Search Results (11)

Current lake and reservoir water body extraction algorithms are confronted with two critical challenges: (1) design dependency on specific geographical features, leading to constrained cross-regional adaptability (e.g., the JRC Global Water Body Dataset achieves ~90% overall accuracy globally, while the ESA WorldCover 2020 reaches ~92% for water body classification, both showing degraded performance in complex karst terrains); (2) information loss due to cloud occlusion, compromising dynamic monitoring accuracy. To address these limitations, this study presents a multi-feature fusion and multi-level hierarchical extraction algorithm for lake and reservoir water bodies, leveraging the Google Earth Engine (GEE) cloud platform and Sentinel-2 multispectral imagery in the karst landscape of Bijie City. The proposed method integrates the Automated Water Extraction Index (AWEIsh) and Modified Normalized Difference Water Index (MNDWI) for initial water body extraction, followed by a comprehensive fusion of multi-source data—including Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), Normalized Difference Red-Edge Index (NDREI), Sentinel-2 B8/B9 spectral bands, and Digital Elevation Model (DEM). This strategy hierarchically mitigates vegetation shadows, topographic shadows, and artificial feature non-water targets. A temporal flood frequency algorithm is employed to restore cloud-occluded water bodies, complemented by morphological filtering to exclude non-target water features (e.g., rivers and canals). Experimental validation using high-resolution reference data demonstrates that the algorithm achieves an overall extraction accuracy exceeding 96% in Bijie City, effectively suppressing dark object interference (e.g., false positives due to topographic and anthropogenic features) while preserving water body boundary integrity. Compared with single-index methods (e.g., MNDWI), this method reduces false positive rates caused by building shadows and terrain shadows by 15–20%, and improves the IoU (Intersection over Union) by 6–13% in typical karst sub-regions. This research provides a universal technical framework for large-scale dynamic monitoring of lakes and reservoirs, particularly addressing the challenges of regional adaptability and cloud compositing in karst environments. Full article

We explore a new approach for the parsimonious, generalizable, efficient, and potentially automatable characterization of spectral diversity of sparse targets in spectroscopic imagery. The approach focuses on pixels which are not well modeled by linear subpixel mixing of the Substrate, Vegetation and Dark (S, V, and D) endmember spectra which dominate spectral variance for most of Earth’s land surface. We illustrate the approach using AVIRIS-3 imagery of anthropogenic surfaces (primarily hydrocarbon extraction infrastructure) embedded in a background of Arctic tundra near Prudhoe Bay, Alaska. Computational experiments further explore sensitivity to spatial and spectral resolution. Analysis involves two stages: first, computing the mixture residual of a generalized linear spectral mixture model; and second, nonlinear dimensionality reduction via manifold learning. Anthropogenic targets and lakeshore sediments are successfully isolated from the Arctic tundra background. Dependence on spatial resolution is observed, with substantial degradation of manifold topology as images are blurred from 5 m native ground sampling distance to simulated 30 m ground projected instantaneous field of view of a hypothetical spaceborne sensor. Degrading spectral resolution to mimicking the Sentinel-2A MultiSpectral Imager (MSI) also results in loss of information but is less severe than spatial blurring. These results inform spectroscopic characterization of sparse targets using spectroscopic images of varying spatial and spectral resolution. Full article

We studied charcoal from several types of natural soil archives, including cultural layers of archaeological sites (hillforts), surrounding forest and arable soils, and sediments in lower parts of the slopes associated with hillforts and moraine hills. The stratigraphy of the charcoals was described, and 41 samples were radiocarbon-dated. Analysis of 2277 charcoals showed the presence of 13 taxa of woody species; Pinus and Picea charcoals dominated. Charcoals older than 300 BC were found only in sediment and in several pits formed after treefalls with uprooting. The greatest diversity of woody species was found in the hillforts’ cultural layers composed of Anthropogenic Dark Earth soils formed between 300 BC and 300 cal. AD (Early Iron Age). All charcoals from ancient arable soils were younger than charcoals from the hillforts. Charcoals indicated that burning for arable farming started in the study region in the 6th century AD. Woody taxa exhibited a decrease in number of species and a decrease in the proportion of nemoral (broadleaved) species from the Early Iron Age to the Middle Ages and to the present. Quercus, Tilia, and Corylus have become relatively rare, although they still occur in the study region. Ulmus and Acer are now rare in the Upper Volga region and were not found in the vicinity of the study sites. Full article

