TY - GEN

T1 - Increasing the Distinctness of Clearings and Forest Vegetation Using Vegetation Indices from Satellite Images

AU - Zraenko, S. M.

N1 - THE WORK WAS SUPPORTED BY RFBR, PROJECT N 19-29-09022.

PY - 2024

Y1 - 2024

N2 - The article presents results of study the ability of distinctness of forests and clearings according to remote sensing data. Six vegetation indices were used: the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), the Atmospherically Resistant Vegetation Index (ARVI), the Enhanced Vegetation Index (EVI), the Vegetation Index (GCI), and the Structure Insensitive Pigmentation Index (SIPI). Differences between the analyzed objects were determined quantitatively by the difference of two values. The first one was formed by the value of the mathematical expectation of the vegetation index for the forest. By it, the doubled mean square deviation of this index was subtracted. The second one was the mathematical expectation of the vegetation index for the clearing, to whom the mean square deviation of this index was added twice. As it was shown, for all summer images, the use of this criterion does not allow reliable separation of the forest from the clearings. To increase the difference of the studied objects, the aggregation of two, three, four, five, and six vegetation indices in their various combinations was carried out. The maximum difference between the forest and the clearings of 0.0566 was obtained by combining three vegetation indices – NDVI, ARVI and SIPI, calculated for the July snapshot. This result suggests the effectiveness of aggregation of vegetation indices for the detection of clearings. The fact that when combining four, five, and six vegetation indices, the ability of distinctness of objects is worsened since the basis formed from them is not orthogonal. The obtained results are supposed to be used in conducting research for determining the areas of unauthorized logging (on the basis of the remote sensing data).

AB - The article presents results of study the ability of distinctness of forests and clearings according to remote sensing data. Six vegetation indices were used: the Normalized Difference Vegetation Index (NDVI), the Soil Adjusted Vegetation Index (SAVI), the Atmospherically Resistant Vegetation Index (ARVI), the Enhanced Vegetation Index (EVI), the Vegetation Index (GCI), and the Structure Insensitive Pigmentation Index (SIPI). Differences between the analyzed objects were determined quantitatively by the difference of two values. The first one was formed by the value of the mathematical expectation of the vegetation index for the forest. By it, the doubled mean square deviation of this index was subtracted. The second one was the mathematical expectation of the vegetation index for the clearing, to whom the mean square deviation of this index was added twice. As it was shown, for all summer images, the use of this criterion does not allow reliable separation of the forest from the clearings. To increase the difference of the studied objects, the aggregation of two, three, four, five, and six vegetation indices in their various combinations was carried out. The maximum difference between the forest and the clearings of 0.0566 was obtained by combining three vegetation indices – NDVI, ARVI and SIPI, calculated for the July snapshot. This result suggests the effectiveness of aggregation of vegetation indices for the detection of clearings. The fact that when combining four, five, and six vegetation indices, the ability of distinctness of objects is worsened since the basis formed from them is not orthogonal. The obtained results are supposed to be used in conducting research for determining the areas of unauthorized logging (on the basis of the remote sensing data).

UR - http://www.scopus.com/inward/record.url?partnerID=8YFLogxK&scp=85196516309

U2 - 10.1063/5.0210570

DO - 10.1063/5.0210570

M3 - Conference contribution

SN - 978-073544954-1

VL - 3094

T3 - AIP Conference Proceedings

BT - AIP Conference Proceedings

PB - American Institute of Physics Inc.

T2 - International Conference of Numerical Analysis and Applied Mathematics 2022, ICNAAM 2022

Y2 - 19 September 2022 through 25 September 2022

ER -