Land-use land-cover classification by machine learning classifiers for satellite observations—A review

S Talukdar, P Singha, S Mahato, S Pal, YA Liou… - Remote sensing, 2020‏ - mdpi.com
Rapid and uncontrolled population growth along with economic and industrial development,
especially in develo** countries during the late twentieth and early twenty-first centuries …

A review of accuracy assessment for object-based image analysis: From per-pixel to per-polygon approaches

S Ye, RG Pontius Jr, R Rakshit - ISPRS Journal of Photogrammetry and …, 2018‏ - Elsevier
Object-based image analysis (OBIA) has gained widespread popularity for creating maps
from remotely sensed data. Researchers routinely claim that OBIA procedures outperform …

Potential flood hazard zonation and flood shelter suitability map** for disaster risk mitigation in Bangladesh using geospatial technology

K Uddin, MA Matin - Progress in disaster science, 2021‏ - Elsevier
Low-lying Bangladesh is known as one of the most flood-prone countries in the world.
During the last few decades, the frequency, intensity, and duration of floods have increased …

[HTML][HTML] Automated detection of rock glaciers using deep learning and object-based image analysis

BA Robson, T Bolch, S MacDonell, D Hölbling… - Remote sensing of …, 2020‏ - Elsevier
Rock glaciers are an important component of the cryosphere and are one of the most visible
manifestations of permafrost. While the significance of rock glacier contribution to streamflow …

Map** paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data

Y Cai, H Lin, M Zhang - Advances in Space Research, 2019‏ - Elsevier
Rice is one of the world's major staple foods, especially in China. In this study, we proposed
an object-based random forest (RF) method for paddy rice map** using time series …

Large-scale rice map** under different years based on time-series Sentinel-1 images using deep semantic segmentation model

P Wei, D Chai, T Lin, C Tang, M Du, J Huang - ISPRS journal of …, 2021‏ - Elsevier
Identifying spatial distribution of crop planting in large-scale is one of the most significant
applications of remote sensing imagery. As an active remote sensing system, synthetic …

Zoning eco-environmental vulnerability for environmental management and protection

AK Nguyen, YA Liou, MH Li, TA Tran - Ecological Indicators, 2016‏ - Elsevier
Eco-environmental vulnerability assessment is crucial for environmental and resource
management. However, evaluation of eco-environmental vulnerability over large areas is a …

Map** paddy rice using a convolutional neural network (CNN) with Landsat 8 datasets in the Dongting Lake Area, China

M Zhang, H Lin, G Wang, H Sun, J Fu - Remote Sensing, 2018‏ - mdpi.com
Rice is one of the world's major staple foods, especially in China. Highly accurate monitoring
on rice-producing land is, therefore, crucial for assessing food supplies and productivity …

Global map** of eco-environmental vulnerability from human and nature disturbances

KA Nguyen, YA Liou - Science of the total environment, 2019‏ - Elsevier
Global environments are threatened by intensively natural variation and continuously
increased human-made disturbances. Assessment of the global eco-environment …

[HTML][HTML] Plant drought impact detection using ultra-high spatial resolution hyperspectral images and machine learning

PD Dao, Y He, C Proctor - … Journal of Applied Earth Observation and …, 2021‏ - Elsevier
Early drought stress detection is crucial for restoring productivity, ensuring recovery, and
providing vital information for mortality prevention. Hyperspectral remote sensing which is …