scholarly journals Applying remote sensing techniques to monitor green areas in Tashkent Uzbekistan

2021 ◽  
Vol 258 ◽  
pp. 04012
Author(s):  
Ilhomjon Aslanov ◽  
Uzbekkhon Mukhtorov ◽  
Rahimjon Mahsudov ◽  
Umida Makhmudova ◽  
Saida Alimova ◽  
...  
Keyword(s):  
Accuracy Assessment ◽  
Ground Truth ◽  
Population Increase ◽  
Visual Interpretation ◽  
Ground Truth Data ◽  
Capital Cities ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Remote Sensing Techniques

Land use and land cover (LULC) change are one of the most important signals of regional environmental monitoring and study. Recently, the pull of capital cities has snowballed, an increasing number of people moving to the cities, especially in developing countries. Consequently, as more people arrive at cities, the more pressure will be on land. Land price getting high and constructions try using open green areas. A wide variety of green areas of different sizes will be solve many urban diseases and ecological problems at the same time improve the quality and life of urban residents, as urban green area provides various ecosystem services. The green area includes parks, woodlands, nature reserves and bare lands. With the population increase and expansion of cities, an increasing amount of open area, woodland and bare land has been converted into construction land, buildings due to the increasing demands and residential land. For the accuracy assessment, we applied an automatically supervised classification using the software QGIS 3.18. The reference values were based on ground truth data and visual interpretation.

scholarly journals LAND COVER CHANGE DETECTION ANALYSIS ON URBAN GREEN AREA LOSS USING GIS AND REMOTE SENSING TECHNIQUES

2013 ◽  
Vol 11 ◽  
Author(s):  
Noorzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mohd Nasrul Hanis Manzahani
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Kuala Lumpur ◽  
Gis And Remote Sensing ◽  
Detection Analysis ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Erdas Imagine ◽  
Remote Sensing Techniques

The loss of green area has been rising all over the world particularly in big cities. For a number of decades, urban sprawl and developments have changed the natural landscapes of urban areas where areas with green areas have been converted into built up developments and other land uses. Thus this research intends to study the changes of green areas in Kuala Lumpur based on land use detection analysis approach where 3 series of remote sensing images namely SPOT2, SPOT4 and IKONOS for year 1990, 2001 and 2010 have been used to acquire the data on the green area changes aided by ERDAS IMAGINE 2011 and ARGIS 9.2. The finding of the study shows that there is a decrease in the size of green area in Kuala Lumpur from year 1990-2010 due to pressure of urban developments. Two significant factors which contribute to the changes of green area in Kuala Lumpur have been identified in the study, which are the increase in built up areas and sprawl development pattern.

LAND COVER CHANGE DETECTION ANALYSIS ON URBAN GREEN AREA LOSS USING GIS AND REMOTE SENSING TECHNIQUES

2013 ◽  
Vol 11 (3) ◽  
Author(s):  
Norzailawati Mohd Noor ◽  
Alias Abdullah ◽  
Mohd Nasrul Hanis Manzahani
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Kuala Lumpur ◽  
Gis And Remote Sensing ◽  
Detection Analysis ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Erdas Imagine ◽  
Remote Sensing Techniques

The loss of green area has been rising all over the world particularly in big cities. For a number of decades, urban sprawl and developments have changed the natural landscapes of urban areas where areas with green areas have been converted into built up developments and other land uses. Thus this research intends to study the changes of green areas in Kuala Lumpur based on land use detection analysis approach where 3 series of remote sensing images namely SPOT2, SPOT4 and IKONOS for year 1990, 2001 and 2010 have been used to acquire the data on the green area changes aided by ERDAS IMAGINE 2011 and ARGIS 9.2. The finding of the study shows that there is a decrease in the size of green area in Kuala Lumpur from year 1990-2010 due to pressure of urban developments. Two significant factors which contribute to the changes of green area in Kuala Lumpur have been identified in the study, which are the increase in built up areas and sprawl development pattern.

scholarly journals Multi-Temporal Vineyard Monitoring through UAV-Based RGB Imagery

2018 ◽  
Vol 10 (12) ◽  
pp. 1907 ◽  
Author(s):  
Luís Pádua ◽  
Pedro Marques ◽  
Jonáš Hruška ◽  
Telmo Adão ◽  
Emanuel Peres ◽  
...  
Keyword(s):  
Accuracy Assessment ◽  
Low Cost ◽  
Ground Truth ◽  
Volume Estimation ◽  
Height Range ◽  
Ground Truth Data ◽  
Operational Technique ◽  
Digital Elevation ◽  
Multi Temporal ◽  
Aerial Vehicle

