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1.
InSAR to support sustainable urbanization over compacting aquifers: The case of Toluca Valley,Mexico
This paper illustrates how InSAR alone can be used to delineate potential ground fractures related to aquifer system compaction. An InSAR-derived ground fracturing map of the Toluca Valley, Mexico, is produced and validated through a field campaign. The results are of great interest to support sustainable urbanization and show that InSAR processing of open-access Synthetic Aperture Radar (SAR) data from the Sentinel-1 satellites can lead to reliable and cost-effective products directly usable by cities to help decision-making.The Toluca Valley Aquifer (TVA) sustains the water needs of two million inhabitants living within the valley, a growing industry, an intensively irrigated agricultural area, and 38% of the water needs of the megalopolis of Mexico City, located 40 km east of the valley. Ensuring water sustainability, infrastructure integrity, along with supporting the important economic and demographic growth of the region, is a major challenge for water managers and urban developers. This paper presents a long-term analysis of ground fracturing by interpreting 13 years of InSAR-derived ground displacement measurements. Small Baseline Subset (SBAS) and Persistent Scatterer Interferometry (PSI) techniques are applied over three SAR datasets totalling 93 acquisitions from Envisat, Radarsat-2, and Sentinel-1A satellites and covering the period from 2003 to 2016.From 2003 to 2016, groundwater level declines of up to 1.6 m/yr, land subsidence up to 77 mm/yr, and major infrastructure damages are observed. Groundwater level data show highly variable seasonal responses according to their connectivity to recharge areas. However, the trend of groundwater levels consistently range from −0.5 to −1.5 m/yr regardless of the well location and depth. By analysing the horizontal gradients of vertical land subsidence, we provide a potential ground fracture map to assist in future urban development planning in the Toluca Valley. 相似文献
2.
Significant structural damages to urban infrastructures caused by compaction of over-exploited aquifers are an important problem in Central Mexico. While the case of Mexico City has been well-documented, insight into land subsidence problems in other cities of Central Mexico is still limited. Among the cities concerned, we present and discuss the cases of five of them, located within the Trans-Mexican Volcanic Belt (TMVB): Toluca, Celaya, Aguascalientes, Morelia, and Queretaro. Applying the SBAS-InSAR method to C-Band RADARSAT-2 data, five high resolution ground motion time-series were produced to monitor the spatio-temporal variations of displacements and fracturing from 2012 to 2014. The study presents recent changes of land subsidence rates along with concordant geological and water data. It aims to provide suggestions to mitigate future damages to infrastructure and to assist in groundwater resources management.Aguascalientes, Celaya, Morelia and Queretaro (respectively in order of decreasing subsidence rates) are typical cases of fault-limited land subsidence of Central Mexico. It occurs as a result of groundwater over-exploitation in lacustrine and alluvial deposits covering highly variable bedrock topography, typical of horst-graben geological settings. Aguascalientes and Toluca show high rates of land subsidence (up to 10 cm/yr), while Celaya and Morelia show lower rates (from 2 to 5 cm/yr). Comparing these results with previous studies, it is inferred that the spatial patterns of land subsidence have changed in the city of Toluca. This change appears to be mainly controlled by the spatial heterogeneity of compressible sediments since no noticeable change occurred in groundwater extraction and related drawdown rates. While land subsidence of up to 8 cm/yr has been reported in the Queretaro Valley before 2011, rates inferior to 1 cm/yr are measured in 2013–2014. The subsidence has been almost entirely mitigated by major changes in the water management practices of the city, i.e., a 122 km long pipeline bringing surface water from an adjacent state allowed to cease pumping in half of the wells. 相似文献
3.
