• Megharani B Mayani
• Dr. Rajeshwari L Itagi

Remote sensing is gaining popularity in agriculture systems due to the advancements in technology which are heading towards precise spatial and temporal data sensed by satellites carrying the minute significant information. Despite considerable maturity of Earth Observation satellites in land and water monitoring; atmospheric attenuation has a big role to play in Optical satellites. Snow / cloud cover / aerosols degrade the recorded values considerably. Agriculture based applications such as crop identification, crop health, pest management, yield prediction, etc. are done by analyzing satellite images with huge data involved; but the indices used for above mentioned applications can be accurately computed if and only if the sensor values are reliable. Cloudy pixel value makes the analysis less accurate. To handle such pixel values a technique to reconstruct or predict the missing values is much needed. Also, the Machine learning / Deep learning models have proven to be efficient when fed with a gap free data. Research has been done to find a technique to get the best estimate of the missing pixel values. Rolling statistics (Moving Average), Savitzky Golay filtering, Interpolation with Savitzky Golay filtering was done on Normalized Difference Vegetation Index (NDVI) over a period of four years at a sugarcane farmland region. Using Google Earth Engine as a cloud computing service and satellite dataset provider the NDVI values obtained with above techniques were compared with the actual ground values. The observations and inferences are discussed in this paper. Research conducted showed that interpolation fused with filtering gave better approximations of missing values compared to other statistical methods.

Normalized Difference Vegetation Index (NDVI), Cloud Coverage, Google Earth Engine (GEE), Moving Average (MA), Savitzky Golay (SG) filter, Interpolation

"Temporal Processing of Remotely Sensed Optical Images of a Sugarcane Farmland on Google Earth Engine.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 3, page no.h599-h604, March-2024, Available :http://www.jetir.org/papers/JETIR2403778.pdf

"Temporal Processing of Remotely Sensed Optical Images of a Sugarcane Farmland on Google Earth Engine.", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 3, page no. pph599-h604, March-2024, Available at : http://www.jetir.org/papers/JETIR2403778.pdf