Spatial prediction of groundwater potential map** based on convolutional neural network (CNN) and support vector regression (SVR)

M Panahi, N Sadhasivam, HR Pourghasemi… - Journal of …, 2020 - Elsevier
Freshwater shortages have become much more common globally in recent years. Water
resources that are naturally available beneath the surface are capable of reversing this …

Flood detection and susceptibility map** using sentinel-1 remote sensing data and a machine learning approach: Hybrid intelligence of bagging ensemble based …

H Shahabi, A Shirzadi, K Ghaderi, E Omidvar… - Remote Sensing, 2020 - mdpi.com
Map** flood-prone areas is a key activity in flood disaster management. In this paper, we
propose a new flood susceptibility map** technique. We employ new ensemble models …

Shallow landslide susceptibility map**: A comparison between logistic model tree, logistic regression, naïve bayes tree, artificial neural network, and support vector …

VH Nhu, A Shirzadi, H Shahabi, SK Singh… - International journal of …, 2020 - mdpi.com
Shallow landslides damage buildings and other infrastructure, disrupt agriculture practices,
and can cause social upheaval and loss of life. As a result, many scientists study the …

Interpretability of simple RNN and GRU deep learning models used to map land susceptibility to gully erosion

H Gholami, A Mohammadifar, S Golzari, Y Song… - Science of the Total …, 2023 - Elsevier
Gully erosion possess a serious hazard to critical resources such as soil, water, and
vegetation cover within watersheds. Therefore, spatial maps of gully erosion hazards can be …

A review on assessing and map** soil erosion hazard using geo-informatics technology for farming system management

S Senanayake, B Pradhan, A Huete, J Brennan - Remote sensing, 2020 - mdpi.com
Soil erosion is a severe threat to food production systems globally. Food production in
farming systems decreases with increasing soil erosion hazards. This review article focuses …

Flash-flood susceptibility assessment using multi-criteria decision making and machine learning supported by remote sensing and GIS techniques

R Costache, QB Pham, E Sharifi, NTT Linh, SI Abba… - Remote Sensing, 2019 - mdpi.com
Concerning the significant increase in the negative effects of flash-floods worldwide, the
main goal of this research is to evaluate the power of the Analytical Hierarchy Process …

GIS-based machine learning algorithms for gully erosion susceptibility map** in a semi-arid region of Iran

X Lei, W Chen, M Avand, S Janizadeh, N Kariminejad… - Remote Sensing, 2020 - mdpi.com
In the present study, gully erosion susceptibility was evaluated for the area of the Robat Turk
Watershed in Iran. The assessment of gully erosion susceptibility was performed using four …

Evaluation of different boosting ensemble machine learning models and novel deep learning and boosting framework for head-cut gully erosion susceptibility

W Chen, X Lei, R Chakrabortty, SC Pal… - Journal of …, 2021 - Elsevier
The objective of this study is to assess the gully head-cut erosion susceptibility and identify
gully erosion prone areas in the Meimand watershed, Iran. In recent years, this study area …

Landslide susceptibility map** using machine learning algorithms and remote sensing data in a tropical environment

VH Nhu, A Mohammadi, H Shahabi, BB Ahmad… - International journal of …, 2020 - mdpi.com
We used AdaBoost (AB), alternating decision tree (ADTree), and their combination as an
ensemble model (AB-ADTree) to spatially predict landslides in the Cameron Highlands …

Assessing the performance of GIS-based machine learning models with different accuracy measures for determining susceptibility to gully erosion

Y Garosi, M Sheklabadi, C Conoscenti… - Science of the Total …, 2019 - Elsevier
The main purpose was to compare discrimination and reliability of four machine learning
models to create gully erosion susceptibility map (GESM) in a part of Ekbatan Dam Basin …