[HTML][HTML] High-quality vegetation index product generation: A review of NDVI time series reconstruction techniques
Normalized difference vegetation index (NDVI) derived from satellites has been ubiquitously
utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations …
utilized in the field of remote sensing. Nevertheless, there are multitudinous contaminations …
An overview of global leaf area index (LAI): Methods, products, validation, and applications
Leaf area index (LAI) is a critical vegetation structural variable and is essential in the
feedback of vegetation to the climate system. The advancement of the global Earth …
feedback of vegetation to the climate system. The advancement of the global Earth …
Deep learning based multi-temporal crop classification
This study aims to develop a deep learning based classification framework for remotely
sensed time series. The experiment was carried out in Yolo County, California, which has a …
sensed time series. The experiment was carried out in Yolo County, California, which has a …
Machine learning in agricultural and applied economics
This review presents machine learning (ML) approaches from an applied economist's
perspective. We first introduce the key ML methods drawing connections to econometric …
perspective. We first introduce the key ML methods drawing connections to econometric …
[HTML][HTML] Advances in remote sensing of agriculture: Context description, existing operational monitoring systems and major information needs
C Atzberger - Remote sensing, 2013 - mdpi.com
Many remote sensing applications are devoted to the agricultural sector. Representative
case studies are presented in the special issue “Advances in Remote Sensing of …
case studies are presented in the special issue “Advances in Remote Sensing of …
Impacts of climate change on vegetation phenology and net primary productivity in arid Central Asia
Vegetation is highly sensitive to climate changes in arid regions. The relationship between
vegetation and climate changes can be effectively characterized by vegetation phenology …
vegetation and climate changes can be effectively characterized by vegetation phenology …
Interpretable stock price forecasting model using genetic algorithm-machine learning regressions and best feature subset selection
Recent stock market studies adopting machine learning and deep learning techniques have
achieved remarkable performances with convenient accessibility. However, machine …
achieved remarkable performances with convenient accessibility. However, machine …
A dynamic Landsat derived normalized difference vegetation index (NDVI) product for the conterminous United States
Satellite derived vegetation indices (VIs) are broadly used in ecological research, ecosystem
modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI) …
modeling, and land surface monitoring. The Normalized Difference Vegetation Index (NDVI) …
Performance of smoothing methods for reconstructing NDVI time-series and estimating vegetation phenology from MODIS data
Many time-series smoothing methods can be used for reducing noise and extracting plant
phenological parameters from remotely-sensed data, but there is still no conclusive …
phenological parameters from remotely-sensed data, but there is still no conclusive …
Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology
Several models have been fitted in the past to smooth time-series vegetation index data from
different satellite sensors to estimate vegetation phenological parameters. However …
different satellite sensors to estimate vegetation phenological parameters. However …