This study aimed to characterize vineyard vegetation thorough multi-temporal monitoring using a commercial low-cost rotary-wing unmanned aerial vehicle (UAV) equipped with a consumer-grade red/green/blue (RGB) sensor. Ground-truth data and UAV-based imagery were acquired on nine distinct dates, covering the most significant vegetative growing cycle until harvesting season, over two selected vineyard plots. The acquired UAV-based imagery underwent photogrammetric processing resulting, per flight, in an orthophoto mosaic, used for vegetation estimation. Digital elevation models were used to compute crop surface models. By filtering vegetation within a given height-range, it was possible to separate grapevine vegetation from other vegetation present in a specific vineyard plot, enabling the estimation of grapevine area and volume. The results showed high accuracy in grapevine detection (94.40%) and low error in grapevine volume estimation (root mean square error of 0.13 m and correlation coefficient of 0.78 for height estimation). The accuracy assessment showed that the proposed method based on UAV-based RGB imagery is effective and has potential to become an operational technique. The proposed method also allows the estimation of grapevine areas that can potentially benefit from canopy management operations.

scholarly journals A study on landuse and landcover classification using microwave data in Joida taluk of Uttara Kannada district, Karnataka

2020 ◽  
Vol 12 (1) ◽  
pp. 9-12
Author(s):  
Arjun G. Koppad ◽  
Syeda Sarfin ◽  
Anup Kumar Das
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Accuracy Assessment ◽  
Ground Truth ◽  
Land Cover Classification ◽  
Data Sets ◽  
Radiometric Calibration ◽  
Ground Truth Data ◽  
Dense Forest ◽  
Sar Data

The study has been conducted for land use and land cover classification by using SAR data. The study included examining of ALOS 2 PALSAR L- band quad pol (HH, HV, VH and VV) SAR data for LULC classification. The SAR data was pre-processed first which included multilook, radiometric calibration, geometric correction, speckle filtering, SAR Polarimetry and decomposition. For land use land cover classification of ALOS-2-PALSAR data sets, the supervised Random forest classifier was used. Training samples were selected with the help of ground truth data. The area was classified under 7 different classes such as dense forest, moderate dense forest, scrub/sparse forest, plantation, agriculture, water body, and settlements. Among them the highest area was covered by dense forest (108647ha) followed by horticulture plantation (57822 ha) and scrub/Sparse forest (49238 ha) and lowest area was covered by moderate dense forest (11589 ha).   Accuracy assessment was performed after classification. The overall accuracy of SAR data was 80.36% and Kappa Coefficient was 0.76.  Based on SAR backscatter reflectance such as single, double, and volumetric scattering mechanism different land use classes were identified.

Field Spectroscopy Measurements over Asprokremmos Dam in Cyprus Intended for Water Quality Monitoring

2012 ◽  
Vol 500 ◽  
pp. 813-819 ◽  
Author(s):  
Christiana Papoutsa ◽  
Diofantos G. Hadjimitsis
Keyword(s):  
Water Quality ◽  
Ground Truth ◽  
Water Quality Monitoring ◽  
Quality Parameters ◽  
Ground Truth Data ◽  
Suspended Particulate ◽  
Fibre Optic Probe ◽  
High Concentrations ◽  
Optic Probe ◽  
Remote Sensing Techniques

High concentrations of suspended particulate matter in reservoir waters directly affect the water treatment plants by occurring damages to the filters during the pretreatment. The objective of this project is to define the support that can be derived from the use of remote sensing techniques in order to determine the spatial variations of Total Suspended Solids (TSS) in Asprokremmos Dam in Paphos District in Cyprus. Such techniques have been successfully applied to the retrieval of TSS concentration and other water quality parameters in various geographical locations and environmental settings. This paper describes the results obtained by an existing running campaign in which in-situ spectroradiometric measurements and water sampling measurements of turbidity have been acquired at the study area. A GER-1500 field sperctro-radiometer equipped with a fibre optic probe is used to retrieve the spectral signatures of the Asprokremmos Dam and a portable turbidity meter is used for the determination of turbidity values. Ground-truth data based on the spectro-radiometric measurements were simulated to comply with the Landsat TM/ETM+ visible and infrared bands, so that identification of the ‘best-suited’ spectral region in which turbidity can be retrieved, was performed.

