The Bigger Picture – Tropical Forest Change in Context, Concept and Practice

2009 ◽  
pp. 15-43 ◽  
Author(s):  
Alan Grainger
Keyword(s):  
Tropical Forest ◽  
Forest Change

scholarly journals Tropical Forest Remote Sensing Services for the Democratic Republic of Congo inside the EU FP7 ReCover Project (Final Results 2000-2012)

2015 ◽  
Vol XL-7/W3 ◽  
pp. 397-402 ◽  
Author(s):  
J. Haarpaintner ◽  
D. de la Fuente Blanco ◽  
F. Enßle ◽  
P. Datta ◽  
A. Mazinga ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Service Delivery ◽  
Tropical Forest ◽  
Method Development ◽  
Service Providers ◽  
Forest Degradation ◽  
Tropical Region ◽  
Forest Change ◽  
Alos Palsar ◽  
Forest Maps

‘ReCover’ was a 3-year EU-FP7 project (Nov. 2010 – Dec. 2013), aiming to develop and improve science based remote sensing services to support tropical forest management and activities to reduce emission from deforestation and forest degradation (REDD) in the tropical region (Häme et al., 2012). This is an overview of the final ReCover service delivery of 2000-2012 single-year optical (Landsat, ALOS AVNIR-2, RapidEye) and C-and L-band SAR (Envisat ASAR and ALOS Palsar, respectively) image mosaics, their derived forest/non-forest maps, a multi-sensor forest change map (2000-2010) and a biomass map (based on 2003-2009 ICESat GLAS) o he user of he De ocr ic Repub ic of Congo DRC), he Observatoir Satellitale des Forê s d’Afrique Cen r e OSFAC). The results are an improvement from a first iteration service delivery in 2012 after a critical review and validation process by both, the user and service providers, further method development and research, like a prior statistical data analysis considering temporal/seasonal variability, improved data pre-processing, and through the use of ground reference data collected in March 2013 for classification training. Validation with Kompsat-2 VHR data for the 2010 forest/non-forest maps revealed accuracies of 87% and 88% for optical and radar sensors, respectively.

scholarly journals Tropical Forest Monitoring: Challenges and Recent Progress in Research

2021 ◽  
Vol 13 (12) ◽  
pp. 2252
Author(s):  
Jennifer Murrins Misiukas ◽  
Sarah Carter ◽  
Martin Herold
Keyword(s):  
Literature Review ◽  
Tropical Forest ◽  
Recent Progress ◽  
Forest Monitoring ◽  
Future Research ◽  
Anthropogenic Influences ◽  
Forest Change ◽  
Rapid Pace ◽  
Changes Over Time ◽  
Over Time

Forest monitoring is the recurrent measurement of forest parameters to identify changes over time. There is currently a rising demand for monitoring, as well as growing capacities for it. This study identifies recent research on tropical forest monitoring using a systematic literature review. The research explores whether the location of these studies is in the countries where monitoring is most needed. Three characteristics, biophysical conditions, anthropogenic influences, and forest monitoring capacities were used to identify the need for tropical forest monitoring advances. This provided an understanding as to where research should be targeted in the future. The findings revealed that research appears to be concentrated in countries with strong forest monitoring capabilities that face challenges due to biophysical and anthropogenic influences (e.g., logistically difficult ground sampling and rapid pace of forest change, respectively). Consequently, future research could be targeted in countries with lower capacities and higher needs, in order to improve forest monitoring and conservation.

