HEALTH ANALYSIS OF SUGARCANE PLANTS USING COMPARISON OF LANDSAT-8 SATELLITE IMAGE TIME SERIES (CASE STUDY: PAKIS DISTRICT, MALANG REGENCY)
DOI:
https://doi.org/10.12962/j27745449.v3i2.567Keywords:
Sugarcane, LST, NDVI, NDMIAbstract
Sugarcane is one of the most widely cultivated plant commodities in Indonesia. The need for sugar consumption in Indonesia is very high, in 2021 it required 3.2 million tons of sugar consumption. Sugar productivity is strongly influenced by the physical condition of the sugarcane plant which can be influenced by nature, be it weather, temperature, and humidity and the effect of sugarcane plant care in providing plant nutrition and so on. Therefore, an analysis of the health of sugarcane was carried out using the time series comparison method of Landsat-8 satellite imagery with a case study in Pakis District, Malang Regency. In 2017, Pakis Subdistrict contributed 89,793 tons of sugarcane production from a total of 4,001,879 tons of sugarcane production. The productivity level is the age and health of sugarcane. Based on the results obtained using vegetation indices such as the Normalized Different Vegetation Index and Normalized Different Moisture Index and using the Land Surface Temperature parameter, it can be seen that the highest NDVI (Normalized Difference Vegetation Index) and NDMI (Normalized Difference Moisture Index) values occur in February 2022 and the lowest in August 2021 while the highest soil surface temperature occurred in August 2021 and the lowest in February 2022. The sugarcane plants studied had NDVI values ranging from 0.392 to 0.726 and NDMI values ranging from 0 to 0.4. The index value is included in the category of healthy sugar cane. So, if there is a point area outside this value, then there is unhealthy sugar cane. This value is associated with the Pearson correlation so that NDVI and NDMI are very strongly correlated, while the correlation between LST-NDMI and LST-NDVI has a moderate to very strong correlation. However, these parameters need validation in the field to determine the original conditions and the accuracy of the results obtained.