Banca de QUALIFICAÇÃO: JOÃO VICTOR PAIXÃO DE SOUSA FERREIRA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE : JOÃO VICTOR PAIXÃO DE SOUSA FERREIRA
DATA : 16/01/2020
HORA: 08:30
LOCAL: ICA Sala 5
TÍTULO:

TEXTURAL INDEXES OF LOGGING AREAS IN RIO CAPIM FOREST MANAGEMENT UNIT, PARAGOMINAS, PARÁ STATE

PALAVRAS-CHAVES:

Geoprocessing, Satellite imagery, Textural descriptors, Forest harvesting

PÁGINAS: 30
GRANDE ÁREA: Ciências Agrárias
ÁREA: Recursos Florestais e Engenharia Florestal
RESUMO:

ABSTRACT

The Brazilian territory is now increasingly under the eyes of the world, either by its large carbon reserve, which comprises much of the total biomass of terrestrial plants, or negatively by the high levels of burning and deforestation. Regarding the ways employed for monitoring, control and detection of forests affected by logging intensities, the use of remote sensing and geoprocessing are evidenced, which certainly subsidize possible techniques for the detection of modifications under the forest canopy, resulting from logging. Mappings carried out in areas where forestry activities are carried out generally use Landsat series satellites. From satellite images, one can extract the textural information from the image. Texture is one of the most important attributes for recognizing and categorizing objects and scenes and can be characterized by transitions in pixel values that repeat regularly or randomly throughout the image or object. In this context, the present study seeks to identify areas before and after logging and to monitor the development of forest structure through biometric information of the area and processing / analysis of satellite images. The study will be carried out in the municipality of Paragominas, Pará, in the forest management area of the Rio Capim farm, specifically in the Annual Production Unit-UPA 7, Work Unit-UT 14, where the forest inventory information is monitored in the 2004 to 2014. This information will be correlated with the textural information of the satellite image, which will undergo a preprocessing process (radiometric and atmospheric corrections) and subsequent generation of texture images. These procedures will be performed using ENVI 5.3 and QGIS 3.6 software. The statistical analysis will consider the relation of the gray level average of the textural attributes and the sum of the basal area (m² / ha) in each sample unit, to calculate the determination coefficient (R²) and the ANOVA significance test. From the results will be shown the relationship of biometric data (forest inventory data) with textural variables (correlation, SMA, entropy, among others.), observing if this relationship is statistically significant for the study periods, and if the coefficients of determination indicate that the values of the variance proportion of the dependent variable (remaining basal area) around its mean can be satisfactorily explained by the explanatory variables (Haralick texture), with a probability of confidence (α = 95 %).

MEMBROS DA BANCA:
Presidente - 142.060.489-91 - JOSE NATALINO MACEDO SILVA - Oxford
Externo à Instituição - CARLOS DE SOUZA JUNIOR - NENHUMA
Externo à Instituição - ORLANDO DOS SANTOS WATRIN - EMBRAPA
Externo à Instituição - PEDRO WALFIR MARTINS E SOUZA - UFPA