Impact of agricultural land use in Central Asia: a review

A Hamidov, K Helming, D Balla - Agronomy for sustainable development, 2016 - Springer
Agriculture is major sector in the economy of Central Asia. The sustainable use of
agricultural land is therefore essential to economic growth, human well-being, social equity …

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 …

A high-performance and in-season classification system of field-level crop types using time-series Landsat data and a machine learning approach

Y Cai, K Guan, J Peng, S Wang, C Seifert… - Remote sensing of …, 2018 - Elsevier
Accurate and timely spatial classification of crop types based on remote sensing data is
important for both scientific and practical purposes. Spatially explicit crop-type information …

Evaluation of deformation procedure in waterbed of rivers

A Arifjanov, S Akmalov, I Akhmedov… - IOP Conference Series …, 2019 - iopscience.iop.org
The article is about the questions study of procedure in waterbed with modern GIS
(Geographic Information System) technologies. Data from the Landsat satellite innovation …

3D convolutional neural networks for crop classification with multi-temporal remote sensing images

S Ji, C Zhang, A Xu, Y Shi, Y Duan - Remote Sensing, 2018 - mdpi.com
This study describes a novel three-dimensional (3D) convolutional neural networks (CNN)
based method that automatically classifies crops from spatio-temporal remote sensing …

Self-attention for raw optical satellite time series classification

M Rußwurm, M Körner - ISPRS journal of photogrammetry and remote …, 2020 - Elsevier
The amount of available Earth observation data has increased dramatically in recent years.
Efficiently making use of the entire body of information is a current challenge in remote …

Vits for sits: Vision transformers for satellite image time series

M Tarasiou, E Chavez… - Proceedings of the IEEE …, 2023 - openaccess.thecvf.com
In this paper we introduce the Temporo-Spatial Vision Transformer (TSViT), a fully-
attentional model for general Satellite Image Time Series (SITS) processing based on the …

Multi-temporal land cover classification with sequential recurrent encoders

M Rußwurm, M Körner - ISPRS International Journal of Geo-Information, 2018 - mdpi.com
Earth observation (EO) sensors deliver data at daily or weekly intervals. Most land use and
land cover classification (LULC) approaches, however, are designed for cloud-free and …

[HTML][HTML] Crop map** from image time series: Deep learning with multi-scale label hierarchies

MO Turkoglu, S D'Aronco, G Perich, F Liebisch… - Remote Sensing of …, 2021 - Elsevier
The aim of this paper is to map agricultural crops by classifying satellite image time series.
Domain experts in agriculture work with crop type labels that are organised in a hierarchical …

Segmentation of images by color features: A survey

F Garcia-Lamont, J Cervantes, A López, L Rodriguez - Neurocomputing, 2018 - Elsevier
Image segmentation is an important stage for object recognition. Many methods have been
proposed in the last few years for grayscale and color images. In this paper, we present a …