser, and A. K. Srivastava. 2022. “Simulation of Dew Point Temperature in Different Time Scales Based on Grasshopper Algorithm Optimized Extreme Gradient Boosting.” Journal of Hydrology 606:127452. https://doi.org/10.1016/j.jhydrol.2022.127452.
   Web of Science ®Google Scholar
• Dou, Y., J. N. Quan, X. C. Jia, Q. Wang, and Y. Liu. 2021. “Near-Surface Warming Reduces Dew Frequency in China” Geophysical Research Letters 48:e2020GL091923. https://doi.org/10.1029/2020GL091923.
   Web of Science ®Google Scholar
• Famiglietti, C. A., J. B. Fisher, G. Halverson, and E. E. Borbas. 2018. “Global Validation of MODIS Near-Surface air and Dew Point Temperatures.” Geophysical Research Letters 45:7772–7780. https://doi.org/10.1029/2018GL077813.
   Web of Science ®Google Scholar
• Hashimoto, H., J. L. Dungan, M. A. White, F. Yang, A. R. Michaelis, S. W. Running, and R. R. Nemani. 2008. “Satellite-Based Estimation of Surface Vapor Pressure Deficits Using MODIS Land Surface Temperature Data.” Remote Sensing of Environment 112:142–155. https://doi.org/10.1016/j.rse.2007.04.016.
   Web of Science ®Google Scholar
• Hwang, K., and M. Choi. 2013. “Seasonal Trends of Satellite-Based Evapotranspiration Algorithms Over a Complex Ecosystem in East Asia.” Remote Sensing of Environment 137:244–263. https://doi.org/10.1016/j.rse.2013.06.006.
   Web of Science ®Google Scholar
• Iyakaremye, V., G. Zeng, X. Y. Yang, G. W. Zhang, I. Ullah, A. Gahigi, F. Vuguziga, T. G. Asfaw, and B. Ayugi. 2021. “Increased High-Temperature Extremes and Associated Population Exposure in Africa by the mid-21st Century.” Science of the Total Environment 790:148162. https://doi.org/10.1016/j.scitotenv.2021.148162.
   PubMed Web of Science ®Google Scholar
• Ji, P., X. Yuan, C. X. Shi, L. P. Jiang, G. Q. Wang, and K. Yang. 2023. “A Long-Term Simulation of Land Surface Conditions at High Resolution Over Continental China.” Journal of Hydrometeorology 24 (2): 285–314. https://doi.org/10.1175/JHM-D-22-0135.1.
   Web of Science ®Google Scholar
• Jiao, Z. H., G. J. Yan, J. Zhao, T. X. Wang, and L. Chen. 2015. “Estimation of Surface Upward Longwave Radiation from MODIS and VIIRS Clear-Sky Data in the Tibetan Plateau.” Remote Sensing of Environment 162:221–237. https://doi.org/10.1016/j.rse.2015.02.021.
   Web of Science ®Google Scholar
• Kim, J., and T. S. Hogue. 2008. “Evaluation of a MODIS-Based Potential Evapotranspiration Product at the Point Scale.” Journal of Hydrometeorology 9:444–460. https://doi.org/10.1175/2007JHM902.1.
   Web of Science ®Google Scholar
• King, M. D., W. P. Menzel, Y. J. Kaufman, D. Tanre, Bo-Cai Gao, S. Platnick, S. A. Ackerman, L. A. Remer, R. Pincus, and P. A. Hubanks. 2003. “Cloud and Aerosol Properties, Precipitable Water, and Profiles of Temperature and Water Vapor from MODIS.” IEEE Transactions on Geoscience and Remote Sensing 41:442–458. https://doi.org/10.1109/TGRS.2002.808226.
   Web of Science ®Google Scholar
• Li, Z. L., H. Wu, Si-Bo Duan, W. Zhao, H. Z. Ren, X. Y. Liu, P. Leng, et al. 2023. “Satellite Remote Sensing of Global Land Surface Temperature: Definition, Methods, Products, and Applications.” Reviews of Geophysics 61:e2022R–G000777. https://doi.org/10.1029/2022RG000777.
