Deep learning in the mapping of agricultural land use using Sentinel-2 satellite data

G Singh, S Singh, G Sethi, V Sood - Geographies, 2022 - mdpi.com
Continuous observation and management of agriculture are essential to estimate crop yield
and crop failure. Remote sensing is cost-effective, as well as being an efficient solution to …

Qualitative and quantitative analysis of artificial neural network-based post-classification comparison to detect the earth surface variations using hyperspectral and …

N Dahiya, S Gupta, S Singh - Journal of Applied Remote …, 2023 - spiedigitallibrary.org
Remote sensing is an effective way to analyze land surface changes on regular basis
globally. In the previous literature, numerous change detection models were developed to …

Land-use and habitat quality prediction in the Fen River Basin based on PLUS and InVEST models

Y Hou, J Wu - Frontiers in Environmental Science, 2024 - frontiersin.org
Assessment and prediction analyses of the ecological environmental quality of river basins
are pivotal to realize ecological protection and high-quality coordinated development …

TTNet: A Temporal-Transform Network for Semantic Change Detection Based on Bi-Temporal Remote Sensing Images

L Jiang, F Li, L Huang, F Peng, L Hu - Remote Sensing, 2023 - mdpi.com
Semantic change detection (SCD) holds a critical place in remote sensing image
interpretation, as it aims to locate changing regions and identify their associated land cover …

ENVINet5 deep learning change detection framework for the estimation of agriculture variations during 2012–2023 with Landsat series data

G Singh, N Dahiya, V Sood, S Singh… - Environmental Monitoring …, 2024 - Springer
Remote sensing is one of the most important methods for analysing the multitemporal
changes over a certain period. As a cost-effective way, remote sensing allows the long-term …

Synergistic application of digital outcrop characterization techniques and deep learning algorithms in geological exploration

Z Dong, P Tang, G Chen, S Yin - Scientific Reports, 2024 - nature.com
In order to meet the needs of geologists for the analysis of data characterizing field outcrops
(rock sections or formations exposed on the ground surface), this study developed a field …

Detection of Soil Moisture Variations with Fusion-Based Change Detection Algorithm for MODIS and SCATSAT-1 Datasets

R Kaur, RK Tiwari, R Maini - Journal of the Indian Society of Remote …, 2024 - Springer
Soil moisture is a vital parameter in the study of hydrology, agriculture and meteorology. The
estimation of soil moisture is important for crop yield estimation, crop growth analysis and …

Waterlogged Area Identification Models Based on Object-Oriented Image Analysis and Deep Learning Methods in Sloping Croplands of Northeast China

P Xie, S Wang, M Wang, R Ma, Z Tian, Y Liang, X Shi - Sustainability, 2024 - mdpi.com
Drainage difficulties in the waterlogged areas of sloping cropland not only impede crop
development but also facilitate the formation of erosion gullies, resulting in significant soil …

A novel image fusion-based post classification framework for agricultural variations detection using Sentinel-1 and Sentinel-2 data

N Vyas, S Singh, GK Sethi - Earth Science Informatics, 2025 - Springer
Agriculture is crucial for economic growth, rural development, and food security. Remote
sensing aids in cost-effective agricultural mapping, but challenges like limited resolution …

Quantitative and Qualitative Analysis of PCC-based Change detection methods over Agricultural land using Sentinel-2 Dataset

G Singh, GK Sethi, S Singh - 2022 3rd International …, 2022 - ieeexplore.ieee.org
To plan production, the sowing, and harvesting of a particular crop, and the performance of
marketing activities information about yields is important for both the traders and producers …