Knowledge on the interaction of active structures is essential to understand mechanics of continental deformation and estimate the earthquake potential in complex tectonic settings. Here we use Sentinel-1A radar imagery to investigate coseismic deformation associated with the 2016 Menyuan (Qinghai) earthquake, which occurred in the vicinity of the left-lateral Haiyuan fault. The ascending and descending interferograms indicate thrust-dominated slip, with the maximum line-of-sight displacements of 58 and 68 mm, respectively. The InSAR observations fit well with the uniform-slip dislocation models except for a larger slip-to-width ratio than that predicted by the empirical scaling law. We suggest that geometric complexities near the Leng Long Ling restraining bend confine rupture propagation, resulting in high slip occurred within a small area and much higher stress drop than global estimates. Although InSAR observations cannot distinguish the primary plane, we prefer the west-dipping solution considering aftershocks distribution and the general tectonic context. Both InSAR modelling and aftershock locations indicate that the rupture plane linked to the Haiyuan fault at 10 km depth, a typical seismogenic depth in Tibet. We suggest that the earthquake more likely occurred on a secondary branch at a restraining bend of the Haiyuan fault, even though we cannot completely rule out the possibility of it being on a splay of the North Qilian Shan thrusts. 相似文献
4.
Image classification using multispectral sensors has shown good performance in detecting macrophytes at the species level. However, species level classification often does not utilize the texture information provided by high resolution images. This study investigated whether image texture provides useful vector(s) for the discrimination of monospecific stands of three floating macrophyte species in Quickbird imagery of the South Nation River. Semivariograms indicated that window sizes of 5 × 5 and 13 × 13 pixels were the most appropriate spatial scales for calculation of the grey level co-occurrence matrix and subsequent texture attributes from the multispectral and panchromatic bands. Of the 214 investigated vectors (13 Haralick texture attributes * 15 bands + 9 spectral bands + 10 transformations/indices), feature selection determined which combination of spectral and textural vectors had the greatest class separability based on the Mann–Whitney U-test and Jefferies–Matusita distance. While multispectral red and near infrared (NIR) performed satisfactorily, the addition of panchromatic-dissimilarity slightly improved class separability and the accuracy of a decision tree classifier (Kappa: red/NIR/panchromatic-dissimilarity – 93.2% versus red/NIR – 90.4%). Class separability improved by incorporating a second texture attribute, but resulted in a decrease in classification accuracy. The results suggest that incorporating image texture may be beneficial for separating stands with high spatial heterogeneity. However, the benefits may be limited and must be weighed against the increased complexity of the classifier. 相似文献
5.
Terrestrial laser scanning (TLS) has been used to estimate a number of biophysical and structural vegetation parameters. Of these stem diameter is a primary input to traditional forest inventory. While many experimental studies have confirmed the potential for TLS to successfully extract stem diameter, the estimation accuracies differ strongly for these studies – due to differences in experimental design, data processing and test plot characteristics. In order to provide consistency and maximize estimation accuracy, a systematic study into the impact of these variables is required. To contribute to such an approach, 12 scans were acquired with a FARO photon 120 at two test plots (Beech, Douglas fir) to assess the effects of scan mode and circle fitting on the extraction of stem diameter and volume. An automated tree stem detection algorithm based on the range images of single scans was developed and applied to the data. Extraction of stem diameter was achieved by slicing the point cloud and fitting circles to the slices using three different algorithms (Lemen, Pratt and Taubin), resulting in diameter profiles for each detected tree. Diameter at breast height (DBH) was determined using both the single value for the diameter fitted at the nominal breast height and by a linear fit of the stem diameter vertical profile. The latter is intended to reduce the influence of outliers and errors in the ground level determination. TLS-extracted DBH was compared to tape-measured DBH. Results show that tree stems with an unobstructed view to the scanner can be successfully extracted automatically from range images of the TLS data with detection rates of 94% for Beech and 96% for Douglas fir. If occlusion of trees is accounted for stem detection rates decrease to 85% (Beech) and 84% (Douglas fir). As far as the DBH estimation is concerned, both DBH extraction methods yield estimates which agree with reference measurements, however, the linear fit based approach proved to be more robust for the single scan DBH extraction (RMSE range 1.39–1.74 cm compared to 1.47–2.43 cm). With regard to the different circle fit algorithms applied, the algorithm by Lemen showed the best overall performance (RMSE range 1.39–1.65 cm compared to 1.49–2.43 cm). The Lemen algorithm was also found to be more robust in case of noisy data. Compared to the single scans, the DBH extraction from the merged scan data proved to be superior with significant lower RMSE’s (0.66–1.21 cm). The influence of scan mode and circle fitting is reflected in the stem volume estimates, too. Stem volumes extracted from the single scans exhibit a large variability with deviations from the reference volumes ranging from −34% to 44%. By contrast volumes extracted from the merged scans only vary weakly (−2% to 6%) and show a marginal influence of circle fitting. 相似文献
6.