   Web of Science ®Google Scholar
• Lin, S. P., N. J. Moore, J. P. Messina, M. H. Devisser, and J. P. Wu. 2012. “Evaluation of Estimating Daily Maximum and Minimum Air Temperature with MODIS Data in East Africa.” International Journal of Applied Earth Observation and Geoinformation 18:128–140. https://doi.org/10.1016/j.jag.2012.01.004.
   Web of Science ®Google Scholar
• Liu, N., A. C. Oishi, C. F. Miniat, and P. Bolstad. 2021. “An Evaluation of ECOSTRESS Products of a Temperate Montane Humid Forest in a Complex Terrain Environment.” Remote Sensing of Environment 265:112662. https://doi.org/10.1016/j.rse.2021.112662.
   Web of Science ®Google Scholar
• Mahmood, R., and K. G. Hubbard. 2005. “Assessing Bias in Evapotranspiration and Soil Moisture Estimates Due to the Use of Modeled Solar Radiation and Dew Point Temperature Data.” Agricultural and Forest Meteorology 130:71–84. https://doi.org/10.1016/j.agrformet.2005.02.004.
   Web of Science ®Google Scholar
• Masoumi, Z., J. L. van Genderen, and M. S. Mesgari. 2020. “Modelling and Predicting the Spatial Dispersion of Skin Cancer Considering Environmental and Socio-Economic Factors Using a Digital Earth Approach.” International Journal of Digital Earth 13 (6): 661–682. https://doi.org/10.1080/17538947.2018.1551944.
   Web of Science ®Google Scholar
• Mendez, A. 2004. “Estimate Ambient Air Temperature at Regional Level Using Remote Sensing Techniques.” International Institute for Geoinformation Science and Earth Observation (ITC), The Netherlands. https://webapps.itc.utwente.nl/librarywww/papers_2004/msc/nrm/mendez.pdf
   Google Scholar
• Merva, G. E. 1975. “Physioengineering Principles.” Avi, 353.
   Google Scholar
• Mu, Q., L. A. Jones, J. S. Kimball, K. C. McDonald, and S. W. Running. 2009. “Satellite Assessment of Land Surface Evapotranspiration for the pan-Arctic Domain” Water Resources Research 45:W09420. https://doi.org/10.1029/2008WR007189.
   Web of Science ®Google Scholar
• Oyler, J. W., S. Z. Dobrowski, Z. A. Holden, and S. W. Running. 2016. “Remotely Sensed Land Skin Temperature as a Spatial Predictor of Air Temperature Across the Conterminous United States.” Journal of Applied Meteorology and Climatology 55:1441–1457. https://doi.org/10.1175/JAMC-D-15-0276.1.
   Web of Science ®Google Scholar
• Paredes, P., and L. S. Pereira. 2019. “Computing FAO56 Reference Grass Evapotranspiration PM-ETo from Temperature with Focus on Solar Radiation.” Agricultural Water Management 215:86–102. https://doi.org/10.1016/j.agwat.2018.12.014.
   Web of Science ®Google Scholar
• Paredes, P., L. S. Pereira, J. Almorox, and H. Darouich. 2020. “Reference Grass Evapotranspiration with Reduced Data Sets: Parameterization of the FAO Penman-Monteith Temperature Approach and the Hargeaves-Samani Equation Using Local Climatic Variables.” Agricultural Water Management 240:106210. https://doi.org/10.1016/j.agwat.2020.106210.
   Web of Science ®Google Scholar
• Park, H., J. Lee, C. Yoo, S. Sim, and J. Im. 2021. “Estimation of Spatially Continuous Near-Surface Relative Humidity Over Japan and South Korea.” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14:8614–8626. https://doi.org/10.1109/JSTARS.2021.3103754.
   Web of Science ®Google Scholar
• Pumo, D., and L. V. Noto. 2021. “Exploring the Linkage Between Dew Point Temperature and Precipitation Extremes: A Multi-Time-Scale Analysis on a Semi-Arid Mediterranean Region.” Atmospheric Research 254:105508. https://doi.org/10.1016/j.atmosres.2021.105508.
   Web of Science ®Google Scholar
• Qiu, R. J., L. A. Li, S. Z. Kang, C. W. Liu, Z. C. Wang, E. P. Cajucom, B. Z. Zhang, and E. Agathokleous. 2021. “An Improved Method to Estimate Actual Vapor Pressure Without Relative Humidity Data.” Agricultural and Forest Meteorology 298-299:108306. https://doi.org/10.1016/j.agrformet.2020.108306.
