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Land-use land-cover classification by machine learning classifiers for satellite observations—A review
Rapid and uncontrolled population growth along with economic and industrial development,
especially in develo** countries during the late twentieth and early twenty-first centuries …
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
Object-based image analysis (OBIA) has gained widespread popularity for creating maps
from remotely sensed data. Researchers routinely claim that OBIA procedures outperform …
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
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 …
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
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 …
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
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 …
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
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 …
applications of remote sensing imagery. As an active remote sensing system, synthetic …
Zoning eco-environmental vulnerability for environmental management and protection
Eco-environmental vulnerability assessment is crucial for environmental and resource
management. However, evaluation of eco-environmental vulnerability over large areas is a …
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
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 …
on rice-producing land is, therefore, crucial for assessing food supplies and productivity …
Global map** of eco-environmental vulnerability from human and nature disturbances
Global environments are threatened by intensively natural variation and continuously
increased human-made disturbances. Assessment of the global eco-environment …
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
Early drought stress detection is crucial for restoring productivity, ensuring recovery, and
providing vital information for mortality prevention. Hyperspectral remote sensing which is …
providing vital information for mortality prevention. Hyperspectral remote sensing which is …