1
Wetland habitat vulnerability of lower Punarbhaba river basin of the uplifted Barind region of Indo-Bangladesh
2
Groundwater potential zones for sustainable management plans in a river basin of India and Bangladesh
3
Dynamics of ecosystem services (ESs) in response to land use land cover (LU/LC) changes in the lower Gangetic plain of India
4
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
5
Debris Flow Susceptibility Mapping Using Machine-Learning Techniques in Shigatse Area, China
6
Auxiliary datasets improve accuracy of object-based land use/land cover classification in heterogeneous savanna landscapes
7
Evaluation and comparison of eight machine learning models in land use/land cover mapping using Landsat 8 OLI: a case study of the northern region of Iran
8
Effects of damming on the hydrological regime of Punarbhaba river basin wetlands
9
Monitoring of land use/land-cover dynamics using remote sensing: a case of Tana River Basin, Kenya
10
Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data
11
Changing pattern of urban landscape and its effect on land surface temperature in and around Delhi
12
A Comparative Assessment of Machine-Learning Techniques for Land Use and Land Cover Classification of the Brazilian Tropical Savanna Using ALOS-2/PALSAR-2 Polarimetric Images
13
Deep learning in remote sensing applications: A meta-analysis and review
14
Global mapping of eco-environmental vulnerability from human and nature disturbances.
15
Long-Term Satellite Image Time-Series for Land Use/Land Cover Change Detection Using Refined Open Source Data in a Rural Region
16
Mapping global eco-environment vulnerability due to human and nature disturbances
17
Spatio-Temporal Patterns of Land Use/Land Cover Change in the Heterogeneous Coastal Region of Bangladesh between 1990 and 2017
18
Comparison of two-dimensional multitemporal Sentinel-2 data with three-dimensional remote sensing data sources for forest inventory parameter estimation over a boreal forest
19
Assessment of public open spaces (POS) and landscape quality based on per capita POS index in Delhi, India
20
Estimating long-term LULC changes in an agriculture-dominated basin using CORONA (1970) and LISS IV (2013–14) satellite images: a case study of Ramganga River, India
21
Comparison of machine learning algorithms for classification of LiDAR points for characterization of canola canopy structure
22
Joint Deep Learning for land cover and land use classification
23
A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks
24
Land-use change from arable lands to orchards reduced soil erosion and increased nutrient loss in a small catchment.
25
Assessing the Effects of Land-Use Types in Surface Urban Heat Islands for Developing Comfortable Living in Hanoi City
26
Guidance on and comparison of machine learning classifiers for Landsat-based land cover and land use mapping
27
A 30-m landsat-derived cropland extent product of Australia and China using random forest machine learning algorithm on Google Earth Engine cloud computing platform
28
Groundwater Potential Mapping in a Rural River Basin by Union (OR) and Intersection (AND) of Four Multi-criteria Decision-Making Models
29
A Futuristic Deep Learning Framework Approach for Land Use-Land Cover Classification Using Remote Sensing Imagery
30
Assessing the role of hydrological modifications on land use/land cover dynamics in Punarbhaba river basin of Indo-Bangladesh
31
Land cover and land use change analysis using multi-spatial resolution data and object-based image analysis
32
Implementation of machine-learning classification in remote sensing: an applied review
33
Fuzziness-based active learning framework to enhance hyperspectral image classification performance for discriminative and generative classifiers
34
Comparison of Random Forest, k-Nearest Neighbor, and Support Vector Machine Classifiers for Land Cover Classification Using Sentinel-2 Imagery
35
Improving Land Use/Land Cover Classification by Integrating Pixel Unmixing and Decision Tree Methods
36
Semiautomatic approach for land cover classification: a remote sensing study for arid climate in southeastern Tunisia
37
Assessing spatiotemporal eco-environmental vulnerability by Landsat data
38
A review of supervised object-based land-cover image classification
39
Detection of land use and land cover change and land surface temperature in English Bazar urban centre
40
Accuracy Assessment of Land Use/Land Cover Classification Using Remote Sensing and GIS
41
A SAR-Based Index for Landscape Changes in African Savannas
42
Land use classification and change detection by using multi-temporal remotely sensed imagery: The case of Chunati wildlife sanctuary, Bangladesh
43
Land use/land cover change detection combining automatic processing and visual interpretation
44
Comparison of support vector machine, random forest and neural network classifiers for tree species classification on airborne hyperspectral APEX images
45
Zoning eco-environmental vulnerability for environmental management and protection
46
A Comparison of Machine Learning Algorithms for Mapping of Complex Surface-Mined and Agricultural Landscapes Using ZiYuan-3 Stereo Satellite Imagery
47
Influence of anthropogenic land‐use change on hillslope erosion in the Waipaoa River Basin, New Zealand
48
Object-Based Urban Tree Species Classification Using Bi-Temporal WorldView-2 and WorldView-3 Images
49
FORMOSAT‐2 Quick Imaging
50
Land use/land cover classification and its change detection using multi-temporal MODIS NDVI data
51
Flood Mapping Based on Multiple Endmember Spectral Mixture Analysis and Random Forest Classifier - The Case of Yuyao, China
52
Change analysis of land use/land cover and modelling urban growth in Greater Doha, Qatar
