Behind the general pattern of forest loss and gain: A long-term assessment of semi-natural and secondary forest cover change at country level

Accurate remote sensing of mountainous forest cover change is important for myriad social and ecological reasons, but is challenged by topographic and illumination conditions that can affect detection of forests. Several topographic illumination correction (TIC) approaches have been developed to mitigate these effects, but existing research has focused mostly on whether TIC improves forest cover classification accuracy and has usually found only marginal gains. However, the beneficial effects of TIC may go well beyond accuracy since TIC promises to improve detection of low illuminated forest cover and thereby normalize measurements of the amount, geographic distribution, and rate of forest cover change regardless of illumination. To assess the effects of TIC on the extent and geographic distribution of forest cover change, in addition to classification accuracy, we mapped forest cover across mountainous Nepal using a 25-year (1992–2016) gap-filled Landsat time series in two ways—with and without TIC (i.e., nonTIC)—and classified annual forest cover using a Random Forest classifier. We found that TIC modestly increased classifier accuracy and produced more conservative estimates of net forest cover change across Nepal (−5.2% from 1992–2016) TIC. TIC also resulted in a more even distribution of forest cover gain across Nepal with 3–5% more net gain and 4–6% more regenerated forest in the least illuminated regions. These results show that TIC helped to normalize forest cover change across varying illumination conditions with particular benefits for detecting mountainous forest cover gain. We encourage the use of TIC for satellite remote sensing detection of long-term mountainous forest cover change.

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Mexican agricultural frontier communities differ in forest dynamics with consequences for conservation and restoration

10.32942/osf.io/qxje8 ◽

2021 ◽

Author(s):

Madelon Lohbeck ◽

Ben DeVries ◽

Frans Bongers ◽

Miguel Martinez-Ramos ◽

Armando Navarrete-Segueda ◽

...

Keyword(s):

Temporal Variation ◽

Forest Conservation ◽

Forest Cover ◽

Secondary Forest ◽

Forest Loss ◽

Secondary Forests ◽

High Quality ◽

Agricultural Frontier ◽

Forest Regrowth ◽

Land Availability

Forest regrowth is key to achieve restoration commitments, but we need to better understand under what circumstances it takes place and how long secondary forests persist. We studied a recently colonized agricultural frontier in southern Mexico. We quantified the spatiotemporal dynamics of forest loss and regrowth and tested how temporal variation in climate, and spatial variation in land availability, land quality and accessibility affect forest disturbance, regrowth and secondary forest persistence. Marqués de Comillas consistently exhibits more forest loss than regrowth, resulting in a net decrease of 30% forest cover (1991-2016). Secondary forest cover remained relatively constant while secondary forest persistence increased, suggesting that farmers are moving away from shifting cultivation. Temporal variation in disturbance and regrowth were explained by the annual variation in the Oceanic El Niño index combined with dry season rainfall and key policy and market interventions.Across communities the availability of high-quality soil overrules the effects of land availability and accessibility, but that at the pixel-level all three factors contributed to explaining forest conservation and restoration. Communities with more high-quality soils were able to spare land for forest conservation, and had less secondary forest that persisted for longer. Old forest and secondary forests were better represented on low-quality lands and on communal land. Both old and secondary forest were less common close to the main road, where secondary forests were also less persistent. Forest conservation and restoration can be explained by a complex interplay of biophysical and social drivers across time, space and scale. We warrant that stimulating private land ownership may cause remaining forest patches to be lost and that conservation initiatives should benefit the whole community. Forest regrowth and secondary forest persistence competes with agricultural production and ensuring farmers can access restoration benefits is key to success.

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Impact of Forest Cover Change on Available Water Resources: Long-Term Forest Cover Dynamics of the Semi-Arid Dhofar Cloud Forest, Oman

Frontiers in Earth Science ◽

10.3389/feart.2020.00299 ◽

2020 ◽

Vol 8 ◽

Author(s):

Romy Arnold ◽

Jan-Karl Haug ◽

Maximilian Lange ◽

Jan Friesen

Keyword(s):

Water Resources ◽

Forest Cover ◽

Cloud Forest ◽

Forest Cover Change ◽

Available Water ◽

Semi Arid

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Uncertainty in Historical Land-Use Reconstructions with Topographic Maps

Quaestiones Geographicae ◽

10.2478/quageo-2014-0029 ◽

2014 ◽

Vol 33 (3) ◽

pp. 55-63 ◽

Cited By ~ 23

Author(s):

Dominik Kaim ◽

Jacek Kozak ◽

Krzysztof Ostafin ◽

Monika Dobosz ◽

Katarzyna Ostapowicz ◽

...

