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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Soil salinity assessment by using near-infrared channel and Vegetation Soil Salinity Index derived from Landsat 8 OLI data: a case study in the Tra Vinh Province, Mekong Delta, Vietnam

Progress in Earth and Planetary Science, Journal Year: 2020, Volume and Issue: 7(1)

Published: Jan. 6, 2020

Abstract Salinity intrusion is a pressing issue in the coastal areas worldwide. It affects natural environment and causes massive economic loss due to its impacts on agricultural productivity food safety. Here, we assessed salinity Tra Vinh Province, Mekong Delta of Vietnam. Landsat 8 OLI image was utilized derive indices for soil estimate including single bands, Vegetation Soil Index (VSSI), Adjusted (SAVI), Normalized Difference (NDVI), (NDSI). Statistical analysis between electrical conductivity (EC 1:5 , dS/m) environmental derived from performed. Results indicated that spectral values near-infrared (NIR) band VSSI were better correlated with EC ( r 2 = 0.8 0.7, respectively) than other indices. Comparative results show consistent situ data coefficient determination, R 0.89 RMSE 0.96 dS/m NIR 0.77 1.27 index. Findings this study demonstrate images reveal high potential spatiotemporally monitoring magnitude at top layer. Outcomes are useful activities, planners, farmers by mapping contamination selection accomodating crop types reduce economical context climate change. Our proposed method estimates using satellite-derived variables can be potentially as fast-approach detect regions low cost considerable accuracy.

Language: Английский

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Vulnerability of Vietnam to typhoons: A spatial assessment based on hazards, exposure and adaptive capacity

The Science of The Total Environment, Journal Year: 2019, Volume and Issue: 682, P. 31 - 46

Published: April 9, 2019

Language: Английский

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Eco-engineering controls vegetation trends in southwest China karst

The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 770, P. 145160 - 145160

Published: Jan. 14, 2021

Language: Английский

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Spatio–temporal Assessment of Drought in Ethiopia and the Impact of Recent Intense Droughts

Remote Sensing, Journal Year: 2019, Volume and Issue: 11(15), P. 1828 - 1828

Published: Aug. 5, 2019

The recent droughts that have occurred in different parts of Ethiopia are generally linked to fluctuations atmospheric and ocean circulations. Understanding these large-scale phenomena play a crucial role vegetation productivity is important. In view this, several techniques datasets were analyzed study the spatio–temporal variability response changing climate. this study, 18 years (2001–2018) Moderate Resolution Imaging Spectroscopy (MODIS) Terra/Aqua, normalized difference index (NDVI), land surface temperature (LST), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) daily precipitation, Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) soil moisture processed. Pixel-based Mann–Kendall trend analysis Vegetation Condition Index (VCI) used assess drought patterns during cropping season. Results indicate central highlands northwestern part Ethiopia, which cover dominated by cropland, had experienced decreasing precipitation NDVI trends. About 52.8% pixels showed trend, significant trends focused on low areas. Also, 41.67% especially major region Ethiopia. Based test VCI analysis, countrywide El Niño 2009 2015 years. Furthermore, Pearson correlation coefficient assures was mainly attributed water availability soils. This provides valuable information identifying locations potential concern planning for immediate action relief measures. paper presents results first attempt apply recently developed index, Normalized Difference Latent Heat (NDLI), monitor conditions. show NDLI has high (r = 0.96), 0.81), 0.73), LST −0.67). successfully captures historical shows notable climatic variables. using radiances green, red, short wave infrared (SWIR), simplified crop monitoring model satisfactory accuracy easiness can be developed.

