scholarly journals Quantification of green areas

2021 ◽  
Vol 9 (74) ◽  
Author(s):  
Ramon Octaviano de Castro Matoso ◽  
Lucas do Vale Souza ◽  
Cézar Henrique Barra Rocha
Keyword(s):  
Aerial Images ◽  
Likelihood Method ◽  
Landsat 8 ◽  
High Definition ◽  
Large Area ◽  
Aerial Photos ◽  
Small Areas ◽  
Accuracy And Precision ◽  
Green Areas ◽  
Remote Sensing Techniques

The monitoring of green areas has been researched and analyzed by several surveys, however it is not trivial to find data with reliable accuracy and precision. There are well-defined and widely used methodologies for the classification of large area images, but in the case of small areas some authors recommend the analog analysis of aerial photos for classification. However, the acquisition of high definition aerial images is not inexpensive. In addition to being a fully manual and labor intensive classification. The present work proposes a methodology for the collection of a quantitative historical database using remote sensing techniques and Digital images, using the NDVI as a comparison criterion. In this work, free images of the Landsat-5, Landsat-8 and Sentinel-2 satellites were used to verify if it is possible to extract reliable information from areas considered small to use the classification supervised by the maximum likelihood method using the ENVI 5.1 software.

scholarly journals IMG2nDSM: Height Estimation from Single Airborne RGB Images with Deep Learning

2021 ◽  
Vol 13 (12) ◽  
pp. 2417
Author(s):  
Savvas Karatsiolis ◽  
Andreas Kamilaris ◽  
Ian Cole
Keyword(s):  
Deep Learning ◽  
State Of The Art ◽  
Aerial Imagery ◽  
Aerial Images ◽  
Surface Model ◽  
Large Area ◽  
Digital Terrain ◽  
Terrain Models ◽  
Architectural Features ◽  
Rgb Images

Estimating the height of buildings and vegetation in single aerial images is a challenging problem. A task-focused Deep Learning (DL) model that combines architectural features from successful DL models (U-NET and Residual Networks) and learns the mapping from a single aerial imagery to a normalized Digital Surface Model (nDSM) was proposed. The model was trained on aerial images whose corresponding DSM and Digital Terrain Models (DTM) were available and was then used to infer the nDSM of images with no elevation information. The model was evaluated with a dataset covering a large area of Manchester, UK, as well as the 2018 IEEE GRSS Data Fusion Contest LiDAR dataset. The results suggest that the proposed DL architecture is suitable for the task and surpasses other state-of-the-art DL approaches by a large margin.

scholarly journals Evaluation of the Consistency of Simultaneously Acquired Sentinel-2 and Landsat 8 Imagery on Plastic Covered Greenhouses

2020 ◽  
Vol 12 (12) ◽  
pp. 2015 ◽  
Author(s):  
Manuel Ángel Aguilar ◽  
Rafael Jiménez-Lao ◽  
Abderrahim Nemmaoui ◽  
Fernando José Aguilar ◽  
Dilek Koc-San ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
Surface Reflectance ◽  
Remote Sensing Techniques ◽  
Image Pairs ◽  
Study Sites ◽  
High Level ◽  
Sentinel 2

Remote sensing techniques based on medium resolution satellite imagery are being widely applied for mapping plastic covered greenhouses (PCG). This article aims at testing the spectral consistency of surface reflectance values of Sentinel-2 MSI (S2 L2A) and Landsat 8 OLI (L8 L2 and the pansharpened and atmospherically corrected product from L1T product; L8 PANSH) data in PCG areas located in Spain, Morocco, Italy and Turkey. The six corresponding bands of S2 and L8, together with the normalized difference vegetation index (NDVI), were generated through an OBIA approach for each PCG study site. The coefficient of determination (r2) and the root mean square error (RMSE) were computed in sixteen cloud-free simultaneously acquired image pairs from the four study sites to evaluate the coherence between the two sensors. It was found that the S2 and L8 correlation (r2 > 0.840, RMSE < 9.917%) was quite good in most bands and NDVI. However, the correlation of the two sensors fluctuated between study sites, showing occasional sun glint effects on PCG roofs related to the sensor orbit and sun position. Moreover, higher surface reflectance discrepancies between L8 L2 and L8 PANSH data, mainly in the visible bands, were always observed in areas with high-level aerosol values derived from the aerosol quality band included in the L8 L2 product (SR aerosol). In this way, the consistency between L8 PANSH and S2 L2A was improved mainly in high-level aerosol areas according to the SR aerosol band.