scholarly journals Sentinel 1A SAR Backscattering Signature of Maize and Cotton Crops

2017 ◽  
Vol 104 (.1-.4) ◽  
Author(s):  
Kumaraperumal R ◽  
◽  
Shama M ◽  
Balaji Kannan ◽  
Ragunath K P ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Ground Truth ◽  
Backscattering Coefficient ◽  
Ground Truth Data ◽  
Crop Monitoring ◽  
Multi Temporal ◽  
The Mean ◽  
Sar Data ◽  
Remote Sensing Techniques ◽  
Crop Discrimination

Crop discrimination is a key issue for agricultural monitoring using remote sensing techniques. Synthetic Aperture Radar (SAR) data are advantageous for crop monitoring and classification because of their all-weather imaging capabilities. The multi-temporal Sentinel 1A SAR data was acquired from 08th August, 2015 to 23rd January, 2016 at 12 days interval covering the extent of Perambalur district of Tamil Nadu. Both the Vertical - Vertical (VV) and Vertical-Horizontal (VH) polarized data are compared. The ground truth data collection was performed for cotton and maize during the vegetative, flowering and harvesting stages. The temporal backscattering coefficient (σ0 ) for cotton and maize are extracted using the training datasets. The mean backscattering values for cotton during the entire cropping period ranges from -10.58 dB to -6.28 dB and -20.59 dB to -14.53 dB for VV and VH polarized data respectively, and for maize it ranges from -11.08 dB to -7.07 dB and -19.85 dB to -14.14 dB for VV and VH polarized data respectively.

scholarly journals Monitoring and assessment of forest cover disturbance in the Middle Volga region of Russia using Landsat images

2021 ◽  
Vol 932 (1) ◽  
pp. 012007
Author(s):  
O N Vorobev ◽  
E A Kurbanov ◽  
S A Lezhnin ◽  
D M Dergunov ◽  
L V Tarasova
Keyword(s):  
Forest Cover ◽  
Forest Disturbance ◽  
Accuracy Assessment ◽  
Ground Truth ◽  
Volga Region ◽  
Landsat Images ◽  
Middle Volga Region ◽  
Ground Truth Data ◽  
Hybrid Strategy ◽  
Middle Volga

Abstract The knowledge of the disturbance effect on the forest ecosystems is crucial for sustainable development on the global level. It is important to quantify, map and monitor forest cover resulting from natural and anthropogenic disturbances. This research presents spatio-temporal trend analyses of forest cover disturbance in the Middle Volga region of Russia, using a time series of Landsat images. We generated a series of image composites at different year intervals between 1985 and 2018 and utilized a hybrid strategy consisting of Tasseled Cap transformation, sampling ground truth data and post-classification analyses. For validation of the disturbance maps, we used a point-based accuracy assessment, using local forest inventory reports and ground truth sample plots data for 2016-2018. The produced Landsat 1985, 2001 и 2018 thematic maps for 7 classes of forest cover show that coniferous area decreased by 4%. At the same time, there is a decrease in small-leaved (19%), mixed (8%) and an increase in young stands (23%). A significant disturbed forest area 85,120 ha was observed between 2014-2018, where much of the loss occurs due to severe wildfires. More research is needed with the inclusion of the additional number of anthropogenic and natural factors to increase the accuracy of monitoring and detection of forest disturbance of the region.

scholarly journals Mapping the Extent of Invasive Phragmites australis subsp. australis From Airborne Hyperspectral Imagery

2021 ◽  
Vol 9 ◽  
Author(s):  
Kathryn Elmer ◽  
Margaret Kalacska ◽  
J. Pablo Arroyo-Mora
Keyword(s):  
Remote Sensing ◽  
Invasive Species ◽  
Early Detection ◽  
Target Detection ◽  
Phragmites Australis ◽  
Hyperspectral Imagery ◽  
Ground Truth ◽  
Detection Algorithm ◽  
Visual Interpretation ◽  
Ground Truth Data

