scholarly journals Landsat Time-Series for Estimating Forest Aboveground Biomass and Its Dynamics across Space and Time: A Review

2019 ◽  
Vol 12 (1) ◽  
pp. 98 ◽  
Author(s):  
Trung H. Nguyen ◽  
Simon Jones ◽  
Mariela Soto-Berelov ◽  
Andrew Haywood ◽  
Samuel Hislop
Keyword(s):  
Time Series ◽  
Aboveground Biomass ◽  
Forest Disturbance ◽  
Forest Monitoring ◽  
Space And Time ◽  
Long Time ◽  
Data Policy ◽  
Disturbance And Recovery ◽  
Forest Aboveground Biomass

The free open access data policy instituted for the Landsat archive since 2008 has revolutionised the use of Landsat data for forest monitoring, especially for estimating forest aboveground biomass (AGB). This paper provides a comprehensive review of recent approaches utilising Landsat time-series (LTS) for estimating AGB and its dynamics across space and time. In particular, we focus on reviewing: (1) how LTS has been utilised to improve the estimation of AGB (for both single-date and over time) and (2) recent LTS-based approaches used for estimating AGB and its dynamics across space and time. In contrast to using single-date images, the use of LTS can benefit forest AGB estimation in two broad areas. First, using LTS allows for the filling of spatial and temporal data gaps in AGB predictions, improving the quality of AGB products and enabling the estimation of AGB across large areas and long time-periods. Second, studies have demonstrated that spectral information extracted from LTS analysis, including forest disturbance and recovery metrics, can significantly improve the accuracy of AGB models. Throughout the last decade, many innovative LTS-based approaches for estimating forest AGB dynamics across space and time have been demonstrated. A general trend is that methods have evolved as demonstrated through recent studies, becoming more advanced and robust. However, most of these methods have been developed and tested in areas that are either supported by established forest inventory programs and/or can rely on Lidar data across large forest areas. Further investigations should focus on tropical forest areas where inventory data are often not systematically available and/or out-of-date.

Phenology Modelling and Forest Disturbance Mapping with Sentinel-2 time series in Austria

2020 ◽  
Author(s):  
Markus Löw ◽  
Koukal Tatjana
Keyword(s):  
Time Series ◽  
Bark Beetle ◽  
Forest Ecosystems ◽  
Forest Disturbance ◽  
Spatial Scales ◽  
Data Access ◽  
Forest Monitoring ◽  
Forest Disturbances ◽  
Disturbance Dynamics ◽  
Sentinel 2

Abstract Background Worldwide, forests provide natural resources and ecosystem services. However, forest ecosystems are threatened by increasing forest disturbance dynamics, caused by direct human activities or an altering natural environment. It is decisive to trace the intra- to trans-annual dynamics of these forest ecosystems. National to local forest communities request detailed area-wide maps that delineate forest disturbance dynamics at various spatial scales. Methods We developed a remote sensing based time series analysis (TSA) framework that comprises data access, data management, image pre-processing, and an advanced but flexible TSA. The data basis is a dense time series of multispectral Sentinel-2 images with a spatial resolution of 10 metres. We use a dynamic Savitzky-Golay-filtering approach to reconstruct robust but sensitive phenology courses. Deviations from the latter are further used to derive spatiotemporal information on forest disturbances. In a first case study, we apply the TSA to map forest disturbances directly or indirectly linked to recurring bark beetle infestation in Northern Austria. Finally, we use zonal statistics on different spatial scales to provide aggregated information on the extent of forest disturbances between 2018 and 2019.Results and Conclusion The outcomes are a) individual phenology models and deduced phenology metrics for each 10 metres by 10 metres forest pixel in Austria and b) forest disturbance maps useful to investigate the occurrence, development and extent of bark beetle infestation. The phenology modelling results provide area-wide consistent data, also useful for downstream analyses (e.g. forest type classification). Results of the forest disturbance detection demonstrate that the TSA is capable to systematically delineate disturbed forest areas. Information derived from such a forest monitoring tool is highly relevant for various stakeholders in the forestry sector, either for forest management purposes or for decision-making processes on different levels.

