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International journal of applied earth observation and geoinformation
International Institute for Aerospace Survey and Earth Sciences
International journal of applied earth observation and geoinformation

International Institute for Aerospace Survey and Earth Sciences

1569-8432

International journal of applied earth observation and geoinformation/Journal International journal of applied earth observation and geoinformationISTPSCIAHCI
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    Revisiting effectiveness of turbidity index for the switching scheme of NIR-SWIR combined ocean color atmospheric correction algorithm

    Li, QingquanWu, GuofengLiu, HuizengHu, Shuibo...
    9页
    查看更多>>摘要：Accurately removing atmospheric interferences and retrieving water-leaving reflectance are decisive for subsequent ocean color applications. Over turbid waters, the black pixel assumption at the near-infrared (NIR) spectral region does not hold, and shortwave infrared (SWIR)-based atmospheric correction algorithm should be applied. Turbidity index is proposed to detect turbid waters and worked as a criterion for NIR-SWIR combined algorithm. However, studies demonstrated that turbidity index did not work well as expected. This study, using simulated data and satellite images, aimed to revisit the effectiveness of turbidity index for the switching scheme of NIR-SWIR algorithm. The simulated data were obtained from aerosol look-up tables, and the Aqua MODIS images were used. The variations of turbidity index calculated from aerosol reflectance and Rayleigh-corrected reflectance were explored. Results showed that turbidity index did not obey the assumption that it should be close to one over clear waters with negligible NIR water-leaving reflectance; its value calculated from simulated aerosol reflectance ranged from 0.7 to 2.2; and the turbidity index values varied depending on fine-mode fraction, aerosol optical thickness, relative humidity and observing geometries. Therefore, more effective switching scheme should be developed for the NIR-SWIR combined atmospheric correction algorithm.
      原文链接:
    • NSTL
    • Elsevier

    Remote sensing data in lithium (Li) exploration: A new approach for the detection of Li-bearing pegmatites

    Cardoso-Fernandes, JoanaTeodoro, Ana C.Lima, Alexandre
    16页
    查看更多>>摘要：Remote sensing has proved to be a powerful resource in geology capable of delineating target exploration areas for several deposit types. Only recently, these methodologies have been used for the detection of lithium (Li)-bearing pegmatites. This happened because of the growing importance and demand of Li for the construction of Li-ion batteries for electric cars. The objective of this study was to develop innovative and effective remote sensing methodologies capable of identifying Li-pegmatites through alteration mapping and through the direct identification of Li-bearing minerals. For that, cloud free Landsat-5, Landsat-8, Sentinel-2 and ASTER images with low vegetation coverage were used. The image processing methods included: RGB (red, green, blue) combinations, band ratios and selective principal component analysis (PCA). The study area of this work is the Fregeneda (Salamanca, Spain)-Almendra (Vila Nova de Foz Coa, Portugal) region, where different known types of Li-pegmatites have been mapped. This study proposes new RGB combinations, band ratios and subsets for selective PCA capable of differentiating the spectral signatures of the Li-bearing pegmatites from the spectral signatures of the host rocks. The potential and limitations of the methodologies proposed are discussed, but overall there is a great potential for the identification of Li-bearing pegmatites using remote sensing. The results obtained could be improved using sensors with a better spatial and spectral resolution.
      原文链接:
    • NSTL
    • Elsevier

    Identification and mapping of winter wheat by integrating temporal change information and Kullback-Leibler divergence

