Development and application of microwave assisted extraction (MAE) for the extraction of five polycyclic aromatic hydrocarbons in sediment samples in Johannesburg area, South Africa

A microwave-assisted extraction (MAE) method was verified and applied for the extraction of polycyclic aromatic hydrocarbons (PAHs) in sediment samples. Soxhlet extraction was used as the reference method. The optimum MAE was carried out with 20 mL of hexane/acetone (1:1, v/v) mixture in a 1-g sample at 250 W for 20 min. Soxhlet extraction was carried out with 250 mL of dichloromethane:hexane (1:1, v/v) mixture in a 15-g sample for 24 h in a water bath maintained at 60 °C. The collected extracts were both cleaned up, reduced to 1 mL under nitrogen and then injected into an HPLC fluorescence. To increase the sample throughput, simultaneous MAE was performed. The obtained percentage recoveries ranged from 61 to 93 and 88–98 for MAE and SE, respectively. The optimised MAE method was validated using certified reference material. It was then applied to real sediment samples from in and around the greater Johannesburg area. The sediments from Jukskei River were found to be the most polluted while Hartbeespoort Dam sediments were found to be least polluted. The overall order of concentrations for the studied PAHs per site was as follows: Jukskei River?>?Kempton Park?>?Centurion Dams?>?Natalspruit River (PIT)?>?Hartbeespoort Dam.     

DDT, DDE, and 1-hydroxypyrene levels in children (in blood and urine samples) from Chiapas and Oaxaca, Mexico

The aim of this study was to evaluate the DDT, DDE, and 1-hydroxypyrene exposure levels of children living in communities located in southeastern Mexico. The study communities were Lacanja and Victoria in Chiapas state and Ventanilla in Oaxaca state. Children living in Lacanja had total blood DDT levels (mean?±?SD, 29,039.6?±?11,261.4 ng/g lipid) that were significantly higher than those of children in Victoria (10,220.5?±?7,893.1 ng/g lipid) and Ventanilla (11,659.7?±?6,683.7 ng/g lipid). With respect to the 1-hydroxypyrene levels in urine samples, the levels in Lacanja (4.8?±?4.1 μg/L or 4.5?±?3.9 μmol/mol creatinine) and Victoria (4.6?±?3.8 μg/L or 3.9?±?3.0 μmol/mol Cr) were significantly higher than levels found in Ventanilla (3.6?±?1.4 μg/L or 2.5?±?0.5 μmol/mol Cr). In conclusion, our data indicate high levels of exposure in children living in the communities studied in this work. The evidence found in this study could be further used as a trigger to revisit local policies on environmental exposures.     

Quantification of triazine herbicides in soil by microwave-assisted extraction and high-performance liquid chromatography

A method for the determination of herbicides residues, triazine (atrazine, metribuzin, ametryn, and terbutryn), in soil samples with high-performance liquid chromatography (HPLC)?CUV detection is described. The proposed method is based on microwave-assisted extraction (MAE) of soil samples for 4 min at 80% of 850-W magnetron outputs in the presence of mixture of solvents (methanol/acetonitrile/ethylacetate). Related important factors influencing the MAE efficiency, such as the solvent type and volume, irradiation energy, and time, were optimized in detail. Calibration curve ranges established using HPLC for metribuzin, atrazine, ametryn, and terbutryn are 1.0?C19.0, 0.9?C18.0, 0.6?C11.0, and 0.7?C11.0 µg mL^???1, respectively. The limits of detection of metribuzin, atrazine, ametryn, and terbutryn are 0.30, 0.24, 0.16, and 0.20 µg mL^???1 while limits of quantification are 1.0, 0.80, 0.50, and 0.60 µg mL^???1, respectively. A Plackett?CBurman factorial design was used as a screening method in order to select the variables that influence MAE extraction. The recoveries of the method at three different spiked levels were assessed by analyzing real soil samples and were found to be in the range of 83.33 ± 0.12?C96.33 ± 0.23 with good precision (<8%).     

