December/23 Report
DEFORESTATION MONITORING TECHNICAL REPORT
The study area comprises the "Fazenda Floresta Amazônica" located in the municipality of Apuí-AM (Figure1). 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 vegetation cover by NDVI (Normalized Difference Vegetation Index) to monitor possible changes in vegetation within the area called "Fazenda Floresta Amazônica" as well as detecting degraded and deforested areas.
In addition, deforestation alerts from the INPE (Instituto Nacional de Pesquisas Espaciais - National Institute for Space Research) and Imazon (brazilian research institute) databases, deforestation alerts were monitored from December 1st to December 31st, 2023.
2023, both in the area of the farm and in its surroundings.
In remote sensing, the monitoring of changes in vegetation cover at regional and
scales, the normalized difference vegetation index (NDVI) is commonly used (Shi et al. (NDVI) is commonly used (Shi et al.,2021, Wu et al., 2020).
NDVI is an important indicator that reflects the state of the vegetation, which is affected by precipitation, anthropogenic activities, temperature and soil water content.
NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI)
To draw up the NDVI map for the period between December 1st until December 15th and December 16th until December 31th, Landsat 9 satellite images were used.
On December 7th, satisfactory conditions were found for drawing up the NDVI map, with cloud cover of 20%. In addition, the image from December 31th was used, with cloud cover of 30%.
Following the usual procedure, the NDVI was obtained by applying the algorithm based on the difference in near-infrared reflectance and the reflectance of the reflectance divided by the sum of the spectral bands (1), where NIR is the infrared electromagnetic spectrum and
R is the red electromagnetic spectrum, varying between -1 and 1 (ROUSE et al., 1974), as shown in the equation:
| Satelite | Date | Year | Bands |
|---|---|---|---|
Landsat 9 | December 7th | 2023 | B4-B5 |
Landsat 9 | December 31th | 2023 | B4-B5 |
Table 1. Specifications of the satellite image used to calculate NDVI
SOIL ADJUSTED VEGETATION INDEX (SAVI)
Besides, a SAVI map was drawn up to evaluate and prove that there is no deforestation in the study area.
The Soil Adjusted Vegetation Index (SAVI) is a variation of the Normalized Difference Vegetation Index (NDVI).
Normalized Difference Vegetation Index (NDVI) that takes into account the influence of the soil on the spectral response of plants.
It is used to estimate the density and vigor of vegetationcorrecting for the effects of the soil present in the satellite image.
The same NDVI images captured December 7th.
The SAVI formula is as follows:
Where: NIR is the reflectance value in the infrared band; RED is the reflectance value in the red band and L is the soil adjustment factor, which varies from -1 to 1 (usually defined as 0.5)
Including the soil adjustment factor (L) in the formula makes it possible to compensate for the influence of soil on reflectance, especially in areas with sparse vegetation or exposed soil. The value of L is generally set at 0.5, but can vary depending on the characteristics of the vegetation and soil in the study region.
NORMALIZED BURNING RATIO (NBR)
In order to gain a better understanding of the indices used in the study area, a map of the Normalized Burn Index (NBR) was also drawn up in Qgis software (https://qgis.org/en/site/). This is a index widely used to detect areas affected by (Key and Benson, 1999), deforestation or damaged vegetation.
It uses the near (NIR) and mid-infrared (MIR) bands of satellite images to map the extent and severity of fires.
TheLandsat 9 satellite images were used, specifically bands 5 and 7, dated December 7th, 2023, captured at 02:20 PM (available at https://earthexplorer.usgs.gov/).
The NBR formula is as follows:
Where: NIR is the reflectance value in the band and MIR is the reflectance value in the mid-infrared band.
The Normalized Burn Index (NBR) varies on a scale of values according to the methodology and scale used.
However, a common convention is for the NBR to have values from -1 to 1.
Negative NBR values (-1 to 0) generally indicate areas affected by recent fires, deforestation or damaged vegetation.
Values closer to -1 indicate greater severity of burning or damage to vegetation.
