Multi-temporal Forest Cover Change and Forest Density Trend Detection in a Mediterranean Environment

The loss of forests along with the various types of shrubs in the Mediterranean region is seen as an important driver of climate change and has been repeatedly related with the observed land degradation and desertification in the region. Nevertheless, the extent of woody perennial vegetation cover (WPVC) and its density remain largely unclear. Here, we apply a series of algorithms and methods operationally used in Australia for large-scale WPVC mapping and monitoring and demonstrate their applicability in the Mediterranean region using a Spanish area as the trial site. Five Landsat TM and ETM+ images from various dates spanning 14 years are used to map changes in the extent of WPVC and to identify areas with a declining, stabilising or recovering trend. Results show that the applied methodology, which incorporates (i) preprocessing of the Landsat imagery, (ii) a canonical variate analysis to spectrally discriminate between woody and non-woody land cover types, (iii) a conditional probability network and (iv) spectral indices for mapping woody cover and density trend, is highly successful and well suited for use in Mediterranean environments. A rigorous accuracy assessment is undertaken producing overall accuracies above 97% for both woody and non-woody cover types and all dates. Results also show that in the area of study, the majority of WPVC disturbances were due to forest fires, which represent the region's most frequent natural and anthropogenic disturbance. This raises significant concerns about the future of the area's WPVC. Regeneration compensated to some degree for the high disturbance rates. Copyright © 2015 John Wiley & Sons, Ltd

High-resolution global maps of tidal flat ecosystems from 1984 to 2019

Assessments of the status of tidal flats, one of the most extensive coastal ecosystems, have been hampered by a lack of data on their global distribution and change. Here we present globally consistent, spatially-explicit data of the occurrence of tidal flats, defined as sand, rock or mud flats that undergo regular tidal inundation. More than 1.3 million Landsat images were processed to 54 composite metrics for twelve 3-year periods, spanning four decades (1984–1986 to 2017–2019). The composite metrics were used as predictor variables in a machine-learning classification trained with more than 10,000 globally distributed training samples. We assessed accuracy of the classification with 1,348 stratified random samples across the mapped area, which indicated overall map accuracies of 82.2% (80.0–84.3%, 95% confidence interval) and 86.1% (84.2–86.8%, 95% CI) for version 1.1 and 1.2 of the data, respectively. We expect these maps will provide a means to measure and monitor a range of processes that are affecting coastal ecosystems, including the impacts of human population growth and sea level rise

A study of the usefulness of Skylab EREP data for earth resources studies in Australia

The author has identified the following significant results. In subhumid, vegetated areas, S190B photography: (1) has a potentially operational role in detecting lineaments in 1:100,000 scale geological mapping and in major civil engineering surveys; (2) is of limited value for regional lithological mapping at 1:500,000 scale; and (3) provided much useful synoptic information and some detailed information of direct value to the mapping of nonmineral natural resources such as vegetation, land soil, and water. In arid, well exposed areas, S190B photography could be used: (1) with a limited amount of field traverses, to produce reliable 1:500,000 scale geological maps of sedimentary sequences; (2) to update superficial geology on 1:250,000 scale maps; and (3) together with the necessary field studies, to prepare landform, soil, and vegetation maps at 1:1,000,000 scale. Skylab photography was found to be more useful than LANDSAT images for small scale mapping of geology and land types, and for the revision of topographic maps at 1:100,000 scale, because of superior spatial resolution and stereoscopic coverage

Using dense Sentinel-2 time series to explore combined fire and drought impacts in eucalypt forests

