Application of aerial hyperspectral images in monitoring tree biophysical parameters in urban areas

Abstract Monitoring of trees in urban areas can be conducted using remote sensing, but should be supported by field measurements. The article aims to present the research method used to evaluate discolouration and defoliation of trees and tree damage in the city of Białystok in Poland. The analyses were done using AISA hyperspectral images. Field measurements encompassed determining the locations, species and levels of discolouration and defoliation of trees. Remote sensing indices of vegetation were calculated and correlated with the field-measured values of discolouration and defoliation. Based on that, values of discolouration and defoliation were calculated and evaluated against the field studies. The RMSE of the acquired data was around 16%. Using parameter values, a map of tree damage was drawn up. Based on the analysis, it can be stated that a significant number of trees is undamaged, although a large portion of the trees falls into the warning class.

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Identificação de Ilhas de Calor na Cidade de Campina Grande-PB Utilizando Sensoriamento Remoto (Identification of Heat Islands in Campina Grande City-PB Using Remote Sensing)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v9.2.p614-626 ◽

2016 ◽

Vol 9 (2) ◽

pp. 614 ◽

Cited By ~ 2

Author(s):

Elânia Daniele Silva Araújo

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Rural Areas ◽

Urban Areas ◽

Spatial And Temporal Variability ◽

Heat Islands ◽

Social Nature ◽

Spatial Changes ◽

Remote Sensing Techniques ◽

The City

A intensa urbanização causa diversos problemas de natureza ambiental, climática e social. O crescimento não planejado da população urbana e a remoção da vegetação são fatores que intensificam estes problemas. As temperaturas na cidade são significativamente mais quentes do que as suas zonas rurais circundantes devido às atividades humanas. As intensas mudanças espaciais em áreas urbanas, promovem significativo aumento na temperatura, causando o chamado efeito de Ilha de Calor Urbano (ICU). Campina Grande é uma cidade de tamanho médio que experimentou um crescimento desordenado, desde o tempo do comércio de algodão e, como qualquer cidade de grande ou médio porte, sofre alterações em seu espaço. Dessa forma, este estudo teve por objetivo analisar a variabilidade espaço-temporal da temperatura da superfície (Ts) e detectar ICU, através de técnicas de sensoriamento remoto. Para o efeito, foram utilizadas imagens dos satélites Landsat 5 e 8, dos anos de 1995, 2007 e 2014. Aumentos da Ts foram bem evidentes e foram detectadas duas ICU. Campina Grande mostra um padrão de tendência: o crescimento urbano não planejado é responsável por mudanças no ambiente físico e na forma e estrutura espacial da cidade, o que se reflete sobre o microclima e, em última análise, na qualidade de vida das pessoas. ABSTRACT The intense urbanization causes several problems of environmental, climate and social nature. The unplanned growth of urban population and the vegetation removal are factors that deepen these problems. Temperatures in the city are significantly warmer than its surrounding rural areas due to human activities. Large spatial changes in urban areas promote significant increase in temperature, causing the so-called Urban Heat Island effect (UHI). Campina Grande is a medium-sized town that experienced an uncontrolled growth since the time of the cotton trade and like any large or medium-sized city, undergoes changes in its space. Therefore, this study aimed to analyze surface temperature spatial and temporal variability and to detect potential UHI, through remote sensing techniques. Spectral images from Landsat 5 and 8 satellites were used. Using images from years 1995, 2007 and 2014, considerable increases in temperature were identified and two UHI were recognize. Campina Grande shows a trend pattern: the urban unplanned growth is responsible for changes in the physical environment and in the form and spatial structure of the city, reflecting on people quality of life. Keywords: change detection, surface temperature, heat islands, urbanization.

