Robust trends of landscape dynamics in the Arctic Lena Delta with temporally dense Landsat time-series stacks, with links to GeoTIFFs

Arctic permafrost landscapes are among the most vulnerable and dynamic landscapes globally, but due to their extent and remoteness most of the landscape changes remain unnoticed. In order to detect disturbances in these areas we developed an automated processing chain for the calculation and analysis of robust trends of key land surface indicators based on the full record of available Landsat TM, ETM +, and OLI data. The methodology was applied to the ~ 29,000 km**2 Lena Delta in Northeast Siberia, where robust trend parameters (slope, confidence intervals of the slope, and intercept) were calculated for Tasseled Cap Greenness, Wetness and Brightness, NDVI, and NDWI, and NDMI based on 204 Landsat scenes for the observation period between 1999 and 2014. The resulting datasets revealed regional greening trends within the Lena Delta with several localized hot-spots of change, particularly in the vicinity of the main river channels. With a 30-m spatial resolution various permafrost-thaw related processes and disturbances, such as thermokarst lake expansion and drainage, fluvial erosion, and coastal changes were detected within the Lena Delta region, many of which have not been noticed or described before. Such hotspots of permafrost change exhibit significantly different trend parameters compared to non-disturbed areas. The processed dataset, which is made freely available through the data archive PANGAEA, will be a useful resource for further process specific analysis by researchers and land managers. With the high level of automation and the use of the freely available Landsat archive data, the workflow is scalable and transferrable to other regions, which should enable the comparison of land surface changes in different permafrost affected regions and help to understand and quantify permafrost landscape dynamics.

Mapping decadal land cover changes in the woodlands of north eastern Namibia using the Landsat satellite archive (1975-2014)

Woodland savannahs provide essential ecosystem functions and services to communities. On the African continent, they are widely utilized and converted to intensive land uses. This study investigates the land cover changes of 108,038 km**2 in NE Namibia using multi-temporal, multi-sensor Landsat imagery, at decadal intervals from 1975 to 2014, with a post-classification change detection method and supervised Regression Tree classifiers. We discuss likely impacts of land tenure and reforms over the past four decades on changes in land use and land cover. These changes included losses, gains and exchanges between predominant land cover classes. Exchanges comprised logical conversions between woodland and agricultural classes, implying woodland clearing for arable farming, cropland abandonment and vegetation succession. The most dominant change was a reduction in the area of the woodland class due to the expansion of the agricultural class, specifically, small-scale cereal and pastoral production. Woodland area decreased from 90% of the study area in 1975 to 83% in 2014, while cleared land increased from 9% to 14%. We found that the main land cover changes are conversion from woodland to agricultural and urban land uses, driven by urban expansion and woodland clearing for subsistence-based agriculture and pastoralism.

Table 1: Glacier measurements from air photos 1969 and landsat images 1972 and 1973

The extent of snow cover at the end of the ablation season on glaciers in the Tyrolean Alps in 1972 and 1973 was determined from Landsat-1 Multispectral Scanner (MSS) images. For snovv mapping the MSS-images with a ground resolution of 80 meters were enlarged to a scale of 1: 100.000 by photographic methods. Different appearance of snow cover in the 4 MSS-channels is discussed in connection with ground truth control. The accuracy of snow and ice mapping from Landsat images was checked on 15 glaciers with an area from 1 to 10 km2 by aerial photography and/or ground truth control. These comparisons imply the usefulness of Landsat images for snow mapping on glaciers of a few square kilometers. The altitude of the equilibrium line was determined from Landsat images for 53 glaciers in the Tyrolean Alps. The regional differences in the equilibrium line altitude correspond to the regional precipitation patterns. The equilibrium line was identical with the snow line at the end of the budget year 1971/1972; therefore it was possible to determine the equilibrium line from satellite images. For 1968/69 the equilibrium line was mapped from aerial photographs for several glaciers. In 1972/73 mass balance was strongly negative and the equilibrimn line was within the firn area of the glaciers. Therefore it was not possible to distinguish between accumulation and ablation areas from the Landsat images of September 1973; however, snow and ice areas could be olearly differentiated. The ratios of accumulation area 01' snow area to the total area of the glaciers were determineel from satellite images and aerial photography separately for aelvancing anel for retreating glaciers and were relateel to the mass balance. In the budget years 1968/69 and 1972/73 with negative mass balance the accumulation area ratios of the advancing glacien; were olearly different from the ratios of the retreating glaciers, in 1971/72 with positive 01' balanced mass budget the differences between advancing and retreating glaciers were not significant.