Invasive species pose one of the greatest threats to global biodiversity. Early detection of invasive species is critical in order to prevent or manage their spread before they exceed the ability of land management groups to control them. Optical remote sensing has been established as a useful technology for the early detection and mapping of invasive vegetation populations. Through the use of airborne hyperspectral imagery (HSI), this study establishes a target detection methodology used to identify and map the invasive reed Phragmites australis subsp. australis within the entire extent of Îles-de-Boucherville National Park (Quebec, ON, Canada). We applied the Spectral Angle Mapper (SAM) target detection algorithm trained with a high accuracy GNSS ground truth data set to produce a park-wide map illustrating the extent of detected Phragmites. The total coverage of detected Phragmites was 26.74 ha (0.267 km2), which represents 3.28% of the total park area of 814 ha (8.14 km2). The inherent spatial uncertainty of the airborne HSI (∼2.25 m) was accounted for with uncertainty buffers, which, when included in the measurement of detected Phragmites, lead to a total area of 59.17 ha (0.591 km2), or 7.26% of the park. The overall accuracy of the Phragmites map was 84.28%, with a sensitivity of 76.32% and a specificity of 91.57%. Additionally, visual interpretation of the validation ground truth dataset was performed by 10 individuals, in order to compare their performance to that of the target detection algorithm. The overall accuracy of the visual interpretation was lower than the target detection (i.e., 69.18%, with a sensitivity of 59.21% and a specificity of 78.31%). Overall, this study is one of the first to utilize airborne HSI and target detection to map the extent of Phragmites over a moderately large extent. The uses and limitations of such an approach are established, and the methodology described here in detail could be adapted for future remote sensing studies of Phragmites or other vegetation species, native or invasive, at study sites around the world.

scholarly journals ICMS Ecológico

2021 ◽  
Vol 17 (2) ◽  
Author(s):  
Matheus Maramaldo Andrade Silva ◽  
Maria do Carmo Lima Bezerra
Keyword(s):  
Quality Of Life ◽  
Financial Incentives ◽  
Conservation Units ◽  
Urban Green ◽  
Current Period ◽  
Green Area ◽  
Urban Green Area ◽  
Green Areas ◽  
Regulatory Instruments

The Urban Green Areas System (UGAS) performs relevant functions for the quality of life by making cities healthier, which has become even more necessary in the current period of pandemic. However, even with these benefits, the practice of urban management indicates difficulties not only in the implementation, but also in the maintenance of the UGAS. One of the aspects that may explain the challenge of implementing and maintaining green areas in cities is the absence of regulatory instruments and financial incentives that support this system. In this line, in order to contribute to this discussion, one of the instruments that proved to be effective in environmental management will be studied, in this case for the creation and implementation of Conservation Units: the “ICMS Ecológico”. This article will study the characteristics of the UGAS associated with ecological and urban functions; the logic of adopting the “ICMS Ecológico” and will seek to define criteria that can be used for the implementation of a UGAS that prioritizes ecosystem thinking associated with the function of urban health. We started with the discussion about the mechanisms for adopting the “ICMS Ecológico” and followed the analysis of the standards established in the states for its application. As a result, it was found that there are similarities that can be applied to an implementation in the urban green area systems, which allowed the recommendation of criteria that can be used as a reference for the application of the “ICMS Ecológico” to support the UGAS and the promotion of healthier cities.

scholarly journals Importance of Urban Green at Reduction of Particulate Matters in Sihwa Industrial Complex, Korea

2020 ◽  
Vol 12 (18) ◽  
pp. 7647 ◽  
Author(s):  
Sin-Yee Yoo ◽  
Taehee Kim ◽  
Suhan Ham ◽  
Sumin Choi ◽  
Chan-Ryul Park
Keyword(s):  
Particulate Matter ◽  
Reduction Rate ◽  
Residential Area ◽  
Industrial Complex ◽  
Urban Green ◽  
Area Reduction ◽  
Green Area ◽  
Urban Green Areas ◽  
Urban Green Area ◽  
Green Areas

The utilization of urban green areas has increased, but it is unclear whether urban green areas can decrease the concentration of particulate matter at an industrial complex city in Korea. We measured the extent of particulate matter (PM) reduction at a buffer green area in the Sihwa Industrial Complex. PM was measured at the industrial complex, the urban green area, and a nearby residential area from April to October 2019. PM reduction rates were highest at the urban green area in August and October, which is related to increased atmospheric mixing height and the active west wind blowing from the industrial complex to the residential area. Reduction rates of PM10 and PM2.5 at the urban green area showed the lowest values, namely 14.4% and 25.3%, respectively. The air temperature, wind speed, and humidity could affect the PM reduction rate by influencing the movement and dispersion of PM at the micro-spatiotemporal scale. These results indicated that PM concentration could be reduced by the structural change of a forest layer at a micro scale in urban green areas.

Sign in / Sign up

Export Citation Format

Share Document