On July 11, 1995, an Mw 6.8 earthquake struck eastern Myanmar near the Chinese border; hereafter referred to as the 1995 Myanmar–China earthquake. Coseismic surface displacements associated with this event are identified from JERS-1 (Japanese Earth Resources Satellite-1) SAR (Synthetic Aperture Radar) images. The largest relative displacement reached 60 cm in the line-of-sight direction. We speculate that a previously unrecognized dextral strike-slip subvertical fault striking NW–SE was responsible for this event. The coseismic slip distribution on the fault planes is inverted based on the InSAR-derived deformation. The results indicate that the fault slip was confined to two lobes. The maximum slip reached approximately 2.5 m at a depth of 5 km in the northwestern part of the focal region. The inverted geodetic moment was approximately Mw = 6.69, which is consistent with seismological results. The 1995 Myanmar–China earthquake is one of the largest recorded earthquakes that has occurred around the “bookshelf faulting” system between the Sagaing fault in Myanmar and the Red River fault in southwestern China. 相似文献
7.
We developed a method to produce a 3-D voxel-based solid model of a tree based on portable scanning lidar data for accurate estimation of the volume of the woody material. First, we obtained lidar measurements with a high laser pulse density from several measurement positions around the target, a Japanese zelkova tree. Next, we converted lidar-derived point-cloud data for the target into voxels. The voxel size was 0.5 cm × 0.5 cm × 0.5 cm. Then, we used differences in the spatial distribution of voxels to separate the stem and large branches (diameter > 1 cm) from small branches (diameter ⩽ 1 cm). We classified the voxels into sets corresponding to the stem and to each large branch and then interpolated voxels to fill out their surfaces and their interiors. We then merged the stem and large branches with the small branches. The resultant solid model of the entire tree was composed of consecutive voxels that filled the outer surface and the interior of the stem and large branches, and a cloud of voxels equivalent to small branches that were discretely scattered in mainly the upper part of the target. Using this model, we estimated the woody material volume by counting the number of voxels in each part and multiplying the number of voxels by the unit voxel volume (0.13 cm3). The percentage error of the volume of the stem and part of a large branch was 0.5%. The estimation error of a certain part of the small branches was 34.0%. 相似文献
8.
9.
This paper assesses the capability of hyperspectral remote sensing to detect hydrocarbon leakages in pipelines using vegetation status as an indicator of contamination. A field experiment in real scale and in tropical weather was conducted in which Brachiaria brizantha H.S. pasture plants were grown over soils contaminated with small volumes of liquid hydrocarbons (HCs). The contaminations involved volumes of hydrocarbons that ranged between 2 L and 12.7 L of gasoline and diesel per m3 of soil, which were applied to the crop parcels over the course of 30 days. The leaf and canopy reflectance spectra of contaminated and control plants were acquired within 350–2500 nm wavelengths. The leaf and canopy reflectance spectra were mathematically transformed by means of first derivative (FD) and continuum removal (CR) techniques. Using principal component analysis (PCA), the spectral measurements could be grouped into either two or three contamination groups. Wavelengths in the red edge were found to contain the largest spectral differences between plants at distinct, evolving contamination stages. Wavelengths centred on water absorption bands were also important to differentiating contaminated from healthy plants. The red edge position of contaminated plants, calculated on the basis of FD spectra, shifted substantially to shorter wavelengths with increasing contamination, whereas non-contaminated plants displayed a red shift (in leaf spectra) or small blue shift (in canopy spectra). At leaf scale, contaminated plants were differentiated from healthy plants between 550–750 nm, 1380–1550 nm, 1850–2000 nm and 2006–2196 nm. At canopy scale, differences were substantial between 470–518 nm, 550–750 nm, 910–1081 nm, 1116–1284 nm, 1736–1786 nm, 2006–2196 nm and 2222–2378 nm. The results of this study suggests that remote sensing of B. brizantha H.S. at both leaf and canopy scales can be used as an indicator of gasoline and diesel contaminations for the detection of small leakages in pipelines. 相似文献
10.