    Zhang, XiwangQiu, FangQin, Fen
    14页
    查看更多>>摘要：Crop acreage and its spatial distribution are a base for agriculture related works. Current research combining medium and low spatial resolution images focuses on data fusion and unmixing methods. The purpose of the former is to generate synthetic fine spatial resolution data instead of directly solving the problem. In the latter, high-resolution data is only used to provide endmembers and the result is usually an abundance map rather than the true spatial distribution data. To solve this problem, this paper designs a conceptual model which divides the study area into different types of pixels at a MODIS 250 m scale. Only three types of pixels contain winter wheat, i.e., pure winter wheat pixels (P-A), the mixed pixels comprising winter wheat and other vegetation (M-A) and the mixed pixels comprising winter wheat and other crops (M-B). Different strategies are used in processing them. (1) Within the pure cultivated land pixels, the Kullback-Leibler (KL) divergence is employed to analyze the similarity between unknown pixels and the pure winter wheat samples on the temporal change characteristics of NDVI. Further P-A is identified. (2) For M-A, a proposed reverse unmixing method is firstly used to extract the temporal change information of cultivated land components, after which winter wheat is identified from the cultivated land components as previously described. (3) For M-B which only appears on the border of P-A, a mask is created by expanding the P-A and temporal difference is utilized to identify winter wheat under the mask. Finally, these three results are integrated at a TM scale with the aid of 25 to resolution land use data. We applied the proposed solution and obtained a good result in the main agricultural area of the Yiluo River Basin. The identified winter wheat planting acreage is 161,050.00 hm(2). The result is validated based on the five-hundred random validation points. Overall accuracy is 94.80% and Kappa coefficient is 0.85. This demonstrates that the temporal information reflecting crop growth is also an important indicator, and the KL divergence makes it more convenient in identifying winter wheat. This research provided a new perspective for the combination of low and medium spatial resolution remote sensing images. The proposed solution can also be effectively applied in other places and countries for the crop which has a clear temporal change characteristic that is different from others.
      原文链接:
    • NSTL
    • Elsevier

    An updated delineation of stand ages of deciduous rubber plantations during 1987-2018 using Landsat-derived bi-temporal thresholds method in an antichronological strategy

    Xiao, ChiweiFeng, ZhimingLiu, XiaonaLi, Peng...
    11页
    查看更多>>摘要：Timely and accurately monitoring stand ages of deciduous rubber plantations is of great importance for ecological studies and plantations management. The re-establishment of rubber plantations usually experiences a short period (several years) of land clearance and transplantation of rubber seedlings, along with a noticeable landscape change from well-grown forest to bare land and sparse vegetation in situ. With Landsat times series (LTS) data of four commonly-used vegetation indices (VIs), namely the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Moisture Index (NDMI), and Normalized Burn Ratio (NBR), and three non-visible spectral bands, i.e. the near-infrared (NIR) and shortwave-infrared (SWIR1/2), in this study, an approach by combining the inter-annual defoliating and foliating features of rubber trees and the intra-annual landscape changes of rubber plantations was presented to detect and map stand ages of deciduous rubber plantations in an anti-chronological manner across Xishuangbanna between 1987 and 2018, one of the most intensive regions of deciduous rubber plantations within the tropics. The approach highlighted the repeated distribution of newly-cleared and replanted plot (NCRP) of rubber seedlings due to rubber management. It applied the bi-temporal VIs thresholds of zero of NBR and NDMI during the defoliation to foliation phases to delineate the stand ages of deciduous rubber plantations at an interval of five years, by combining a Landsat-based rubber map in 2018 and 32-year NCRPs as well as quadri-classified age-groups and seven subcategories (i.e. <= 5 as infantile rubber plantations (IRP), 6-10 as young rubber plantations (YRP), 11-15 and 16-20 as mature rubber plantations (MRP), 21-25, 26-30, and >= 31 years as old rubber plantations (ORP)). The results showed that the areas of IRP, YRP, MRP, and ORP were 19.1 km(2), 817.1 km(2), 1681.7 km(2), and 573.7 km(2) in 2018, respectively. Spatially, the YRP are mainly around the outskirts of two county-level administrative centers (Jinghong and Mengla), while ORP primarily distributed along main roads. Nearly 53.9% of ORP, 51.8% of IRP, 47.3% of MRP and 46.3% of YRP were in Jinghong City, and Mengla County had 50.5% of YRP, 48.8% of MRP, 42.4% of IRP and 36.3% of ORP. This study demonstrates that the bi-temporal VIs thresholds method (i.e. NBRdefoliation < 0, NDMIdefoliation, < 0, NBRfoliation < 0, and NDMIfoliation, < 0) have great potential for detecting stand ages of deciduous rubber plantations.
      原文链接:
    • NSTL
    • Elsevier