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Simulation of the Cooking Organic Aerosol Concentration Variability in an Urban Area

10.5194/egusphere-egu21-10090 ◽

2021 ◽

Author(s):

Evangelia Siouti ◽

Ksakousti Skyllakou ◽

Ioannis Kioutsioukis ◽

Giancarlo Ciarelli ◽

Spyros N. Pandis

Keyword(s):

Urban Area ◽

Urban Areas ◽

Temporal Distribution ◽

Late Summer ◽

Field Studies ◽

Organic Aerosol ◽

Basis Set ◽

Cooking Times ◽

The City ◽

Lunch Time

Cooking operations can be an important fine PM source for urban areas. Cooking emissions are a source of pollution that has been often ignored and are not included or are seriously underestimated in urban emission inventories. However, several field studies in cities all over Europe suggest that cooking organic aerosol (COA) can be an important component of the total organic PM. In this study we propose and evaluate a methodology for the simulation of the COA concentration and its variability in space and time in an urban area. The city of Patras, the third biggest in Greece is used for this first application for a typical late summer period. The spatial distribution of COA emissions is based on the exact location of restaurants and grills, while the emissions on the meat consumption in Greece. We estimated COA emissions of 150 kg d-1 that corresponds to 0.6 g d-1 per person. The temporal distribution of COA was based on the known cooking times and the results of the past field studies in the area. Half of the daily COA is emitted during dinner time (21:00-0:00 LT), while approximately 25% during lunch time (13:00-16:00 LT). The COA is simulated using the Volatility Basis Set with a volatility distribution measured in the laboratory and is treated as semivolatile and reactive. The maximum average COA concentration during the simulation period is predicted to be 1.3 &#956;g m-3 in a mainly pedestrian area with a high density of restaurants. Peak hourly COA concentrations in this area exceed 10 &#956;g m-3 during several nights. The local production of secondary COA is predicted to be slow and it represents just a few percent of the total COA.&#160;

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Mapping Urban Areas Using a Combination of Remote Sensing and Geolocation Data

Remote Sensing ◽

10.3390/rs11121470 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1470 ◽

Cited By ~ 7

Author(s):

Nan Xia ◽

Liang Cheng ◽

ManChun Li

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Urban Areas ◽

Large Scale ◽

High Spatial Resolution ◽

Human Life ◽

Human Movement ◽

Night Time ◽

Urban Mapping ◽

The City

Urban areas are essential to daily human life; however, the urbanization process also brings about problems, especially in China. Urban mapping at large scales relies heavily on remote sensing (RS) data, which cannot capture socioeconomic features well. Geolocation datasets contain patterns of human movement, which are closely related to the extent of urbanization. However, the integration of RS and geolocation data for urban mapping is performed mostly at the city level or finer scales due to the limitations of geolocation datasets. Tencent provides a large-scale location request density (LRD) dataset with a finer temporal resolution, and makes large-scale urban mapping possible. The objective of this study is to combine multi-source features from RS and geolocation datasets to extract information on urban areas at large scales, including night-time lights, vegetation cover, land surface temperature, population density, LRD, accessibility, and road networks. The random forest (RF) classifier is introduced to deal with these high-dimension features on a 0.01 degree grid. High spatial resolution land cover (LC) products and the normalized difference built-up index from Landsat are used to label all of the samples. The RF prediction results are evaluated using validation samples and compared with LC products for four typical cities. The results show that night-time lights and LRD features contributed the most to the urban prediction results. A total of 176,266 km2 of urban areas in China were extracted using the RF classifier, with an overall accuracy of 90.79% and a kappa coefficient of 0.790. Compared with existing LC products, our results are more consistent with the manually interpreted urban boundaries in the four selected cities. Our results reveal the potential of Tencent LRD data for the extraction of large-scale urban areas, and the reliability of the RF classifier based on a combination of RS and geolocation data.

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Thermal Infrared Hyperspectral Imaging for Mineralogy Mapping of a Mine Face

Remote Sensing ◽

10.3390/rs10101518 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1518 ◽

Cited By ~ 3

Author(s):

Stephane Boubanga-Tombet ◽

Alexandrine Huot ◽

Iwan Vitins ◽

Stefan Heuberger ◽

Christophe Veuve ◽

...