   Web of Science ®Google Scholar
• Qiu, R. J., L. A. Li, L. F. Wu, E. Agathokleous, C. W. Liu, and B. Z. Zhang. 2022. “Comparison of Machine Learning and Dynamic Models for Predicting Actual Vapour Pressure When Psychrometric Data Are Unavailable.” Journal of Hydrology 610:127989. https://doi.org/10.1016/j.jhydrol.2022.127989.
   Web of Science ®Google Scholar
• Razafimaharo, C., S. Krähenmann, S. Höpp, M. Rauthe, and T. Deutschländer. 2020. “New High-Resolution Gridded Dataset of Daily Mean, Minimum, and Maximum Temperature and Relative Humidity for Central Europe (HYRAS).” Theoretical and Applied Climatology 142:1531–1553. https://doi.org/10.1007/s00704-020-03388-w.
   Web of Science ®Google Scholar
• Raziei, T., and L. S. Pereira. 2013. “Estimation of ETo with Hargreaves–Samani and FAO-PM Temperature Methods for a Wide Range of Climates in Iran.” Agricultural Water Management 121:1–18. https://doi.org/10.1016/j.agwat.2012.12.019.
   Web of Science ®Google Scholar
• Ritter, F., Max Berkelhammer, and D. Beysens. 2019. “Dew Frequency Across the US from a Network of in Situ Radiometers.” Hydrology and Earth System Sciences 23:1179–1197. https://doi.org/10.5194/hess-23-1179-2019.
   Web of Science ®Google Scholar
• Ryu, Y., D. D. Baldocchi, H. Kobayashi, C. van Ingen, J. Li, T. A. Black, J. Beringer, et al. 2011. “Integration of MODIS Land and Atmosphere Products with a Coupled-Process Model to Estimate Gross Primary Productivity and Evapotranspiration from 1 km to Global Scales” Global Biogeochemical Cycles 25:GB4017. https://doi.org/10.1029/2011GB004053.
   Web of Science ®Google Scholar
• Sein, Z. M. M., I. Ullah, and V. Iyakaremye. 2022. “Observed Spatiotemporal Changes in air Temperature, Dew Point Temperature and Relative Humidity Over Myanmar During 2001-2019.” Meteorology and Atmospheric Physics 134:7. https://doi.org/10.1007/s00703-021-00837-7.
   Web of Science ®Google Scholar
• Shank, D. B., G. Hoogenboom, and R. W. McClendon. 2008. “Dewpoint Temperature Prediction Using Artificial Neural Networks.” Journal of Applied Meteorology and Climatology 47:1757–1769. https://doi.org/10.1175/2007JAMC1693.1.
   Web of Science ®Google Scholar
• Shiff, S., D. Helman, and I. M. Lensky. 2021. “Worldwide Continuous gap-Filled MODIS Land Surface Temperature Dataset.” Scientific Data 8:74. https://doi.org/10.1038/s41597-021-00861-7.
   PubMed Web of Science ®Google Scholar
• Sobrino, J. A., J. C. Jiménez-Muñoz, C. Mattar, and G. Sòria. 2015. “Evaluation of Terra/MODIS Atmospheric Profiles Product (MOD07) Over the Iberian Peninsula: A Comparison with Radiosonde Stations.” International Journal of Digital Earth 8 (10): 771–783. https://doi.org/10.1080/17538947.2014.936973.
   Web of Science ®Google Scholar
• Tang, B. H., and L. L. Zhao. 2008. “Estimation of Instantaneous net Surface Longwave Radiation from MODIS Cloud-Free Data.” Remote Sensing of Environment 112:3482–3492. https://doi.org/10.1016/j.rse.2008.04.004.
   Web of Science ®Google Scholar
• Todorovic, M., B. Karic, and L. S. Pereira. 2013. “Reference Evapotranspiration Estimate with Limited Weather Data Across a Range of Mediterranean Climates.” Journal of Hydrology 481:166–176. https://doi.org/10.1016/j.jhydrol.2012.12.034.
   Web of Science ®Google Scholar
• Turner, D. P., S. V. Ollinger, and J. S. Kimball. 2004. “Integrating Remote Sensing and Ecosystem Process Models for Landscape- to Regional-Scale Analysis of the Carbon Cycle” BioScience 54 (6): 573–584. https://doi.org/10.1641/0006-3568(2004)054[0573:IRSAEP]2.0.CO;2.