Based on recent insights about intensive soil husbandry by some Neolithic farmers combined with the required techniques for efficient use of stone tools, this research questions the emphasis in the experimental archaeology literature on felling of large trees by stone-axe-wielding males working alone. To reflect conditions after the short fallows now thought to have been favored by farmers using stone tools, young (8–12 years) and small (3.5–5.6 cm diameter) Quercus hemisphaerica (laurel oak) trees were felled in this study by both male and female participants. Felling with a stone axe required an average of 75 more strokes than for felling a similar sized tree with a steel axe. One novel finding in this study is that when the Quercus hemisphaerica (laurel oak) saplings were bent over/tensioned by a co-worker, the predicted numbers of felling strokes declined by 123 (73%) for stone axes and by 15 (72%) for steel axes. We also observed no effect of sex on felling efficiency with stone axes. These results suggest that stone-tool wielding farmers of both sexes worked together to clear trees from their fallowed fields. Full article

NASA’s Gateway to Astronaut Photography of Earth contains over 30,000 photos of ~2500 cataloged urban lightscapes (anthropogenic night light) taken from the International Space Station. A subset of over 100 of these multispectral DSLR photos are of sufficient spatial resolution, sharpness and exposure to be potentially useful for broadband spectral characterization of urban lightscapes. Spectral characterization of multiple urban lightscapes can provide a basis for quantifying intra and interurban variability in night light brightness, color and extent, as well as the potential for change analyses. A comparative analysis of simulated atmospheric transmissivity from the MODTRAN radiative transfer model indicates that the spectral slopes of transmissivity spectra are relatively insensitive model atmospheres, with variations in atmospheric path length and aerosol optical depth primarily affecting the bias of the spectrum rather than the slope. A mosaic of 18 intercalibrated, transmissivity-compensated RGB photos renders a spectral feature space bounded by four clearly defined spectral endmembers corresponding to white, yellow and red light sources, with brightness modulated by a dark background endmember. These four spectral endmembers form the basis of a linear spectral mixture model which can be inverted to provide estimates of the areal fraction of each endmember present within every pixel field of view. The resulting spectral feature spaces consistently show two distinct mixing trends extending from the dark endmember to flat spectrum (white–yellow) and warm spectrum (orange) sources. The distribution of illuminated pixels is strongly skewed toward a lower luminance background of warm spectrum street lighting with brighter lights, generally corresponding to point sources and major thoroughfares. Full article