Keyword(s):

Remote Sensing ◽

Spectral Resolution ◽

Remote Sensing Data ◽

Field Measurements ◽

Thermal Infrared ◽

Field Studies ◽

Hyperspectral Data ◽

Spectral Bands ◽

Remote Sensing Systems ◽

Viewing Perspective

Remote sensing systems are largely used in geology for regional mapping of mineralogy and lithology mainly from airborne or spaceborne platforms. Earth observers such as Landsat, ASTER or SPOT are equipped with multispectral sensors, but suffer from relatively poor spectral resolution. By comparison, the existing airborne and spaceborne hyperspectral systems are capable of acquiring imagery from relatively narrow spectral bands, beneficial for detailed analysis of geological remote sensing data. However, for vertical exposures, those platforms are inadequate options since their poor spatial resolutions (metres to tens of metres) and NADIR viewing perspective are unsuitable for detailed field studies. Here, we have demonstrated that field-based approaches that incorporate thermal infrared hyperspectral technology with about a 40-nm bandwidth spectral resolution and tens of centimetres of spatial resolution allow for efficient mapping of the mineralogy and lithology of vertical cliff sections. We used the Telops lightweight and compact passive thermal infrared hyperspectral research instrument for field measurements in the Jura Cement carbonate quarry, Switzerland. The obtained hyperspectral data were analysed using temperature emissivity separation algorithms to isolate the different contributions of self-emission and reflection associated with different carbonate minerals. The mineralogical maps derived from measurements were found to be consistent with the expected carbonate results of the quarry mineralogy. Our proposed approach highlights the benefits of this type of field-based lightweight hyperspectral instruments for routine field applications such as in mining, engineering, forestry or archaeology.

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Studies and Researches on Monitoring by GIS Models Extreme Phenomenons in the Popular Center

Present Environment and Sustainable Development ◽

10.2478/pesd-2018-0037 ◽

2018 ◽

Vol 12 (2) ◽

pp. 155-165

Author(s):

Iustina Lateș ◽

Alexandru-Lucian Luca ◽

Ștefania Chirica ◽

Mihail Luca

Keyword(s):

Urban Areas ◽

Water Channel ◽

Field Measurements ◽

Supply Networks ◽

Existing Building ◽

The Public ◽

Gis Model ◽

Intervention Teams ◽

Textual Data ◽

The City

Abstract The work involves the realization of a GIS model that includes both information on real estate cadastre and water supply networks. This shows the stages of making such a model, starting from field measurements, to structuring the database and custom layouts. In the study, the distribution pipelines equipped with fire hydrants and the existing building types in the area were considered as the main elements. Buildings were classified according to importance, height, destination, mapping indexes, etc. and have been integrated into the GIS model. GIS programs aim at specifying as much as possible the textual data attached to perform complex analyzes. Autocad and ArcMap programs allow you to get thematic maps on building types, pipeline network analysis on which hydrants are located, and how to protect firewalls. The study model was developed only for a sector in the city of Iaşi, but it can be extended to an application that can be used in other urban areas for the purpose of being used by the water-channel directorate, the intervention teams, the public administration local, etc.

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Data and techniques for studying the urban heat island effect in Johannesburg

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-203-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 203-206 ◽

Cited By ~ 3

Author(s):

C. H. Hardy ◽

A. L. Nel

Keyword(s):

Remote Sensing ◽

Urban Heat Island ◽

Urban Areas ◽

Remote Sensing Data ◽

Urban Heat Island Effect ◽

Heat Island ◽

Sensing Data ◽

Island Effect ◽

Urban Heat ◽

The City

The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability of the levels of vegetation across Johannesburg’s residential regions has an influence on the urban heat island effect within the city. Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis of influencing factors.

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The ectomycorrhizal community of urban linden trees in Gdańsk, Poland

10.1101/2020.07.30.228668 ◽

2020 ◽

Author(s):

Jacek Olchowik ◽

Marzena Suchocka ◽

Paweł Jankowski ◽

Tadeusz Malewski ◽

Dorota Hilszczańska

Keyword(s):

Urban Areas ◽

Classification Tree ◽

Principal Component ◽

Distribution Patterns ◽

Fungal Species ◽

Urban Environments ◽

Cenococcum Geophilum ◽

Tree Damage ◽

Ectomycorrhizal Communities ◽

The City

The linden tree ( Tilia spp.) is a popular tree for landscaping and urban environments in central and northwest European countries, and it is one of the most popular in cities in Poland. Ectomycorrhizal fungi form a symbiosis with many urban tree species and protect the host plant from heavy metals and against salinity. The aim of this study was to characterize the ECM fungal community of urban linden trees along the tree damage gradient. The study was performed on two homogeneous sites located in the centre of the city of Gdańsk, in northern Poland. The vitality assessment of urban linden trees was made according to Roloff’s classification. Tree damage classes were related to soil characteristics using principal component analysis. The five ectomycorrhizal fungal species were shared among all four tree damage classes, and Cenococcum geophilum was found to be the most abundant and frequent ectomycorrhizal fungal species in each class. Park soil had significantly lower pH and Na, Cl and Pb content than street soils. Our knowledge of ectomycorrhizal communities in urban areas is still limited, and these findings provide new insights into ectomycorrhizal distribution patterns in urban areas.