   Web of Science ®Google Scholar
• Ullah, I., F. Saleem, V. Iyakaremye, J. Yin, X. Y. Ma, S. Syed, S. Hina, T. G. Asfaw, and A. Omer. 2022. “Projected Changes in Socioeconomic Exposure to Heatwaves in South Asia Under Changing Climate.” Earth's Future 10 (2): 2328–4277. https://doi.org/10.1029/2021EF002240.
   Web of Science ®Google Scholar
• UNEP. 1997. “Environmental Management of Industrial Estates.” Industry and Environment. United Nations Environment Programme (UNEP), p. 150.
   Google Scholar
• Vancutsem, C., P. Ceccato, T. Dinku, and S. J. Connor. 2010. “Evaluation of MODIS Land Surface Temperature Data to Estimate air Temperature in Different Ecosystems Over Africa.” Remote Sensing of Environment 114:449–465. https://doi.org/10.1016/j.rse.2009.10.002.
   Web of Science ®Google Scholar
• Venturini, V., L. Rodriguez, and G. Bisht. 2011. “A Comparison Among Different Modified Priestley and Taylor Equations to Calculate Actual Evapotranspiration with MODIS Data.” International Journal of Remote Sensing 32:1319–1338. https://doi.org/10.1080/01431160903547965.
   Web of Science ®Google Scholar
• Verma, Manish, J. B. Fisher, K. Mallick, Y. Ryu, H. Kobayashi, A. Guillaume, G. Moore, et al. 2016. “Global Surface net-Radiation at 5 km from MODIS Terra.” Remote Sensing 8:739. https://doi.org/10.3390/rs8090739.
   Web of Science ®Google Scholar
• Viggiano, M., E. Geraldi, D. Cimini, F. Di Paola, D. Gallucci, S. Gentile, S. Larosa, S. T. Nilo, E. Ricciardelli, and F. Romano. 2021. “The Role of Temporal Resolution of Meteorological Inputs from Reanalysis Data in Estimating air Humidity for Modelling Applications.” Agricultural and Forest Meteorology 311:108672. https://doi.org/10.1016/j.agrformet.2021.108672.
   Web of Science ®Google Scholar
• Wan, Z. M. 2019. “Collection-6 MODIS Land Surface Temperature Products Users’ Guide.” https://modisland.gsfc.nasa.gov/pdf/MOD11_User_Guide_V61.pdf
   Google Scholar
• Wang, Y. M., and X. Yuan. 2022. “Land-atmosphere Coupling Speeds Up Flash Drought Onset.” Science of The Total Environment 851:158109. https://doi.org/10.1016/j.scitotenv.2022.158109.
   PubMed Web of Science ®Google Scholar
• Wood, E. F., J. K. Roundy, T. J. Troy, L. P. H. van Beek, Marc F. P. Bierkens, El. Blyth, Ad. Roo, et al. 2011. “Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water.” Water Resources Research 47:W05301. https://doi.org/10.1029/2010WR010090.
   Web of Science ®Google Scholar
• Wu, C. Y., J. Peng, P. Ciais, J. Peñuelas, H. J. Wang, S. Beguería, T. A. Black, et al. 2022. “Increased Drought Effects on the Phenology of Autumn Leaf Senescence.” Nature Climate Change 12:943–949. https://doi.org/10.1038/s41558-022-01464-9.
   Web of Science ®Google Scholar
• Yoo, C., J. Im, S. Park, and L. J. Quackenbush. 2018. “Estimation of Daily Maximum and Minimum air Temperatures in Urban Landscapes Using MODIS Time Series Satellite Data.” ISPRS Journal of Photogrammetry and Remote Sensing 137:149–162. https://doi.org/10.1016/j.isprsjprs.2018.01.018
   Web of Science ®Google Scholar
• You, Q. L., J. Z. Min, H. B. Lin, N. Pepin, M. Sillanpää, and S. Kang. 2015. “Observed Climatology and Trend in Relative Humidity in the Central and Eastern Tibetan Plateau.” Journal of Geophysical Research: Atmospheres 120:3610–3621. https://doi.org/10.1002/2014JD023031.