scholarly journals Rapid large-area mapping of ice flow using Landsat 8

2016 ◽  
Vol 185 ◽  
pp. 84-94 ◽  
Author(s):  
Mark Fahnestock ◽  
Ted Scambos ◽  
Twila Moon ◽  
Alex Gardner ◽  
Terry Haran ◽  
...  
Keyword(s):  
Landsat 8 ◽  
Large Area ◽  
Ice Flow

scholarly journals Application of UAV-SfM photogrammetry and aerial lidar to a disastrous flood: repeated topographic measurement of a newly formed crevasse splay of the Kinu River, central Japan

2017 ◽  
Vol 17 (9) ◽  
pp. 1505-1519 ◽  
Author(s):  
Atsuto Izumida ◽  
Shoichiro Uchiyama ◽  
Toshihiko Sugai
Keyword(s):  
Lidar Data ◽  
High Definition ◽  
Central Japan ◽  
Aerial Photos ◽  
Data Resolution ◽  
Disastrous Flood ◽  
Surface Models ◽  
Elevation Changes ◽  
Aerial Vehicle ◽  
Crevasse Splay

Abstract. Geomorphic impacts of a disastrous crevasse splay that formed in September 2015 and its post-formation modifications were quantitatively documented by using repeated, high-definition digital surface models (DSMs) of an inhabited and cultivated floodplain of the Kinu River, central Japan. The DSMs were based on pre-flood (resolution: 2 m) and post-flood (resolution: 1 m) aerial light detection and ranging (lidar) data from January 2007 and September 2015, respectively, and on structure-from-motion (SfM) photogrammetry data (resolution: 3.84 cm) derived from aerial photos taken by an unmanned aerial vehicle (UAV) in December 2015. After elimination of systematic errors among the DSMs and down-sampling of the SfM-derived DSM, elevation changes on the order of 10−1 m – including not only topography but also growth of vegetation, vanishing of flood waters, and restoration and repair works – were detected. Comparison of the DSMs showed that the volume eroded by the flood was more than twice the deposited volume in the area within 300–500 m of the breached artificial levee, where the topography was significantly affected. The results suggest that DSMs based on a combination of UAV-SfM and lidar data can be used to quantify, rapidly and in rich detail, topographic changes on floodplains caused by floods.

scholarly journals Water stress coefficient determined by orbital remote sensing techniques

2020 ◽  
Vol 24 (12) ◽  
pp. 847-853
Author(s):  
Élvis da S. Alves ◽  
Roberto Filgueiras ◽  
Lineu N. Rodrigues ◽  
Fernando F. da Cunha ◽  
Catariny C. Aleman
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Irrigation Management ◽  
Simple Algorithm ◽  
Landsat 8 ◽  
Stress Coefficient ◽  
Use Efficiency ◽  
Remote Sensing Techniques ◽  
Water Stress Coefficient ◽  
The Relationship

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

scholarly journals Consideration of land use in the evaluation of erosive processes in gully erosion

2020 ◽  
Vol 24 ◽  
pp. e25
Author(s):  
Tamara Vieira Pascoto ◽  
Simone Andrea Furegatti ◽  
Anna Silvia Palcheco Peixoto
Keyword(s):  
Land Use ◽  
Visual Analysis ◽  
Aerial Images ◽  
Aerial Photos ◽  
City Hall ◽  
Erosion Processes ◽  
Main Factors ◽  
The City ◽  
Erosive Feature

