UAV: Low-cost remote sensing for high-resolution investigation of landslides

2015 ◽  
Author(s):  
Daniele Giordan ◽  
Andrea Manconi ◽  
Dwayne D. Tannant ◽  
Paolo Allasia
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Low Cost

scholarly journals COMPARISON OF SAFER AND METRIC-BASED ACTUAL EVAPOTRANSPIRATION MODELS IN A SUBTROPICAL AREA OF BRAZIL

Irriga ◽  
2019 ◽  
Vol 1 (1) ◽  
pp. 48-55
Author(s):  
Cesar De Oliveira Ferreira Silva ◽  
Rodrigo Lilla Manzione ◽  
Jos´é Luiz Albuquerque Filho
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Low Cost ◽  
Simple Algorithm ◽  
Sao Paulo ◽  
Actual Evapotranspiration ◽  
Landsat 8 ◽  
São Paulo ◽  
Subtropical Area ◽  
Internal Calibration

COMPARISON OF SAFER AND METRIC-BASED ACTUAL EVAPOTRANSPIRATION MODELS IN A SUBTROPICAL AREA OF BRAZIL     CÉSAR DE OLIVEIRA FERREIRA SILVA1; RODRIGO LILLA MANZIONE2 E JOSÉ LUIZ ALBUQUERQUE FILHO3   1Agronomical Sciences Faculty, Universidade Estadual Paulista, Av. Universitária, 3780, Altos do Paraíso, 18610-034, São Paulo/SP, Brazil, [email protected]. 2School of Sciences and Engineering, Universidade Estadual Paulista, Rua Domingos da Costa Lopes,780, Jd. Itaipu, 17602-496, Tupã/SP, Brazil, [email protected]. 3Department of Hydrogeology, Institute of Technological Research (IPT), Av. Prof. Almeida Prado, 532, Cid. Universitária – Butantã, 05508-901, São Paulo/SP, Brazil, [email protected].     1 ABSTRACT   Remote sensing algorithms are well known to estimate surface energy fluxes in regional to global scales with low cost. The remote sensing approach has an advantage of estimating evapotranspiration (ET) on larger spatiotemporal scales when compared with traditional methods. This study compared the result of ET estimates from the “Simple Algorithm for Evapotranspiration Retrieving” (SAFER) and “Mapping Evapotranspiration at high Resolution with Internal Calibration” (METRIC) models on varied land uses of a subtropical area located in Southeast Brazil by using a image from the sensor OLI of LANDSAT-8. The results showed similarity of ET estimate from both models, although slight deviation especially at high ET values. It happened due differences as the need of anchor pixel in METRIC, which requires two points with extrem thermohydrological conditions in the same area. Minimum ground data requirement is the major advantage of the METRIC over the SAFER model. The maximum value, the sum and ET range by METRIC was higher than SAFER. This study has considered both models feasible for estimation of ET from satellite data in the study area.   Keywords: remote sensing, modelling, superficial temperature, Landsat-8, agriwater.                                                            SILVA, C. O. F.; MANZIONE, R. L.; ALBUQUERQUE FILHO, J. L. COMPARAÇÃO DE MODELOS DE EVAPOTRANSPIRAÇÃO REAL SAFER E METRIC EM UMA ÁREA SUBTROPICAL DO BRASIL     2 RESUMO   Algoritmos de sensoriamento remoto são conhecidos por estimar fluxos de energia de superfície em escalas regionais a globais com baixo custo. A abordagem de sensoriamento remoto tem a vantagem de estimar a evapotranspiração (ET) em escalas espaço-temporais maiores que os métodos tradicionais. Este estudo compara o resultado da estimativa de ET do “Simple Algorithm for Evapotranspiration Retrieving” (SAFER) e “Mapping Evapotranspiration at high Resolution with Internal Calibration” (METRIC) em variados usos da terra de uma área subtropical localizada no Sudeste do Brasil usando uma imagem do sensor OLI do satélite LANDSAT-8. Os resultados mostraram similaridade da estimativa da ET em ambos os modelos, embora houvesse desvio, especialmente em altos valores de ET. Isto é devido a diferenças como a necessidade de âncora de pixel no modelo METRIC, que necessita de dois pontos com condições termohidrológicas extremas em uma mesma área. A exigência mínima de dados terrestres é a principal vantagem do METRIC sobre o modelo SAFER. Esse estudo considerou ambos os modelos viáveis ​​para a estimativa de ET a partir de dados de satélite na área de estudo. Neste estudo, o valor máximo, a soma e a variação do ET pelo METRIC foram maiores que o do SAFER.   Palavras-chave: sensoriamento remoto, modelagem, temperatura de superfície, Landsat-8, agriwater.

