Remote sensing big data for water environment monitoring: current status, challenges, and future prospects
J Chen, S Chen, R Fu, D Li, H Jiang, C Wang… - Earth's …, 2022 - Wiley Online Library
Accurate water extraction and quantitative estimation of water quality are two key and
challenging issues for remote sensing of water environment. Recent advances in remote …
challenging issues for remote sensing of water environment. Recent advances in remote …
A novel deep learning method for detection and classification of plant diseases
The agricultural production rate plays a pivotal role in the economic development of a
country. However, plant diseases are the most significant impediment to the production and …
country. However, plant diseases are the most significant impediment to the production and …
Resnet-based modified red deer optimization with DLCNN classifier for plant disease identification and classification
SRG Reddy, GPS Varma, RL Davuluri - Computers and Electrical …, 2023 - Elsevier
The manual inspections of plant diseases resulted in low accuracy with high time
consumption and unable to predict the multiple diseases of plants. To address these …
consumption and unable to predict the multiple diseases of plants. To address these …
Time series analysis for global land cover change monitoring: A comparison across sensors
Comparing the performance of different satellite sensors in global land cover change (LCC)
monitoring is necessary to assess their potential and limitations for more accurate and …
monitoring is necessary to assess their potential and limitations for more accurate and …
[HTML][HTML] A full resolution deep learning network for paddy rice mapping using Landsat data
Rice is the most important food crop in the developing world, and more than half of the
global population consumes it as a staple food. Mapping the area of rice cultivation in a …
global population consumes it as a staple food. Mapping the area of rice cultivation in a …
[HTML][HTML] Evaluation of a deep-learning model for multispectral remote sensing of land use and crop classification
L Wang, J Wang, Z Liu, J Zhu, F Qin - The Crop Journal, 2022 - Elsevier
High-resolution deep-learning-based remote-sensing imagery analysis has been widely
used in land-use and crop-classification mapping. However, the influence of composite …
used in land-use and crop-classification mapping. However, the influence of composite …
[HTML][HTML] Continental-scale wetland mapping: A novel algorithm for detailed wetland types classification based on time series Sentinel-1/2 images
Wetlands have suffered from considerable degradation due to anthropogenic and natural
disturbances in recent decades. Although some advancements have been made, effective …
disturbances in recent decades. Although some advancements have been made, effective …
PlanetScope contributions compared to Sentinel-2, and Landsat-8 for LULC mapping
S Acharki - Remote Sensing Applications: Society and …, 2022 - Elsevier
Up-to-date and accurate land use and land cover (LULC) maps are vital for monitoring
various environmental and natural resources management. In this study, we evaluate …
various environmental and natural resources management. In this study, we evaluate …
[HTML][HTML] Comparison of optimized object-based RF-DT algorithm and SegNet algorithm for classifying Karst wetland vegetation communities using ultra-high spatial …
B Fu, M Liu, H He, F Lan, X He, L Liu, L Huang… - International Journal of …, 2021 - Elsevier
Karst wetlands have the characteristics of small scale and poor stability. At present, the
wetland is being severely damaged and its area is seriously degraded, and the accurate …
wetland is being severely damaged and its area is seriously degraded, and the accurate …
[HTML][HTML] 3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer
Many ecosystems, particularly wetlands, are significantly degraded or lost as a result of
climate change and anthropogenic activities. Simultaneously, developments in machine …
climate change and anthropogenic activities. Simultaneously, developments in machine …