There are several factors that directly or indirectly influence erosion processes. In order to properly understand the behavior of these processes, some factors need to be analyzed together. Determining them wrongly can compromise the study resulting in wrong actions. For this reason, methodologies are always sought to measure them quantitatively and qualitatively in the most accurate possible way. Land use is one of the main factors liable to inaccuracies in its determination. To use this parameter in mapping erosive processes, researchers need to delimit it, classify it, and measure it. In order to better understand the complexity of considering this parameter, the present study analyzed an erosive feature that, although stabilized, has a component in constant development. Initially, a visual analysis indicated the same classification of land use for both conditions, despite having different behaviors, leading to the need for a detailed analysis. Such analysis comprised a historical survey through aerial photos and interviews with residents and employees of the city hall about the evolution of the feature from 2008 to 2019. It also included the analysis of other influencing factors that could be responsible for this difference in behavior in the area. Two different traces of the contribution areas of the gully and branch were also considered. One considering only aerial images, and the other considering the knowledge acquired during the research about the evolution of the feature. It was concluded, then, that an analysis of the use-only occupation factor based on aerial images can accentuate the inaccuracy of the measurement of this factor.

Integration of Satellite Remote Sensing Techniques and Landscape Metrics to Characterize Land Cover Change and Dynamics

2013 ◽  
pp. 228-244
Author(s):  
Carmelo Riccardo Fichera ◽  
Giuseppe Modica ◽  
Maurizio Pollino
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Landscape Metrics ◽  
Landsat Images ◽  
Aerial Photos ◽  
Multi Temporal ◽  
Urban Rural ◽  
Remote Sensing Techniques

One of the most relevant applications of Remote Sensing (RS) techniques is related to the analysis and the characterization of Land Cover (LC) and its change, very useful to efficiently undertake land planning and management policies. Here, a case study is described, conducted in the area of Avellino (Southern Italy) by means of RS in combination with GIS and landscape metrics. A multi-temporal dataset of RS imagery has been used: aerial photos (1954, 1974, 1990), Landsat images (MSS 1975, TM 1985 and 1993, ETM+ 2004), and digital orthophotos (1994 and 2006). To characterize the dynamics of changes during a fifty year period (1954-2004), the approach has integrated temporal trend analysis and landscape metrics, focusing on the urban-rural gradient. Aerial photos and satellite images have been classified to obtain maps of LC changes, for fixed intervals: 1954-1985 and 1985-2004. LC pattern and its change are linked to both natural and social processes, whose driving role has been clearly demonstrated in the case analysed. In fact, after the disastrous Irpinia earthquake (1980), the local specific zoning laws and urban plans have significantly addressed landscape changes.

Remote Sensing Techniques and Its Application in Arid Zones of India

2017 ◽  
pp. 193-211
Author(s):  
Lokesh Kumar Jain
Keyword(s):  
Remote Sensing ◽  
Water Status ◽  
Leaf Age ◽  
Nutrient Status ◽  
Arid Zones ◽  
Large Area ◽  
Leaf Reflectance ◽  
Agronomic Management ◽  
Crop Type ◽  
Remote Sensing Techniques

Remote sensing technologies offer the potential for contributing the security to human existence on arid zones in the country in variety of ways. Remote Sensing in agriculture particularly for natural resource management. It provides important coverage, mapping and classification of land cover features. The remote view of the sensor and the ability to store, analyze, and display the sensed data on field maps are make remote sensing a potentially important tool for agriculture. The aerial photography gives two main advantages viz., speedy survey in very large area or remote area and precise description and recording of resources status. Remotely sensed images provide a means to assess field conditions and gave valuable insights into agronomic management. It led to understanding of leaf reflectance and leaf emittance changes in response to leaf thickness, species, canopy shape, leaf age, nutrient status, and water status. Understanding of leaf reflectance has led to quantify various agronomic parameters, e.g., leaf area, crop cover, biomass, crop type, nutrient status, and yield.

scholarly journals Combining Satellite Multispectral Imagery and Topographic Data for the Detection and Mapping of Fluvial Avulsion Processes in Lowland Areas