Keyword(s):

Land Use ◽

Forest Cover ◽

Reliability Assessment ◽

Swiss Alps ◽

Topographic Maps ◽

Forest Cover Change ◽

Change Analysis ◽

Polish Carpathians ◽

Historical Land Use

Abstract The paper presents the outcomes of the uncertainty investigation of a long-term forest cover change analysis in the Polish Carpathians (nearly 20,000 km2) and Swiss Alps (nearly 10,000 km2) based on topographic maps. Following Leyk et al. (2005) all possible uncertainties are grouped into three domains - production-oriented, transformation- oriented and application-oriented. We show typical examples for each uncertainty domain, encountered during the forest cover change analysis and discuss consequences for change detection. Finally, a proposal for reliability assessment is presented.

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Mapping Mangrove Forest Change in Nijhum Dwip Island

Journal of Environmental Science and Natural Resources ◽

10.3329/jesnr.v11i1-2.43388 ◽

2019 ◽

Vol 11 (1-2) ◽

pp. 217-225

Author(s):

MM Rahman ◽

MAT Pramanik ◽

MI Islam ◽

S Razia

Keyword(s):

Mangrove Forest ◽

Forest Cover ◽

Storm Surges ◽

Forest Loss ◽

Forest Conversion ◽

Forest Cover Change ◽

Forest Change ◽

Change Analysis ◽

Coastal Belt ◽

Land Covers

Mangroves have been planting in the coastal belt of Bangladesh to protect the inhabitants of the coastal areas from cyclones and storm surges. Nijhum Dwip is located at the southern part of Hatiya Island. Most part of the island has been planted with the mangroves in the 1970s and 1980s; while parts of the mangroves have been deforested during the past few decades. The objectives of this research were to delineate and quantify the changes in the extent of mangroves in the island. The Landsat data of 1989, 2001, 2010 and 2018 have been utilized in the study. Three major land covers, namely forest, water and other land have been interpreted and delineated by using on-screen digitizing. The quantity of mangrove forest loss in the island is estimated as 1,024 ha, while 395 ha were afforested during 1989-2018. In the decadal change analysis, it was revealed that net forest cover change was higher in 2000s compared to other two decades and it was -425 ha. The result of the study is helpful to understand the extent and pattern of forest conversion in the island and to halt further forest loss and conserve the remaining forest. J. Environ. Sci. & Natural Resources, 11(1-2): 217-225 2018

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Migration, Remittances, and Forest Cover Change in Rural Guatemala and Chiapas, Mexico

Land ◽

10.3390/land9030088 ◽

2020 ◽

Vol 9 (3) ◽

pp. 88 ◽

Cited By ~ 1

Author(s):

Arild Angelsen ◽

Mariel Aguilar-Støen ◽

John Ainembabazi ◽

Edwin Castellanos ◽

Matthew Taylor

Keyword(s):

Remote Sensing ◽

Rural Communities ◽

Forest Cover ◽

Agricultural Land ◽

Remote Sensing Data ◽

Forest Loss ◽

Household Surveys ◽

Forest Cover Change ◽

Household Members ◽

Migration Flows

This article investigates how migration and remittances affect forest cover in eight rural communities in Guatemala and Chiapas, Mexico. Based on household surveys and remote sensing data, we found little evidence to support the widespread claim that migration takes pressure off forests. In the Chiapas sites, we observed no significant changes in forest cover since 1990, while in the Guatemalan sites, migration may have increased demand for agricultural land, leading to an average annual forest loss of 0.73% during the first decade of the millennium. We suggest that when attractive opportunities exist to invest in agriculture and land expansion, remittances and returnee savings provide fresh capital that is likely to increase pressure on forests. Our study also has implications for the understanding of migration flows; in particular, migration has not implied an exodus out of agriculture for the remaining household members nor for the returning migrants. On the contrary, returning migrants are more likely to be involved in farming activities after their return than they were before leaving.

