Land-Use Land-Cover Classification by Machine Learning Classifiers for Satellite Observations—A Review

Remote Sensing, Journal Year: 2020, Volume and Issue: 12(7), P. 1135 - 1135

Published: April 2, 2020

Rapid and uncontrolled population growth along with economic industrial development, especially in developing countries during the late twentieth early twenty-first centuries, have increased rate of land-use/land-cover (LULC) change many times. Since quantitative assessment changes LULC is one most efficient means to understand manage land transformation, there a need examine accuracy different algorithms for mapping order identify best classifier further applications earth observations. In this article, six machine-learning algorithms, namely random forest (RF), support vector machine (SVM), artificial neural network (ANN), fuzzy adaptive resonance theory-supervised predictive (Fuzzy ARTMAP), spectral angle mapper (SAM) Mahalanobis distance (MD) were examined. Accuracy was performed by using Kappa coefficient, receiver operational curve (RoC), index-based validation root mean square error (RMSE). Results coefficient show that all classifiers similar level minor variation, but RF algorithm has highest 0.89 MD (parametric classifier) least 0.82. addition, visual cross-validation (correlations between normalised differentiation water index, vegetation index built-up are 0.96, 0.99 1, respectively, at 0.05 significance) comparison other adopted. Findings from literature also proved ANN classifiers, although non-parametric like SAM (Kappa 0.84; area under (AUC) 0.85) better consistent than algorithms. Finally, review concludes classifier, among examined it necessary test morphoclimatic conditions future.

Language: Английский

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Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

International Journal of Applied Earth Observation and Geoinformation, Journal Year: 2018, Volume and Issue: 67, P. 30 - 42

Published: Jan. 3, 2018

Language: Английский

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Assessment of land use land cover changes and its impact on variations of land surface temperature in Asansol-Durgapur Development Region

The Egyptian Journal of Remote Sensing and Space Science, Journal Year: 2018, Volume and Issue: 22(2), P. 203 - 218

Published: Dec. 10, 2018

Fast transformation of land use/land cover because urban expansion profoundly influences biodiversity and ecosystem function, as well local regional climate. One the more serious impacts urbanization is formation heat island (UHI) effect. Asansol-Durgapur Development Region second largest identity in West Bengal just after Kolkata agglomeration. Rapid growth has brought about fast LULC pattern which turn significantly affect LST. use significant changes The study attempts to examine influence (LULC) on surface temperature by employing multi temporal satellite data. LST extracted three different phases seasonally (e.g. winter, summer post- monsoon periods) using LANDSAT 4–5 TM 8 OLI over period 1993, 2009 2015. Results depict that increases 0.06 °C/year winter 0.43 periods respectively difference radiant existing units. result revealed impervious surface, industrial area coal mining high (38 °C) water bodies vegetation experienced low (27 °C). also examined causality association between deriving factors such NDVI, NDBI NDWI. reveals maximally controls (r = 0.95) than 0.62) 0.61).

Language: Английский

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Modelling future land use land cover changes and their impacts on land surface temperatures in Rajshahi, Bangladesh

Remote Sensing Applications Society and Environment, Journal Year: 2020, Volume and Issue: 18, P. 100314 - 100314

Published: April 1, 2020

Language: Английский

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Dynamics of ecosystem services (ESs) in response to land use land cover (LU/LC) changes in the lower Gangetic plain of India

Ecological Indicators, Journal Year: 2020, Volume and Issue: 112, P. 106121 - 106121

Published: Feb. 1, 2020

The ecosystems provide a range of material as well non-material services that contribute to human well-being supply necessary resources for the organisms. land use/ cover (LU/LC) changes have been taken place due several natural and anthropogenic reasons, which significantly influence ecosystem services. Therefore, present study aimed explore minor variations provided by particular use types area. we divided area into nine grids. classifications performed using support vector machine techniques (SVM) 1999–2019. Based on multi-temporal maps, used global coefficient value 1997 2003 valuation different types. Then employed elasticity analyse response over service valuation. findings showed overall built-up has increased 29.14% since 1999, while water-body decreased 15.81%. correspondingly areas converted from others do not able any values become nil, is suitable good health ecosystem. can be foundation planners scientists prepare sustainable plans management local based minorly impact LULC

Language: Английский

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Assessment of land surface temperature variation due to change in elevation of area surrounding Jaipur, India

The Egyptian Journal of Remote Sensing and Space Science, Journal Year: 2017, Volume and Issue: 21(1), P. 87 - 94

Published: Jan. 24, 2017

Land surface temperature (LST) is a key parameter for energy balance and urban climatology studies. LST affected by the characteristics of land such as vegetation cover its type, use-land imperviousness. Incessant urbanization has resulted in many fold increase area it caused significant changes surface. The difference altitude two points, that are located at different parts vast study area, may be large. aim present to investigate effect change elevation over LST. data from Moderate Resolution Imaging Spectroradiometer (MODIS) digital model ASTER have been used. Consistent inverse linear trend observed between all seasons. High correlation (R2 = 0.73–0.87) found mean It seen due points separated space horizontal direction varies 3.5 °C 4.6 per 1000 m which relatively lesser than condition when vertical (5.0 °C–10.0 m) i.e. along column air. concludes any related with spatial distribution large locations shall also considered LSTs location rationalized on basis their comparative elevations.

