Neural Computing and Applications, Journal Year: 2021, Volume and Issue: 34(1), P. 515 - 533
Published: Aug. 13, 2021
Language: Английский
Neural Computing and Applications, Journal Year: 2021, Volume and Issue: 34(1), P. 515 - 533
Published: Aug. 13, 2021
Language: Английский
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
Citations
897Land Use Policy, Journal Year: 2020, Volume and Issue: 99, P. 104868 - 104868
Published: July 1, 2020
Language: Английский
Citations
170Remote Sensing, Journal Year: 2020, Volume and Issue: 12(21), P. 3539 - 3539
Published: Oct. 28, 2020
Garlic and winter wheat are major economic grain crops in China, their boundaries have increased substantially recent decades. Updated accurate garlic maps critical for assessing impacts on society the environment. Remote sensing imagery can be used to monitor spatial temporal changes croplands such as maize. However, our knowledge, few studies focusing area mapping. Here, we proposed a method coupling active passive satellite identification of both Northern China. First, (Sentinel-2 Landsat-8 images) extract (garlic wheat) with high accuracy. Second, applied (Sentinel-1 distinguish from wheat. Third, generated map by above two classification results. For evaluation classification, overall accuracy was 95.97%, kappa coefficient 0.94 eighteen validation quadrats (3 km 3 km). The user’s producer’s accuracies 95.83% 95.85%, respectively; wheat, these 97.20% 97.45%, respectively. This study provides practical exploration targeted crop mixed planting areas using multisource remote data.
Language: Английский
Citations
149Remote Sensing, Journal Year: 2022, Volume and Issue: 14(9), P. 1977 - 1977
Published: April 20, 2022
Accurate and real-time land use/land cover (LULC) maps are important to provide precise information for dynamic monitoring, planning, management of the Earth. With advent cloud computing platforms, time series feature extraction techniques, machine learning classifiers, new opportunities arising in more accurate large-scale LULC mapping. In this study, we aimed at finding out how two composition methods spectral–temporal metrics extracted from satellite can affect ability a classifier produce maps. We used Google Earth Engine (GEE) platform create cloud-free Sentinel-2 (S-2) Landsat-8 (L-8) over Tehran Province (Iran) as 2020. Two methods, namely, seasonal composites percentiles metrics, were define four datasets based on series, vegetation indices, topographic layers. The random forest was classification identifying most variables. Accuracy assessment results showed that S-2 outperformed L-8 overall class level. Moreover, comparison indicated percentile both series. At level, improved performance related their better about phenological variation different classes. Finally, conclude methodology GEE an fast way be
Language: Английский
Citations
149The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 801, P. 149697 - 149697
Published: Aug. 20, 2021
Language: Английский
Citations
128Ecological Indicators, Journal Year: 2021, Volume and Issue: 126, P. 107612 - 107612
Published: March 30, 2021
Land-use and land-cover (LULC) changes have become a crucial issue that urgently needs to be addressed due global environmental change. Many studies employed remote sensing data for assessing LULC changes, however, the investigation of fragmentation probability modeling is still scarce in existing literature. Thus, coupling bagging, random forest (RF), subspace (RSS), their ensemble model with multi-temporal datasets within GIS environment makes it possible Teesta River Basin (TRB), Bangladesh. The number patch (NP), edge density (ED), largest index (LPI), contagion (%) (CONTAG), aggregation (AI), perimeter area ratio (P/A ratio), class (CA), percentage landscape (PLAND), (PD), total (TE), shape (LSI) core (TCA) were matrices, which derived from maps using FRAGSTATS software. machine learning-based sensitivity models, such as decision tree support vector machine-based feature selection techniques implemented explore influence parameters modeling. results showed water bodies barren land substantially decreased by (6.21%), (14.59%) respectively while built-up areas increased 1.45% 2010 2019. Results revealed dominance agricultural has been human interference elevated TRB. However, twelve class-level matrices used delineate zone aid RF, RSS algorithms. images models validated kappa coefficient under curve (AUC) receiver operating characteristics (ROC). validation outcomes depicted three bagging (AUC = 0.864), RF 0.819), 0.859), 0.912) good capability appraise probability, highest precision level among models. Nearly 49% (1789 km2) was high very potential requires protected direct measures. analysis patches significantly influenced model, least sensitive parameter
Language: Английский
Citations
124Geology Ecology and Landscapes, Journal Year: 2021, Volume and Issue: 7(1), P. 46 - 58
Published: May 18, 2021
The aim of this research was to assess the land use/land cover (LULC) changes and its impact on surface temperature (LST) using remote-sensing (RS) technique in district Khanewal, Punjab, Pakistan. Data were pre-processed ERDAS imagine 15 Arc GIS 10.4 software for layer stacking, mosaicking, sub-setting Landsat images. After pre-processing, supervised classification scheme applied years 1980, 2000, 2020, which explains maximum likelihood algorithm identify LULC observed study area. "Built-up area" 1980 occupied 1.75% but build-up area increased (5.27%) compared 2020. Vegetation decreased by 4.12% from 2020 Khanewal. It that there has been a rapid change vegetation LST values 0.50°C due increasing East West direction Maximum minimum normalized difference index (NDVI) 0.72 −0.2 regression line produced definitive explanation, showing strong negative correlation with NDVI LST. outcomes indicated dramatic transformation took place Khanewal regarding decrease greenness increase population density, urban growth, other infrastructural developments. Thus, these results will be used regional planning managing agriculture coming environmental changes.
Language: Английский
Citations
117The Science of The Total Environment, Journal Year: 2021, Volume and Issue: 806, P. 151310 - 151310
Published: Oct. 29, 2021
Globally, wetlands have been severely damaged due to natural environment and human activities. Understanding the spatiotemporal dynamics of their driving forces is essential for effective protection. This study proposes a research framework explore interaction between activities its impact on wetland changes, by introducing Partial Least Squares Structural Equation Modeling (PLS-SEM) Geographically Weighted Regression (GWR) model, then applying methodology in Wuhan, typical city China. The validity reliability evaluation indicated that PLS-SEM model reasonable. results showed area Wuhan decreased 10.98% 1990-2018 four obvious direct pathways influence were found. Positive soil terrain conditions are conducive maintaining wetlands, while rapid urbanization drastically reduce distribution wetlands. It remarkable climate gradually shifting from positive negative. Furthermore, potential indirect affecting shown enhance negative distribution, impacts weaken soil's impact. provides quantitative determining causes loss; it can also be applied other cities or regions, which more measures protect
Language: Английский
Citations
108International Journal of Disaster Risk Reduction, Journal Year: 2022, Volume and Issue: 78, P. 103119 - 103119
Published: June 17, 2022
Language: Английский
Citations
74Engineering Applications of Artificial Intelligence, Journal Year: 2022, Volume and Issue: 117, P. 105579 - 105579
Published: Nov. 16, 2022
Language: Английский
Citations
72