53
Object-Based Flood Mapping and Affected Rice Field Estimation with Landsat 8 OLI and MODIS Data
54
Performance analysis of radial basis function networks and multi-layer perceptron networks in modeling urban change: a case study
55
Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery
56
Remote Sensing for Landslide Investigations: An Overview of Recent Achievements and Perspectives
57
Evaluation of different machine learning methods for land cover mapping of a Mediterranean area using multi-seasonal Landsat images and Digital Terrain Models
58
Comparison of two Classification methods (MLC and SVM) to extract land use and land cover in Johor Malaysia
59
Comparative Assessment of Supervised Classifiers for Land Use–Land Cover Classification in a Tropical Region Using Time-Series PALSAR Mosaic Data
60
Land-use/cover classification in a heterogeneous coastal landscape using RapidEye imagery: evaluating the performance of random forest and support vector machines classifiers
61
Changes in glaciers and glacial lakes and the identification of dangerous glacial lakes in the Pumqu River Basin, Xizang (Tibet)
62
Dynamic Artificial Neural Networks with Affective Systems
63
Assessment of Disaster Losses in Rice Paddy Field and Yield after Tsunami Induced by the 2011 Great East Japan Earthquake
64
Selection of classification techniques for land use - land cover change investigation
65
An Evaluation of Bagging, Boosting, and Random Forests for Land-Cover Classification in Cape Cod, Massachusetts, USA
66
Class-Specific Mahalanobis Distance Metric Learning for Biological Image Classification
67
Evaluation of Stiffened End-Plate Moment Connection through Optimized Artificial Neural Network
68
Assessment of Land use/land cover Change in the North-West District of Delhi Using Remote Sensing and GIS Techniques
69
Supervised and unsupervised landuse map generation from remotely sensed images using ant based systems
70
A New Approach to Change Vector Analysis Using Distance and Similarity Measures
71
Introduction to the Issue on Advances in Remote Sensing Image Processing
72
Support vector machines in remote sensing: A review
73
A comparison of classification techniques to support land cover and land use analysis in tropical coastal zones
74
Monitoring Urban Sprawl Using Remote Sensing and GIS Techniques of a Fast Growing Urban Centre, India
75
Flood and Erosion Induced Population Displacements: A Socio-economic Case Study in the Gangetic Riverine Tract at Malda District, West Bengal, India
76
Multiple regression, ANN (RBF, MLP) and ANFIS models for prediction of swell potential of clayey soils
77
Use of high-resolution FORMOSAT-2 satellite images for post-earthquake disaster assessment: a study following the 12 May 2008 Wenchuan Earthquake
78
A Comparison of Spectral Angle Mapper and Artificial Neural Network Classifiers Combined with Landsat TM Imagery Analysis for Obtaining Burnt Area Mapping
79
Land cover change assessment using decision trees, support vector machines and maximum likelihood classification algorithms
80
Land use and land cover change detection using satellite remote sensing techniques in the mountainous Three Gorges Area, China
81
Improving the Accuracy of Land Use and Land Cover Classification of Landsat Data Using Post-Classification Enhancement
82
Analyzing Land Use/Land Cover Changes Using Remote Sensing and GIS in Rize, North-East Turkey
83
PCA‐based land‐use change detection and analysis using multitemporal and multisensor satellite data
84
Expert system classification of urban land use/cover for Delhi, India
85
Harshness in image classification accuracy assessment
86
Mapping land-cover modifications over large areas: A comparison of machine learning algorithms
87
Multiclass and Binary SVM Classification: Implications for Training and Classification Users
88
Multispectral landuse classification using neural networks and support vector machines: one or the other, or both?
89
A survey of image classification methods and techniques for improving classification performance
90
Assessment of ASTER land cover and MODIS NDVI data at multiple scales for ecological characterization of an arid urban center
91
The future of satellite remote sensing in hydrogeology
92
Random forest classifier for remote sensing classification
93
Assessment of the effectiveness of support vector machines for hyperspectral data
94
Comparison of maximum likelihood classification method with supervised artificial neural network algorithms for land use activities
95
Accuracy assessment using sub-pixel fractional error matrices of global land cover products derived from satellite data
96
An assessment of support vector machines for land cover classification
97
Retrieving soil moisture from simulated brightness temperatures by a neural network
98
A neural-network approach to radiometric sensing of land-surface parameters
99
Introduction Neural networks in remote sensing
100
Artificial Neural Networks for Land-Cover Classification and Mapping
101
Comparing global vegetation maps with the Kappa statistic
102
Fast Learning in Networks of Locally-Tuned Processing Units
103
Assessing the Accuracy of Multi-Temporal Built-Up Land Layers across Rural-Urban Trajectories in the United States.
104
Parameter investigation of Artificial Neural Network and Support Vector Machine for image classification
105
Support Vector Machines for Classification
106
Comparisons of using Random Forest and Maximum Likelihood Classifiers with Worldview-2 imagery for classifying Crop Types
107
Classification and Regression by randomForest
109
Fuzzy ARTMAP supervised classification of multi-spectral remotely-sensed images
110
Fuzzy ARTMAP — A Neural Classifier for Multispectral Image Classification