Following one of the driest years on record, millions of hectares of forests in southeast Australia were burned in the 2019-20200 "Black Summer" wildfires. In addition to the areas burned, drought related canopy collapse, dieback and tree mortality was widely observed. In this paper, we present a method to map canopy damage due to drought and fire across a large area. Sentinel-2 satellite imagery was used in a monthly time series to highlight areas of forest where the Normalized Burn Ratio index was significantly below a pre-disturbance "stable" period. The stable period was defined as the 3 years prior to 2019 and the disturbance thresholds are based on bioregion specific standard deviations below pre-disturbance means. The novel methods enabled drought impacted forests to be identified, including those which were subsequently burned by wildfire. Across the 20 Mha of forests studied, 9.9 Mha (49%) fell below the disturbance threshold. Of that, 5.8 Mha was disturbed by fire and a further 4.1 Mha by drought outside of the fire extent. Within the fire extent, almost 0.9 Mha was identified as being significantly drought affected prior to being burned. An analysis of spectral recovery following substantial rainfall from February 2020 onward indicates that most of the areas impacted by both drought and fire have similar rates of recovery to those impacted only by fire. There are some areas, however, where the combined effects of the "double disturbance "appears to be hindering recovery. The methods presented here are easily transferrable and demonstrate an approach for monitoring forest disturbance at higher temporal and spatial scales than those typically used

Multi-decadal trends in global terrestrial evapotranspiration and its components

Evapotranspiration (ET) is the process by which liquid water becomes water vapor and energetically this accounts for much of incoming solar radiation. If this ET did not occur temperatures would be higher, so understanding ET trends is crucial to predict future temperatures. Recent studies have reported prolonged declines in ET in recent decades, although these declines may relate to climate variability. Here, we used a well-validated diagnostic model to estimate daily ET during 1981–2012, and its three components: transpiration from vegetation (Et), direct evaporation from the soil (Es) and vaporization of intercepted rainfall from vegetation (Ei). During this period, ET over land has increased significantly (p < 0.01), caused by increases in Et and Ei, which are partially counteracted by Es decreasing. These contrasting trends are primarily driven by increases in vegetation leaf area index, dominated by greening. The overall increase in Et over land is about twofold of the decrease in Es. These opposing trends are not simulated by most Coupled Model Intercomparison Project phase 5 (CMIP5) models, and highlight the importance of realistically representing vegetation changes in earth system models for predicting future changes in the energy and water cycle

A multi-agency project of the Western Australian Salinity Action Plan supported by the Natural Heritage Trust

Land Monitor is a multi-agency project of the Western Australian Salinity Action Plan supported by the Natural Heritage Trust. It will provide land managers and administrators with baseline salinity and vegetation data for monitoring changes over time, and land height data from which contours accurate to two metre intervals can be produced. The Project will also provide estimates of areas at risk from secondary or future salinisation. Land Monitor will cover the 18 million hectares of agricultural area of south-west, Western Australia. Sequences of calibrated Landsat Thematic Mapper satellite images integrated with landform information derived from height data, ground truthing and other existing mapped data sets are used as the basis for monitoring changes in salinity and woody vegetation. Heights are derived on a 10m grid from stereo aerial photography flown at 1:40,000 scale, using soft-copy automatic terrain extraction (image correlation) techniques. Proposed Land Monitor products include salinity maps, predicted salinity maps, enhanced imagery, vegetation status maps and spectral / temporal statistics. These products will be available in a range of formats and scales, from paddock, farm to catchment and shire scales to suit customer needs

Remote Sensing of Savannas and Woodlands

Savannas and woodlands are one of the most challenging targets for remote sensing. This book provides a current snapshot of the geographical focus and application of the latest sensors and sensor combinations in savannas and woodlands. It includes feature articles on terrestrial laser scanning and on the application of remote sensing to characterization of vegetation dynamics in the Mato Grosso, Cerrado and Caatinga of Brazil. It also contains studies focussed on savannas in Europe, North America, Africa and Australia. It should be important reading for environmental practitioners and scientists globally who are concerned with the sustainability of the global savanna and woodland biome

Remote sensing environmental change in southern African savannahs : a case study of Namibia

