Natural Resource Modeling. 2020;e12262. wileyonlinelibrary.com/journal/nrm © 2020 Wiley Periodicals, Inc. | 1 of 26 https://doi.org/10.1111/nrm.12262 Received: 21 August 2019 | Accepted: 18 February 2020 DOI: 10.1111/nrm.12262 Assessment of trends of land surface vegetation distribution, snow cover and temperature over entire Himachal Pradesh using MODIS datasets Mohd Anul Haq 1 | Prashant Baral 2 | Shivaprakash Yaragal 3 | Gazi Rahaman 2 1 Department of Computer Science, College of Computer and Information Sciences, Majmaah University, Al Majma'ah, Saudi Arabia 2 Geographic Information Systems, NIIT University, Neemrana, Rajasthan, India 3 Esri India Technologies Ltd., Noida, Uttar Pradesh, India Correspondence Mohd Anul Haq, Department of Computer Science, College of Computer and Information Sciences, Majmaah University, Al Majma'ah 11952, Saudi Arabia. Email: m.anul@mu.edu.sa Abstract We examine spatial and temporal variability in normalized difference vegetation index (NDVI), snow cover and land surface temperature (LST) in Himachal Pradesh between 2001 and 2017 using Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. Mann–Kendall trend tests and Sen's slope estimates indicate increasing NDVI trends during the postmonsoon period. Increasing snow cover trend is observed during winter and premonsoon whereas decreasing annual LST trends are observed for Himachal Pradesh. Pearson's cor- relation coefficient (PCC) indicate a strong positive correlation between NDVI and LST (PCC = .808) and strong negative correlation between LST and snow cover (PCC = -.809) and NDVI and snow cover (PCC = -.838). Coefficient of determination greater than .90, between MODIS LST and snow cover observations and weather station records, indicate fair representation of ground conditions using the MODIS dataset. Low (2.4°C/1,000 m) and