    Warming trends in Patagonian subantartic forest

    Olivares-Contreras, V. A.Mattar, C.Gutierrez, A. G.Jimenez, J. C....
    15页
    查看更多>>摘要：The forests in the Aysen region (ca. 43-49 degrees S, Chile) have a high degree of wilderness and cover more than 4.8 million hectares, making it one of the largest areas of subantarctic forest in the Southern Hemisphere. The impact of global warming on this region is poorly documented. The main objective of this work was to analyze the normalized difference vegetation index (NDVI), land surface temperature (LST) and precipitation over Aysen forests in the context of ongoing global warming. We used average monthly images of LST and NDVI derived from the MODIS sensor covering the period 2001-2016 and precipitation from gridded datasets. The Aysen region was divided into three nested spatial scales: i) regional, ii) regional considering only forests, iii) local scale considering an evergreen subantarctic forest area covering around 5 x 5 km and a local deciduous forest area (dominated by Nothofagus pumilio). Trend analysis showed a warming rate of +0.78 K/decade (p &lt;= 0.05) over the subantarctic forest zone, greening of +0.01/decade for NDVI (p &lt;= 0.05) over the western zone, and a drying trend (p &lt;= 0.05) over the eastern zone. The minimum temperature anomalies showed an increase of about 4.5 K during the period under analysis. LST, NDVI and precipitation were also analyzed here. The recent trends in temperature, greening and precipitation over the forests of Aysen detected in this research contribute to a better understanding of global warming impacts on subantarctic forests in the southern tip of South America. Nevertheless, to get a better estimation of the impact of global warming at multiple scales is needed to have better quality and quantity of data in situ.
      原文链接:
    • NSTL
    • Elsevier

    Reflectance variation in boreal landscape during the snow melting period using airborne imaging spectroscopy

    Heinila, KirsikkaSalminen, MiiaMetsamaki, SariPellikka, Petri...
    11页
    查看更多>>摘要：We aim a better understanding of the effect of spring-time snow melt on the remotely sensed scene reflectance by using an extensive amount of optical spectral data obtained from an airborne hyperspectral campaign in Northern Finland. We investigate the behaviour of thin snow reflectance for different land cover types, such as open areas, boreal forests and treeless fells. Our results not only confirm the generally known fact that the reflectance of a melting thin snow layer is considerably lower than that of a thick snow layer, but we also present analyses of the reflectance variation over different land covers and in boreal forests as a function of canopy coverage. According to common knowledge, the highly variating reflectance spectra of partially transparent, most likely also contaminated thin snow pack weakens the performance of snow detection algorithms, in particular in the mapping of Fractional Snow Cover (FSC) during the end of the melting period. The obtained results directly support further development of the SCAmod algorithm for FSC retrieval, and can be likewise applied to develop other algorithms for optical satellite data (e.g. spectral unmixing methods), and to perform accuracy assessments for snow detection algorithms.
      原文链接:
    • NSTL
    • Elsevier

    The long-wave infrared (8-12 mu m) spectral features of selected rare earth element-Bearing carbonate, phosphate and silicate minerals

    Laakso, KatiTurner, David J.Rivard, BenoitSanchez-Azofeifa, Arturo...
    7页
    查看更多>>摘要：Rare earth elements (REEs) are a group of metals essential to high technology industries. This high demand, combined with a high supply risk, has led to an understanding that REEs are critical to society. Despite the potential that hyperspectral imaging (HSI) data offers for a fast and non-invasive characterization of the REEs, it is still poorly understood whether REEs have some information in the long-wave infrared (LWIR; 8-12 mu m) wavelength range that can be used for their identification. To partially fill this gap, we have investigated the spectroscopy of twelve REE-bearing mineral samples using relatively high spatial and spectral resolution LWIR hyperspectral imaging data. These samples were formerly characterized using electron probe microanalysis (EPMA), scanning electron microscopy (SEM), and hyperspectral imaging data acquired in the 0.4-2.5 mu m wavelength range. Results from these analyses were compared to and used to guide the analysis of the HSI data recorded in the LWIR range. This information was further compared to a reference spectral library of rare earth oxides. Our findings suggest that the spectral features of the samples can generally be traced to the asymmetric degenerate stretching and bending modes of the X-O (X = C, Si, P) groups. Moreover and contrary to what has been observed in the shorter wavelengths, there are no definitive spectral features in the LWIR wavelength region that could be assigned to any specific REE.
      原文链接:
    • NSTL
    • Elsevier

    Predictive mapping of mosquito distribution based on environmental and anthropogenic factors in Taita Hills, Kenya

