Open AccessJournal Article
An efficient and accurate method for mapping forest clearcuts in the Pacific Northwest using Landsat imagery
TL;DR: In this article, two variations of image differencing were compared, one based on unsupervised classification, repeated five times, using five sequential date-pairs of difference images between 1972 and 1993.
read more
Abstract: Two variations of image differencing were compared. The first was based on unsupervised classification, repeated five times, using five sequential date-pairs of difference images between 1972 and 1993. Referred to as merged image differencing, this method required merging the results from five separate time intervals into a single map of forest harvest activity. The other method involved a single unsupervised classification of the full sequential difference image data set, and was referred to as simultaneous image differencing. A thorough harvest map error assessment using an independent reference database was compared to two methods of assessment based on visual interpretation of the Landsat data used to develop the difference images. Results indicate that harvest activity was mapped using merged image differencing with greater than 90 percent accuracy, and that visual methods of error assessment using the Landsat images gave nearly identical results with those of the independent reference data. Simultaneous image differencing resulted in a map that was consistent with merged image differencing, and was considerably more cost-effective to implement.
read more
Chat with Paper
AI Agents for this Paper
Find similar papers on Google Scholar, PubMed and Arxiv
Write a critical review of this paper
Analyze citations of this paper to find unaddressed research gaps
Citations
Digital change detection methods in ecosystem monitoring: a review
TL;DR: This review paper, which summarizes the methods and the results of digital change detection in the optical/infrared domain, has as its primary objective a synthesis of the state of the art today.
Object-based cloud and cloud shadow detection in Landsat imagery
Zhe Zhu,Curtis E. Woodcock +1 more
TL;DR: The goal is development of a cloud and cloud shadow detection algorithm suitable for routine usage with Landsat images and as high as 96.4%.
2K
Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms
TL;DR: LandTrendr (Landsat-based detection of Trends in Disturbance and Recovery), a new approach to extract spectral trajectories of land surface change from yearly Landsat time-series stacks, appears to be a feasible and robust means of increasing information extraction from the Landsat archive.
1.6K
An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks
TL;DR: In this article, a highly automated algorithm called vegetation change tracker (VCT) has been developed for reconstructing recent forest disturbance history using Landsat time series stacks (LTSS).
910
Detection of forest harvest type using multiple dates of Landsat TM imagery
TL;DR: In this paper, a simple and relatively accurate technique for classifying time-series Landsat Thematic Mapper (TM) imagery to detect levels of forest harvest is the topic of this research.
820
References
Tropical Deforestation and Habitat Fragmentation in the Amazon: Satellite Data from 1978 to 1988
David L. Skole,Compton J. Tucker +1 more
TL;DR: Although this rate of deforestation is lower than previous estimates, the effect on biological diversity is greater and tropical forest habitat, severely affected with respect to biological diversity, increased.
The tasselled cap - A graphic description of the spectral-temporal development of agricultural crops as seen by Landsat
R. J. Kauth,G. S. Thomas +1 more
- 01 Jan 1976
TL;DR: In this article, the time trajectories of agricultural data points as seen in Landsat signal space form a pattern suggestive of a tasselled woolly cap, which is used to estimate and correct atmospheric haze and moisture effects.
Digital change detection in forest ecosystems with remote sensing imagery
Pol Coppin,Marvin E. Bauer +1 more
- 01 Jan 1996
TL;DR: In this article, a review of the methods and the results of digital change detection primarily in temperate forest ecosystems is presented, and the appropriate choice of digital imagery acquisition dates and interval length for change detection are discussed.
757
Estimating the age and structure of forests in a multi-ownership landscape of western Oregon, U.S.A.
TL;DR: In this paper, the authors estimated and mapped forest age and structure in 1988 over a 1 237 482 ha area on the west side of the Oregon Cascade Range with an overall accuracy of 82 per cent.
385
•Journal Article
Using remote sensing to detect and monitor land-cover and land-use change.
K. Green,D. Kempka,L. Lackey +2 more
TL;DR: The significance of these changes increases as the world's population grows, the available land base declines, and the resiliency of our environment becomes increasingly taxed as discussed by the authors, as a result, many organizations need to monitor change in land cover and land use.
367