Mapping trees outside forests using high-resolution aerial imagery: a comparison of pixel- and object-based classification approaches

Discrete trees and small groups of trees in nonforest settings are considered an essential resource around the world and are collectively referred to as trees outside forests (ToF). ToF provide important functions across the landscape, such as protecting soil and water resources, providing wildlife habitat, and improving farmstead energy efficiency and aesthetics. Despite the significance of ToF, forest and other natural resource inventory programs and geospatial land cover datasets that are available at a national scale do not include comprehensive information regarding ToF in the United States. Additional ground-based data collection and acquisition of specialized imagery to inventory these resources are expensive alternatives. As a potential solution, we identified two remote sensing-based approaches that use free high-resolution aerial imagery from the National Agriculture Imagery Program (NAIP) to map all tree cover in an agriculturally dominant landscape. We compared the results obtained using an unsupervised per-pixel classifier (independent component analysis—[ICA]) and an object-based image analysis (OBIA) procedure in Steele County, Minnesota, USA. Three types of accuracy assessments were used to evaluate how each method performed in terms of: (1) producing a county-level estimate of total tree-covered area, (2) correctly locating tree cover on the ground, and (3) how tree cover patch metrics computed from the classified outputs compared to those delineated by a human photo interpreter. Both approaches were found to be viable for mapping tree cover over a broad spatial extent and could serve to supplement ground-based inventory data. The ICA approach produced an estimate of total tree cover more similar to the photo-interpreted result, but the output from the OBIA method was more realistic in terms of describing the actual observed spatial pattern of tree cover.     

Coral communities of the remote atoll reefs in the Nansha Islands, southern South China Sea

During the months of May and June in the year 2007, a survey was conducted regarding coral reef communities in the remote atolls (Zhubi Reef and Meiji Reef) of Nansha Islands, southern South China Sea. The goals of the survey were to: (1) for the first time, compile a scleractinian coral check-list; (2) estimate the total richness, coral cover, and growth forms of the community; and (3) describe preliminary patterns of community structure according to geomorphological units. Findings of this survey revealed a total of 120 species of scleractinia belonging to 40 genera, while the average coral cover was 21 %, ranging from less than 10 % to higher than 50 %. Branching and massive corals were also found to be the most important growth forms of the whole coral community, while Acropora, Montipora, and Porites were the three dominant genera in the overall region, with their contributions to total coral cover measuring 21, 22, and 23 %, respectively. Overall, coral communities of the Nansha Islands were in a relative healthy condition with high species diversity and coral cover. Spatial pattern of coral communities existed among various geomorphological units. Mean coral cover was highest in the patch reef within the lagoon, followed by the fore reef slope, reef flat, and lagoon slope. The greatest contributors to total coral cover were branching Acropora (45 %) in the lagoon slope, branching Montipora (44 %) in the reef flat, and massive Porites (51 %) in the patch reef. Coral cover in the fore reef revealed a greater range of genera than in other habitats. The leeward fore reef slope had higher coral cover (>50 %) when compared with the windward slope (<10 %). The coral communities of the inner reef flat were characterized by higher coral cover (27 %) and dominant branching Montipora corals, while lower coral cover (4 %) was dominated by Psammocora with massive growth forms on the outer reef flat. Destructive fishing and coral bleaching were two major threats to coral communities in the study area.     

Detecting new Buffel grass infestations in Australian arid lands: evaluation of methods using high-resolution multispectral imagery and aerial photography

We assess the feasibility of using airborne imagery for Buffel grass detection in Australian arid lands and evaluate four commonly used image classification techniques (visual estimate, manual digitisation, unsupervised classification and normalised difference vegetation index (NDVI) thresholding) for their suitability to this purpose. Colour digital aerial photography captured at approximately 5 cm of ground sample distance (GSD) and four-band (visible–near-infrared) multispectral imagery (25 cm GSD) were acquired (14 February 2012) across overlapping subsets of our study site. In the field, Buffel grass projected cover estimates were collected for quadrates (10 m diameter), which were subsequently used to evaluate the four image classification techniques. Buffel grass was found to be widespread throughout our study site; it was particularly prevalent in riparian land systems and alluvial plains. On hill slopes, Buffel grass was often present in depressions, valleys and crevices of rock outcrops, but the spread appeared to be dependent on soil type and vegetation communities. Visual cover estimates performed best (r ² 0.39), and pixel-based classifiers (unsupervised classification and NDVI thresholding) performed worst (r ² 0.21). Manual digitising consistently underrepresented Buffel grass cover compared with field- and image-based visual cover estimates; we did not find the labours of digitising rewarding. Our recommendation for regional documentation of new infestation of Buffel grass is to acquire ultra-high-resolution aerial photography and have a trained observer score cover against visual standards and use the scored sites to interpolate density across the region.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Spatial and temporal analysis of land cover changes and water quality in the Lake Issaqueena watershed,South Carolina