    Uusitalo, RuutSiljander, MikaCulverwell, C. LornaMutai, Noah C....
    9页
    查看更多>>摘要：Mosquitoes are vectors for numerous pathogens, which are collectively responsible for millions of human deaths each year. As such, it is vital to be able to accurately predict their distributions, particularly in areas where species composition is unknown. Species distribution modeling was used to determine the relationship between environmental, anthropogenic and distance factors on the occurrence of two mosquito genera, Culex Linnaeus and Stegomyia Theobald (syn. Aedes), in the Taita Hills, southeastern Kenya. This study aims to test whether any of the statistical prediction models produced by the Biomod2 package in R can reliably estimate the distributions of mosquitoes in these genera in the Taita Hills; and to examine which factors best explain their presence. Mosquito collections were acquired from 122 locations between January-March 2016 along transects throughout the Taita Hills. Environmental-, anthropogenic- and distance-based geospatial data were acquired from the Taita Hills geo-database, satellite- and aerial imagery and processed in GIS software. The Biomod2 package in R, intended for ensemble forecasting of species distributions, was used to generate predictive models. Slope, human population density, normalized difference vegetation index, distance to roads and elevation best estimated Culex distributions by a generalized additive model with an area under the curve (AUC) value of 0.791. Mean radiation, human population density, normalized difference vegetation index, distance to roads and mean temperature resulted in the highest AUC (0.708) value in a random forest model for Stegomyia distributions. We conclude that in the process towards more detailed species-level maps, with our study results, general assumptions can be made about the distribution areas of Culex and Stegomyia mosquitoes in the Taita Hills and the factors which influence their distribution.
      原文链接:
    • NSTL
    • Elsevier

    Optimizing and comparing gap-filling techniques using simulated NDVI time series from remotely sensed global data

    Julien, YvesSobrino, Jose A.
    19页
    查看更多>>摘要：NDVI (Normalized Difference Vegetation Index) time series usually suffer from remaining cloud presence, even after data pre-processing. To address this issue, numerous gap-filling (or reconstruction) techniques have been developed in the literature, although their comparison has mainly been local to regional, with only two global studies to date, and has led to sometimes contradictory results. This study builds on these different comparisons, by testing different parameterizations for five NDVI temporal profile reconstruction techniques, namely HANTS (Harmonic Analysis of Time Series), IDR (iterative Interpolation for Data Reconstruction), Savitzky-Golay, Asymmetric Gaussian and Double Logistic, and then comparing them as generally parameterized, and then with the best of the tested parameterizations. These comparisons show that the HANTS reconstruction technique provides lower errors in cloud prone areas, while the IDR method works best with shorter cloud covers. However, the remaining errors in cloud prone areas are still high, and there is room for new reconstruction techniques. Although these results are only applicable to the range of the tested parameterizations, these latter have been chosen within widely used configurations, and should provide interested users with a better understanding of the different methods and the best parameterization for their needs, as well as an estimate of the expected error in the reconstruction of NDVI time series.
      原文链接:
    • NSTL
    • Elsevier

    Remote sensing based yield monitoring: Application to winter wheat in United States and Ukraine

    Franch, B.Vermote, E. F.Skakun, S.Roger, J. C....
    16页
    查看更多>>摘要：Accurate and timely crop yield forecasts are critical for making informed agricultural policies and investments, as well as increasing market efficiency and stability. Earth observation data from space can contribute to agricultural monitoring, including crop yield assessment and forecasting. In this study, we present a new crop yield model based on the Difference Vegetation Index (DVI) extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) data at 1 km resolution and the un-mixing of DVI at coarse resolution to a pure wheat signal (100% of wheat within the pixel). The model was applied to estimate the national and subnational winter wheat yield in the United States and Ukraine from 2001 to 2017. The model at the subnational level shows very good performance for both countries with a coefficient of determination higher than 0.7 and a root mean square error (RMSE) of lower than 0.6 t/ha (15-18%). At the national level for the United States (US) and Ukraine the model provides a strong coefficient of determination of 0.81 and 0.86, respectively, which demonstrates good performance at this scale. The model was also able to capture low winter wheat yields during years with extreme weather events, for example 2002 in US and 2003 in Ukraine. The RMSE of the model for the US at the national scale is 0.11 t/ha (3.7%) while for Ukraine it is 0.27 t/ha (8.4%).
      原文链接:
    • NSTL
    • Elsevier