Urban Phytophysiognomy Characterization Using NDVI from Satellites Images and Free Software

Gonçalves, Ariadne Barbosa; Godoi, Raquel de Faria; Filho, Antônio Conceição Paranhos; Folhes, Marcelo Theophilo; Pistori, Hemerson

doi:10.11137/2018_3_24_36

Cited by 6 publications

(7 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…We analyzed RapidEye satellite images from the urban area (MMA, 2013) (Figure 1). We classified the terrain of the city in five classes: 1) water, 2) anthropized area, 3) dense vegetation, 4) herbaceous vegetation, and 5) open vegetation (Gonçalves et al, 2018). RapidEye images and NDVI (Gonçalves et al 2018).…”

Section: Description Of Urban Vegetation Surveymentioning

confidence: 99%

“…We classified the terrain of the city in five classes: 1) water, 2) anthropized area, 3) dense vegetation, 4) herbaceous vegetation, and 5) open vegetation (Gonçalves et al, 2018). RapidEye images and NDVI (Gonçalves et al 2018). The green tones are dense, herbaceous or dense vegetation, the beige tone is anthropized areas and the blue color is the area with water resources.…”

Section: Description Of Urban Vegetation Surveymentioning

confidence: 99%

“…The Brazilian savanna has diverse vegetation, characterized by tortuous trees, e.g., the Caryocaceae pollen is related to Cerradão woodland (Pott and Pott, 1994), therefore classified as dense vegetation. The classification of dense, herbaceous and open vegetation used in this work follows Gonçalves et al (2018).…”

Section: Pollen Grain Imagesmentioning

confidence: 99%

“…To estimate the probability of each pollen found in the cases occurring in the vegetation class found in the map of Campo Grande (Gonçalves et al, 2018), we evaluated the number of pixels per vegetation class relating the occurrence of each pollen family per vegetation class. It is possible to establish the probability of occurrence for each set of pollen grains using the distance of the cases from the vegetation class and the type of origin of vegetation class in each case.…”

Section: Experiment: Validation In Forensic Casesmentioning

confidence: 99%

“…We used a classified NDVI image from the urban area of Campo Grande (Gonçalves et al, 2018) as the entrance to the urban study center for the vegetation class tracing. By doing this, we could find coordinates of corpses, thus, able to establish the radius to surroundings of the case, which is defined by the user.…”

Section: Experiment: Validation In Forensic Casesmentioning

confidence: 99%

See 4 more Smart Citations

Forensic palynology: computer vision and geotechnologies to support criminalistics expertise

Gonçalves

Albuquerque

Alves

et al. 2022

RSD

View full text Add to dashboard Cite

Pollen grains can provide valuable information to forensic palynology, such as the time of death or the possible origin of a corpse. Forensic Palynology is a vital tool to be used in a criminal investigation because the different environment has distinct pollen signatures. Brazil has a rich and diversified flora that is suitable for the application of forensic palynology. The purpose of this research is to introduce palynology automation as a tool to improve the investigative method in forensic palynology and apply it to forensic palynology automation. The studied city has different vegetation types, in which we performed assessments to identify its correspondent pollen types. PALINOVIC algorithm was developed using computer vision and geotechnology techniques. Our results show that it is possible to correlate pollen grains found in forensic samples by automatic pollen identification and with a mapping of the likely vegetation. Our results show that it is possible to relate the presence of pollen grains found in forensic samples through the automatic identification of images together with a database of georeferenced plant species. It was possible to analyze the pollen grains collected in eight bodies, where the algorithm presented a performance of 90.51% in the pollen grain classification tests. Furthermore, pollen grains could be correlated with the type of vegetation where the body was found. Thus, the technique developed can be applied in other urban centers from a previous georeferencing of plants, as well as a pollen database.

show abstract

Section: Description Of Urban Vegetation Surveymentioning

confidence: 99%

Section: Description Of Urban Vegetation Surveymentioning

confidence: 99%

Section: Pollen Grain Imagesmentioning

confidence: 99%

Section: Experiment: Validation In Forensic Casesmentioning

confidence: 99%

Section: Experiment: Validation In Forensic Casesmentioning

confidence: 99%

See 3 more Smart Citations

Forensic palynology: computer vision and geotechnologies to support criminalistics expertise

Gonçalves

Albuquerque

Alves

et al. 2022

RSD

View full text Add to dashboard Cite

show abstract

Urban land cover mapping, using open satellite data. Case study of the municipality of Thessaloniki.

Tsolakidis

Vafiadis

2020

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

The use of open satellite data has become a valuable tool for monitoring the urban environment due to high temporal, spectral and spatial resolution. Planners and stakeholders can rely on these data since they offer an alternative point of view of a very complex urban scenery. The processing of satellite images with the combined use of different types of data (statistical, in situ etc) can extract information for the present situation, in urban and suburban areas. This study use image data from the Sentinel satellite mission, in order to extract urban land cover characteristics in Thessaloniki city. The Sentinel mission started the image acquisition on 2014. The data set are freely available for downloading. The use of high resolution satellite images (e.g IKONOS) in urban studies, has been proved very useful all these years. On the other hand the use of a medium size spatial resolution satellite, as Sentinel-2, with 10m pixel size, is a very promising optical earth-observation satellite, which is tested in this study. Image processing techniques used to produce classified map of urban characteristics and land cover classes (built up areas, vegetation etc). The contribution of a radar image of Sentinel-1, in the classification process, is also tested. All the above processing is done with an automatic procedure, giving additional value to the proposed methodology. The final classified map will give planners a management tool for decision-making concerning the sustainable urban development and will be the basis for implementing hydrology studies, planning, land use change detection and other.

show abstract

Study of regional regulation on “Kawasan Bandung Utara” impact on flood discharges from the perspective of spatial variations of extreme precipitation in Bandung basin

Harmadianto

Suwarman

Riawan

et al. 2020

IOP Conf. Ser.: Earth Environ. Sci.

View full text Add to dashboard Cite

This research was built from the probability of shifting urbanization patterns as a result of the Regional Regulation about Northern Bandung Region (Perda KBU). Moreover, extreme precipitation in the Bandung Basin not only happens in KBU but also varies spatially. The probability of urbanization shifting and spatial variation of extreme precipitation can increase flood discharge in other places. Three stages to understand how the spatial variations of extreme precipitation and land use affect flood discharge in Bandung Basin, namely: 1) Extreme precipitation data processing, 2) Land-use data processing, and 3) Hydrology Model simulation using HEC-HMS. Urbanization shifting to north non-KBU and east areas occurs as an impact of Perda KBU. It significantly affects flood discharge in the east area but relatively no impact in the north non-KBU area. Additionally, despite extreme precipitation frequency and volume, the south area has the biggest value. It opens the possibility that the South Bandung area has the potential to be the biggest contributor to Bandung Basin discharge. Therefore, flood study in the south area is needed as a priority.

show abstract

Urban Phytophysiognomy Characterization Using NDVI from Satellites Images and Free Software

Cited by 6 publications

References 0 publications

Forensic palynology: computer vision and geotechnologies to support criminalistics expertise

Forensic palynology: computer vision and geotechnologies to support criminalistics expertise

Urban land cover mapping, using open satellite data. Case study of the municipality of Thessaloniki.

Study of regional regulation on “Kawasan Bandung Utara” impact on flood discharges from the perspective of spatial variations of extreme precipitation in Bandung basin

Contact Info

Product

Resources

About