May/24 Report
DEFORESTATION MONITORING TECHNICAL REPORT
The study area comprises the "Fazenda Floresta Amazônica" located in the municipality of Apuí-AM (Figure 1). According to the IBGE vegetation classification (2021), the area of the farm falls into two types of vegetation: Open Ombrophilous Forest (FOA) and Dense Ombrophilous Forest (FOD).
Caption translation
Área de estudo = Study area
Brasil = Brazil
Presentation
This technical report uses NDVI vegetation cover monitoring to monitor possible changes in vegetation within the area called "Amazon Forest Farm", as well as detect possible degraded and deforested areas. Furthermore, based on images of deforestation alerts from the INPE and Imazon database, deforestation alerts were monitored in the period from May 1st to 31th, 2024, both in the farm area and in its surroundings.
In remote sensing, monitoring changes in vegetation cover at regional and global scales, the normalized difference vegetation index (NDVI) is commonly used (Shi et al., 2021, Wu et al., 2020). NDVI is an important indicator that reflects the state of vegetation, which is affected by precipitation, anthropogenic activities, temperature and soil water content.
NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)
For the creation of the NDVI map for the periods from May 1 to May 15 and from May 16 to May 31, Sentinel L2A satellite images were used. On May 11, satisfactory conditions for the NDVI map were observed, with 5% cloud cover. Additionally, the image from May 31 was utilized, showing 2% cloud cover.
Following the standard procedure, NDVI was obtained by applying an algorithm based on the difference in near-infrared (NIR) and red reflectance divided by their sum of spectral bands (1), where NIR represents near-infrared electromagnetic spectrum and R the red electromagnetic spectrum, ranging between -1 and 1 (ROUSE et al., 1974), as follows:
| Satelite | Date | Year | Bands |
|---|---|---|---|
Landsat 9 | 05/11/24 | 2024 | B8-B4 |
Landsat 9 | 05/31/24 | 2024 | B8-B4 |
Table 1. Specifications of the satellite image used for NDVI calculation
SOIL ADJUSTED VEGETATION INDEX (SAVI)
Additionally, a Soil Adjusted Vegetation Index (SAVI) map was developed to assess and confirm that thereis no deforestation occurring within the study area. The Soil Adjusted Vegetation Index (SAVI) is a variation of the Normalized Difference Vegetation Index (NDVI) that takes into account the influence of soil on the spectral response of plants. It is used to estimate vegetation density and vigor by correcting soil effects present in satellite images.
The same images from NDVI captured on April 26th were used. The formula for SAVI is as follows:
Where: NIR is the reflectance value in the near-infrared band; RED is the reflectance value in the red band; and L is the soil adjustment factor, which ranges from -1 to 1 (typically set to 0.5).
The inclusion of the soil adjustment factor (L) in the formula allows compensating the influence of soil reflectance, especially in areas with sparse vegetation or exposed soil. The value of L is typically set to 0.5, but it can vary depending on the characteristics of the vegetation and soil in the study area.
NORMALIZED BURNING RATIO (NBR)
To provide a more comprehensive understanding of the indexes used in the study area, a Normalized Burn Ratio (NBR) map was also created in QGIS. This index is widely used to detect areas affected by fires (Key and Benson, 1999), deforestation, or damaged vegetation. It utilizes the near-infrared (NIR) and mid-infrared (MIR) bands from satellite images to map the extent and severity of burns. Landsat 9 satellite images, specifically bands 5 and 7 dated from May 31th, 2024, were used (available at https://earthexplorer.usgs.gov/).
The formula for NBR is as follows:
Where: NIR is the reflectance value in the near-infrared band, and MIR is the reflectance value in the midinfrared band.
The Normalized Burn Ratio (NBR) varies on a scale of values depending on the methodology and scale used. However, a common convention is for NBR to range from -1 to 1. Negative values of NBR (-1 to 0) typically indicate areas affected by recent fires, deforestation, or damaged vegetation. Values closer to -1 indicate higher severity of the burn or vegetation damage. Positive values of NBR (0 to 1) are often associated with areas of healthy vegetation. Values closer to 1 indicate greater vegetation vigor.
DEFORESTATION ALERTS
To assess deforestation expansion around the farm "Fazenda Floresta Amazônica" area, a radius of 50 km was determined. Databases from deforestation alerts provided by INPE and Imazon were utilized. The data obtained for February were in shapefile format, and all processing and filtering of alert points within the radius were conducted using QGIS software.
The Imazon Deforestation Alert System (SAD) currently employs NASA's Landsat 7 and 8 satellites, as well as ESA's Sentinel 1A, 1B, 2A, and 2B satellites. SAD detects forest degradation or deforestation events that occur in areas larger than 1 hectare.
INPE utilizes imagery from the WFI sensor on the CBERS-4 satellite and the AWiFS sensor on the Indian Remote Sensing Satellite (IRS), which have spatial resolutions of 64 and 56 meters, respectively.