Language: Английский

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Domestic tourism spending and economic vulnerability

Annals of Tourism Research, Journal Year: 2020, Volume and Issue: 85, P. 103063 - 103063

Published: Oct. 20, 2020

Language: Английский

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Drought risk assessment in China: Evaluation framework and influencing factors

Geography and sustainability, Journal Year: 2020, Volume and Issue: 1(3), P. 220 - 228

Published: July 4, 2020

Global warming and rapid economic development have led to increased levels of disaster risk in China. Previous attempts at assessing drought were highly subjective terms assessment methods selection the indicators which resulted appreciable uncertainty results these assessments. Based on assumption that areas with historically high losses are more likely suffer future losses, we develop a new model includes historical loss data. With this model, map regional differentiation Chinese risk. Regions (extreme high) account for 4.3% China's area. Five significant high-risk been identified: Northeast China, North east part Northwest Southwest China small west Areas extreme dominant Heilongjiang Province, accounting 32% total area, followed by Ningxia Hui Autonomous Region, 26% The contribution each influencing factor has quantified, indicates high-exposure high-vulnerability drought. We recommend measures like strengthening protection cultivated land reducing dependence primary industry should be taken mitigate drought-induced losses.

Language: Английский

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A systematic review of the flood vulnerability using geographic information system

Heliyon, Journal Year: 2022, Volume and Issue: 8(3), P. e09075 - e09075

Published: March 1, 2022

The world has faced many disasters in recent years, but flood impacts have gained immense importance and attention due to their adverse effects. More than half of global destruction damages occur the Asia region, which causes losses life, damage infrastructure, creates panic conditions among communities. To provide a better understanding hazard management, vulnerability assessment is primary objective. In this case, central construct analysis assessment. Many researchers defined different approaches methods understand how geographic information systems assess associated risk. Geographic track predict disaster trend mitigate risk damages. This study systematically reviews methodologies used measure floods vulnerabilities by integrating system. Articles on from 2010 2020 were selected reviewed. Through systematic review methodology five research engines, discovered difference tools techniques that can be bridged high-resolution data with multidimensional methodology. reviewed several components directly examined shortcomings at levels. contributed indicator-based approach gives system provides an effective environment for mapping precise disaster.

Language: Английский

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The Carbon Sink Potential of Southern China After Two Decades of Afforestation

Earth s Future, Journal Year: 2022, Volume and Issue: 10(12)

Published: Nov. 18, 2022

Afforestation and land use changes that sequester carbon from the atmosphere in form of woody biomass have turned southern China into one largest sinks globally, which contributes to mitigating climate change. However, forest growth saturation available can be forested limit longevity this sink, while a plethora studies quantified vegetation over last decades, remaining sink potential area is currently unknown. Here, we train model with multiple predictors characterizing heterogeneous landscapes predict carrying capacity region for 2002-2017. We compare observed predicted density find during about two decades afforestation, 2.34 PgC been sequestered between 2002 2017, total 5.32 Pg potentially still sequestrated. This means has reached 73% its aboveground 12% more than 2002, equal decrease 0.77% per year. identify afforestation areas 2.39 PgC, old new forests 87% their 1.85 remaining. Our work locates where not yet full but also shows long-term solution change mitigation.

Language: Английский

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A remote sensing assessment index for urban ecological livability and its application

Geo-spatial Information Science, Journal Year: 2022, Volume and Issue: 27(2), P. 289 - 310

Published: June 14, 2022

Remote sensing provides us with an approach for the rapid identification and monitoring of spatiotemporal changes in urban ecological environment at different scales. This study aimed to construct a remote assessment index livability continuous fine resolution data from Landsat MODIS overcome dilemma single image-based, single-factor analysis, due limitations atmospheric conditions or revisit period satellite platforms. The proposed Ecological Livability Index (ELI) covers five primary indicators – greenness, temperature, dryness, water-wetness, turbidity which are geometrically aggregated by non-equal weights based on entropy method. Considering multisource time-series each indicator, ELI can quickly comprehensively reflect characteristics Quality (ELQ) is also comparable time Based ELI, central area Wuhan, China, 2002 2017, seasons was analyzed every 5 years. ELQ Wuhan found be generally medium level (ELI ≈0.6) showed initial trend degradation but then improved. Moreover, spring autumn near rivers lakes better, whereas expansion has led outward afforestation enhanced environment. In general, this paper demonstrates that exemplary embodiment research, will support protection planning construction.

Language: Английский

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