2020 ◽  
Vol 12 (14) ◽  
pp. 2243 ◽  
Author(s):  
Giulia Iacobucci ◽  
Francesco Troiani ◽  
Salvatore Milli ◽  
Paolo Mazzanti ◽  
Daniela Piacentini ◽  
...  
Keyword(s):  
Methodological Approach ◽  
Field Work ◽  
Network Evolution ◽  
Landsat 8 ◽  
Multispectral Imagery ◽  
Economic Activities ◽  
Topographic Analysis ◽  
Climate Conditions ◽  
Topographic Data ◽  
Remote Sensing Techniques

Fluvial avulsion is an important process in the dynamics of the riverscapes and plays a key role in the drainage network evolution in lowland areas, also influencing past and present social processes and economic activities. Crevasse splays represent significant geomorphological features for understanding the fluvial morphodynamics in lowland areas dominated by avulsion processes. Within wide floodplains characterized by very low elevation ranges, the detection and accurate mapping of crevasse splay morphology and features, such as crevasse channels, levees, and deposit, can be very challenging considering floodplain extension, anthropic impact on the natural channels network, logistic difficulties, and in some cases, climate conditions that prevent field work. This research aims at improving the detection and mapping of crevasse splays in lowland areas through the combination of different remote sensing techniques based on optical multispectral imagery and topographic data derived from satellite earth observation missions. The Lower Mesopotamia Plain (LMP) offers a unique opportunity to study the avulsion processes because it presents numerous examples of crevasse splays, characterized by different sizes and states of activity. Furthermore, in this area, a strong correlation exists between the formation and development of crevasse splays and the expansion of agriculture and early societies since the Early Holocene. Different supervised classification (SC) methods of Landsat 8 satellite images have been tested together with topographic analysis of the microrelief, carried out based on two different 1-arcsec DEMs (AW3D30 and GDEM2). The results of this study demonstrate that the combination of multispectral imagery analysis and topographic analysis of the microrelief is useful for discerning different crevasse elements, distinguishing between active and relict landforms. The methodological approach proved helpful for improving the mapping of erosional and depositional landforms generated by the avulsion process and, in the study area, provided the best results for the active landforms.

Urinary Tract Endometriosis

2009 ◽  
Vol 1 (2) ◽  
pp. 72-78 ◽  
Author(s):  
Peter Rehder ◽  
Bernhard Glodny ◽  
Renate Pichler ◽  
Andrea Kerschbaumer ◽  
Michael Mitterberger
Keyword(s):  
Urinary Tract ◽  
Ureteral Obstruction ◽  
Genetic Disorder ◽  
Large Area ◽  
Distal Ureter ◽  
Small Areas ◽  
Boari Flap ◽  
Bladder Endometriosis ◽  
Psoas Hitch ◽  
Symptoms And Signs

Endometriosis is a multifactorial polygenic genetic disorder that affects 10–20% of women. The urinary tract is affected in only 1–5% of cases and here most commonly the urinary bladder. Diagnosis of urinary tract endometriosis is made late due to its commonly asymptomatic course. The management of urinary tract endometriosis depends on the severity of the symptoms and signs, the extent of the disease, its location and the presence of renal damage because of ureteral obstruction. A conservative medical treatment is recommended for small areas of endometriosis in the bladder. For urinary tract endometriosis covering a large area, or where infiltration causes architectural damage, surgery is recommended. Partial cystectomy should be considered because of the transmural nature of bladder endometriosis. In cases of ureteral endometriosis, the surgical technique is determined by the location and extent of the lesion. For the distal ureter an ureterocystoneostomy using the Psoas hitch or Boari flap is recommended. For short, proximal ureteral involvement an end-to-end anastomosis or endoscopic incision may be used, and for extended areas, ileum interposition or kidney mobilization using nephropexy. A multidisciplinary approach is strongly recommended. Endometriosis with urological involvement more often needs surgical treatment, especially when ureteral obstruction leads to progressive kidney damage.

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