Landsat derived percent vegetation cover of Israel (as of 2003)

Wildfires are part of the Mediterranean ecosystem, however, in Israel all wildfires are human caused, either intentionally or un-intentionally. In this study we aimed to develop and test a new method for mapping fire scars from MODIS imagery, to examine the temporal and spatial patterns of wildfires in Israel in the 2000s and to examine the factors controlling Israel's wildfire regime. To map the fires we used two 'off-the-shelf' MODIS fire products as our basis-the 1 km MODIS Collection 5 fire hotspots, the 500 m MCD45A1 burnt areas-and we created a new set of fire scar maps from the 250 m MOD13Q1 product. We carried out a cross comparison of the three MODIS based wildfire scar maps and evaluated them independently against the wild fire scars mapped from 30 m Landsat TM imagery. To examine the factors controlling wildfires we used GIS layers of rainfall, land use, and a Landsat-based national vegetation map. Wildfires occurred in areas where annual rainfall was above 250 mm, mostly in areas with herbaceous vegetation. Wildfire frequency was especially high in the Golan Heights and in the foothills of the Judean mountains, and a high correspondence was found between military training zones and the spatial distribution of fire scars. The use of MODIS satellite images enabled us to map wildfires at a national scale due to the high temporal resolution of the sensor. Our MOD13Q1 based mapping of fire scars adequately mapped large (>1 km**2) fires with accuracies above 80%. Such large fires account for a large proportion of all fires, and pose the greatest threats. This database can aid managers in determining wildfire risks in space and in time.

Classified Adélie penguin colonies from Landsat data

Breeding distribution of the Adelie penguin, Pygoscelis adeliae, was surveyed with Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data along the coastline of Antarctica, an area covering approximately 330° of longitude. An algorithm was designed to minimize the radiometric contribution from exogenous sources and to retrieve Adelie penguin colony location and spatial extent from the ETM+ data. In all, 9143 individual pixels were classified as belonging to an Adelie penguin colony class out of the entire dataset of 195 ETM+ scenes, where the dimension of each pixel is 30 m by 30 m, and each scene is approximately 180 km by 180 km. Pixel clustering identified a total of 187 individual Adelie penguin colonies, ranging in size from a single pixel (900 m**2) to a maximum of 875 pixels (0.788 km**2). Colony retrievals have a very low error of commission, on the order of 1 percent or less, and the error of omission was estimated to be 2.9 percent by population based on comparisons with direct observations from surveys across east Antarctica. Thus, the Landsat retrievals can successfully locate Adelie penguin colonies that account for ~97 percent of a regional population. Geographic coordinates and the spatial extent of each colony retrieved from the Landsat data are available publically. Regional analysis found several areas where the Landsat retrievals suggest populations that are significantly larger than published estimates. Six Adelie penguin colonies were found that are believed to be unreported in the literature.

The Lena River Delta - Land cover classification of tundra environments based on Landsat 7 ETM+ data and its application for upscaling of methane emissions

The Lena River Delta, situated in Northern Siberia (72.0 - 73.8° N, 122.0 - 129.5° E), is the largest Arctic delta and covers 29,000 km**2. Since natural deltas are characterised by complex geomorphological patterns and various types of ecosystems, high spatial resolution information on the distribution and extent of the delta environments is necessary for a spatial assessment and accurate quantification of biogeochemical processes as drivers for the emission of greenhouse gases from tundra soils. In this study, the first land cover classification for the entire Lena Delta based on Landsat 7 Enhanced Thematic Mapper (ETM+) images was conducted and used for the quantification of methane emissions from the delta ecosystems on the regional scale. The applied supervised minimum distance classification was very effective with the few ancillary data that were available for training site selection. Nine land cover classes of aquatic and terrestrial ecosystems in the wetland dominated (72%) Lena Delta could be defined by this classification approach. The mean daily methane emission of the entire Lena Delta was calculated with 10.35 mg CH4/m**2/d. Taking our multi-scale approach into account we find that the methane source strength of certain tundra wetland types is lower than calculated previously on coarser scales.

Land cover classification of Samoylov Island and Landsat subpixel water cover of Lena River Delta, Siberia, with links to ESRI grid files

Ignoring small-scale heterogeneities in Arctic land cover may bias estimates of water, heat and carbon fluxes in large-scale climate and ecosystem models. We investigated subpixel-scale heterogeneity in CHRIS/PROBA and Landsat-7 ETM+ satellite imagery over ice-wedge polygonal tundra in the Lena Delta of Siberia, and the associated implications for evapotranspiration (ET) estimation. Field measurements were combined with aerial and satellite data to link fine-scale (0.3 m resolution) with coarse-scale (upto 30 m resolution) land cover data. A large portion of the total wet tundra (80%) and water body area (30%) appeared in the form of patches less than 0.1 ha in size, which could not be resolved with satellite data. Wet tundra and small water bodies represented about half of the total ET in summer. Their contribution was reduced to 20% in fall, during which ET rates from dry tundra were highest instead. Inclusion of subpixel-scale water bodies increased the total water surface area of the Lena Delta from 13% to 20%. The actual land/water proportions within each composite satellite pixel was best captured with Landsat data using a statistical downscaling approach, which is recommended for reliable large-scale modelling of water, heat and carbon exchange from permafrost landscapes.

