A statistical framework for the analysis of long image time series-Reference-Cited by-同舟云学术

A statistical framework for the analysis of long image time series

Published:2005-04 Issue:8 Volume:26 Page:1551-1573
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

de Beurs K. M.¹,Henebry G. M.¹

Affiliation:

1. a Center for Advanced Land Management Information Technologies (CALMIT), School of Natural Resources , University of Nebraska‐Lincoln , 102 East Nebraska Hall, Lincoln, NE, 68588‐0517 USA

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431160512331326657

Reference61 articles.

1. Automatic detection of oil spills in ERS SAR images

2. Agricultural policy reforms and food security in Kazakhstan and Turkmenistan

3. The Variability of Crop Production in Private and Socialized Agriculture: Evidence from Eastern Europe

4. Relationships among phenological growing season, time-integrated normalized difference vegetation index and climate forcing in the temperate region of eastern China

5. An analysis of relationships among plant community phenology and seasonal metrics of Normalized Difference Vegetation Index in the northern part of the monsoon region of China

Cited by 185 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. MODIS fPAR products do not reflect in-situ conditions in a tropical dry forest based on wavelet and cross-wavelet transforms;Remote Sensing Applications: Society and Environment;2024-11

2. Evaluating the Spatiotemporal Distributions of Water Conservation in the Yiluo River Basin under a Changing Environment;Water;2024-08-18

3. Spatio-Temporal Evolution of Ecological Environment Quality Based on High-Quality Time-Series Data Reconstruction: A Case Study in the Sanjiangyuan Nature Reserve of China;Sustainability;2024-07-21

4. Trends in Satellite Time Series Processing for Vegetation Phenology Monitoring;Multitemporal Earth Observation Image Analysis;2024-07-19

5. Analysis of spatiotemporal variation in land surface temperature on the Tibetan Plateau from 2001 to 2020;Remote Sensing Letters;2024-06-29