The use of geotechnologies for the identification of the urban flora in the city of Teresina, Brazil

Mesquita, Marcelo Ribeiro de; Agarwal, Shivani; Lima, Leonardo Henrique Guedes de Morais; Soares, Maria Regiane Araujo; Barbosa, Diogo Brunno e Silva; Silva, Vladimir Costa; Werneck, Guilherme Loureiro; Costa, Carlos Henrique Nery

doi:10.1007/s11252-021-01153-z

Cited by 3 publications

(2 citation statements)

References 31 publications

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“…It should be noted that almost all urban tree studies take a data mining approach in that there were no a priori tree metrics identified for selected tree species (Fassnacht et al, 2016; Pu, 2021; Yang et al, 2022). Most remote sensing software programs, such as ENVI and eCognition, have over 100 feature extraction measures that can be used to extract spectral and LiDAR data (Mesquita et al, 2022; Pu and Landry, 2012). However, there are several important spectral and LiDAR metrics that have been noted in two or more studies which should be of broad use for urban tree identification (Table 3).…”

Section: Review Findingsmentioning

confidence: 99%

Remote sensing approaches to identify trees to species-level in the urban forest: A review

Ocón,

Stavros,

Steinberg

et al. 2024

Progress in Physical Geography: Earth and Environment

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Most urban tree inventories depend on resource-intensive, field-based assessments, which are unevenly distributed in space and time. Recently, these inventories have been conducted using field inventories combined with airborne multispectral, hyperspectral, LiDAR, and spaceborne multispectral remote sensing. Significant advances have been made in urban tree GIS databases and remote sensing methods, which include delineating individual tree crowns, extracting tree species metrics, and employing classification techniques. Generally, remote sensing methods distinguish individual urban trees using either pixel-based or object-based methods, while image classification procedures are typically divided into parametric (e.g., regression-based classification, Bayesian, and principal component analysis) and non-parametric approaches such as machine learning (e.g., random forests support vector machines) and deep learning (e.g., convolutional neural networks). Our synthesis of the current state of science suggests sensors with the highest spatial (m), spectral (bands), and temporal (repeat time) resolutions result in the most accurate tree species identification. Combining airborne LiDAR/hyperspectral or airborne LiDAR/spaceborne high-resolution multispectral sensors yields the highest accuracy for the most diverse urban forests. An object-based non-parametric approach, like a fully convolutional neural network, scores higher in accuracy assessments than pixel-based parametric approaches. Future studies can leverage global/regional GIS field inventory databases to expand the scope of studies within and across multiple cities, utilizing LiDAR and spaceborne sensors.

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Section: Review Findingsmentioning

confidence: 99%

Remote sensing approaches to identify trees to species-level in the urban forest: A review

Ocón,

Stavros,

Steinberg

et al. 2024

Progress in Physical Geography: Earth and Environment

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“…El planteamiento de Mesquita [32] fue elemental para elegir qué tipo de plantas considerar en el inventario propuesto, el cual muestra ciertos parámetros a tomar en cuenta en la recolección de plantas de interés, obteniendo la mayor información importante posible sin dejar sesgo en la recolección de datos, pues en este estudio se utilizan incursiones de campo para investigar las especies más abundantes del área y estas fueron posteriormente identificadas por personal especializado del Herbario USON perteneciente a la Universidad de Sonora, asimismo, se utiliza un dispositivo GPS especializado para mapear los especímenes vegetales. Debido a la gran diversidad de especies vegetales esparcidas en el área, se escogieron las especies más grandes y abundantes encontradas.…”

Section: Metodologíaunclassified

Desarrollo de una metodología para la gestión de inventarios de flora

Ochoa-Hernández,

Canizales Dessens,

Barceló-Valenzuela

2023

Epistemus

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Dentro de las características de los jardines zoológicos, se detectó que no se cuenta con un inventario de toda la flora, ni mucho menos de la que requiere más cuidados, de igual manera, no se conoce su correcta ubicación y/o distribución, lo que propicia un inadecuado control y mantenimiento de la misma. Para ello, se diseñó e implementó una metodología que guiará mediante un procedimiento adecuado, la definición, creación y uso de los inventarios para el Centro Ecológico de Sonora, el cual permitirá el manejo eficiente de sus recursos. Se analizaron y estudiaron diferentes autores con distintos procedimientos, se generó una propuesta que se pueda implementar en éste y en otros centros. Se debe de considerar que para este tipo de proyectos se requieren equipos de georreferenciación profesionales los cuales eviten el desfase de las coordenadas y una incorrecta ubicación de las especies. Como resultado, se obtuvo...

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Techniques of Geoprocessing via Cloud in Google Earth Engine Applied to Vegetation Cover and Land Use and Occupation in the Brazilian Semiarid Region

et al. 2022

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Thematic maps of land cover and use can assist in the environmental monitoring of semiarid regions, mainly due to the advent of climate change, such as drought, and pressures from anthropic activities, such as the advance of urban areas. The use of geotechnologies is key for its effectiveness and low operating cost. The objective was to evaluate and understand the spatiotemporal dynamics of the loss and gain of land cover and use in a region of the Brazilian semiarid region, and identify annual trends from changing conditions over 36 years (1985 to 2020), using cloud remote sensing techniques in Google Earth Engine (GEE). Thematic maps of land cover and land use from MapBiomas Brazil were used, evaluated by Mann–Kendall trend analysis. The Normalized Difference Vegetation Index (NDVI) was also determined from the digital processing of about 800 orbital images (1985 to 2020) from the Landsat series of satellites. The trend analysis for land cover and use detected, over time, the loss of forest areas and water bodies, followed by the advance of exposed soil areas and urban infrastructure. The modification of native vegetation directly influences water availability, and agricultural activities increase the pressure on water resources, mainly in periods of severe drought. The NDVI detected that the period from 2013 to 2020 was most affected by climatic variability conditions, with extremely low average values. Thematic maps of land cover and use and biophysical indices are essential indicators to mitigate environmental impacts in the Brazilian semiarid region.

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The use of geotechnologies for the identification of the urban flora in the city of Teresina, Brazil

Cited by 3 publications

References 31 publications

Remote sensing approaches to identify trees to species-level in the urban forest: A review

Remote sensing approaches to identify trees to species-level in the urban forest: A review

Desarrollo de una metodología para la gestión de inventarios de flora

Techniques of Geoprocessing via Cloud in Google Earth Engine Applied to Vegetation Cover and Land Use and Occupation in the Brazilian Semiarid Region

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