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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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    GlobeLand30 maps show four times larger gross than net land change from 2000 to 2010 in Asia

    Sbafizadeh-Moghadam, HosseinMinaei, MasoudFeng, YongjiuPontiu, Robert Gilmore, Jr....
    9页
    查看更多>>摘要：This article uses the GlobeLand30 maps of land cover to characterize the difference between years 2000 and 2010 in Asia. Methods of Intensity Analysis and Difference Components dissect the transition matrix for nine categories: Barren, Grass, Cultivated, Forest, Shrub, Water, Artificial, Wetland and Ice. Results show that Barren, Grass, Cultivated, and Forest each account for more than 21% of Asia at both 2000 and 2010, while transitions among those four categories account for more than half of the temporal difference. Nearly ten percent of Asia shows overall temporal difference, which is the sum of three components: quantity, exchange and shift. Quantity accounts for less than a quarter of the temporal difference, while exchange accounts for three quarters of the temporal difference. The largest quantity components at the category level are a net gain of Barren and net losses of Grass and Shrub. Shrub demonstrates the most intensive loss and gain relative to a category's size. The largest and most intensive transitions to Barren are from Grass and Shrub. The largest and most intensive transition to Artificial is from Cultivated. Error information is not available for GlobeLand30 concerning 2000 or temporal change, but a confusion matrix is available for the global extent at 2010. This article applies methods to interpret the difference between two time points when a confusion matrix is available for only the latter time point. If the 2010 global confusion matrix reflects errors in Asia, then such errors could help to explain some of the gross gain of Barren and the counter-intuitive loss of Artificial. If the GlobeLand30 data indicate true change, then gross change in Asia is 4.4 times larger than net change.
      原文链接:
    • NSTL
    • Elsevier

    First assessment of the plant phenology index (PPI) for estimating gross primary productivity in African semi-arid ecosystems

    Abdi, A. M.Boke-Olen, N.Jin, H.Eklundh, L....
    12页
    查看更多>>摘要：The importance of semi-arid ecosystems in the global carbon cycle as sinks for CO2 emissions has recently been highlighted. Africa is a carbon sink and nearly half its area comprises and and semi-arid ecosystems. However, there are uncertainties regarding CO2 fluxes for semi-arid ecosystems in Africa, particularly savannas and dry tropical woodlands. In order to improve on existing remote-sensing based methods for estimating carbon uptake across semi-arid Africa we applied and tested the recently developed plant phenology index (PPD. We developed a PPI-based model estimating gross primary productivity (GPP) that accounts for canopy water stress, and compared it against three other Earth observation-based GPP models: the temperature and greenness (T-G) model, the greenness and radiation (GoR) model and a light use efficiency model (MOD17). The models were evaluated against in situ data from four semi-arid sites in Africa with varying tree canopy cover (3-65%). Evaluation results from the four GPP models showed reasonable agreement with in situ GPP measured from eddy covariance fltut towers (EC GPP) based on coefficient of variation (R-2), root-mean-square error (RMSE), and Bayesian information criterion (BIC). The Gott model produced R-2 = 0.73, RMSE = 1.45 g C m(-2) d(-1), and BIC = 678; the T-G model produced R-2 = 0.68, RMSE = 1.57 g C m(-2) d(-1), and BIC = 707; the MOD17 model produced R-2 = 0.49, RMSE = 1.98 g C and BIC = 800. The PPI-based GPP model was able to capture the magnitude of EC GPP better than the other tested models (R-2 = 0.77, RMSE = 1.32 g C Mm(-2) d(-1), and BIC = 631). These results show that a PPI-based GPP model is a promising tool for the estimation of GPP in the semi-arid ecosystems of Africa.
      原文链接:
    • NSTL
    • Elsevier

    Hourly gridded air temperatures of South Africa derived from MSG SEVIRI

    Meyer, HannaSchmidt, JohannesDetsch, FlorianNauss, Thomas...
    7页
    查看更多>>摘要：Monitoring of climate variables such as air temperature is gaining increasing importance under climate change. This study aimed at developing an hourly gridded 3.5 x 3.5 km air temperature (T-air) data set for entire South Africa. In a Random Forest approach, MSG SEVIRI data from 2010 to 2014 were used and related to T-air measured by 78 weather stations. An external validation on new climate stations and years that were not used for model training indicated the ability of the model to predict T-air with a RMSE of 2.61 degrees C and a R-2 of 0.89. The resulting model can be applied to the entire MSG SEVIRI time series since 2004. It hence allows for spatiotemporal pattern analysis as well as for the detection of trends which is relevant in the context of climate change.
      原文链接:
    • NSTL
    • Elsevier