The chlorophyll-a (Chl-a) concentration of eutrophic lakes fluctuates significantly due to the disturbance of wind and anthropogenic activities on the water body. Consequently, estimation of the Chl-a concentration has become an immense challenge. Due to urgent demand and rapid development in high-resolution earth observation systems, it has become crucial to assess hyperspectral satellite imagery capabilities on inland water monitoring. The Orbita hyperspectral (OHS) satellite is the latest hyperspectral sensor with both high spectral and spatial resolution (2.5 nm and 10 m, respectively), which could provide great potential for remotely estimating the concentration of Chl-a for inland waters. However, there are still some deficiencies that are mainly manifested in the Chl-a concentration remote sensing retrieval model assessment and accuracy validation, as well as signal-to-noise ratio (SNR) estimation of OHS imagery for inland waters. Therefore, the radiometric performance of OHS imagery for water quality monitoring is evaluated in this study by comparing different atmospheric correction models and the SNR with several remote sensing images. Several crucial findings can be drawn: (1) the three-band model ((1/B15-1/B17)B19) developed by OHS imagery is most suitable for estimating the Chl-a concentration in Dianchi Lake, with the root-mean-square error (RMSE) and the mean absolute percentage error (MAPE) of 15.55 µg/L and 16.31%, respectively; (2) the applicability of the FLAASH (Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction model for OHS imagery in a eutrophic plateau lake (Dianchi Lake) was better than the 6S (Second Simulation of Satellite Signal in the Solar Spectrum) model, and QUAC (Quick Atmospheric Correction) model, as well as the dark pixel method; (3) the SNR of the OHS imagery was similar to that of Hyperion imagery and was significantly higher than SNR of the HSI imagery; (4) the spatial resolution showed slight influence on the SNR of the OHS imagery. The results show that OHS imagery could be applied to remote sensing retrieval of Chl-a in eutrophic plateau lakes and presents a new tool for dynamic hyperspectral monitoring of water quality. Full article

The polyphyletic group of black fungi within the Ascomycota (Arthoniomycetes, Dothideomycetes, and Eurotiomycetes) is ubiquitous in natural and anthropogenic habitats. Partly because of their dark, melanin-based pigmentation, black fungi are resistant to stresses including UV- and ionizing-radiation, heat and desiccation, toxic metals, and organic pollutants. Consequently, they are amongst the most stunning extremophiles and poly-extreme-tolerant organisms on Earth. Even though ca. 60 black fungal genomes have been sequenced to date, [mostly in the family Herpotrichiellaceae (Eurotiomycetes)], the class Dothideomycetes that hosts the largest majority of extremophiles has only been sparsely sampled. By sequencing up to 92 species that will become reference genomes, the “Shed light in The daRk lineagES of the fungal tree of life” (STRES) project will cover a broad collection of black fungal diversity spread throughout the Fungal Tree of Life. Interestingly, the STRES project will focus on mostly unsampled genera that display different ecologies and life-styles (e.g., ant- and lichen-associated fungi, rock-inhabiting fungi, etc.). With a resequencing strategy of 10- to 15-fold depth coverage of up to ~550 strains, numerous new reference genomes will be established. To identify metabolites and functional processes, these new genomic resources will be enriched with metabolomics analyses coupled with transcriptomics experiments on selected species under various stress conditions (salinity, dryness, UV radiation, oligotrophy). The data acquired will serve as a reference and foundation for establishing an encyclopedic database for fungal metagenomics as well as the biology, evolution, and ecology of the fungi in extreme environments. Full article

Since the introduction of electric lighting over a century ago, and particularly in the decades following the Second World War, indications of artificial light on the nighttime Earth as seen from Earth orbit have increased at a rate exceeding that of world population growth during the same period. Modification of the natural photic environment at night is a clear and imminent consequence of the proliferation of anthropogenic light at night into outdoor spaces, and with this unprecedented change comes a host of known and suspected ecological consequences. In the past two decades, the conservation community has gradually come to view light pollution as a threat requiring the development of best management practices. Establishing those practices demands a means of quantifying the problem, identifying polluting sources, and monitoring the evolution of their impacts through time. The proliferation of solid-state lighting and the changes to source spectral power distribution it has brought relative to legacy lighting technologies add the complication of color to the overall situation. In this paper, I describe the challenge of quantifying light pollution threats to ecologically-sensitive sites in the context of efforts to conserve natural nighttime darkness, assess the current state of the art in detection and imaging technology as applied to this realm, review some recent innovations, and consider future prospects for imaging approaches to provide substantial support for darkness conservation initiatives around the world. Full article