Mangrove cover in the Red Sea (1972-2013)

Across the Earth, mangroves play an important role in coastal protection, both as nurseries and carbon sinks. However, due to various human and environmental impacts, the coverage of mangroves is declining on a global scale. The Red Sea is in the northern-most area of the distribution range of mangroves. Little is known about the surface covered by mangroves at this northern limit or about the changes experienced by Red Sea mangroves. We sought to study changes in the coverage of Red Sea mangroves by using multi-temporal Landsat data (1972, 2000 and 2013). Interestingly, our results show that there has been no decline in mangrove stands in the Red Sea but rather a slight increase. The area covered by mangroves is about 69 km**2 along the African shore and 51 km**2 along the Arabian Peninsula shore. From 1972 to 2013, the area covered by mangroves increased by about 0.29%/y. We conclude that the trend exhibited by Red Sea mangroves departs from the general global decline of mangroves. Along the Red Sea, mangroves expanded by 12% over the 41 years from 1972 to 2013. Losses to Red Sea mangroves, mostly due to coastal development, have been compensated by afforestation projects.

Updated bathymetric chart of the East Aral Sea

The Aral Sea is located in an arid region with much sand and salt deposits in the surrounding barren open land. Hence, significant displacements of sediments into the lakebed by the action of wind, water, gravity, or snow are likely. The bathymetry of the lake was last observed in the 1960s, and within the last half century, the structure of the lakebed has changed. Based on satellite observations of the temporal changes of shoreline (Landsat optical remote sensing) and water level (multi-mission satellite altimetry) over more than one decade an updated bathymetric chart for the East Basin of the Aral Sea has been generated. During this time, the geometry of the shallow East Basin experienced strong fluctuations due to the occurrence of periods of drying and strong inflow. By the year 2014 the East Basin fell dry. The dynamic behavior of the basin allowed for estimating the lake's bathymetry from a series of satellite-based information. The river mouth made its impression in the present East Aral Sea, because its shrinking led to the inflow of much sediment into the lake's interior. In addition, salt deposits along the shorelines increased the corresponding elevation, a phenomenon that is more pronounced in the reduced lakebed because of increased salinity. It must be noted that height estimates from satellite altimetry were only possible down to a minimum elevation of 27 m above sea level due to a lack of reliable altimetry data over the largely reduced water surface. In order to construct a complete bathymetric chart of the lakebed of the East Aral Sea heights below 27 m were obtained solely from Landsat optical images following the SRB (Selected Region Boundary) approach as described by Singh et al. (2015).

Seagrass time-series analysis products, in Moreton Bay, Australia, with links to GeoTIFFs

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (~200 km**2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Mapped distribution of tidal flats across China, Manchuria and Korea (1952-1964)

A map of the tidal flats of China, Manchuria and Korea depicted in US Army Map Service Series L500, L542 and L552 topographic maps (compiled between 1950 and 1964). The topographic maps were georeferenced against prominent topographical features in L1T processed Landsat imagery and the foreshore flat class was manually delineated. For further information refer to Murray et. al. (2014).

Improved digital elevation model (DEM) for Lake Eyre, Australia

Here we demonstrate the applicability of using altimetry data and Landsat imagery to provide the most accurate digital elevation model (DEM) of Australia's largest playa lake - Lake Eyre. We demonstrate through the use of geospatial techniques a robust assessment of lake area and volume of recent lake-filling episodes whilst also providing the most accurate estimates of area and volume for larger lake filling episodes that occurred throughout the last glacial cycle. We highlight that at a depth of 25 m Lake Mega-Eyre would merge with the adjacent Lake Mega-Frome to form an immense waterbody with a combined area of almost 35,000 km**2 and a combined volume of ~520 km**3. This would represent a vast water body in what is now the arid interior of the Australian continent. The improved DEM is more reliable from a geomorphological and hydrological perspective and allows a more accurate assessment of water balance under the modern hydrological regime. The results presented using GLAS/ICESat data suggest that earlier historical soundings were correct and the actual lowest topographic point in Australia is -15.6 m below sea level. The results also contrast nicely the different basin characteristics of two adjacent lake systems; Lake Eyre and Lake Frome.

Time-series of seagrass and land cover maps from 1972 to 2010, in South East Queensland, Australia, with links to GeoTIFFs

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.