    Vegetable classification in Indonesia using Dynamic Time Warping of Sentinel-1A dual polarization SAR time series

    Li, MengmengBijker, Wietske
    13页
    查看更多>>摘要：This study investigates the potential of Sentinel-1A (S1A) dual polarization SAR time series data for vegetable classification in Indonesia. Vegetables are characterized by the temporal changes of observables extracted from time series of S1A data. We extracted observables regarding both backscatter (VH and VV) coefficients and decomposition features (i.e., entropy, angle, and anisotropy). The vegetable classification is based on a time-weighted Dynamic Time Warping dissimilarity measure that is calculated with SPRING strategy for subsequence searching, referred to as twDTWS. This study focuses on three main vegetable types widely planted in Indonesia, namely chili, tomato, and cucumber. We conducted vegetable classification in two areas, Malang and Lampung, using time series of S1A data covering the dry season in 2017. Our results show that the twDTWS method provides a promising means to classify vegetables using time series of S1A data for the dry season, while the features decomposed from dual polarization S1A data have little influence on the classification accuracy. Moreover, the twDTWS method with query sequences (namely reference temporal profiles) defined on the Malang dataset produced an overall accuracy of 0.80 for the classification of chili and cucumber from the Lampung dataset when the query sequences correspond to the growth cycles of vegetables. The variation in the length (i.e., the number of observations) of query sequences can affect the classification accuracy. We conclude that the twDTWS method has a high potential for classifying vegetables in different areas when constructing the query sequences of vegetables based on their growth cycles.
      原文链接:
    • NSTL
    • Elsevier

    Could land surface phenology be used to discriminate Mediterranean pine species?

    Aragones, DavidRodriguez-Galiano, Victor F.Caparros-Santiago, Jose A.Navarro-Cerrillo, Rafael M....
    14页
    查看更多>>摘要：Land surface phenology (LSP) can improve the monitoring of forest areas and their change processes. The aim of this study was to characterize the temporal dynamics in Mediterranean pines and evaluate the potential of LSP for species discrimination. We used 661 mono-specific plots for five different Pinus species (Pinus halepensis, P. pima, P. pinaster, P. sylvestris, P. nigra) and the MOD13Q1-NDVI time series (2000-2016) to perform the analyses. The time series were smoothed to extract the phenological parameters and calculate multi-temporal metrics, to synthesize the inter-annual variability. The potential of ISP for discriminating between Pinus species was evaluated by the application of the Random Forest (RF) classifier from different subsets of explanatory variables: i) the smooth time series; ii) the multi-temporal metrics; and iii) the multi-temporal metrics plus the auxiliary physical variables. This latter subset was also used as input to a Classification and Regression Tree (CART) algorithm to better explain the differences between Pinus species regarding LSP parameters and other environmental drivers. The analysis showed two different patterns: an important NDVI decrease during the summer for P. halepensis, P. pinea, and P. pinaster, and lower NDVI variation along the year for P. sylvestris. P. nigra showed a heterogeneous infra-specific behavior, having locations with different patterns. We distinguished Pinus species plots with a global accuracy of 0.82, when we used multi-temporal metrics of LSP and auxiliary physical variables. More generally, the Mediterranean Pinus species could be differentiated considering the 23rd of July as the start of season and 179 km and 1100 m as distance to the coastline and elevation, respectively.
      原文链接:
    • NSTL
    • Elsevier

    Comparing map-based and library-based training approaches for urban land-cover fraction mapping from Sentinel-2 imagery