Positive NBR values (0 to 1) are often associated with areas with healthy vegetation. Values closer to 1 indicate more vigorous vegetation.
DEFORESTATION ALERTS
To evaluate the spread of deforestation around the "Fazenda Floresta Amazônica" area, a 50 km radius was set.
Deforestation alert databases from INPE and Imazon were used.
The data collected for the month of February was in shapefile format and all the processing and filtering of the alert points within the radius was carried out using the Qgis software.
Imazon's Deforestation Alert System (SAD) currently uses NASA's Landsat 7 and 8 satellites and the European Space Agency's Sentinel 1A, 1B, 2A and 2B satellites.
(ESA).
SAD detects forest degradation or deforestation that has occurred in areas of 1 hectare or more.
INPE uses images from the WFI sensors of the Sino-Brazilian Earth Resources Satellite (CBERS4) and AWiFS from the Indian Remote Sensing Satellite (IRS). (IRS) satellite, with 64 and 56 meters of spatial resolution respectively.
The data is submitted daily to the Brazilian Institute for the Environment and Renewable Natural Resources (IBAMA - "Instituto Brasileiro do Meio Ambiente e Recursos Naturais Renováveis") with no restriction on the minimum area mapped.
However, for the general public the polygons are with a minimum size of 6.25 hectares, thus allowing the establishment of a comparison criteria with the data provided by the PRODES project.
The pattern of forest cover change is identified by visual interpretation based on five main elements (color, tone, texture, shape and context) and uses the Linear Spectral Mixture Model (LSMM) technique, together with its multispectral image in color composition. multispectral image 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
Analysis of the spatio-temporal distribution of the Normalized Difference Vegetation Index (NDVI), obtained from Landsat 9 images dated 7th December, showed a wide range of values, from -0.03 to 0.55.
This data provides a meaningful interpretation of the vegetation cover in the region under study.
Lower NDVI values, between -0.03 and 0.2, often correspond to bodies of water, such as rivers and small areas without vegetation along the banks of these bodies of water.
This distinction is due to the presence of water, which reduces NDVI values, as well as the openness of the forest canopy in these regions.
On the other hand, values between 0.3 and 0.55 are related to areas of dense and healthy forest.
This higher NDVI range indicates robust vegetation, reflecting the density and health of the forest canopy in these specific areas.
Examining the NDVI images dated December 31th (Figure 3) revealed a continuity in values similar to the NDVI recorded on December 7th, ranging from -0.01 to 0.61.between -0.01 and 0.61.
The consistency of these patterns over time strengthens our understanding of the stability and vitality of the vegetation cover in the region under analysis.
When examining the Soil Adjusted Vegetation Index (SAVI), a range of values between -0.07 and 0.85 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 -0.07 to 0.3 range can be associated with bodies of water, such as rivers and exposed areas on river banks.
On the other hand, values above 0.35 indicate areas covered by dense forests and in a good condition of preservation.
Regarding the normalized burning index, there was a variability observed in the mapped values, ranging from -0.01 to 0.55.
In the -0.01 to 0.2 range, the presence of small clearings on the banks of the rivers was identified and, probably, the negative value refers to the presence of clouds in the image used, due to the rainy season in the region.
Index values above 0.3 indicate the presence of dense vegetation.
When comparing the results of this month's index with the previous month, a similarity in the values was noticed.
This consistency suggests the absence of evidence of deforestation or significant fires occurring within the study area during this period.
During the month of December, a single warning point for deforestation was identified, located in the coordinates 765818.03 m E and 9049056.54 m S, covering an area of 3.5 hectares.
This point detection represents an isolated incidence of activity potentially impacting the region.
It is important to note that, over the last three months, only two deforestation warning points were identified in our ongoing monitoring.
CONCLUSION
There is no evidence of deforestation and/or forest degradation inside the farm based on the NDVI, SAVI and NDR maps in December.
A deforestation warning point was identified in the area around the study area.
REFERENCES
CCunha, 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), 15 de janeiro de 2023.
(11) 94004-0092 alessandro@zabottoambiental.com.br www.zabottoambiental.com.br
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