scholarly journals TOWARDS AN AUTOMATED FLOOD AREA EXTRACTION FROM HIGH RESOLUTION SATELLITE IMAGES

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 97-104
Author(s):  
R. G. C. J. Kapilaratne ◽  
S. Kaneta
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Images ◽  
Global Climate ◽  
Low Cost ◽  
Remote Sensing Data ◽  
Flood Events ◽  
Large Area ◽  
High Resolution Satellite Images ◽  
Catastrophic Impact

Abstract. Flooding is considered as one of the most devastated natural disasters due to its adverse effect on human lives as well as economy. Since more population concentrate towards flood prone areas and frequent occurrence of flood events due to global climate change, there is an urgent need in remote sensing community for faster and reliable inundation mapping technologies to increase the preparedness of population and reduce the catastrophic impact. With the recent advancement in remote sensing technologies and integration capability of deep learning algorithms with remote sensing data makes faster mapping of large area is feasible. Therefore, this study attempted to explore a faster and low cost solution for flood area extraction by integrating convolution neural networks (CNNs) with high resolution (1.5 m) SPOT satellite images. By consider the system requirement as a measure of cost, capabilities (speed and accuracy) of a deeper (ResNet101) and a shallower (MobileNetV2) CNNs on flood mapping were examined and compared. The models were trained and tested with satellite images captured during several flood events occurred in Japan. It is observed from the results that ResNet101 obtained better flood area mapping accuracy than MobileNetV2. Whereas, MobileNetV2 is having much higher capabilities in faster mapping in 0.3 s/km2 with a competitive accuracy and minimal system requirements than ResNet101.

scholarly journals Using UAV imagery to perform fine-scale mapping of wetland vegetation

2021 ◽  
Author(s):  
◽  
Patrick Hipgrave
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
High Resolution ◽  
Low Cost ◽  
Digital Camera ◽  
Aerial Photographs ◽  
Fine Scale ◽  
Ancillary Data ◽  
Strong Argument ◽  
Object Based

<p>Differentiating between species of plants in aerial imagery is often challenging and, in some cases, can be impossible without significant field data collection. However, remote sensing technology is developing to the point where it is increasingly possible to eliminate the need for extensive fieldwork entirely and conduct non-disruptive monitoring of fragile environments. The increasing availability of UAV platforms with integrated high-resolution cameras and low-cost image processing software is also making remote sensing operations accessible to those outside the scientific community with an interest in environmental monitoring. This project trialled an emerging set of image analysis techniques called ‘object-based image analysis’ to create fine scale maps of a recovering wetland area, based on aerial photographs collected using a consumer-grade UAV (unmanned aerial vehicle). The effects of including additional ancillary data (such as digital surface models (DSMs) and multispectral imagery) in the classification process were also assessed to compare the ability of a standard digital camera to produce high-accuracy classifications to that of a more specialised multispectral sensor. The inclusion of this extra information was found to significantly improve classification accuracy in almost all cases, making a strong argument for the inclusion of ancillary data whenever possible, especially when considering the ease with which ancillary datasets can be produced. The high-resolution (between 2 and 4cm/pixel) imagery provided sufficient detail to observe 28 distinct land cover classes in total, with around 20 classes per image. While the number of classes in the classification scheme may have imposed limits on the overall accuracy of the classified maps, several classes were classified with a high (70% or greater) level of accuracy, including two invasive species, showing that the object-based school of image classification has potential to be a powerful tool for detecting and tracking individual vegetation types.</p>

scholarly journals Intercomparison of low and high resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO<sub>2</sub>, CH<sub>4</sub> and CO

2019 ◽  
Author(s):  
Mahesh Kumar Sha ◽  
Martine De Mazière ◽  
Justus Notholt ◽  
Thomas Blumenstock ◽  
Huilin Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Greenhouse Gas ◽  
Low Cost ◽  
Low Resolution ◽  
Data Set ◽  
Solar Absorption ◽  
Global Coverage ◽  
Reference Measurements ◽  
Absorption Measurements