    Priem, FrederikOkujeni, Akponavan der Linden, SebastianCanters, Frank...
    11页
    查看更多>>摘要：An improved trade-off between resolution, coverage and revisit time, makes Sentinel-2 multispectral imagery an interesting data source for mapping the composition and spatial-temporal dynamics of urban land cover. To fully realize the potential of Sentinel-2's high amount of available data, efficient urban mapping workflows are required. Machine learning regression is a powerful approach to produce subpixel land cover fractions from remote sensing imagery, yet it requires mixed spectra for model training for which the fractions of the land cover classes present in the pixel are known. Typically, this data is obtained by sampling spectra from the image to be unmixed, and corresponding land-cover fractions from higher-resolution land cover reference data, i.e. map based training. We propose synthetic mixing of library spectra as an alternative for producing land cover fraction training data for regression modelling, i.e. library-based training. The approach is applied to a Sentinel-2 image of the city of Brussels (Belgium) and part of its urban fringe for mapping Vegetation, Impervious, and Soil (VIS) fractions at 20 m resolution. VIS fraction maps obtained with library-based training have mean absolute errors below 0.1 for all three surface types. The composition of these three key surface categories and their spatial distribution is well represented for the entire area in resulting maps. As a proof of concept, library-based training is compared with the map-based training approach. The more flexible library-based training not only achieves similar mapping accuracies, but in most cases, outperforms the map-based training approach in terms of bias and magnitude of error. The outcome of the research suggests that use of spectral libraries and synthetic mixing may provide an efficient modelling framework for regression-based mapping from Sentinel-2 imagery in operational contexts.
      原文链接:
    • NSTL
    • Elsevier

    A dynamic soil endmember spectrum selection approach for soil and crop residue linear spectral unmixing analysis

    Yue, JiboTian, QingjiuTang, ShaofeiXu, Kaijian...
    12页
    查看更多>>摘要：Crop residue deposited on the soil surface helps protect against water and wind erosion, improve soil quality and increase soil organic matter and soil carbon storage. Linear spectral mixture analysis (LSMA) is an important technique in field crop residue estimation. Traditionally, only one single or fixed standard crop residue and soil endmember spectrum is performed for each of the presented endmember classes or field. Because the variation in soil endmember spectrum signatures significantly changes with soil moisture (SM), spectral unmixing with fixed endmember spectra can lead to poor accuracy of the abundance of the spectral constituents of pure crop residue. Herein, this paper presents a dynamic soil endmember spectrum selection approach for improving the performance of soil and rice residue spectral unmixing analysis in rice residue cover (RRC) estimation. This new approach uses SM and soil spectral reflectance model to modify soil endmember spectra in each spectral unmixing analysis. Two validation datasets computed results have verified the feasibility and correctness of the dynamic soil endmember method. Results indicated that the distribution of SM in farmland was crucial for RRC estimation. Compared with traditional fixed min and fixed mean soil endmember spectrum methods, the results of the method developed herein showed this method significantly improved RRC estimation accuracy for an SM content lower than 20% (volumetric water content) over the traditional methods tested. Therefore, our proposed approach can be used to improve RRC estimation accuracy in harvest field.
      原文链接:
    • NSTL
    • Elsevier

    How well do global burned area products represent fire patterns in the Brazilian Savannas biome? An accuracy assessment of the MCD64 collections

    Libonati, RenataPereira, Allan A.Nogueira, Joana M. P.Santos, Filippe L. M....
    14页
    查看更多>>摘要：Knowledge about the current fire dynamics in the Brazilian Savannas (Cerrado) relies heavily on satellite-derived burned area (BA) products applied at the biome level. Nevertheless, there is still a lack of studies analyzing the consistency of available available satellite products concerning BA location and extension for the region. Accordingly, we performed an accuracy assessment of the MODerate resolution Imaging Spectroradiometer (MODIS) collection 6 BA product (MCD64 /C6) over 222,768,000 ha encompassing the Brazilian Cerrado. We used reference data derived from Landsat-8 OLI to perform an intercomparison of MCD64/C6 with 1) the previous collection 5.1 (C5.1); 2) independent active fires from the Visible Infrared Imaging Radiometer Suite (VIIRS); and 3) recent land use patterns. The results of the comparison between C6 and C5.1 indicate that the new collection decreases the omission error in 90% of the analyzed area and increases the burn hits, providing improved BA estimates in 61% of the region. However, the MCD64 product increases the overall commission errors in 74% of the area. The MCD64/C6 product showed a high coefficient of correlation with active fires independently detected by VIIRS (tau = 0.74). For both MCD64 collections 5.1 and 6, the different accuracy assessment measures exhibited a marked performance deterioration from the north towards the south. The largest bum scars and total affected areas occur mainly across the northern Cerrado, explaining the better performance in that area. Conversely, greater inaccuracies were found in the southern Cerrado area, where natural vegetation has been converted into pasture and cropland, leading to fragmented landscapes and small fire patches. Finally, the BAs mapped by both collections were similar in location albeit divergent in the magnitude, with C6 detecting 21% more area than C5.1 during the year 2015.
      原文链接:
    • NSTL
    • Elsevier