Monitoring changes in land cover and the subsequent environmental responses are essential for water quality assessment, natural resource planning, management, and policies. Over the last 75 years, the Lake Issaqueena watershed has experienced a drastic shift in land use. This study was conducted to examine the changes in land cover and the implied changes in land use that have occurred and their environmental, water quality impacts. Aerial photography of the watershed (1951, 1956, 1968, 1977, 1989, 1999, 2005, 2006, and 2009) was analyzed and classified using the geographic information system (GIS) software. Seven land cover classes were defined: evergreen, deciduous, bare ground, pasture/grassland, cultivated, and residential/other development. Water quality data, including sampling depth, water temperature, dissolved oxygen content, fecal coliform levels, inorganic nitrogen concentrations, and turbidity, were obtained from the South Carolina (SC) Department of Health and Environmental Control (SCDHEC) for two stations and analyzed for trends as they relate to land cover change. From 1951 to 2009, the watershed experienced an increase of tree cover and bare ground (+17.4 % evergreen, +62.3 % deciduous, +9.8 % bare ground) and a decrease of pasture/grassland and cultivated land (?42.6 % pasture/grassland and ?57.1 % cultivated). From 2005 to 2009, there was an increase of 21.5 % in residential/other development. Sampling depth ranged from 0.1 to 0.3 m. Water temperature fluctuated corresponding to changing air temperatures, and dissolved oxygen content fluctuated as a factor of water temperature. Inorganic nitrogen content was higher from December to April possibly due to application of fertilizers prior to the growing season. Turbidity and fecal coliform bacteria levels remained relatively the same from 1962 to 2005, but a slight decline in pH can be observed at both stations. Prior to 1938, the area consisted of single-crop cotton farms; after 1938, the farms were abandoned, leaving large bare areas with highly eroded soil. Starting in 1938, Clemson reforested almost 30 % of the watershed. Currently, three fourths of the watershed is forestland, with a limited coverage of small farms and residential developments. Monitoring water quality is essential in maintaining adequate freshwater supply. Water quality monitoring focuses mainly on the collection of field data, but current water quality conditions depend on the cumulative impacts of land cover change over time.     

Quercus ilex L. carbon sequestration capability related to shrub size

CO₂ sequestration capacity of Quercus ilex L., an evergreen species developing in shrub and forest communities widely distributed in the Mediterranean Basin, was analysed. Experiments were carried out in the period of January to December 2009 on 20 shrubs of different size, growing at the Botanical Garden of Rome. At shrub level, the largest differences concern total photosynthetic leaf surface area per shrub and shrub volume. Shrubs structure significantly contribute to reduce total irradiance and air temperature below the canopy. Leaf mass per area is higher in sun leaves than in shade ones (20 ± 1 and 12 ± 2 mg cm^???2, respectively). Sun leaves are also characterised by the highest leaf thickness (78% higher in sun than in shade leaves), the spongy parenchyma thickness (71% higher in sun than in shade leaves) and the highest adaxial cuticle thickness (7.2 ± 1.2 and 4.7 ± 0.5 ??m, respectively). Net photosynthetic rates (P _N) of sun and shade leaves are the highest in spring, and shade leaves contribute 6% to the whole shrub P _N. Q. ilex CO₂ sequestration depends on shrub size. In particular, the CO₂ sequestration per shrub was 0.20 ± 0.02 Kg CO₂ year^???1 in small shrubs, and it was 75% and 98% lower than in medium and large ones. The highest CO₂ sequestration is measured in spring, decreasing 77% during drought. Q. ilex may play a significant role in mitigating carbon dioxide concentration and lowering air and soil temperature in areas around the Mediterranean Basin.     

Carbon, nitrogen, and phosphorus stoichiometry of plankton and the nutrient regime in Cabo Frio Bay, SE Brazil