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Management effectiveness positively influences forest conservation outcomes in protected areas in Mexico

10.32942/osf.io/d4mec ◽

2020 ◽

Author(s):

Kathryn Powlen ◽

Michael C. Gavin ◽

Kelly W. Jones

Keyword(s):

Protected Areas ◽

Forest Cover ◽

Forest Loss ◽

Forest Cover Change ◽

Management Effectiveness ◽

Multiple Stakeholders ◽

Management Quality ◽

Quasi Experimental ◽

Equal Sharing ◽

Careful Design

Understanding the factors that drive protected area outcomes is critical to increase the success of global conservation efforts. Until recently, our understanding of the influence of management effectiveness has been restricted by the limited availability of standardized management data and study design limitations of prior evaluations. Here we use a quasi-experimental matching approach to test the influence of management effectiveness on forest cover change inside 46 protected areas in Mexico. We test the influence of five management categories, including context and planning, administration and finance, use and benefits, governance and social participation, and management quality, as well as an overall effectiveness score, using a subgroup analysis and an interaction term in post-matching multiple linear regression. Our results show that protected areas with higher management effectiveness have a greater effect on reducing deforestation compared to those with low management effectiveness, but that both types of protected areas experience less forest loss compared to similar unprotected areas. We find this trend in all five of the management categories and the overall score, with administration and finance scores having the greatest effect on forest loss outcomes. Our findings suggest careful design and planning, effective participation from multiple stakeholders and equal sharing of benefits, and sufficient human and financial capital can improve the effectiveness of protected areas in preventing forest loss.

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Object-Based Classification of Forest Disturbance Types in the Conterminous United States

Remote Sensing ◽

10.3390/rs11050477 ◽

2019 ◽

Vol 11 (5) ◽

pp. 477 ◽

Cited By ~ 12

Author(s):

Lian-Zhi Huo ◽

Luigi Boschetti ◽

Aaron Sparks

Keyword(s):

United States ◽

Forest Cover ◽

Forest Disturbance ◽

Global Scale ◽

Management Policy ◽

Forest Loss ◽

Forest Cover Change ◽

Forest Change ◽

Goods And Services ◽

Moderate Resolution Imaging Spectroradiometer

Forest ecosystems provide critical ecosystem goods and services, and any disturbance-induced changes can have cascading impacts on natural processes and human socioeconomic systems. Forest disturbance frequency, intensity, and spatial and temporal scale can be altered by changes in climate and human activity, but without baseline forest disturbance data, it is impossible to quantify the magnitude and extent of these changes. Methodologies for quantifying forest cover change have been developed at the regional-to-global scale via several approaches that utilize data from high (e.g., IKONOS, Quickbird), moderate (e.g., Landsat) and coarse (e.g., Moderate Resolution Imaging Spectroradiometer (MODIS)) spatial resolution satellite imagery. While detection and quantification of forest cover change is an important first step, attribution of disturbance type is critical missing information for establishing baseline data and effective land management policy. The objective here was to prototype and test a semi-automated methodology for characterizing high-magnitude (>50% forest cover loss) forest disturbance agents (stress, fire, stem removal) across the conterminous United States (CONUS) from 2003–2011 using the existing University of Maryland Landsat-based Global Forest Change Product and Web-Enabled Landsat Data (WELD). The Forest Cover Change maps were segmented into objects based on temporal and spatial adjacency, and object-level spectral metrics were calculated based on WELD reflectance time series. A training set of objects with known disturbance type was developed via high-resolution imagery and expert interpretation, ingested into a Random Forest classifier, which was then used to attribute disturbance type to all 15,179,430 forest loss objects across CONUS. Accuracy assessments of the resulting classification was conducted with an independent dataset consisting of 4156 forest loss objects. Overall accuracy was 88.1%, with the highest omission and commission errors observed for fire (32.8%) and stress (31.9%) disturbances, respectively. Of the total 172,686 km2 of forest loss, 83.75% was attributed to stem removal, 10.92% to fire and 5.33% to stress. The semi-automated approach described in this paper provides a promising framework for the systematic characterization and monitoring of forest disturbance regimes.