    Global assessment and mapping of changes in mesoscale landscapes: 1992-2015

    Nowosad, JakubStepinski, Tomasz F.Netzel, Pawel
    9页
    查看更多>>摘要：Monitoring global land cover changes is important because of concerns about their impact on environment and climate. The release by the European Space Agency (ESA) of a set of worldwide annual land cover maps covering the 1992-2015 period makes possible a quantitative assessment of land change on the global scale. While ESA land cover mapping effort was motivated by the need to better characterize global and regional carbon cycles, the dataset may benefit a broad range of disciplines. To facilitate utilization of ESA maps for broad-scale problems in landscape ecology and environmental studies, we have constructed a GIS-based vector database of mesoscale landscapes - patterns of land cover categories in 9 km x 9 km tracts of land. First, we reprojected ESA maps to the Fuller projection to assure that each landscape in the database has approximately the same size and shape so the patterns of landscapes at different locations can be compared. Second, we calculated landscape attributes including its compositions in 1992 and 2015, magnitude of pattern change, categories transition matrix for detailed characterization of change, fractional abundances of plant functional types (PFTs) in 1992 and 2015, and change trend type - a simple, overall descriptor of the character of landscape change. Combining change trends and change magnitude information we constructed a global, thematic map of land change; this map offers a visualization of what, where, and to what degree has changed between 1992 and 2015. The database is SQL searchable and supports all GIS vector operations. Using change magnitude attribute we calculated that only 22% of total landmass experienced significant landscape change during the 1992-2015 period, but that change zone accounted for 80% of all pixel-based transitions. Dominant land cover transitions were forest -> agriculture followed by agriculture -> forest. Using PFTs attributes to calculate global aggregation of gross and net changes for major PFTs yielded results in agreement with other recent estimates.
      原文链接:
    • NSTL
    • Elsevier

    Comparison of models describing forest inventory attributes using standard and voxel-based lidar predictors across a range of pulse densities

    Pearse, Grant D.Watt, Michael S.Dash, Jonathan P.Stone, Christine...
    11页
    查看更多>>摘要：Fine-scale characterisation of forest stands using very high-density aerial lidar data holds considerable potential for improving the accuracy of area-based forest inventories. To realise these gains, new methods of characterising dense aerial point clouds are required. This research presents one potential approach using voxel-based metrics often associated with the analysis of terrestrial lidar data. This was accomplished by comparing predictions of forest inventory attributes made using voxel-based metrics, more standard lidar metrics and a combination of both classes of metrics. A high-density lidar dataset was acquired using a helicopter-mounted RIEGL VUX-1UAV laser scanner to produce point clouds with a minimum density of 280 pulses m(-2). Data were obtained from 73 plots presenting a wide range of stand conditions located within two adjacent plantations of Pirtus radiata D.Don in south-eastern New South Wales. Random forests regression models were developed to predict top height, basal area, stand density and total stem volume. To assess the interaction between metric type and pulse density, the point clouds were thinned to 18 pulse densities ranging from 1 to 280 pulses m-2 before fitting models using the metrics generated from data at each target density. Data thinning had little effect on the predictive accuracy of models for any of the four forest attributes predicted from either voxel-based, standard lidar metrics or their combination. Averaged across all pulse densities, models created for top height, basal area, stand density and total stem volume from standard lidar metrics had R-2 of 0.72, 0.44, 0.34 and 0.53 with normalised RMSE (RMSE expressed as a percentage of the mean for each dimension) of 6,6, 25.2, 60.1 and 25.5% respectively. Use of voxel-based metrics resulted in substantial gains in model precision for all dimensions, apart from top height, with R-2 increasing by 0.04, 0.23, 0.24, and 0.22 and nRMSE averaging 6.1, 19.6, 48.6, and 18.7%, respectively, for top height, basal area, stand density, and total stem volume. The precision of models that used both types of lidar metrics was very similar to the precision of models that used only voxel-based metrics. These results demonstrate the considerable potential of voxel-based metrics for improving the accuracy of forest measurement. The gains from voxelised-metrics were not dependent on very high pulse densities and could be achieved at densities typical of conventional lidar surveys undertaken using fixed-wing aircraft.
      原文链接:
    • NSTL
    • Elsevier