Abstract. The Total Carbon Column Observing Network (TCCON) has been the baseline network of instruments that record solar absorption spectra from which accurate and precise column-averaged dry air mole fractions of CO2 (XCO2), CH4 (XCH4), CO (XCO) and other gases are retrieved. The TCCON data have been widely used for carbon cycle science and validation of satellites measuring greenhouse gas concentrations globally. The number of stations in the network (currently about 25) is limited and the stations are distributed mostly in Northern America, Europe, Japan and Oceania leaving gaps in the global coverage. A denser distribution of ground-based solar absorption measurements is needed to cover various atmospheric conditions (humid, dry, polluted, presence of aerosol), various surface conditions (high and low albedo) and a larger latitudinal distribution. More stations in the southern hemisphere are also needed but a further expansion of the network is limited by its costs and logistical requirements. For this reason several groups are investigating supplemental portable low-cost instruments. The European Space Agency (ESA) funded campaign Fiducial Reference Measurements for Ground-Based Infrared Greenhouse Gas Observations (FRM4GHG) at the Sodankylä TCCON site in northern Finland aims at characterising the assessment of several low-cost portable instruments for precise solar absorption measurements of XCO2, XCH4 and XCO. The test instruments under investigation are three Fourier transform spectrometers (FTS): a Bruker EM27/SUN, a Bruker IRcube and a Bruker Vertex70; as well as a Laser Heterodyne spectro-Radiometer (LHR) developed by the UK Rutherford Appleton Laboratory. All four remote sensing instruments performed measurements simultaneously next to the reference TCCON instrument, a Bruker IFS 125HR, for a full year in 2017. The TCCON FTS was operated in its normal high-resolution mode (TCCON data set) and in a special low-resolution mode (HR125LR data set), similar to the portable spectrometers. The remote sensing measurements have been complemented by regular AirCore launches performed from the same site. They provide in-situ vertical profiles of the target gas concentrations as auxiliary reference data for the column retrievals which is traceable to the WMO SI standards. The timeseries, the bias relative to the reference instrument and its scatter and the seasonal and the day-to-day variations of the target gases are shown and discussed. The comparisons with the HR125LR data set gave useful analysis of the resolution dependent effects on the target gas retrieval. The solar zenith angle dependence of the retrievals is shown and discussed. The reference measurements performed with the Bruker IFS 125HR (TCCON and HR125LR data sets) were found to be affected by non-linearity. A non-linearity correction of the TCCON data was performed and compared with the test instruments and AirCore. The non-linearity corrected TCCON data show a better match with the test instruments and AirCore data as compared to the reference TCCON data. The intercomparison results show that the LHR data have a large scatter and biases with a strong diurnal variation relative to the TCCON and other FTS instruments. The LHR is a new instrument under development and these biases are being currently investigated and addressed. The campaign helped to characterise and identify the instrumental biases and possibly retrieval biases which are currently under investigation. Further improvements of the instrument are ongoing. The EM27/SUN, the IRcube, the modified Vertex70 and the HR125LR provided stable and precise measurements of the target gases during the campaign with quantified small biases. The bias dependence on the humidity along the measurement line-of-sight has been investigated and no dependence was found. These three portable low-resolution FTS instruments are suitable to be used for campaign deployment or long-term measurements from any site and offer the ability to complement the TCCON and expand the global coverage of ground-based reference measurements of the target gases.

scholarly journals An Integrated GIS and Remote Sensing Approach for Monitoring Harvested Areas from Very High-Resolution, Low-Cost Satellite Images

2019 ◽  
Vol 11 (21) ◽  
pp. 2539
Author(s):  
Azadeh Abdollahnejad ◽  
Dimitrios Panagiotidis ◽  
Lukáš Bílek
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Satellite Images ◽  
Sustainable Forest Management ◽  
Low Cost ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Monitoring Method ◽  
Gis And Remote Sensing ◽  
Very High