Uncertainty in the construction of global knowledge of tropical forests

2010 ◽  
Vol 34 (6) ◽  
pp. 811-844 ◽  
Author(s):  
Alan Grainger
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Knowledge Exchange ◽  
Remote Sensing Data ◽  
Forest Area ◽  
Forest Monitoring ◽  
Forest Change ◽  
Global Knowledge ◽  
Forest Area Change ◽  
Biodiversity Change

Knowledge of tropical forest change remains uncertain, affecting our ability to produce accurate estimates of globally aggregated parameters to support clear global statements about ‘the tropical forests’. This paper reviews current methods for constructing global knowledge of changes in tropical forest area, carbon density, biodiversity and ecosystem services. It finds a deficiency in formal institutions for global measurement and constructing global knowledge. In their absence, informal institutions have proliferated, increasing the spread of estimates. This is exacerbated by dependence on inaccurate official statistics, which has limited construction of knowledge about forest area change through modelling. Employing the new concept of the Knowledge Exchange Chain shows the interdependence of different disciplines in constructing composite information. Limitations linked to compartmentalization and scale are present, as predicted by the ‘post-normal hypothesis’. Disciplinary compartmentalization has impeded construction of information about forest carbon and biodiversity change. There is growth in interdisciplinary research into modelling forest change and estimating carbon emissions using remote sensing data, but not in studying biodiversity. Continuing uncertainty has implications for implementing the Reduced Emissions from Deforestation and Degradation (REDD) scheme. Uncertainty could be reduced by expanding formal scientific institutions, e.g. by establishing an operational scientific global forest monitoring system, and devising formal generic rules for constructing global environmental knowledge.

scholarly journals National satellite-based humid tropical forest change assessment in Peru in support of REDD+ implementation

2014 ◽  
Vol 9 (12) ◽  
pp. 124012 ◽  
Author(s):  
P V Potapov ◽  
J Dempewolf ◽  
Y Talero ◽  
M C Hansen ◽  
S V Stehman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Change ◽  
Change Assessment ◽  
Humid Tropical Forest

Interdisciplinary analysis of the environment: insights from tropical forest research

2011 ◽  
Vol 38 (2) ◽  
pp. 211-233 ◽  
Author(s):  
SHARACHCHANDRA LELE ◽  
AMIT KURIEN
Keyword(s):  
Tropical Forest ◽  
Well Being ◽  
Environmental Research ◽  
Forest Loss ◽  
Forest Research ◽  
Forest Change ◽  
Tropical Forest Management ◽  
The Social ◽  
Context Specific ◽  
The Impact

SUMMARYTropical forest management is a quintessential interdisciplinary (ID) problem straddling the social-natural divide, and has attracted scholars from many disciplines. This paper is a review of the ID research on tropical forests with a view to understanding the challenges involved in doing ID environmental research in general and the manner in which they might be addressed. Research on two core interdisciplinary questions in tropical forest research, namely causes of tropical forest loss and degradation and its impacts on society, is analysed to illuminate issues facing ID researchers. The challenges stem from differences in implicit values, theories and epistemologies across disciplines, as well as the relationship between individual disciplines, the ID space and the wider applied research audience. Understanding the value-laden nature of terms such as forest loss and degradation leads to a multidimensional and multidisciplinary characterization of the impact of forest change on human well-being. The analysis of causes of change has been enriched by ID research in which forest outcomes are characterized explicitly in terms of their values, measured in terms relevant to these values and linked to chains of socioeconomic variables at the appropriate scale. Explanations from different disciplines may be reconciled to some extent by seeing each as partial and perhaps having context-specific validity, although some core tensions, especially between economists and anthropologists, remain. Insights from ID research have been unevenly internalized in the literature, pointing to the absence of a broadly shared ID space as a consequence of individual social science disciplines appropriating environment as a subject of study. Shifting from theory-driven to problem-driven research and re-engaging self-consciously in this applied ID space will be required to generate more rigorous and relevant ID research on forests.

scholarly journals Tropical Forest Gain and Interactions amongst Agents of Forest Change

Forests ◽  
2016 ◽  
Vol 7 (3) ◽  
pp. 55 ◽  
Author(s):  
Sean Sloan
Keyword(s):  
Tropical Forest ◽  
Forest Change

scholarly journals Wide-Area Near-Real-Time Monitoring of Tropical Forest Degradation and Deforestation Using Sentinel-1

2020 ◽  
Vol 12 (19) ◽  
pp. 3263
Author(s):  
Dirk Hoekman ◽  
Boris Kooij ◽  
Marcela Quiñones ◽  
Sam Vellekoop ◽  
Ita Carolita ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Real Time ◽  
Forest Degradation ◽  
Canopy Gaps ◽  
Selective Logging ◽  
Optical Systems ◽  
Wide Area ◽  
Optical Data ◽  
Small Scale ◽  
Forest Change