This long-term study, performed during the years 2003–2005 and 2008–2009, investigated the carbon (C), nitrogen (N), and phosphorus (P) contents of the phyto- and zooplankton communities and the nutrient regime of Cabo Frio Bay, SE Brazil. The information intends to serve as baseline of the plankton C, N, and P stoichiometry for the calibration of biogeochemical and ecological models in support to future findings related to the local and regional phenomena of climatic change. Cabo Frio Bay is a small semienclosed system set adjacent to a region subject to sporadic coastal upwelling. Zooplankton exhibited average annual C, N, and P contents of 11.6?±?6.9 %, 2.8?±?1.8 %, and 0.18?±?0.08 %, and phytoplankton (>20 μm) 6.8?±?6.0 %, 1.6?±?1.5 %, and 0.09?±?0.08 %, respectively. The C/N/P ratios correspond to the lowest already found to date for a marine environment. The low C contents must have been brought about by a predominance of gelatinous zooplankton, like Doliolids/ Salps and also Pteropods. Average annual nutrient concentrations in the water were 0.21?±?0.1 μM for phosphate, 0.08?±?0.1 μM for nitrite, 0.74?±?1.6 μM for nitrate, and 1.27?±?1.1 μM for ammonium. N/P ratios were around 8:1 during the first study period and 12:1 during the second. The plankton C/N/P and N/P nutrient ratios and elemental concentrations suggest that the system was oligotrophic and nitrogen limited. The sporadic intrusions of upwelling waters during the first study period had no marked effect upon the systems metabolism, likely due to dilution effects and the short residence times of water of the bay.     

Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmaraş, Turkey

This study assessed land cover (LC) changes in Kahramanmara? (K.Mara?) and its environs by using multitemporal Landsat and ASTER imagery, respectively belong to 1989, 2000 and 2004. A priori defined nine land cover classes in the classification scheme were urban and built-up, forest, sparsely vegetated areas, grassland, vegetated stream beds, unvegetated stream beds, bare areas, crop fields, and water bodies. Individual classifications were employed using the combination of both unsupervised and supervised classification methods. Iterative Self Organizing Data Analysis (ISODATA) was used to reduce spectral variation in the scenes arising from complex pattern of crop fields. Maximum Likelihood classifier was used in the LC classification of the individual images. Image pairs of consecutive dates were compared by overlaying the thematic LC maps and cross-tabulating the LC statistics. Urbanization and expansion of agriculture were the major reasons for the dramatic LC conversions. The amount of conversion from crop fields to water occurred as large as 927.67 ha, accounting for 73% of the total land-to-water conversion. Conversions to agriculture have mainly been occurred from grasslands and sparsely vegetated areas as large as 1,314.95 and 1,325.84 ha, respectively. Urban coverage doubled in this period as a result of 1,443.45 ha of increase. Urban area increased in the second period from 2,920 to 3,526 ha. Conversions to agriculture occurred at high amounts. A total of 1,075.79 ha area changed from sparsely vegetated areas to crop fields. A landscape-level environmental monitoring scheme based on satellite remote sensing was proposed for effective environmental resource management.     

Aerial and terrestrial-based monitoring of channel erosion,headcutting, and sinuosity

Headcuts are points of accelerated channel erosion that frequently have ecological consequences. A particularly large and dynamic headcut in southwest Wyoming has affected natural and anthropogenic resources for decades. To better understand and address this issue, we undertook a review of the headcut’s upstream retreat, followed by photogrammetric monitoring of the present condition for erosion monitoring. Aerial photography shows the Bitter Creek headcut retreated >?200 m upstream in 68 years (1948–2016) at ~?1.4 m year^?1. Following installation of a concrete slab structure in the mid-1970s, headcut retreat slowed to ~?0.5 m year^?1. Channel sinuosity downstream of the headcut is greater than upstream, which we attribute to the presence of the headcut, given that there are no major changes in valley geometry, geology, or soils through this reach. Both aerial and terrestrial-based image platforms were used to collect stereo imagery and create 3D photogrammetric models of the headcut in 2016. From these two models, we measured soil loss downstream of the headcut at ~?126 m³ m^?1 valley length. Since 1954, soil loss within the channel has been ~?98 m³ year^?1 or ~871 t ha^?1 year^?1since then. Models created from aerial- and terrestrial-based images differed in volumetric estimates by 2%, indicating that either method could be used for this type of monitoring. The ground-based imagery model showed more detail, especially on vertical and overhanging surfaces, while the aerial imagery model produced a more realistic orthomosaic and efficiently covered a larger area. Ground-based image acquisition took longer and was more costly per unit area, but is an efficient method for small project areas, or areas where aerial imagery cannot be safely or practically acquired. Historical imagery and photogrammetric modeling proved very useful in elucidating stream dynamics associated with this large, dynamic headcut.     

GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa Watershed,Ethiopia

Classifying multi-temporal image data to produce thematic maps and quantify land cover changes is one of the most common applications of remote sensing. Mapping land cover changes at the regional level is essential for a wide range of applications including land use planning, decision making, land cover database generation, and as a source of information for sustainable management of natural resources. Land cover changes in Lake Hawassa Watershed, Southern Ethiopia, were investigated using Landsat MSS image data of 1973, and Landsat TM images of 1985, 1995, and 2011, covering a period of nearly four decades. Each image was partitioned in a GIS environment, and classified using an unsupervised algorithm followed by a supervised classification method. A hybrid approach was employed in order to reduce spectral confusion due to high variability of land cover. Classification of satellite image data was performed integrating field data, aerial photographs, topographical maps, medium resolution satellite image (SPOT 20 m), and visual image interpretation. The image data were classified into nine land cover types: water, built-up, cropland, woody vegetation, forest, grassland, swamp, bare land, and scrub. The overall accuracy of the LULC maps ranged from 82.5 to 85.0 %. The achieved accuracies were reasonable, and the observed classification errors were attributable to coarse spatial resolution and pixels containing a mixture of cover types. Land cover change statistics were extracted and tabulated using the ERDAS Imagine software. The results indicated an increase in built-up area, cropland, and bare land areas, and a reduction in the six other land cover classes. Predominant land cover is cropland changing from 43.6 % in 1973 to 56.4 % in 2011. A significant portion of land cover was converted into cropland. Woody vegetation and forest cover which occupied 21.0 and 10.3 % in 1973, respectively, diminished to 13.6 and 5.6 % in 2011. The change in water body was very peculiar in that the area of Lake Hawassa increased from 91.9 km² in 1973 to 95.2 km² in 2011, while that of Lake Cheleleka whose area was 11.3 km² in 1973 totally vanished in 2011 and transformed into mud-flat and grass dominated swamp. The “change and no change” analysis revealed that more than one third (548.0 km²) of the total area was exposed to change between 1973 and 2011. This study was useful in identifying the major land cover changes, and the analysis pursued provided a valuable insight into the ongoing changes in the area under investigation.     

Co-assessment of biomass and soil organic carbon stocks in a future reservoir area located in Southeast Asia

An assessment of the organic carbon stock present in living or dead vegetation and in the soil on the 450 km² of the future Nam Theun 2 hydroelectric reservoir in Lao People??s Democratic Republic was made. Nine land cover types were defined on the studied area: dense, medium, light, degraded, and riparian forests; agricultural soil; swamps; water; and others (roads, construction sites, and so on). Their geographical distribution was assessed by remote sensing using two 2008 SPOT 5 images. The area is mainly covered by dense and light forests (59%), while agricultural soil and swamps account for 11% and 2%, respectively. For each of these cover types, except water, organic carbon density was measured in the five pools defined by the Intergovernmental Panel on Climate Change: aboveground biomass, litter, deadwood, belowground biomass, and soil organic carbon. The area-weighted mean carbon densities for these pools were estimated at 45.4, 2.0, 2.2, 3.4, and 62.2 tC/ha, respectively, i.e., a total of about 115 ± 15 tC/ha for a soil thickness of 30 cm, corresponding to a total flooded organic carbon stock of 5.1 ± 0.7 MtC. This value is much lower than the carbon density for some South American reservoirs for example where total organic carbon stocks range from 251 to 326 tC/ha. It can be mainly explained by (1) the higher biomass density of South American tropical primary rainforest than of forests in this study and (2) the high proportion of areas with low carbon density, such as agricultural or slash-and-burn zones, in the studied area.     

Climate change impacts detection in dry forested ecosystem as indicated by vegetation cover change in —Laikipia,of Kenya