   Web of Science ®Google Scholar
• Yue, Y. J., W. Q. Yang, and L. Wang. 2022. “Assessment of Drought Risk for Winter Wheat on the Huanghuaihai Plain Under Climate Change Using an EPIC Model-Based Approach.” International Journal of Digital Earth 15 (1): 690–711. https://doi.org/10.1080/17538947.2022.2055174.
   Web of Science ®Google Scholar
• Zeng, C., D. Long, H. F. Shen, P. H. Wu, Y. K. Cui, and Y. Hong. 2018. “A two-Step Framework for Reconstructing Remotely Sensed Land Surface Temperatures Contaminated by Cloud.” ISPRS Journal of Photogrammetry and Remote Sensing 141:30–45. https://doi.org/10.1016/j.isprsjprs.2018.04.005.
   Web of Science ®Google Scholar
• Zhang, H. M., B. F. Wu, N. Yan, W. Zhu, and X. L. Feng. 2014. “An Improved Satellite-Based Approach for Estimating Vapor Pressure Deficit from MODIS Data” Journal of Geophysical Research: Atmospheres 119:12,256–12,271. https://doi.org/10.1002/2014JD022118.
   Web of Science ®Google Scholar
• Zhang, W. J., B. P. Zhang, W. B. Zhu, X. L. Tang, F. J. Li, X. S. Liu, and Q. Yu. 2021. “Different Tree-Ring Width Sensitivities to Satellite-Based Soil Moisture from dry, Moderate and wet Pedunculate oak (Quercus Robur L.) Stands Across a Southeastern Distribution Margin” Science of the Total Environment 800:149536. https://doi.org/10.1016/j.scitotenv.2021.149536.
   PubMed Web of Science ®Google Scholar
• Zhao, W., and Si-Bo Duan. 2020. “Reconstruction of Daytime Land Surface Temperatures Under Cloud-Covered Conditions Using Integrated MODIS/Terra Land Products and MSG Geostationary Satellite Data.” Remote Sensing of Environment 247:111931. https://doi.org/10.1016/j.rse.2020.111931.
   Web of Science ®Google Scholar
• Zhu, W. B., S. F. Jia, and A. F. Lű. 2017a. “A Universal Ts-VI Triangle Method for the Continuous Retrieval of Evaporative Fraction from MODIS Products.” Journal of Geophysical Research: Atmospheres 122:10,206–10,227. https://doi.org/10.1002/2017JD026964.
   Web of Science ®Google Scholar
• Zhu, W. B., A. F. Lű, and S. F. Jia. 2013. “Estimation of Daily Maximum and Minimum air Temperature Using MODIS Land Surface Temperature Products.” Remote Sensing of Environment 130:62–73. https://doi.org/10.1016/j.rse.2012.10.034.
   Web of Science ®Google Scholar
• Zhu, W. B., A. F. Lű, S. F. Jia, J. B. Yan, and R. Mahmood. 2017b. “Retrievals of All-Weather Daytime Air Temperature from MODIS Products.” Remote Sensing of Environment 189:152–163. https://doi.org/10.1016/j.rse.2016.11.011.
   Web of Science ®Google Scholar
• Zhu, W. B., Y. Z. Wang, and S. F. Jia. 2023. “A Remote Sensing-Based Method for Daily Evapotranspiration Mapping and Partitioning in a Poorly Gauged Basin with Arid Ecosystems in the Qinghai-Tibet Plateau.” Journal of Hydrology 616:128807. https://doi.org/10.1016/j.jhydrol.2022.128807.
   Web of Science ®Google Scholar
• Zomer, R. J., A. Trabucco, D. A. Bossio, and L. V. Verchot. 2008. “Climate Change Mitigation: A Spatial Analysis of Global Land Suitability for Clean Development Mechanism Afforestation and Reforestation.” Agriculture, Ecosystems & Environment 126:67–80. https://doi.org/10.1016/j.agee.2008.01.014.
   Web of Science ®Google Scholar
• Zomer, R. J., A. Trabucco, O. van Straaten, and D. Bossio. 2007. “Carbon, Land and Water: A Global Analysis of the Hydrologic Dimensions of Climate Change Mitigation Through Afforestation/Reforestation (Vol. 101).” IWMI Research Report.
   Google Scholar