The use of Sentinel-1 (S1) radar for wide-area, near-real-time (NRT) tropical-forest-change monitoring is discussed, with particular attention to forest degradation and deforestation. Since forest change can relate to processes ranging from high-impact, large-scale conversion to low-impact, selective logging, and can occur in sites having variable topographic and environmental properties such as mountain slopes and wetlands, a single approach is insufficient. The system introduced here combines time-series analysis of small objects identified in S1 data, i.e., segments containing linear features and apparent small-scale disturbances. A physical model is introduced for quantifying the size of small (upper-) canopy gaps. Deforestation detection was evaluated for several forest landscapes in the Amazon and Borneo. Using the default system settings, the false alarm rate (FAR) is very low (less than 1%), and the missed detection rate (MDR) varies between 1.9% ± 1.1% and 18.6% ± 1.0% (90% confidence level). For peatland landscapes, short radar detection delays up to several weeks due to high levels of soil moisture may occur, while, in comparison, for optical systems, detection delays up to 10 months were found due to cloud cover. In peat swamp forests, narrow linear canopy gaps (road and canal systems) could be detected with an overall accuracy of 85.5%, including many gaps barely visible on hi-res SPOT-6/7 images, which were used for validation. Compared to optical data, subtle degradation signals are easier to detect and are not quickly lost over time due to fast re-vegetation. Although it is possible to estimate an effective forest-cover loss, for example, due to selective logging, and results are spatiotemporally consistent with Sentinel-2 and TerraSAR-X reference data, quantitative validation without extensive field data and/or large hi-res radar datasets, such as TerraSAR-X, remains a challenge.

scholarly journals Comparing terrestrial laser scanning and unmanned aerial vehicle structure from motion to assess top of canopy structure in tropical forests

2018 ◽  
Vol 8 (2) ◽  
pp. 20170038 ◽  
Author(s):  
Sabina Roşca ◽  
Juha Suomalainen ◽  
Harm Bartholomeus ◽  
Martin Herold
Keyword(s):  
Tropical Forest ◽  
Tropical Forests ◽  
Structure From Motion ◽  
Laser Scanning ◽  
Canopy Structure ◽  
Terrestrial Laser Scanning ◽  
Tree Height ◽  
Forest Monitoring ◽  
Forest Change ◽  
Forest Inventories

Terrestrial laser scanning (TLS) and unmanned aerial vehicles (UAVs) equipped with digital cameras have attracted much attention from the forestry community as potential tools for forest inventories and forest monitoring. This research fills a knowledge gap about the viability and dissimilarities of using these technologies for measuring the top of canopy structure in tropical forests. In an empirical study with data acquired in a Guyanese tropical forest, we assessed the differences between top of canopy models (TCMs) derived from TLS measurements and from UAV imagery, processed using structure from motion. Firstly, canopy gaps lead to differences in TCMs derived from TLS and UAVs. UAV TCMs overestimate canopy height in gap areas and often fail to represent smaller gaps altogether. Secondly, it was demonstrated that forest change caused by logging can be detected by both TLS and UAV TCMs, although it is better depicted by the TLS. Thirdly, this research shows that both TLS and UAV TCMs are sensitive to the small variations in sensor positions during data collection. TCMs rendered from UAV data acquired over the same area at different moments are more similar (RMSE 0.11–0.63 m for tree height, and 0.14–3.05 m for gap areas) than those rendered from TLS data (RMSE 0.21–1.21 m for trees, and 1.02–2.48 m for gaps). This study provides support for a more informed decision for choosing between TLS and UAV TCMs to assess top of canopy in a tropical forest by advancing our understanding on: (i) how these technologies capture the top of the canopy, (ii) why their ability to reproduce the same model varies over repeated surveying sessions and (iii) general considerations such as the area coverage, costs, fieldwork time and processing requirements needed.

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