The data is sent daily to the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) without a minimum mapped area restriction. However, for the general public, polygons are made available with a minimum size of 6.25 hectares, allowing for comparison with data generated by the PRODES project.
The identification of forest cover change patterns is conducted through visual interpretation based on five main elements (color, tone, texture, shape, and context), using the Spectral Mixture Analysis (SMA) technique along with multispectral imagery in color composition to map the following classes:
Deforestation:
Deforestation with exposed soil and deforestation with vegetation and mining;
Degradation:
Degradation, forest fire scar;
Logging:
Selective Logging Type 1 (Disordered)
Selective Logging Type 2 (Geometric).
RESULTS
The analysis of the spatial-temporal distribution of the Normalized Difference Vegetation Index (NDVI), obtained from Sentinel-L2A images dated May 11, revealed a wide range of values, spanning from -0.94 to 0.94. These data provide significant insight into the vegetation cover in the studied region. Lower NDVI values, ranging from -0.94 to 0.0, generally correspond to water bodies, such as rivers, and small areas lacking vegetation along the banks of these water bodies. This distinction is due to the presence of water, which lowers NDVI values, as well as the openness of the forest canopy in these regions. Conversely, values ranging from 0.4 to 0.94 are associated with dense and healthy forest areas. This higher range of NDVI indicates robust vegetation, reflecting the density and health of the forest canopy in these specific areas.
Upon examining the NDVI images dated May 31 (as illustrated in Figure 3), it was found that the values were consistent with those recorded on May 11, ranging from -0.97 to 0.92. This higher range of NDVI indicates robust vegetation, reflecting the density and health of the forest canopy in these specific areas.
When examining the Soil-Adjusted Vegetation Index (SAVI), a variation in values from -0.14 to 0.77 was identified. These results reinforce the conclusion that there is no evidence of deforestation or significant human activities in the study area. Values in the range of -0.14 to 0.3 can be associated with water bodies, such as rivers, and exposed areas along the riverbanks. Conversely, values above 0.35 indicate areas covered by dense forests in good preservation condition.
Regarding the normalized burn ratio index, variability was observed in the mapped values, ranging from 0.05 to 0.50. It is important to note that no negative values were identified, suggesting the absence of deforestation or burning in the area in question. This finding reinforces the indication of environmental stability in the region, pointing to the preservation of natural conditions.
Values of the index above 0.3 indicate the presence of dense vegetation. This consistency suggests the absence of evidence of deforestation or significant burning events within the study area during this period.
The first point, detected by the Amazonia-1 satellite, has the largest deforested area (176.7 ha) and is located at UTM coordinates 776684.44 m E, 9163289.21 m S. The extent of this area suggests that deforestation has likely been occurring for some time.
The other two deforestation points are close to each other, located at coordinates 828334.14 m E, 9177646.97 m S (8.0 ha of deforested area) and 828817.57 m E, 9177843.93 m S (16 ha of deforested area). Both points were also detected by the Amazonia-1 satellite. The detection of these deforestation points is crucial for monitoring and implementing environmental control measures in the region.
CONCLUSION
There is no indication of deforestation and/or forest degradation within the farm based on the NDVI, SAVI, and NBR maps for the month of May.
The deforestation alert for May indicated 3 points within a 50 km radius of the farm.
REFERENCES
Cunha, A.P.M., Alvala, R.C., Nobre, C.A., Carvalho, M.A., 2015. Monitoring vegetative drought dynamics in the Brazilian semiarid region. Agric. For. Meteorol. 214, 494–505. https://doi.org/10.1016/j.agrformet.2015.09.010.
Chu, H.S., Venevsky, S., Wu, C., Wang, M.H., 2019. NDVIbased vegetation dynamics and its response to climate changes at Amur-Heilongjiang River Basin from 1982 to 2015. Sci. Total Environ. 650, 2051–2062. https://doi.org/10.1016/j.scitotenv.2018.09.115.
Valle Júnior, R.F., Siqueira, H.E., Valera, C.A., Oliveira, C.F., Fernandes, L.F.S., Moura, J. P., Pacheco, F.A.L., 2019. Diagnosis of degraded pastures using an improved NDVI-based remote sensing approach: an application to the environmental protection area of uberaba river basin (minas gerais, Brazil). Remote Sensing Applications: Society and Environment 14, 2033. https://doi.org/10.1016/j.rsase.2019.02.001.
Xu, H.J., Wang, X.P., Yang, T.B., 2017. Trend shifts in satellitederived vegetation growth in Central Eurasia, 1982–2013. Sci. Total Environ. 579, 1658–1674. https://doi.org/10.1016/j.scitotenv.2016.11.182.
Botucatu (SP), June 7th, 2024.
(11) 94004-0092 alessandro@zabottoambiental.com.br www.zabottoambiental.com.br
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