In this study, linear spectral mixture analysis (LSMA) is used to characterize the spectral heterogeneity of lava flows from Nyamuragira volcano, Democratic Republic of Congo, where vegetation and lava are the two main land covers. In order to estimate fractions of vegetation and lava through satellite remote sensing, we made use of 30 m resolution Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Imager (ALI) imagery. 2 m Pleiades data was used for validation. From the results, we conclude that (1) LSMA is capable of characterizing volcanic fields and discriminating between different types of lava surfaces; (2) three lava endmembers can be identified as lava of old, intermediate and young age, corresponding to different stages in lichen growth and chemical weathering; (3) a strong relationship is observed between vegetation fraction and lava age, where vegetation at Nyamuragira starts to significantly colonize lava flows ∼15 years after eruption and occupies over 50% of the lava surfaces ∼40 years after eruption. Our study demonstrates the capability of spectral unmixing to characterize lava surfaces and vegetation colonization over time, which is particularly useful for poorly known volcanoes or those not accessible for physical or political reasons. 相似文献
11.
Land subsidence in the Bandung basin, West Java, Indonesia, is characterized based on differential interferometric synthetic aperture radar (DInSAR) and interferometric point target analysis (IPTA). We generated interferograms from 21 ascending SAR images over the period 1 January 2007 to 3 March 2011. The estimated subsidence history shows that subsidence continuously increased reaching a cumulative 45 cm during this period, and the linear subsidence rate reached ∼12 cm/yr. This significant subsidence occurred in the industrial and densely populated residential regions of the Bandung basin where large amounts of groundwater are consumed. However, in several areas the subsidence patterns do not correlate with the distribution of groundwater production wells and mapped aquifer degradation. We conclude that groundwater production controls subsidence, but lithology is a counteracting factor for subsidence in the Bandung basin. Moreover, seasonal trends of nonlinear surface deformations are highly related with the variation of rainfall. They indicate that there is elastic expansion (rebound) of aquifer system response to seasonal-natural recharge during rainy season. 相似文献
12.
Cyanobacterial blooms in water supply sources in both central Indiana USA (CIN) and South Australia (SA) are a cause of great concerns for toxin production and water quality deterioration. Remote sensing provides an effective approach for quick assessment of cyanobacteria through quantification of phycocyanin (PC) concentration. In total, 363 samples spanning a large variation of optically active constituents (OACs) in CIN and SA waters were collected during 24 field surveys. Concurrently, remote sensing reflectance spectra (Rrs) were measured. A partial least squares–artificial neural network (PLS–ANN) model, artificial neural network (ANN) and three-band model (TBM) were developed or tuned by relating the Rrs with PC concentration. Our results indicate that the PLS–ANN model outperformed the ANN and TBM with both the original spectra and simulated ESA/Sentinel-3/Ocean and Land Color Instrument (OLCI) and EO-1/Hyperion spectra. The PLS–ANN model resulted in a high coefficient of determination (R2) for CIN dataset (R2 = 0.92, R: 0.3–220.7 μg/L) and SA (R2 = 0.98, R: 0.2–13.2 μg/L). In comparison, the TBM model yielded an R2 = 0.77 and 0.94 for the CIN and SA datasets, respectively; while the ANN obtained an intermediate modeling accuracy (CIN: R2 = 0.86; SA: R2 = 0.95). Applying the simulated OLCI and Hyperion aggregated datasets, the PLS–ANN model still achieved good performance (OLCI: R2 = 0.84; Hyperion: R2 = 0.90); the TBM also presented acceptable performance for PC estimations (OLCI: R2 = 0.65, Hyperion: R2 = 0.70). Based on the results, the PLS–ANN is an effective modeling approach for the quantification of PC in productive water supplies based on its effectiveness in solving the non-linearity of PC with other OACs. Furthermore, our investigation indicates that the ratio of inorganic suspended matter (ISM) to PC concentration has close relationship to modeling relative errors (CIN: R2 = 0.81; SA: R2 = 0.92), indicating that ISM concentration exert significant impact on PC estimation accuracy. 相似文献
13.
