scholarly journals Locating and Dating Land Cover Change Events in the Renosterveld, a Critically Endangered Shrubland Ecosystem

2021 ◽  
Vol 13 (5) ◽  
pp. 834
Author(s):  
Glenn R. Moncrieff
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Temporal Frequency ◽  
Natural Vegetation ◽  
Critically Endangered ◽  
High Resolution Imagery ◽  
Change Events ◽  
Natural Land ◽  
Very High Resolution Imagery ◽  
Forested Ecosystems

Land cover change is the leading cause of global biodiversity decline. New satellite platforms allow for monitoring of habitats in increasingly fine detail, but most applications have been limited to forested ecosystems. I demonstrate the potential for detailed mapping and accurate dating of land cover change events in a highly biodiverse, Critically Endangered, shrubland ecosystem—the Renosterveld of South Africa. Using supervised classification of Sentinel 2 data, and subsequent manual verification with very high resolution imagery, I locate all conversion of Renosterveld to non-natural land cover between 2016 and 2020. Land cover change events are further assigned dates using high temporal frequency data from Planet labs. A total area of 478.6 hectares of Renosterveld loss was observed over this period, accounting for 0.72% of the remaining natural vegetation in the region. In total, 50% of change events were dated to within two weeks of their actual occurrence, and 87% to within two months. The Renosterveld loss identified here is almost entirely attributable to conversion of natural vegetation to cropland through ploughing. Change often preceded the planting and harvesting seasons of rainfed annual grains. These results show the potential for new satellite platforms to accurately map land cover change in non-forest ecosystems, and detect change within days of its occurrence. There is potential to use this and similar datasets to automate the process of change detection and monitor change continuously.

scholarly journals Locating and dating land cover change events in the Renosterveld, a Critically Endangered shrubland ecosystem

2020 ◽  
Author(s):  
Glenn R. Moncrieff
Keyword(s):  
Land Cover ◽  
Land Cover Change ◽  
Temporal Frequency ◽  
Critically Endangered ◽  
High Resolution Imagery ◽  
Change Events ◽  
Natural Land ◽  
Very High Resolution Imagery ◽  
Forested Ecosystems

Land cover change is the leading cause of global biodiversity decline. New satellite platforms allow monitoring of habitats in increasingly fine detail, but most applications have been limited to forested ecosystems. I demonstrate the potential for detailed mapping and accurate dating of land cover change events in a highly biodiverse, Critically Endangered, shrubland ecosystem - the Renosterveld of South Africa. Using supervised classification of Sentinel 2 data, and subsequent manual verification with very high resolution imagery, I locate all conversion of Renosterveld to non-natural land cover between 2016 and 2020. Land cover change events are further assigned dates using high temporal frequency data from Planet labs. 478.6 hectares of Renosterveld loss was observed over this period, accounting for 0.72 % of the remaining natural vegetation in the region. 50% of change events were dated to within two weeks of their actual occurrence, and 87% to within two months. Change often preceded the planting and harvesting seasons of rainfed annual grains. These results show the potential for new satellite platforms to accurately map land cover change in non-forest ecosystems, and detect change within days of its occurrence. There is potential to use this and similar datasets to automate the process of change detection and monitor change continuously.

scholarly journals Supervised continuous land cover change detection in a critically endangered shrubland ecosystem

2021 ◽  
Author(s):  
Glenn R Moncrieff
Keyword(s):  
Neural Networks ◽  
Time Series ◽  
Land Cover ◽  
Land Cover Change ◽  
Habitat Loss ◽  
Continuous Monitoring ◽  
Satellite Image ◽  
Change Events ◽  
Natural Dynamics ◽  
Forested Ecosystems

Existing efforts to rapidly detect land cover change in satellite image time-series have mostly focused on forested ecosystems in the tropics and northern hemisphere. The notable difference in reflectance that occurs following deforestation allow for unsupervised methods, often with manually determined thresholds, to detect land cover change with relative accuracy. Less progress has been made in detecting change in low productivity, disturbance-prone vegetation such as grasslands and shrublands, where natural dynamics can be difficult to distinguish from habitat loss. Renosterveld is a hyperdiverse, critically endangered shrubland ecosystem in South Africa with less than 5-10% of its original extent remaining in small, highly fragmented patches. I demonstrate that supervised classification of satellite image time series using neural networks can accurately detect the transformation of Renosterveld within a few days of its occurrence, and that trained models are suitable for operational continuous monitoring. A training dataset of precisely dated vegetation change events between 2016 and 2020 was obtained from daily, high resolution Planet labs satellite data. This dataset was then used to train 1D convolutional neural networks and Transformers to continuously classify land cover change events in multivariate time-series of vegetation activity from Sentinel 2 satellites as new data becomes available. These models reached a f-score of 0.93, a 61% improvement over the f-score of 0.57 achieved using an unsupervised method designed for forested ecosystems. Models have been deployed to operational use and are producing updated detections of habitat loss every 10 days. There is great potential for supervised approaches to continuous monitoring of habitat loss in ecosystems with complex natural dynamics. A key limiting step is the development of accurately dated labelled datasets of land cover change events with which to train machine learning classifiers.

scholarly journals Correlates of long-term land-cover change and protected area performance at priority conservation sites in Africa

2017 ◽  
Vol 45 (1) ◽  
pp. 49-57 ◽  
Author(s):  
ALISON E. BERESFORD ◽  
GRAEME M. BUCHANAN ◽  
BEN PHALAN ◽  
GEORGE W. ESHIAMWATA ◽  
ANDREW BALMFORD ◽  
...  
Keyword(s):  
Land Cover ◽  
Protected Areas ◽  
Land Cover Change ◽  
Protected Area ◽  
Environmental Gradients ◽  
Survival Rates ◽  
Absolute Difference ◽  
Area Network ◽  
Natural Habitats ◽  
Natural Land