scholarly journals Monitoring Mangrove Forest Degradation and Regeneration: Landsat Time Series Analysis of Moisture and Vegetation Indices at Rabigh Lagoon, Red Sea

Forests ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 52
Author(s):  
Mohammed Othman Aljahdali ◽  
Sana Munawar ◽  
Waseem Razzaq Khan
Keyword(s):  
Time Series ◽  
Red Sea ◽  
Vegetation Index ◽  
Forest Disturbance ◽  
Road Construction ◽  
Least Square ◽  
Eastern Coast ◽  
Positive Trend ◽  
Study Region ◽  
Disturbance And Recovery

Rabigh Lagoon, located on the eastern coast of the Red Sea, is an ecologically rich zone in Saudi Arabia, providing habitat to Avicennia marina mangrove trees. The environmental quality of the lagoon has been decaying since the 1990s mainly from sedimentation, road construction, and camel grazing. However, because of remedial measures, the mangrove communities have shown some degree of restoration. This study aims to monitor mangrove health of Rabigh Lagoon during the time it was under stress from road construction and after the road was demolished. For this purpose, time series of EVI (Enhanced Vegetation Index), MSAVI (Modified, Soil-Adjusted Vegetation Index), NDVI (Normalized Difference Vegetation Index), and NDMI (Normalized Difference Moisture Index) have been used as a proxy to plant biomass and indicator of forest disturbance and recovery. Long-term trend patterns, through linear, least square regression, were estimated using 30 m annual Landsat surface-reflectance-derived indices from 1986 to 2019. The outcome of this study showed (1) a positive trend over most of the study region during the evaluation period; (2) most trend slopes were gradual and weakly positive, implying subtle changes as opposed to abrupt changes; (3) all four indices divided the times series into three phases: degraded mangroves, slow recovery, and regenerated mangroves; (4) MSAVI performed best in capturing various trend patterns related to the greenness of vegetation; and (5) NDMI better identified forest disturbance and recovery in terms of water stress. Validating observed patterns using only the regression slope proved to be a challenge. Therefore, water quality parameters such as salinity, pH/dissolved oxygen should also be investigated to explain the calculated trends.

scholarly journals Combining simulated hyperspectral EnMAP and Landsat time series for forest aboveground biomass mapping

2021 ◽  
Vol 98 ◽  
pp. 102307
Author(s):  
Sam Cooper ◽  
Akpona Okujeni ◽  
Dirk Pflugmacher ◽  
Sebastian van der Linden ◽  
Patrick Hostert
Keyword(s):  
Time Series ◽  
Aboveground Biomass ◽  
Biomass Mapping ◽  
Forest Aboveground Biomass

Consumption Inequality over the Last Half Century: Some Evidence Using the New PSID Consumption Measure

2014 ◽  
Vol 104 (5) ◽  
pp. 122-126 ◽  
Author(s):  
Orazio Attanasio ◽  
Luigi Pistaferri
Keyword(s):  
United States ◽  
Time Series ◽  
Income Inequality ◽  
Great Recession ◽  
The United States ◽  
The Great Recession ◽  
Consumption Data ◽  
Long Time ◽  
Imputation Procedure

This paper contributes to the debate regarding trends in consumption inequality in the United States. We present a new measure of consumption inequality based on the redesigned 1999-2011 PSID. We impute consumption to the families observed before 1999 using the more comprehensive consumption data available from 1999 onward. One advantage of this procedure is in sample verification of the quality of the imputation procedure; another is that it yields a long time series (1967-2010). Consumption inequality was stable in the 1970s, as was income inequality. It increased significantly after 1980. The Great Recession was associated with a decline in consumption inequality.

scholarly journals A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series

2017 ◽  
Vol 194 ◽  
pp. 303-321 ◽  
Author(s):  
Joanne C. White ◽  
Michael A. Wulder ◽  
Txomin Hermosilla ◽  
Nicholas C. Coops ◽  
Geordie W. Hobart
Keyword(s):  
Time Series ◽  
Forest Disturbance ◽  
Disturbance And Recovery
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