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Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories.

, , , , , and . Remote Sensing, 10 (1): 122 (2018)

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GIS-Based Assessment of Roof-Mounted Solar Energy Potential in Jiangsu, China., , , , , and . ICDMA, page 565-571. IEEE Computer Society, (2011)A Local Land Use Competition Cellular Automata Model and Its Application., , , , and . ISPRS Int. J. Geo-Information, 5 (7): 106 (2016)Simulating Intraurban Land Use Dynamics under Multiple Scenarios Based on Fuzzy Cellular Automata: A Case Study of Jinzhou District, Dalian., , , , and . Complexity, (2018)Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories., , , , , and . Remote Sensing, 10 (1): 122 (2018)The Impact of Spatial Form of Urban Architecture on the Urban Thermal Environment: A Case Study of the Zhongshan District, Dalian, China., , , , , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 11 (8): 2709-2716 (2018)Spatiotemporal Variability in Start and End of Growing Season in China Related to Climate Variability., , , and . Remote Sensing, 8 (5): 433 (2016)A case study on land use change analysis using RS and GIS in the west jilin province in China., , , and . IGARSS, page 2287-2290. IEEE, (2005)Correction: Shang, R.; Liu, R.; Xu, M.; Liu, Y.; Dash, J.; Ge, Q. Determining the Start of the Growing Season from MODIS Data in the Indian Monsoon Region: Identifying Available Data in the Rainy Season and Modeling the Varied Vegetation Growth Trajectories, Remote Sens. 2018, 10, 122., , , , , and . Remote Sensing, 11 (8): 939 (2019)