Language: Английский

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Using GIS tools to detect the land use/land cover changes during forty years in Lodhran District of Pakistan

Environmental Science and Pollution Research, Journal Year: 2019, Volume and Issue: 27(32), P. 39676 - 39692

Published: Aug. 5, 2019

Language: Английский

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Impact of Land Cover Changes on Land Surface Temperature and Human Thermal Comfort in Dhaka City of Bangladesh

Earth Systems and Environment, Journal Year: 2021, Volume and Issue: 5(3), P. 667 - 693

Published: July 7, 2021

Abstract Urbanization leads to the construction of various urban infrastructures in city area for residency, transportation, industry, and other purposes, which causes major land use change. Consequently, it substantially affects Land Surface Temperature (LST) by unbalancing surface energy budget. Higher LST areas decreases human thermal comfort dwellers environment ecosystem. Therefore, a comprehensive investigation is needed evaluate impact change on LST. Remote Sensing (RS) Geographic Information System (GIS) techniques were used detailed investigation. RS data years 1993, 2007 2020 during summer (March–May) Dhaka prepare cover maps, analyze LST, generate hazard maps relate with using GIS. The results show that built-up increased 67% from 1993 replacing lowland mainly, followed vegetation, bare soil water bodies. LSTs found study ranged 23.26 39.94 °C, 23.69 43.35 °C 24.44 44.58 2020, respectively. increases spatially distributed maximum mean 4.62 6.43 respectively, period 27 while minimum was not substantial. around 0.24 per year discomfort shifted moderate strong heat stress total due increase lands. This also shows normalized difference vegetation index (NDVI) (NDWI) negatively correlated Index (NDBI) (NDBAI) positively methodology developed this can be adapted cities globe.

Language: Английский

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Spatial Variability and Temporal Heterogeneity of Surface Urban Heat Island Patterns and the Suitability of Local Climate Zones for Land Surface Temperature Characterization

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(21), P. 4338 - 4338

Published: Oct. 28, 2021

This study investigated monthly variations of surface urban heat island intensity (SUHII) and the applicability local climate zones (LCZ) scheme for land temperature (LST) differentiation within three spatial contexts, including urban, rural their combination, in Shenyang, China, a city with monsoon-influenced humid continental climate. The SUHII LST Shenyang were obtained through 12 images, one each month (within period between 2018 2020), retrieved from Thermal InfraRed Sensor (TIRS) 10 Landsat 8 based on split window algorithm. Non-parametric analysis Kruskal-Wallis H test multiple pairwise comparison adopted to investigate differentiations LCZs. Overall, LCZ exhibited spatiotemporal variations. July August two months when underwent strong effects. longer cool than effects, occurring November May. June October transition cool–heat heat–cool phenomena, respectively. was dependent definition boundaries, where smaller buffering zone resulted weaker SUHI or (SUCI) phenomenon larger area corresponded SUCI as well. LCZs did not follow fixed order, August, LCZ-10 (Heavy industry) had highest mean LST, followed by LCZ-2 (Compact midrise) then LCZ-7 (Lightweight low-rise). In comparison, LCZ-7, LCZ-8 (Large low-rise) LCZ-9 (Sparsely built) varied -10 built that context, while LCZ-2, LCZ-3 low-rise), LCZ-8, five context. suitability month, October, strongest capability May, it weakest capability. Urban context also made difference suitability, compared whole (the combination areas), either contexts weakened. Moreover, higher level an land-cover suitability.

Language: Английский

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Analysis of urban heat island characteristics and mitigation strategies for eight arid and semi-arid gulf region cities

Environmental Earth Sciences, Journal Year: 2021, Volume and Issue: 80(7)

Published: March 22, 2021

The aim of the study is, therefore, to analyze formation UHIs in eight different cities arid and semi-arid regions. analysis is based on land cover (LC) classification (urban, green, bare areas). found that areas had highest mean LST values compared urban green areas. results show difference temperatures between ranges 1 2 °C, 7 5 °C. Furthermore, varied for each LULC categories, hence some three categories lower or higher than other categories. Hence, one category may not always have value outcomes this may, critical implications planners who seek mitigate UHI effects

Language: Английский

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