The use of artificial intelligence and satellite remote sensing in land cover change detection: review and perspectives
Z Gu, M Zeng - Sustainability, 2023 - mdpi.com
The integration of Artificial Intelligence (AI) and Satellite Remote Sensing in Land Cover
Change Detection (LCCD) has gained increasing significance in scientific discovery and …
Change Detection (LCCD) has gained increasing significance in scientific discovery and …
A machine learning-based approach for land cover change detection using remote sensing and radiometric measurements
An approach combining the Hotelling T 2 control method with a weighted random forest
classifier is proposed and used in the context of detecting land cover changes via remote …
classifier is proposed and used in the context of detecting land cover changes via remote …
Unsupervised monitoring vegetation after the closure of an ore processing site with multi-temporal optical remote sensing
Ore processing is a source of soil heavy metal pollution. Vegetation traits (structural
characteristics such as spatial cover and repartition; biochemical parameters—pigment and …
characteristics such as spatial cover and repartition; biochemical parameters—pigment and …
GeoSensor: semantifying change and event detection over big data
GeoSensor is a novel, open-source system that enriches change detection over satellite
images with event detection over news items and social media content. GeoSensor …
images with event detection over news items and social media content. GeoSensor …
Land-cover evolution class analysis in Image Time Series of Landsat and Sentinel-2 based on Latent Dirichlet Allocation
D Espinoza-Molina, R Bahmanyar… - … Workshop on the …, 2017 - ieeexplore.ieee.org
Satellite Image Time Series (SITS) are widely used in monitoring the Earth's changes for
various applications such as land-cover evolution analysis. In this paper, we propose an …
various applications such as land-cover evolution analysis. In this paper, we propose an …
Monitoring land-cover changes by combining a detection step with a classification step
An approach merging the HotellingT 2 control scheme with weighted random forest classifier
is proposed and used in the context of detecting land cover changes via remote sensing and …
is proposed and used in the context of detecting land cover changes via remote sensing and …
The Use of Geospatial Technologies to Monitor the Variation of LULC for the Period from 1990 to 2020 for Some Agricultural Districts of Ramadi in Anbar Governorate …
AHI Al-Bayati, SA Jabbar - IOP Conference Series: Earth and …, 2021 - iopscience.iop.org
Geospatial technologies were used in the study of variability in LULC for four years 1990,
2000, 2010 and 2020 in 15 agricultural districts, located on the left bank of the Euphrate s …
2000, 2010 and 2020 in 15 agricultural districts, located on the left bank of the Euphrate s …
Monitoring the variation in land use and land cover LULC for some agricultural districts of Ramadi in Anbar Governorate–Iraq using GIS
A Sabti - Journal of Water Resources and Geosciences, 2022 - jwrg.gov.iq
Geospatial technologies were used in the study of variability in LULC for four years 1990,
2000, 2010 and 2020 in 15 agricultural districts, located on the left bank of the Euphrates …
2000, 2010 and 2020 in 15 agricultural districts, located on the left bank of the Euphrates …
A Bag-of-Words framework for natural disaster evaluation on Sentinel-2 image
VB Bărbulescu, A Griparis… - 2020 13th International …, 2020 - ieeexplore.ieee.org
The machine learning algorithms are an essential tool to measure the impact that severe
weather has on the environment. Addressing the land cover changes generated by extreme …
weather has on the environment. Addressing the land cover changes generated by extreme …