Classifying drivers of global forest loss

Science ◽  
2018 ◽  
Vol 361 (6407) ◽  
pp. 1108-1111 ◽  
Author(s):  
Philip G. Curtis ◽  
Christy M. Slay ◽  
Nancy L. Harris ◽  
Alexandra Tyukavina ◽  
Matthew C. Hansen
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Nongovernmental Organizations ◽  
Satellite Imagery ◽  
Forest Disturbance ◽  
Classification Model ◽  
Forest Loss ◽  
Shifting Agriculture ◽  
Commodity Production

Global maps of forest loss depict the scale and magnitude of forest disturbance, yet companies, governments, and nongovernmental organizations need to distinguish permanent conversion (i.e., deforestation) from temporary loss from forestry or wildfire. Using satellite imagery, we developed a forest loss classification model to determine a spatial attribution of forest disturbance to the dominant drivers of land cover and land use change over the period 2001 to 2015. Our results indicate that 27% of global forest loss can be attributed to deforestation through permanent land use change for commodity production. The remaining areas maintained the same land use over 15 years; in those areas, loss was attributed to forestry (26%), shifting agriculture (24%), and wildfire (23%). Despite corporate commitments, the rate of commodity-driven deforestation has not declined. To end deforestation, companies must eliminate 5 million hectares of conversion from supply chains each year.

scholarly journals Changes in Land Cover Analysis in The Gulf Coast Kendari Using High Resolution Satellite Image (Period: 2003-2009)

2013 ◽  
Vol 27 (2) ◽  
pp. 179 ◽  
Author(s):  
Laode Muh. Golok Jaya
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Land Cover ◽  
Public Space ◽  
Land Cover Change ◽  
Satellite Imagery ◽  
Gulf Coast ◽  
Secondary Forest ◽  
Satellite Image ◽  
Primary Forest

This research was aimed to indentify land cover change in coastal area of Kendari Bay in period 2003 to 2009. The satellite imagery data (Ikonos and Quick Bird) collected in 2003 and 2009 were used in this research to obtain the land cover change. The method used in this research was comparing the classification of satellite imagery. Field survey was conducted using handheld GPS for ground truth.  The result of this research showed us the land use change in period 2003-2009. Mangrove vegetation decreased 56.57 Ha and the fishpond also decreased 205.5 Ha. The primary forest decreased into 3.28 Ha in year 2009. The secondary forest also decreases 124.84 Ha. In the same time the urban area increased from 382.37 Ha in year 2003 to 674.37 Ha in 2009. The land use change also occured for the public space which increased from 6.49 Ha in 2003 to 18.46 Ha in 2009 or increased 11,97 Ha.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals Land Use Land Cover map segmentation using Remote Sensing: A Case study of Ajoy river watershed, India

2020 ◽  
Vol 30 (1) ◽  
pp. 273-286
Author(s):  
Kalyan Mahata ◽  
Rajib Das ◽  
Subhasish Das ◽  
Anasua Sarkar
Keyword(s):  
Land Use ◽  
Image Segmentation ◽  
Cellular Automata ◽  
Land Cover ◽  
Satellite Imagery ◽  
Current Model ◽  
Discrete Dynamical System ◽  
Land Use Land Cover ◽  
Data Set ◽  
Validity Indices

Abstract Image segmentation in land cover regions which are overlapping in satellite imagery, is one crucial challenge. To detect true belonging of one pixel becomes a challenging problem while classifying mixed pixels in overlapping regions. In current work, we propose one new approach for image segmentation using a hybrid algorithm of K-Means and Cellular Automata algorithms. This newly implemented unsupervised model can detect cluster groups using hybrid 2-Dimensional Cellular-Automata model based on K-Means segmentation approach. This approach detects different land use land cover areas in satellite imagery by existing K-Means algorithm. Since it is a discrete dynamical system, cellular automaton realizes uniform interconnecting cells containing states. In the second stage of current model, we experiment with a 2-dimensional cellular automata to rank allocations of pixels among different land-cover regions. The method is experimented on the watershed area of Ajoy river (India) and Salinas (California) data set with true class labels using two internal and four external validity indices. The segmented areas are then compared with existing FCM, DBSCAN and K-Means methods and verified with the ground truth. The statistical analysis results also show the superiority of the new method.

scholarly journals First evidence for an Amazonian insect migration in the butterfly Panacea prola (Lepidoptera: Nymphalidae)

2020 ◽  
Author(s):  
Geoffrey Gallice ◽  
Riccardo Mattea ◽  
Allison Stoiser
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Global Climate ◽  
Insect Species ◽  
Forest Loss ◽  
Environmental Cues ◽  
Mass Movements ◽  
Insect Migration ◽  
Nymphalid Butterfly ◽  
The Tropics

ABSTRACTInsect migrations rival those of vertebrates in terms of numbers of migrating individuals and even biomass, although instances of the former are comparatively poorly documented. This is especially true in the world’s tropics, which harbor the vast majority of Earth’s insect species. Understanding these mass movements is of critical and increasing importance as global climate and land use change accelerate and interact to alter the environmental cues that underlie migration, particularly in the tropics. Here, we provide the first evidence for an insect migration for the nymphalid butterfly Panacea prola in the Amazon, the world’s largest and most biodiverse rainforest that is experiencing a shifting climate and rapid forest loss.

scholarly journals Impacts of changes in land use and land cover on atmospheric chemistry and air quality over the 21st century

2011 ◽  
Vol 11 (5) ◽  
pp. 15469-15495 ◽  
Author(s):  
S. Wu ◽  
L. J. Mickley ◽  
J. O. Kaplan ◽  
D. J. Jacob
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Land Use Change ◽  
Land Cover ◽  
21St Century ◽  
Secondary Organic Aerosols ◽  
Surface Ozone ◽  
Organic Aerosols ◽  
Ozone Concentrations ◽  
Anthropogenic Land Use

Abstract. The effects of future land use and land cover change on the chemical composition of the atmosphere and air quality are largely unknown. To investigate the potential effects associated with future changes in vegetation driven by atmospheric CO2 concentrations, climate, and anthropogenic land use over the 21st century, we performed a series of model experiments combining a general circulation model with a dynamic global vegetation model and an atmospheric chemical-transport model. Our results indicate that climate- and CO2-induced changes in vegetation composition and density could lead to decreases in summer afternoon surface ozone of up to 10 ppb over large areas of the northern mid-latitudes. This is largely driven by the substantial increases in ozone dry deposition associated with changes in the composition of temperate and boreal forests where conifer forests are replaced by those dominated by broadleaf tree types, as well as a CO2-driven increase in vegetation density. Climate-driven vegetation changes over the period 2000–2100 lead to general increases in isoprene emissions, globally by 15 % in 2050 and 36 % in 2100. These increases in isoprene emissions result in decreases in surface ozone concentrations where the NOx levels are low, such as in remote tropical rainforests. However, over polluted regions, such as the northeastern United States, ozone concentrations are calculated to increase with higher isoprene emissions in the future. Increases in biogenic emissions also lead to higher concentrations of secondary organic aerosols, which increase globally by 10 % in 2050 and 20 % in 2100. Surface concentrations of secondary organic aerosols are calculated to increase by up to 1 μg m−3 for large areas in Eurasia. When we use a scenario of future anthropogenic land use change, we find less increase in global isoprene emissions due to replacement of higher-emitting forests by lower-emitting cropland. The global atmospheric burden of secondary organic aerosols changes little by 2100 when we account for future land use change, but both secondary organic aerosols and ozone show large regional changes at the surface.

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