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Studi Bahaya Antropogenik yang Disebabkan Pembuangan Sampah di Bentuklahan Fluvio-Marin di Sebagian Muara Angke, Jakarta Menggunakan Data Penginderaan Jauh Udara

Jurnal Tataloka ◽

10.14710/tataloka.23.1.57-66 ◽

2021 ◽

Vol 23 (1) ◽

pp. 57-66

Author(s):

Nurwita Mustika Sari ◽

Mangapul Parlindungan Tambunan

Keyword(s):

Remote Sensing ◽

Waste Management ◽

Waste Disposal ◽

Urban Areas ◽

Remote Sensing Data ◽

Disposal Site ◽

Visual Interpretation ◽

Waste Disposal Site ◽

Aerial Remote Sensing ◽

The City

Anthropogenic hazards are hazards arising from human actions or negligences. Anthropogenic hazards can affect both human and the broader ecosystem and various landforms. Waste as the effect of human activity is a big problem in urban areas related to the difficulty of waste management while waste production continues to increase. The impact of poor waste management in the city is a potential anthropogenic hazard for the region. Part of the city that often receives less attention related to waste or environmental sanitation and has been negatively affected by waste is the coastal area in a big city, which is kind of fluvio-marine landform unit, one of which is Muara Angke, which is the study area of this research. Identification of the waste disposal site is carried out to determine the level of anthropogenic hazard posed by waste in the area. With very high spatial resolution obtained by aerial remote sensing data, identification of objects in urban areas such as waste disposal site can be conducted. The purpose of this study is to identify the waste disposal site in part of Muara Angke region and to identify the potential of anthropogenic hazard caused by waste in the area. The data used is the LSU (LAPAN Surveillance UAV) camera data. The method proposed in this research is visual interpretation LSU camera data. The result showed that waste disposal location can be performed using aerial remote sensing data and visual interpretation to the data.

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BRDF field studies for remote sensing of urban areas∗

Remote Sensing Reviews ◽

10.1080/02757250009532409 ◽

2000 ◽

Vol 19 (1-4) ◽

pp. 37-57 ◽

Cited By ~ 9

Author(s):

Gerhard Meister ◽

André Rothkirch ◽

Hartwig Spitzer ◽

Johann Bienlein

Keyword(s):

Remote Sensing ◽

Urban Areas ◽

Field Studies

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Noise Mapping of the Flyover Highway in Genoa: comparison of different methods

Noise Mapping ◽

10.2478/noise-2014-0007 ◽

2014 ◽

Vol 1 (1) ◽

Cited By ~ 3

Author(s):

Davide Borelli ◽

Simona Repetto ◽

Corrado Schenone

Keyword(s):

Urban Areas ◽

State Of The Art ◽

Field Measurements ◽

Computational Time ◽

Octave Band ◽

Noise Mapping ◽

Modeling Tools ◽

Simulation Tools ◽

The City

AbstractIn urban noise mapping the accuracy of the simulation tools is often challenged by the complexity of the modeled scenario, particularly when its extent coincide with the whole city. In this paper, a meaningful case study is reported concerning the flyover highway “Aldo Moro” in Genoa. The particular morphology of the city and the location of the highway make it a significant test for analyzing the effectiveness of current modeling tools in simulating complex urban areas. Noise mapping has been implemented in accordance with the standardNMPB-Routes- 2008. Results have been then analyzed complying with the END. Next diverse computational methods have been compared, considering ISO 9613-2, NMPB-Routes-1996, and Harmonoise, and even different frequency partitions (octave band or one-third octave band) for the last two standards. The computational time for the different calculation methods has been analyzed. In order to get a reciprocal validation, the simulated noise maps have been finally compared with maps coming from on field measurements. In this way a case study helpful for public administrations and stakeholders facing similar issues is provided, defining the state of the art and the forthcoming perspectives.

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