The objective of the study was to detect and identify land cover changes in Laikipia County of Kenya that have occurred during the last three decades. The land use types of study area are six, of which three are the main and the other three are the minor. The main three, forest, shrub or bush land and grassland, changed during the period, of which grasslands reduced by 5864 ha (40%), forest by 3071 ha (24%) and shrub and bush land increased by 8912 ha (43%). The other three minor land use types were bare land which had reduced by 238 ha (45%), river bed vegetation increased by 209 ha (72%) and agriculture increased by 52 ha (600%) over the period decades. Differences in spatiotemporal variations of vegetation could be largely attributed to the effects of climate factors, anthropogenic activities and their interactions. Precipitation and temperature have been demonstrated to be the key climate factors for plant growth and vegetation development where rainfall decreased by 200 mm and temperatures increased by 1.5 °C over the period. Also, the opinion of the community on the change of land use and management was attributed to climate change and also adaptation strategies applied by the community over time. For example unlike the common understanding that forest resources utilisation increases with increasing human population, Mukogodo dry forested ecosystem case is different in that the majority of the respondents (78.9%) reported that the forest resource use was more in that period than now and also a similar majority (74.2%) had the same opinion that forest resource utilisation was low compared to last 30 years. In Yaaku community, change impacts were evidenced and thus mitigation measures suggested to address the impacts which included the following: controlled bush management and indigenous grass reseeding programme were advocated to restore original grasslands, and agricultural (crop farming) activities are carried out in designated areas outside the forest conservation areas (ecosystem zoning) all in consultation with government (political class), community and other stakeholders. Groups are organised (environmental management committee) to address conservation, political and vulnerability issues in the pastoral dry forested ecosystem which will sustain pastoralism in the ecosystem.     

An object-based image analysis approach for aquaculture ponds precise mapping and monitoring: a case study of Tam Giang-Cau Hai Lagoon, Vietnam

Monitoring and mapping shrimp farms, including their impact on land cover and land use, is critical to the sustainable management and planning of coastal zones. In this work, a methodology was proposed to set up a cost-effective and reproducible procedure that made use of satellite remote sensing, object-based classification approach, and open-source software for mapping aquaculture areas with high planimetric and thematic accuracy between 2005 and 2008. The analysis focused on two characteristic areas of interest of the Tam Giang-Cau Hai Lagoon (in central Vietnam), which have similar farming systems to other coastal aquaculture worldwide: the first was primarily characterised by locally referred “low tide” shrimp ponds, which are partially submerged areas; the second by earthed shrimp ponds, locally referred to as “high tide” ponds, which are non-submerged areas on the lagoon coast. The approach was based on the region-growing segmentation of high- and very high-resolution panchromatic images, SPOT5 and Worldview-1, and the unsupervised clustering classifier ISOSEG embedded on SPRING non-commercial software. The results, the accuracy of which was tested with a field-based aquaculture inventory, showed that in favourable situations (high tide shrimp ponds), the classification results provided high rates of accuracy (>95 %) through a fully automatic object-based classification. In unfavourable situations (low tide shrimp ponds), the performance degraded due to the low contrast between the water and the pond embankments. In these situations, the automatic results were improved by manual delineation of the embankments. Worldview-1 necessarily showed better thematic accuracy, and precise maps have been realised at a scale of up to 1:2,000. However, SPOT5 provided comparable results in terms of number of correctly classified ponds, but less accurate results in terms of the precision of mapped features. The procedure also demonstrated high degrees of reproducibility because it was applied to images with different spatial resolutions in an area that, during the investigated period, did not experience significant land cover changes.     

Assessment and monitoring of long-term forest cover changes in Odisha, India using remote sensing and GIS

Deforestation and fragmentation are important concerns in managing and conserving tropical forests and have global significance. In the Indian context, in the last one century, the forests have undergone significant changes due to several policies undertaken by government as well as increased population pressure. The present study has brought out spatiotemporal changes in forest cover and variation in forest type in the state of Odisha (Orissa), India, during the last 75 years period. The mapping for the period of 1924–1935, 1975, 1985, 1995 and 2010 indicates that the forest cover accounts for 81,785.6 km² (52.5 %), 56,661.1 km² (36.4 %), 51,642.3 km² (33.2 %), 49,773 km² (32 %) and 48,669.4 km² (31.3 %) of the study area, respectively. The study found the net forest cover decline as 40.5 % of the total forest and mean annual rate of deforestation as 0.69 %?year^?1 during 1935 to 2010. There is a decline in annual rate of deforestation during 1995 to 2010 which was estimated as 0.15 %. Forest type-wise quantitative loss of forest cover reveals large scale deforestation of dry deciduous forests. The landscape analysis shows that the number of forest patches (per 1,000) are 2.463 in 1935, 10.390 in 1975, 11.899 in 1985, 12.193 in 1995 and 15.102 in 2010, which indicates high anthropogenic pressure on the forests. The mean patch size (km²) of forest decreased from 33.2 in 1935 to 5.5 in 1975 and reached to 3.2 by 2010. The study demonstrated that monitoring of long term forest changes, quantitative loss of forest types and landscape metrics provides critical inputs for management of forest resources.     