Anthropogenic soils of the Amazon Basin (Terra Preta, Terra Mulata) reveal that pre-Colombian peoples made lasting improvements in the agricultural potential of nutrient-poor soils. Some have argued that applying similar techniques could improve agriculture over much of the humid tropics, enhancing local livelihoods and food security, while also sequestering large quantities of carbon to mitigate climate change. Here, we present preliminary evidence for Anthropogenic Dark Earths (ADEs) in tropical Asia. Our surveys in East Kalimantan (Indonesian Borneo) identified several sites where soils possess an anthropogenic development and context similar in several respects to the Amazon’s ADEs. Similarities include riverside locations, presence of useful fruit trees, spatial extent as well as soil characteristics such as dark color, high carbon content (in some cases), high phosphorus levels, and improved apparent fertility in comparison to neighboring soils. Local people value these soils for cultivation but are unaware of their origins. We discuss these soils in the context of local history and land-use and identify numerous unknowns. Incomplete biomass burning appears key to these modified soils. More study is required to clarify soil transformations in Borneo and to determine under what circumstances such soil improvements might remain ongoing. Full article

The processes of land conversion and agricultural intensification are a significant cause of biodiversity loss, with consequent negative effects both on the environment and the sustainability of food production.The anthrosols associated with pre-Colombian settlements in the Amazonian region are examples of how anthropogenic activities may sustain the native populations against harsh tropical environments for human establishment, even without a previous intentionality of anthropic soil formation. In a case study (Model I—“Slash-and-Burn”) the community structures detected by automated ribosomal intergenic spacer analysis (ARISA) revealed that soil archaeal, bacterial and fungal communities are heterogeneous and each capable of responding differently to environmental characteristics. ARISA data evidenced considerable difference in structure existing between microbial communities in forest and agricultural soils. In a second study (Model II—“Anthropogenic Soil”), the bacterial community structures revealed by terminal restriction fragment length polymorphism (T-RFLP) differed among an Amazonian Dark Earth (ADE), black carbon (BC) and its adjacent non-anthropogenic oxisoil. The bacterial 16S rRNA gene (OTU) richness estimated by pyrosequencing was higher in ADE than BC. The most abundant bacterial phyla in ADE soils and BC were Proteobacteria—24% ADE, 15% BC; Acidobacteria—10% ADE, 21% BC; Actinobacteria—7% ADE, 12% BC; Verrucomicrobia, 8% ADE; 9% BC; Firmicutes—3% ADE, 8% BC. Overall, unclassified bacteria corresponded to 36% ADE, and 26% BC. Regardless of current land uses, our data suggest that soil microbial community structures may be strongly influenced by the historical soil management and that anthrosols in Amazonia, of anthropogenic origins, in addition to their capacity of enhancing crop yields, may also improve microbial diversity, with the support of the black carbon, which may sustain a particular and unique habitat for the microbes. Full article

The emergence of sedentism and agriculture in Amazonia continues to sit uncomfortably within accounts of South American pre-Columbian history. This is partially because deep-seated models were formulated when only ceramic evidence was known, partly because newer data continue to defy simple explanations, and partially because many discussions continue to ignore evidence of pre-Columbian anthropogenic landscape transformations. This paper presents the results of recent geoarchaeological research on Amazonian anthropogenic soils. It advances the argument that properties of two different types of soils, terras pretas and terras mulatas, support their interpretation as correlates of, respectively, past settlement areas and fields where spatially-intensive, organic amendment-reliant cultivation took place. This assessment identifies anthropogenic soil formation as a hallmark of the Amazonian Formative and prompts questions about when similar forms of enrichment first appear in the Amazon basin. The paper reviews evidence for embryonic anthrosol formation to highlight its significance for understanding the domestication of a key Amazonian crop: manioc (Manihot esculenta ssp. esculenta). A model for manioc domestication that incorporates anthropogenic soils outlines some scenarios which link the distribution of its two broader varieties—sweet and bitter manioc—with the widespread appearance of Amazonian anthropogenic dark earths during the first millennium AD. Full article