Advanced monitoring and mapping of forest areas using the latest technological advances in satellite imagery is an alternative solution for sustainable forest management compared to conventional ground measurements. Remote sensing products have been a key source of information and cost-effective options for monitoring changes in harvested areas. Despite recent advances in satellite technology with a broad variety of spectral and temporal resolutions, monitoring the areal extent of harvested forest areas in managed forests is still a challenge, primarily due to the highly dynamic spatiotemporal patterns of logging activities. Our goal was to introduce a plot-based method for monitoring harvested forest areas from very high-resolution (VHR), low-cost satellite images. Our method encompassed two data categories, which included vegetation indices (VIs) and texture analysis (TA). Each group of data was used to model the amount of harvested volume both independently and in combination. Our results indicated that the composition of all spectral bands can improve the accuracy of all models of average volume by 23.52 RMSE reduction and total volume by 33.57 RMSE reduction. This method demonstrated that monitoring and extrapolation of the calculated relation and results from smaller forested areas could be applied as an automatic remote-based supervised monitoring method over larger forest areas.

scholarly journals Mosaicking Opportunistically Acquired Very High-Resolution Helicopter-Borne Images over Drifting Sea Ice Using COTS Sensors

Sensors ◽  
2019 ◽  
Vol 19 (5) ◽  
pp. 1251
Author(s):  
Chang-Uk Hyun ◽  
Joo-Hong Kim ◽  
Hyangsun Han ◽  
Hyun-cheol Kim
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Sea Ice ◽  
Low Cost ◽  
Three Dimensional ◽  
Ground Truth ◽  
Synthetic Aperture Radar Image ◽  
Arctic Sea Ice ◽  
Sea Ice Concentration ◽  
Very High

Observing sea ice by very high-resolution (VHR) images not only improves the quality of lower-resolution remote sensing products (e.g., sea ice concentration, distribution of melt ponds and pressure ridges, sea ice surface roughness, etc.) by providing details on the ground truth of sea ice, but also assists sea ice fieldwork. In this study, two fieldwork-based methods are proposed, one for the practical acquisition of VHR images over drifting Arctic sea ice using low-cost commercial off-the-shelf (COTS) sensors equipped on a helicopter, and the other for quantifying the compensating effect from continuously drifting sea ice that reduces geolocation uncertainty in the image mosaicking procedure. The drifting trajectory of the target ice was yielded from that recorded by an icebreaker that was tightly anchored to the floe and was then used to reversely compensate the locations of acquired VHR images. After applying the compensation, three-dimensional geolocation errors of the VHR images were decreased by 79.3% and 24.2% for two pre-defined image groups, respectively. The enhanced accuracy of the imaging locations was affected by imaging duration causing variable drifting distances of individual images. Further applicability of the mosaicked VHR image was discussed by comparing it with a TerraSAR-X synthetic aperture radar image containing the target ice, suggesting that the proposed methods can be used for precise comparison with satellite remote sensing products.

scholarly journals Intercomparison of low- and high-resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO<sub>2</sub>, CH<sub>4</sub>, and CO

2020 ◽  
Vol 13 (9) ◽  
pp. 4791-4839
Author(s):  
Mahesh Kumar Sha ◽  
Martine De Mazière ◽  
Justus Notholt ◽  
Thomas Blumenstock ◽  
Huilin Chen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Southern Hemisphere ◽  
Reference Data ◽  
Low Cost ◽  
Data Set ◽  
Solar Absorption ◽  
Global Coverage ◽  
Reference Measurements ◽  
Absorption Measurements