Estimation of late twentieth century land-cover change in California

We present the first comprehensive multi-temporal analysis of land-cover change for California across its major ecological regions and primary land-cover types. Recently completed satellite-based estimates of land-cover and land-use change information for large portions of the United States allow for consistent measurement and comparison across heterogeneous landscapes. Landsat data were employed within a pure-panel stratified one-stage cluster sample to estimate and characterize land-cover change for 1973?C2000. Results indicate anthropogenic and natural disturbances, such as forest cutting and fire, were the dominant changes, followed by large fluctuations between agriculture and rangelands. Contrary to common perception, agriculture remained relatively stable over the 27-year period with an estimated loss of 1.0% of agricultural land. The largest net declines occurred in the grasslands/shrubs class at 5,131 km² and forest class at 4,722 km². Developed lands increased by 37.6%, composing an estimated 4.2% of the state??s land cover by 2000.     

Assessing post-industrial land cover change at the Pine Point Mine,NWT, Canada using multi-temporal Landsat analysis and landscape metrics

This study investigates land cover change near the abandoned Pine Point Mine in Canada’s Northwest Territories. Industrial mineral development transforms local environments, and the effects of such disturbances are often long-lasting, particularly in subarctic, boreal environments where vegetation conversion can take decades. Located in the Boreal Plains Ecozone, the Pine Point Mine was an extensive open pit operation that underwent little reclamation when it shut down in 1988. We apply remote sensing and landscape ecology methods to quantify land cover change in the 20 years following the mine’s closure. Using a time series of near-anniversary Landsat images, we performed a supervised classification to differentiate seven land cover classes. We used raster algebra and landscape metrics to track changes in land cover composition and configuration in the 20 years since the mine shut down. We compared our results with a site in Wood Buffalo National Park that was never subjected to extensive anthropogenic disturbance. This space-for-time substitution provided an analog for how the ecosystem in the Pine Point region might have developed in the absence of industrial mineral development. We found that the dense conifer class was dominant in the park and exhibited larger and more contiguous patches than at the mine site. Bare land at the mine site showed little conversion through time. While the combination of raster algebra and landscape metrics allowed us to track broad changes in land cover composition and configuration, improved access to affordable, high-resolution imagery is necessary to effectively monitor land cover dynamics at abandoned mines.     

Vegetation dynamics, and land use and land cover change in the Bale Mountains, Ethiopia

Shifts in biological communities are occurring at rapid rates as human activities induced global climate change increases. Understanding the effects of the change on biodiversity is important to reduce loss of biodiversity and mass extinction, and to insure the long-term persistence of natural resources and natures’ services. Especially in remote landscapes of developing countries, precise knowledge about on-going processes is scarce. Here we apply satellite imagery to assess spatio-temporal land use and land cover change (LULCC) in the Bale Mountains for a period of four decades. This study aims to identify the main drivers of change in vegetation patterns and to discuss the implications of LULCC on spatial arrangements and trajectories of floral communities. Remote sensing data acquired from Landsat MSS, Landsat ETM + and SPOT for four time steps (1973, 1987, 2000, and 2008) were analyzed using 11 LULC units defined based on the dominant plant taxa and cover types of the habitat. Change detection matrices revealed that over the last 40?years, the area has changed from a quite natural to a more cultural landscape. Within a representative subset of the study area (7,957.5?km^?2), agricultural fields have increased from 1.71% to 9.34% of the total study area since 1973. Natural habitats such as upper montane forest, afroalpine grasslands, afromontane dwarf shrubs and herbaceous formations, and water bodies also increased. Conversely, afromontane grasslands have decreased in size by more than half (going from 19.3% to 8.77%). Closed Erica forest also shrank from 15.0% to 12.37%, and isolated Erica shrubs have decreased from 6.86% to 5.55%, and afroalpine dwarf shrubs and herbaceous formations reduced from 5.2% to 1.56%. Despite fluctuations the afromontane rainforest (Harenna forest), located south of the Bale Mountains, has remained relatively stable. In conclusion this study documents a rapid and ecosystem-specific change of this biodiversity hotspot due to intensified human activities (e.g., deforestation, agriculture, infrastructure expansion). Specifically, the ecotone between the afromontane and the afroalpine area represent a “hotspot of biodiversity loss” today. Taking into consideration the projections of regional climate warming and modified precipitation regimes, LULCC can be expected to become even more intensive in the near future. This is likely to impose unprecedented pressures on the largely endemic biota of the area.