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Nonfrontier Deforestation in the Eastern Amazon

Earth Interactions ◽

10.1175/2009ei290.1 ◽

2010 ◽

Vol 14 (1) ◽

pp. 1-15 ◽

Cited By ~ 11

Author(s):

Arlete Silva de Almeida ◽

Thomas A. Stone ◽

Ima Célia G. Vieira ◽

Eric A. Davidson

Keyword(s):

Land Use ◽

Forest Cover ◽

Secondary Forest ◽

Average Rate ◽

Landsat Imagery ◽

Steady Increase ◽

Initial Increase ◽

Secondary Forests ◽

Human Occupation

Abstract While interest in Amazonian deforestation mostly focuses on frontier areas, the amount of forest cover in areas already dominated by human settlement is also changing. Secondary forests play an increasingly important role for maintaining genetic diversity, hydrological functioning, and greenhouse gas emissions of altered landscapes, but secondary forests are also being converted to more intensive agricultural uses. Five dates of Landsat imagery from 1984 to 2002 were analyzed, covering 8000 km2 of the Zona Bragantina of the eastern part of the Brazilian state of Pará, which underwent its most intensive wave of deforestation several decades ago. However, even in this area of relatively long-term human occupation, ongoing decreases of forest cover were found, both in the small remaining areas of mature forest and in the more widespread areas of secondary forests, as human population increased and land use intensified. Although there was an initial increase in the area of secondary forest from 1984 to 1994, there has been a steady decline since then, from 75% secondary forest cover in 1994 to 54% in 2002. The amount of pasture was relatively stable from 1984 to 1994 but more recently has shown a steady increase, reaching 37% cover in 2002. The average rate of carbon loss over the 18-yr study period was 0.9 Mg C ha−1 yr−1 for the 8000 km2 study area. Forests in this long-settled region of eastern Amazonia continue to be degraded, resulting in the loss of ecosystem services and carbon stocks due to continued land-use change.

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Quantifying the Actual Impacts of Forest Cover Change on Surface Temperature in Guangdong, China

Remote Sensing ◽

10.3390/rs12152354 ◽

2020 ◽

Vol 12 (15) ◽

pp. 2354

Author(s):

Wenjuan Shen ◽

Jiaying He ◽

Chengquan Huang ◽

Mingshi Li

Keyword(s):

Surface Temperature ◽

Air Temperature ◽

Land Surface ◽

Forest Cover ◽

Temperature Response ◽

Forest Loss ◽

Forest Cover Change ◽

Local Surface ◽

Forest Change ◽

Gain And Loss

Forest cover change is critical in the regulation of global and regional climate change through the alteration of biophysical features across the Earth’s surface. The accurate assessment of forest cover change can improve our understanding of its roles in the regulation processes of surface temperature. In spite of this, few researchers have attempted to discern the varying effects of multiple satellite-derived forest changes on local surface temperatures. In this study, we quantified the actual contributions of forest loss and gain associated with evapotranspiration (ET) and albedo to local surface temperature in Guangdong Province, China using an improved spatiotemporal change pattern analysis method, and explored the interrelationships between surface temperature and air temperature change. We specifically developed three forest change products for Guangdong, combining satellite observations from Landsat, PALSAR, and MODIS for comparison. Our results revealed that the adjusted simple change detection (SCD)-based Landsat/PALSAR forest cover data performed relatively well. We found that forest loss and gain between 2000 and 2010 had opposite effects on land surface temperature (LST), ET, and albedo. Forest gain led to a cooling of −0.12 ± 0.01 °C, while forest loss led to a warming of 0.07 ± 0.01 °C, which were opposite to the anomalous change of air temperature. A reduced warming to a considerable cooling was estimated due to the forest gain and loss across latitudes. Specifically, mid-subtropical forest gains increased LST by 0.25 ± 0.01 °C, while tropical forest loss decreased LST by −0.16 ± 0.05 °C, which can demonstrate the local differences in an overall cooling. ET induced cooling and warming effects were appropriate for most forest gain and loss. Meanwhile, the nearby temperature changes caused by no-change land cover types more or less canceled out some of the warming and cooling. Albedo exhibited negligible and complex impacts. The other two products (i.e., the GlobeLand30 and MCD12Q1) affect the magnitude of temperature response due to the discrepancies in forest definition, methodology, and data resolution. This study highlights the non-negligible contributions of high-resolution maps and a robust temperature response model in the quantification of the extent to which forest gain reverses the climate effects of forest loss under global warming.

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