Integrated Object-Based Spatiotemporal Characterization of Forest Change from an Annual Time Series of Landsat Image Composites-Reference-Cited by-同舟云学术

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Integrated Object-Based Spatiotemporal Characterization of Forest Change from an Annual Time Series of Landsat Image Composites

Published:2015-07-04 Issue:4 Volume:41 Page:271-292
ISSN:0703-8992
Container-title:Canadian Journal of Remote Sensing
language:en
Short-container-title:Canadian Journal of Remote Sensing

Author:

Gómez Cristina¹,White Joanne C.²,Wulder Michael A.²,Alejandro Pablo³

Affiliation:

1. Department of Geography and Environment, School of Geoscience, University of Aberdeen, Aberdeen AB24 3UE, Scotland, UK

2. Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, British Columbia, V8Z 1M5, Canada

3. 17 Deveron Park, Huntly, AB54 8UZ, Scotland, UK

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/07038992.2015.1089162

Reference117 articles.

1. Landsat-7 Long-Term Acquisition Plan

2. The impact of landscape disturbance on grizzly bear habitat use in the Foothills Model Forest, Alberta, Canada

3. Geographic Object-Based Image Analysis – Towards a new paradigm

4. Historical comparison of the 2001/2002 drought in the Canadian Prairies

Cited by 10 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. Forest disturbance characterization in the era of earth observation big data: A mapping review;International Journal of Applied Earth Observation and Geoinformation;2024-04

2. Predicting net growth rates in boreal forests using Landsat time series and permanent sample plot data;Forestry: An International Journal of Forest Research;2023-11-20

3. Machine Learning Classification of Mediterranean Forest Habitats in Google Earth Engine Based on Seasonal Sentinel-2 Time-Series and Input Image Composition Optimisation;Remote Sensing;2021-02-07

4. Mapping Annual Land Use and Land Cover Changes in the Yangtze Estuary Region Using an Object-Based Classification Framework and Landsat Time Series Data;Sustainability;2020-01-16

5. Object-Based Time-Constrained Dynamic Time Warping Classification of Crops Using Sentinel-2;Remote Sensing;2019-05-27

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