Soil moisture, defined as the presence or amount of water in the soil, is a critical element in hydrology,

agriculture, and climate science, vital for understanding soil health, water cycle, and plant growth. Remote

sensing, particularly using satellites like Sentinel-2 which is equipped with Multispectral instruments, offers a

powerful tool for monitoring soil moisture across large areas. Therefore, this study was conducted to generate

soil moisture maps of Solano Nueva Vizcaya through Geographic Information System by using Sentinel-2 Near

InfraRed and Short Wavelength InfraRed bands for the years 2020 and 2025. It further aimed to determine the

soil moisture level of the study area and compare soil moisture level differences between the years 2020 and

2025, and at the same time identify the minimum, maximum, and the mean soil moisture per barangay. The

results revealed that the municipality of Solano has a minimum soil moisture level increased by 0.304678159,

while the maximum decreased by 0.062563121. It was also revealed that most of the dry soil are located within

understanding soil health, water cycle, and plant growth (Jackson & Hsu, 2004). The great needs for measuring

soil moisture content also extends for the purpose of water management, prediction of crop yield, and climate

modelling. Traditionally, ground-based methods are mainly used to measure soil moisture, but because of the

use of modern technology such as remote sensing instruments, the ability to monitor soil moisture in larger scales

have improved (Entekhabi et al., 2010).

Evidences of the importance of soil moisture can be seen across different fields. In agriculture, influencing crop

growth and yield, hence considered important for the optimization of irrigation practices and ensuring food

security (Jackson & Hsu, 2004). In hydrology, soil moisture is also important as it affects water infiltration,

recharge of groundwater, and runoff. Also, soil moisture is a very important element in energy fluxes and rate of

evaporation, which justifies its benefit in the field of climate science (Entekhabi et al., 2010).

2 satellites are part of the Copernicus program launched by the European Space Agency. Multispectral

Instruments (MSI) are installed within these satellites enabling them to capture data across 13 spectral bands

which ranges from the visible to the shortwave infrared. The resolution for visible and near-infrared bands is 10

meters while the shortwave infrared band has a resolution of 20 meters. One spatial index that can be used in

estimating the soil moisture which can be derived from Sentinel- 2 data is the Normalized Difference Moisture

Index (NDMI). For this index, the NIR and SWIR specifically the bands 8a and 11 are used to calculate the soil

moisture level. If the calculated value is high, it generally indicates higher soil moisture levels, on the other hand,

drier conditions can be associated with lower values (ESA, 2022).

By integrating NDMI data derived from the Sentinel-2 satellite and processing it through GIS software, a

relatively accurate soil moisture estimate can be achieved, and the results can be projected through a soil moisture

This study utilized a qualitative research design to generate a soil moisture index map of the study area.

Geospatial data, such as the Near Infrared band and Shortwave Infrared band, was collected as a secondary data

through the Sentinel’s opensource website. Moreover, the detailed explanation of the soil moisture index map is

descriptive and illustrative in nature.

The conceptual framework illustrates the input, process, and output of the study. The figure shows that the inputs

are Sentinel-2 data from Copernicus website specifically the band 8A or the Near Infrared band, and the band 11

or the Shortwave Infrared band. These bands are crucial for calculating the Normalized Difference Moisture

within Solano, Nueva Vizcaya.

Solano is a 1st-class municipality in the province of Nueva Vizcaya, situated in the Cagayan Valley region of

Luzon, Philippines, located approximately at coordinates 16°31'N latitude and 121°11'E longitude. The

municipality has an elevation ranging from approximately 240 meters to 573 meters above sea level. Solano

encompasses a total land area of 139.80 square kilometers divided into 22 barangays. The landscape of Solano

is characterized by a mix of rolling hills and agricultural plains, with the Magat River and its tributaries playing

a significant role in the local ecosystem and agricultural practices. Similar to the broader region, Solano

In this study, the researcher utilized the Sentinel- 2 Copernicus for the preprocessing of data. This involves cloud

masking to identify and exclude cloud-covered areas in the satellite images, as clouds can interfere with the

accuracy of the soil moisture index to detect and mask clouds, ensuring only clear-sky pixels are used in the

analysis. Moreover, the software ArcGIS 10.8 was used as the primary tool for data processing, mapping, and

analysis, which will include the importing of the TIFF file exported from Sentinel- 2 Copernicus, and creation

of the thematic map.

The data gathering procedure involved acquiring geospatial data for spatial analysis. The first step in the data

gathering procedure involved acquiring satellite imagery from the Copernicus Open Access Hub, which provides

free access to Sentinel-2 imagery. The researcher then specified Solano, Nueva Vizcaya, as the Area of Interest

(AOI) by uploading a shapefile of the study area. The temporal filters were then set to select imagery from the

specific time period. Next, the data filters were applied to select Sentinel-2 imagery, focusing on Level-2A

(Bottom-Of-Atmosphere or BOA reflectance) products, which are reflectance values corrected for atmospheric

In this study, the researcher used zonal statistics as a suitable statistical tool to facilitate the analysis of the soil

moisture data. Zonal statistics involves dividing the study area into smaller, more homogeneous zones and then

calculating the average soil moisture content within each of these zones. This method was used for the whole

For Problem 2, the researcher compared the mean, minimum, and maximum soil moisture levels of the whole

municipality for the years 2020 and 2025, and descriptively drew conclusion based on the compared values.

For Problem 3, the researcher used the in-system tool in Sentinel-2 Copernicus to compute for the mean,

minimum, and maximum soil moisture values per barangay for the years 2020 and 2025.

The creation of soil moisture index map involved the application of spatial analysis tools in ArcGIS 10.8. The

following provides a concise description of the procedural steps that will be followed to generate the soil

moisture index map.

After importing the TIFF data from the Sentinel-2 Copernicus consisting of the necessary Sentinel-2 spectral

bands, the Clip tool from the Geoprocessing toolbox was used to focus on the study area. The Project Raster tool

The researcher then applied appropriate symbology and choose a color ramp that effectively represents soil

moisture levels. After all these steps, supplementary steps was done to design the final map layout for this

thematic map, the Kriging Interpolation was applied with a spatial resolution of 10 meters by 10 meters.

Table 3 shows the soil moisture data for the year 2020, categorized by barangays within the whole municipality

of Solano. The data includes minimum, maximum, and mean soil moisture values, along with a soil moisture

classification and rank for each barangay.

barangays and at the municipal level between 2020 and 2025. In 2020, the distribution of soil moisture among

barangays exhibited considerable diversity. Some barangays, such as Dadap, Poblacion South, Bangar, and

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5. Bindlish, N., & Cosh, M. H. (2013). Remote Sensing of Soil Moisture: Recent Advances and Challenges.