Remote Sensing has been widely used over the last decades by the rapid technological development of multispectral imaging sensors, in addition to innovative technological concepts for the development of models and methods that can explore and evaluate new forms of spatial data acquisition. In this context, this work aims to investigate LiDAR data integrated with CBERS-4 multispectral orbital images for the evaluation of a new index based on environmental parameters. To this end, the integrated use of LiDAR data on CBERS-4 images using altitude slicing with the physical indices NDVI, NDWI and NDBI and the development of a new index for better enforcement of environmental legislation were analyzed. As a result, the accuracy of the supervised land use and land cover classification by Kappa coefficient pointed (Good Quality), and the Global Accuracy index indicated 100% separability of targets for the images of the periods August 29th, 2019 and January 22th, 2015. In the development of the new environmental index, the mathematical formula based on the physical indices NDVI and NDBI, by the trial and error criterion of interval between -1 to +1 that met the needs of integration was the value zero (0), in logarithmic scale log10. As a conclusion, the results confirm that it is possible, using altitude slicing with the physical indices NDVI and NDBI to analyze the integrated use of 3D LiDAR data on CBERS-4 orbital multispectral images to create a new physical environmental index.

Júnior-CRB6/2422 O conteúdo dos artigos e seus dados em sua forma, correção e confiabilidade são de responsabilidade exclusiva dos autores. 2019 Permitido o download da obra e o compartilhamento desde que sejam atribuídos créditos aos autores, mas sem a possibilidade de alterá-la de nenhuma forma ou utilizá-la para fins comerciais.

Remote Sensing (RS) has been widely used over the last decades by the rapid technological development of multispectral imaging sensors and by its numerous applications dedicated to understanding and analyzing spectral, radiometric, spatial and temporal heterogeneities of the most varied targets of the Earth's surface. Among the various techniques employed, the use of physical indices stands out because it makes it easier to obtain information about different targets. When one intends to analyze physical NDVI and NDBI index values, one must take into account the correlation of the target by digital numbers (ND) and by reflectance to identify the best method to be used. In this context, this work aims to compare by ND and reflectance the NDVI and NDBI indices and evaluate similarities or significant variations between the targets (vegetation, urban and water). For this, two distinct images from the CBERS-4 satellite MUX and IRS sensors were used. All calculations and analysis were performed using the QGIS software and tools in version 3.16.2. As a result, it was observed that there was similarity between the Vegetation and Urban targets, being noticed significant variations with and without radiometric correction for the Water target, year 2016 and 2019. Thus, after performing radiometric correction the reflectance values of the targets for NDVI and NDBI have more accurate responses and therefore more sensitive when compared to ND. It is worth noting, that the relationship ND and reflectance for NDVI and NDBI are approximately linear, identifying no significant differences.