Savannah biomes cover a fifth of Earth’s surface, harbour many of the world’s most iconic species and most of its livestock and rangeland, while sustaining the livelihoods of an important proportion of its human population. They provide essential ecosystem services and functions, ranging from forest, grazing and water resources, to global climate regulation and carbon sequestration. However, savannahs are highly sensitive to human activities and climate change. Across sub-Saharan Africa, climatic shifts, destructive wars and increasing anthropogenic disturbances in the form of agricultural intensification and urbanization, have resulted in widespread land degradation and loss of ecosystem services. Yet, these threatened ecosystems are some of the least studied or protected, and hence should be given high conservation priority. Importantly, the scale of land degradation has not been fully explored, thereby comprising an important knowledge gap in our understanding of ecosystem services and processes, and effectively impeding conservation and management of these biodiversity hotspots. The primary drivers of land degradation include deforestation, triggered by the increasing need for urban and arable land, and concurrently, shrub encroachment, a process in which the herbaceous layer, a defining characteristic of savannahs, is replaced with hardy shrubs. These processes have significant repercussions on ecosystem service provision, both locally and globally, although the extents, drivers and impacts of either remain poorly quantified and understood. Additionally, regional aridification anticipated under climate change, will lead to important shifts in vegetation composition, amplified warming and reduced carbon sequestration. Together with a growing human population, these processes are expected to compound the risk of land degradation, thus further impacting key ecosystem services. Namibia is undergoing significant environmental and socio-economic changes. The most pervasive change processes affecting its savannahs are deforestation, degradation and shrub encroachment. Yet, the extent and drivers of such change processes are not comprehensively quantified, nor are the implications for rural livelihoods, sustainable land management, the carbon cycle, climate and conservation fully explored. This is partly due to the complexities of mapping vegetation changes with satellite data in savannahs. They are naturally spatially and temporally variable owing to erratic rainfall, divergent plant functional type phenologies and extensive anthropogenic impacts such as fire and grazing. Accordingly, this thesis aims to (i) quantify distinct vegetation change processes across Namibia, and (ii) develop methodologies to overcome limitations inherent in savannah mapping. Multi-sensor satellite data spanning a range of spatial, temporal and spectral resolutions are integrated with field datasets to achieve these aims, which are addressed in four journal articles. Chapters 1 and 2 are introductory. Chapter 3 exploits the Landsat archive to track changes in land cover classes over five decades throughout the Namibian Kalahari woodlands. The approach addresses issues implicit in change detection of savannahs by capturing the distinct phenological phases of woody vegetation and integrating multi-sensor, multi-source data. Vegetation extent was found to have decreased due to urbanization and small-scale arable farming. An assessment of the limitations leads to Chapter 4, which elaborates on the previous chapter by quantifying aboveground biomass changes associated with deforestation and shrub encroachment. The approach centres on fusing multiple satellite datasets, each acting as a proxy for distinct vegetation properties, with calibration/validation data consisting of concurrent field and LiDAR measurements. Biomass losses predominate, demonstrating the contribution of land management to ecosystem carbon changes. To identify whether biomass is declining across the country, Chapter 5 focuses on regional, moderate spatial resolution time-series analyses. Phenological metrics extracted from MODIS data are used to model observed fractional woody vegetation cover, a proxy for biomass. Trends in modelled fractional woody cover are then evaluated in relation to the predominant land-uses and precipitation. Negative trends slightly outweighed positive trends, with decreases arising largely in protected, urban and communal areas. Since precipitation is a fundamental control on vegetation, Chapter 6 investigates its relation to NDVI, by assessing to what extent observed trends in vegetation cover are driven by rainfall. NDVI is modelled as a function of precipitation, with residuals assumed to describe the fraction of NDVI not explained by rainfall. Mean annual rainfall and rainfall amplitude show a positive trend, although extensive “greening” is unrelated to rainfall. NDVI amplitude, used as a proxy for vegetation density, indicates a widespread shift to a denser condition. In Chapter 7, trend analysis is applied to a Landsat time-series to overcome spatial and temporal limitations characteristic of the previous approaches. Results, together with those of the previous chapters, are synthesized and a synopsis of the main findings is presented. Vegetation loss is predominantly caused by demand for urban and arable land. Greening trends are attributed to shrub encroachment and to a lesser extent conservation laws, agroforestry and rangeland management, with precipitation presenting little influence. Despite prevalent greening, degradation processes associated with shrub encroachment, including soil erosion, are likely to be widespread. Deforestation occurs locally while shrub encroachment occurs regionally. This thesis successfully integrates multi-source data to map, measure and monitor distinct change processes across scales