Abstract. The Total Carbon Column Observing Network (TCCON) is the baseline ground-based network of instruments that record solar absorption spectra from which accurate and precise column-averaged dry-air mole fractions of CO2 (XCO2), CH4 (XCH4), CO (XCO), and other gases are retrieved. The TCCON data have been widely used for carbon cycle science and validation of satellites measuring greenhouse gas concentrations globally. The number of stations in the network (currently about 25) is limited and has a very uneven geographical coverage: the stations in the Northern Hemisphere are distributed mostly in North America, Europe, and Japan, and only 20 % of the stations are located in the Southern Hemisphere, leaving gaps in the global coverage. A denser distribution of ground-based solar absorption measurements is needed to improve the representativeness of the measurement data for various atmospheric conditions (humid, dry, polluted, presence of aerosol), various surface conditions such as high albedo (>0.4) and very low albedo, and a larger latitudinal distribution. More stations in the Southern Hemisphere are also needed, but a further expansion of the network is limited by its costs and logistical requirements. For this reason, several groups are investigating supplemental portable low-cost instruments. The European Space Agency (ESA) funded campaign Fiducial Reference Measurements for Ground-Based Infrared Greenhouse Gas Observations (FRM4GHG) at the Sodankylä TCCON site in northern Finland aims to characterise the assessment of several low-cost portable instruments for precise solar absorption measurements of XCO2, XCH4, and XCO. The test instruments under investigation are three Fourier transform spectrometers (FTSs): a Bruker EM27/SUN, a Bruker IRcube, and a Bruker Vertex70, as well as a laser heterodyne spectroradiometer (LHR) developed by the UK Rutherford Appleton Laboratory. All four remote sensing instruments performed measurements simultaneously next to the reference TCCON instrument, a Bruker IFS 125HR, for a full year in 2017. The TCCON FTS was operated in its normal high-resolution mode (TCCON data set) and in a special low-resolution mode (HR125LR data set), similar to the portable spectrometers. The remote sensing measurements are complemented by regular AirCore launches performed from the same site. They provide in situ vertical profiles of the target gas concentrations as auxiliary reference data for the column retrievals, which are traceable to the WMO SI standards. The reference measurements performed with the Bruker IFS 125HR were found to be affected by non-linearity of the indium gallium arsenide (InGaAs) detector. Therefore, a non-linearity correction of the 125HR data was performed for the whole campaign period and compared with the test instruments and AirCore. The non-linearity-corrected data (TCCONmod data set) show a better match with the test instruments and AirCore data compared to the non-corrected reference data. The time series, the bias relative to the reference instrument and its scatter, and the seasonal and the day-to-day variations of the target gases are shown and discussed. The comparisons with the HR125LR data set gave a useful analysis of the resolution-dependent effects on the target gas retrieval. The solar zenith angle dependence of the retrievals is shown and discussed. The intercomparison results show that the LHR data have a large scatter and biases with a strong diurnal variation relative to the TCCON and other FTS instruments. The LHR is a new instrument under development, and these biases are currently being investigated and addressed. The campaign helped to characterise and identify instrumental biases and possibly retrieval biases, which are currently under investigation. Further improvements of the instrument are ongoing. The EM27/SUN, the IRcube, the modified Vertex70, and the HR125LR provided stable and precise measurements of the target gases during the campaign with quantified small biases. The bias dependence on the humidity along the measurement line of sight has been investigated and no dependence was found. These three portable low-resolution FTS instruments are suitable to be used for campaign deployment or long-term measurements from any site and offer the ability to complement the TCCON and expand the global coverage of ground-based reference measurements of the target gases.

scholarly journals Using UAV imagery to perform fine-scale mapping of wetland vegetation

2021 ◽  
Author(s):  
◽  
Patrick Hipgrave
Keyword(s):  
Remote Sensing ◽  
Image Analysis ◽  
High Resolution ◽  
Low Cost ◽  
Digital Camera ◽  
Aerial Photographs ◽  
Fine Scale ◽  
Ancillary Data ◽  
Strong Argument ◽  
Object Based

<p>Differentiating between species of plants in aerial imagery is often challenging and, in some cases, can be impossible without significant field data collection. However, remote sensing technology is developing to the point where it is increasingly possible to eliminate the need for extensive fieldwork entirely and conduct non-disruptive monitoring of fragile environments. The increasing availability of UAV platforms with integrated high-resolution cameras and low-cost image processing software is also making remote sensing operations accessible to those outside the scientific community with an interest in environmental monitoring. This project trialled an emerging set of image analysis techniques called ‘object-based image analysis’ to create fine scale maps of a recovering wetland area, based on aerial photographs collected using a consumer-grade UAV (unmanned aerial vehicle). The effects of including additional ancillary data (such as digital surface models (DSMs) and multispectral imagery) in the classification process were also assessed to compare the ability of a standard digital camera to produce high-accuracy classifications to that of a more specialised multispectral sensor. The inclusion of this extra information was found to significantly improve classification accuracy in almost all cases, making a strong argument for the inclusion of ancillary data whenever possible, especially when considering the ease with which ancillary datasets can be produced. The high-resolution (between 2 and 4cm/pixel) imagery provided sufficient detail to observe 28 distinct land cover classes in total, with around 20 classes per image. While the number of classes in the classification scheme may have imposed limits on the overall accuracy of the classified maps, several classes were classified with a high (70% or greater) level of accuracy, including two invasive species, showing that the object-based school of image classification has potential to be a powerful tool for detecting and tracking individual vegetation types.</p>

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