A method for integrating MODIS and Landsat data for systematic monitoring of forest cover and change in the Congo Basin

2008 ◽  
Vol 112 (5) ◽  
pp. 2495-2513 ◽  
Author(s):  
Matthew C. Hansen ◽  
David P. Roy ◽  
Erik Lindquist ◽  
Bernard Adusei ◽  
Christopher O. Justice ◽  
...  
Keyword(s):  
Forest Cover ◽  
Congo Basin ◽  
Landsat Data ◽  
Systematic Monitoring

scholarly journals State and evolution of the African rainforests between 1990 and 2010

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120300 ◽  
Author(s):  
Philippe Mayaux ◽  
Jean-François Pekel ◽  
Baudouin Desclée ◽  
François Donnay ◽  
Andrea Lupi ◽  
...  
Keyword(s):  
West Africa ◽  
Forest Cover ◽  
Central Africa ◽  
Congo Basin ◽  
Landsat Images ◽  
Deforestation Rate ◽  
Rural And Urban ◽  
Moderate Resolution ◽  
Underlying Causes ◽  
Moderate Resolution Imaging Spectroradiometer

This paper presents a map of Africa's rainforests for 2005. Derived from moderate resolution imaging spectroradiometer data at a spatial resolution of 250 m and with an overall accuracy of 84%, this map provides new levels of spatial and thematic detail. The map is accompanied by measurements of deforestation between 1990, 2000 and 2010 for West Africa, Central Africa and Madagascar derived from a systematic sample of Landsat images—imagery from equivalent platforms is used to fill gaps in the Landsat record. Net deforestation is estimated at 0.28% yr −1 for the period 1990–2000 and 0.14% yr −1 for the period 2000–2010. West Africa and Madagascar exhibit a much higher deforestation rate than the Congo Basin, for example, three times higher for West Africa and nine times higher for Madagascar. Analysis of variance over the Congo Basin is then used to show that expanding agriculture and increasing fuelwood demands are key drivers of deforestation in the region, whereas well-controlled timber exploitation programmes have little or no direct influence on forest-cover reduction at present. Rural and urban population concentrations and fluxes are also identified as strong underlying causes of deforestation in this study.

scholarly journals The national determinants of deforestation in sub-Saharan Africa

2013 ◽  
Vol 368 (1625) ◽  
pp. 20120405 ◽  
Author(s):  
Thomas K. Rudel
Keyword(s):  
Forest Cover ◽  
Driving Forces ◽  
National Level ◽  
Congo Basin ◽  
Sub Saharan Africa ◽  
Small Scale ◽  
Urban Migration ◽  
Forest Cover Change ◽  
Level Data ◽  
Sub Saharan

For decades, the dynamics of tropical deforestation in sub-Saharan Africa (SSA) have defied easy explanation. The rates of deforestation have been lower than elsewhere in the tropics, and the driving forces evident in other places, government new land settlement schemes and industrialized agriculture, have largely been absent in SSA. The context and causes for African deforestation become clearer through an analysis of new, national-level data on forest cover change for SSA countries for the 2000–2005 period. The recent dynamic in SSA varies from dry to wet biomes. Deforestation occurred at faster rates in nations with predominantly dry forests. The wetter Congo basin countries had lower rates of deforestation, in part because tax receipts from oil and mineral industries in this region spurred rural to urban migration, declines in agriculture and increased imports of cereals from abroad. In this respect, the Congo basin countries may be experiencing an oil and mineral fuelled forest transition. Small farmers play a more important role in African deforestation than they do in southeast Asia and Latin America, in part because small-scale agriculture remains one of the few livelihoods open to rural peoples.

scholarly journals Natural Afforestation on Abandoned Agricultural Lands during Post-Soviet Period: A Comparative Landsat Data Analysis of Bordering Regions in Russia and Belarus

2022 ◽  
Vol 14 (2) ◽  
pp. 322
Author(s):  
Dmitry V. Ershov ◽  
Egor A. Gavrilyuk ◽  
Natalia V. Koroleva ◽  
Elena I. Belova ◽  
Elena V. Tikhonova ◽  
...  
Keyword(s):  
Time Series ◽  
Field Data ◽  
Forest Cover ◽  
Arable Land ◽  
Google Earth ◽  
Soviet Period ◽  
Ecosystem Functions ◽  
Landsat Data ◽  
Agricultural Lands ◽  
Post Soviet Period

Remote monitoring of natural afforestation processes on abandoned agricultural lands is crucial for assessments and predictions of forest cover dynamics, biodiversity, ecosystem functions and services. In this work, we built on the general approach of combining satellite and field data for forest mapping and developed a simple and robust method for afforestation dynamics assessment. This method is based on Landsat imagery and index-based thresholding and specifically targets suitability for limited field data. We demonstrated method’s details and performance by conducting a case study for two bordering districts of Rudnya (Smolensk region, Russia) and Liozno (Vitebsk region, Belarus). This study area was selected because of the striking differences in the development of the agrarian sectors of these countries during the post-Soviet period (1991-present day). We used Landsat data to generate a consistent time series of five-year cloud-free multispectral composite images for the 1985–2020 period via the Google Earth Engine. Three spectral indices, each specifically designed for either forest, water or bare soil identification, were used for forest cover and arable land mapping. Threshold values for indices classification were both determined and verified based on field data and additional samples obtained by visual interpretation of very high-resolution satellite imagery. The developed approach was applied over the full Landsat time series to quantify 35-year afforestation dynamics over the study area. About 32% of initial arable lands and grasslands in the Russian district were afforested by the end of considered period, while the agricultural lands in Belarus’ district decreased only by around 5%. Obtained results are in the good agreement with the previous studies dedicated to the agricultural lands abandonment in the Eastern Europe region. The proposed method could be further developed into a general universally applicable technique for forest cover mapping in different growing conditions at local and regional spatial levels.

scholarly journals Legacy of logging roads in the Congo Basin: How persistent are the scars in forest cover?