SUMMARYThe loss of natural habitats is a major threat to biodiversity, and protected area designation is one of the standard responses to this threat. However, greater understanding of the drivers of habitat loss and of the circumstances under which protected areas succeed or fail is still needed. We use visual assessment of satellite images to quantify land-cover change over periods of up to 30 years in and around a matched sample of protected and unprotected Important Bird and Biodiversity Areas (IBAs) in Africa. We modelled the annual survival of forests and other natural land covers as a function of a range of environmental and anthropic predictors of plausible drivers. The best-supported model indicated that survival rates of natural land cover were highest in steeper areas, at higher altitudes, in areas with lower human population densities and in areas where the cover of natural habitats was already higher at the start of the period. Survival rates of natural land cover in protected areas were, on average, around twice those in unprotected areas, but the differences between them varied along different environmental gradients. The overall survival rates of both protected and unprotected forests were significantly lower than those of other natural land-cover types, but the net benefit of protection, in terms of the absolute difference in rates of loss between protected and unprotected sites, was higher in forests. Interaction terms indicated that as slope and altitude increased, the natural protection offered by topography increasingly nullified the additional benefits of legislative protection. Furthermore, protected area designation offered reduced additional benefits to the survival of natural land cover in areas where rates of conversion were higher at the start of the observation period. Variation in the impacts of protected area status along different environmental gradients indicates that targets to improve the world's protected area network, such as Aichi Target 11 of the Convention on Biological Diversity, need to look beyond simple area-based metrics. Our methods and results contribute to the development of a protocol for prioritizing places where protection is likely to have the greatest effect.

scholarly journals Holocene vegetation and biomass changes on the Tibetan Plateau – a model-pollen data comparison

2011 ◽  
Vol 7 (3) ◽  
pp. 881-901 ◽  
Author(s):  
A. Dallmeyer ◽  
M. Claussen ◽  
U. Herzschuh ◽  
N. Fischer
Keyword(s):  
Tibetan Plateau ◽  
Land Cover ◽  
Land Cover Change ◽  
Vegetation Change ◽  
Climatic Factors ◽  
Warm Season ◽  
Total Biomass ◽  
The Tibetan Plateau ◽  
Vegetation Shift ◽  
Natural Land

Abstract. Results of a transient numerical experiment performed in a coupled atmosphere-ocean-vegetation model with orbital forcing alone are compared to pollen-based vegetation reconstructions covering the last 6000 yr from four representative sites on the Tibetan Plateau. Causes of the vegetation change and consequences of the biomass storage are analysed. In general, simulated and reconstructed vegetation trends at each site are in good agreement. Both methods reveal a general retreat of the biomass-rich vegetation that is particularly manifested in a strong decrease of forests. However, model and reconstructions often differ with regard to the climatic factors causing the vegetation change at each site. The reconstructions primarily identify decreasing summer monsoon precipitation and changes in the temperature of the warm season as the responsible mechanisms for the vegetation shift. In the model, the land cover change mainly originates from differences in warm/cold seasonal temperatures and only to a lesser extent from precipitation changes. According to the model results, the averaged forest fraction on the Plateau shrinks by almost one-third from mid-Holocene (41.4 %) to present-day (28.3 %). Shrubs, whose fraction is quadrupled at present-day (12.3 %), replace most of this forest. Grass fraction increases from 38.1 % during the mid-Holocene to 42.3 % at present-day. This land cover change results in a decrease of living biomass by 0.62 kgC m−2. Total biomass on the Tibetan Plateau decreases by 1.9 kgC m−2, i.e. approx. 6.64 PgC are released due to the natural land cover change.

scholarly journals Mapping Human Induced Landscape Changes in Israel Between the end of the 19Th Century and the Beginning of the 21Th Century

2014 ◽  
Vol 7 (1) ◽  
pp. 110-145 ◽  
Author(s):  
Gad Schaffer ◽  
Noam Levin
Keyword(s):  
Land Cover ◽  
Protected Areas ◽  
Natural Vegetation ◽  
Physical Factors ◽  
Landscape Changes ◽  
Remnant Vegetation ◽  
Natural Land ◽  
Land Cover Map ◽  
Desert Areas ◽  
The 19Th Century

Abstract This paper examines changes in Israel's landscape by comparing two time periods, 1881 and 2011. For this purpose we compared land cover derived from the Palestine Exploration Fund historical map to a present land cover map that was compiled from 38 different present-day GIS layers. The research aims were (1) to quantitatively examine what were the changes in Israel's landscape between 1881 and 2011; (2) to identify and explain spatial patterns in these landscape changes. Landscape transformation was categorized into five classes: 'residual bare' (no change in natural vegetation, mostly in desert areas); 'residual' (i.e. remnant; no change in natural vegetation class); 'transformed' (changes between different natural vegetation areas); 'replaced' (area which became managed); 'removed' (no or minimal natural vegetation). We found that only 21% of the area retained similar landscape classes as in the past, with the largest changes taking place in ecoregions that were favorable for developing agriculture - Jezreel Valley and the Sharon Plain. Two physical factors had a strong effect on the type of change in the landscape: (1) most of the agricultural areas and human settlements were found in areas ranging between 400-600 mm/year (2) natural land cover features were more common in areas with steeper slopes. We found that the majority of protected areas, 54.6%, are comprised of remnant vegetation classes (i.e. residual transformation class) however more than half of protected areas are located in desert areas and are thus biased in their representation of land cover classes.

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