Ecosphere ◽  
2015 ◽  
Vol 6 (4) ◽  
pp. 1-17 ◽  
Author(s):  
Fritz Kleinschroth ◽  
Sylvie Gourlet-Fleury ◽  
Plinio Sist ◽  
Fréderic Mortier ◽  
John R. Healey
Keyword(s):  
Forest Cover ◽  
Congo Basin ◽  
Logging Roads

scholarly journals Historical Aerial Surveys Map Long-Term Changes of Forest Cover and Structure in the Central Congo Basin

2020 ◽  
Vol 12 (4) ◽  
pp. 638 ◽  
Author(s):  
Koen Hufkens ◽  
Thalès de Haulleville ◽  
Elizabeth Kearsley ◽  
Kim Jacobsen ◽  
Hans Beeckman ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Forest Cover ◽  
Congo Basin ◽  
Spatial And Temporal Patterns ◽  
Smallholder Farming ◽  
Aboveground Carbon ◽  
Decadal Scale ◽  
Long Term Changes ◽  
The Impact

Given the impact of tropical forest disturbances on atmospheric carbon emissions, biodiversity, and ecosystem productivity, accurate long-term reporting of Land-Use and Land-Cover (LULC) change in the pre-satellite era (<1972) is an imperative. Here, we used a combination of historical (1958) aerial photography and contemporary remote sensing data to map long-term changes in the extent and structure of the tropical forest surrounding Yangambi (DR Congo) in the central Congo Basin. Our study leveraged structure-from-motion and a convolutional neural network-based LULC classifier, using synthetic landscape-based image augmentation to map historical forest cover across a large orthomosaic (~93,431 ha) geo-referenced to ~4.7 ± 4.3 m at submeter resolution. A comparison with contemporary LULC data showed a shift from previously highly regular industrial deforestation of large areas to discrete smallholder farming clearing, increasing landscape fragmentation and providing opportunties for substantial forest regrowth. We estimated aboveground carbon gains through reforestation to range from 811 to 1592 Gg C, partially offsetting historical deforestation (2416 Gg C), in our study area. Efforts to quantify long-term canopy texture changes and their link to aboveground carbon had limited to no success. Our analysis provides methods and insights into key spatial and temporal patterns of deforestation and reforestation at a multi-decadal scale, providing a historical context for past and ongoing forest research in the area.

scholarly journals Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

2015 ◽  
Vol XL-7/W3 ◽  
pp. 557-562 ◽  
Author(s):  
A. Wijaya ◽  
R. A. Sugardiman Budiharto ◽  
A. Tosiani ◽  
D. Murdiyarso ◽  
L.V. Verchot
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Spatial Information ◽  
Brazilian Amazon ◽  
Congo Basin ◽  
Reliable Estimate ◽  
Forest Conversion ◽  
Forest Cover Change ◽  
Forest Change

Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.

scholarly journals Paleoclimate, ecoregion size, and degree of isolation explain regional biodiversity differences among terrestrial vertebrates within the Congo Basin

2019 ◽  
Vol 149 (1) ◽  
Author(s):  
Frederik Van de Perre ◽  
Herwig Leirs ◽  
Erik Verheyen
Keyword(s):  
Forest Cover ◽  
Climatic Variability ◽  
Congo Basin ◽  
Sampling Effort ◽  
Global Biodiversity Information Facility ◽  
Lower Vertebrate ◽  
Terrestrial Vertebrates ◽  
Congo River ◽  
History Of ◽  
Biodiversity Pattern

One of the most widely recognized patterns in ecology is the increase in species richness from poles to tropics. Literature suggests that the Congolian lowland rainforest does not follow this pattern: the Central Congolian forest (CCLF), south of the Congo River, is thought to harbor fewer vertebrate species and endemics than the Northeastern (NELF) and Northwestern lowland rainforests (NWLF) north of the Congo River. We used data from the Global Biodiversity Information Facility (GBIF) database on terrestrial vertebrates (mammals, birds, and reptiles), to test whether differences in sampling effort caused the irregular biodiversity pattern in this region. Our results show that even though the diversity within the Congolian lowland rainforests remains to be fully mapped, current differences in richness are unlikely to be caused by undersampling alone. We argue that the lower vertebrate richness in the CCLF is due to both its relatively small size and isolated position: Forest cover fluctuated throughout the history of the Congo Basin due to climatic variability, reducing speciation and increasing extinction, while immigration towards the CCLF is limited due to the barrier effect of the Congo River. The implications of these findings are discussed in the context of both fundamental ecology and conservation management.

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