Seagrass habitats in subtidal coastal waters provide a variety of ecosystem functions and services and there is an increasing need to acquire information on spatial and temporal dynamics of this resource. Here, we explored the capability of IKONOS (IKO) data of high resolution (4 m) for mapping seagrass cover [submerged aquatic vegetation (%SAV) cover] along the mid-western coast of Florida, USA. We also compared seagrass maps produced with IKO data with that obtained using the Landsat TM sensor with lower resolution (30 m). Both IKO and TM data, collected in October 2009, were preprocessed to calculate water depth invariant bands to normalize the effect of varying depth on bottom spectra recorded by the two satellite sensors and further the textural information was extracted from IKO data. Our results demonstrate that the high resolution IKO sensor produced a higher accuracy than the TM sensor in a three-class % SAV cover classification. Of note is that the OA of %SAV cover mapping at our study area created with IKO data was 5–20% higher than that from other studies published. We also examined the spatial distribution of seagrass over a spatial range of 4–240 m using the Ripley’s K function [L(d)] and IKO data that represented four different grain sizes [4 m (one IKO pixel), 8 m (2 × 2 IKO pixels), 12 m (3 × 3 IKO pixels), and 16 m (4 × 4 IKO pixels)] from moderate-dense seagrass cover along a set of six transects. The Ripley’s K metric repeatedly indicated that seagrass cover representing 4 m × 4 m pixels displayed a dispersed (or slightly dispersed) pattern over distances of <4–8 m, and a random or slightly clustered pattern of cover over 9–240 m. The spatial pattern of seagrass cover created with the three additional grain sizes (i.e., 2 × 24 m IKO pixels, 3 × 34 m IKO pixels, and 4 × 4 m IKO pixels) show a dispersed (or slightly dispersed) pattern across 4–32 m and a random or slightly clustered pattern across 33–240 m. Given the first report on using satellite observations to quantify seagrass spatial patterns at a spatial scale from 4 m to 240 m, our novel analyses of moderate-dense SAV cover utilizing Ripley’s K function illustrate how data obtained from the IKO sensor revealed seagrass spatial information that would be undetected by the TM sensor with a 30 m pixel size. Use of the seagrass classification scheme here, along with data from the IKO sensor with enhanced resolution, offers an opportunity to synoptically record seagrass cover dynamics at both small and large spatial scales. 相似文献
14.
Co-seismic deformation associated with the Lushan (China) earthquake that occurred along the south-western segment of the Longmenshan Fault Zone (LFZ) on the 20th April 2013 has been estimated by differential interferometric SAR (DInSAR) technique using Radarsat-2 data. The Lushan earthquake resulted in the deformation of the Sichuan basin and the Longmenshan ranges in proximity to the LFZ. The line of sight (LOS) displacement values obtained from DInSAR technique mainly range between −4.0 cm to +3.0 cm. The western Sichuan basin shows oblique westward movement with predominant downward component in areas farther from LFZ and predominant westward component over the downward movement in areas closer to the source fault. Inversion modelling has been used to derive the seismic source characteristics from DInSAR derived deformation values using elastic dislocation source type. The linear inversion model converged at a double-fault source solution consisting of a deeper, steep, NW dipping fault plane-1 of 60 km × 16 km dimension and a shallower, gentle, NW dipping fault plane-2 of 60 km × 15 km dimension, with distributed slip values varying between 0 to 2.26 m. These fault planes (fault planes-1 and -2) coincide with the Dachuan-Shuangshi fault and the buried Range Front Fault, respectively. The inversion model gives a moment magnitude of 6.81 and the geodetic moment of 2.07 × 1019 Nm, comparable to those given in literature, derived using teleseismic body wave data. Thus DInSAR technique helped to quantify the co-seismic deformation and to retrieve the source characteristics from the estimated deformation values. The study also evaluated the distribution pattern of earthquake induced landslides (EIL) triggered fresh or re-activated during the Lushan earthquake and found that they show spatial association with the seismic source zone and also with various pre-conditioning factors of slope instability. 相似文献
15.
In the present study, we aimed to map canopy heights in the Brazilian Amazon mainly on the basis of spaceborne LiDAR and cloud-free MODIS imagery with a new method (the Self-Organizing Relationships method) for spatial modeling of the LiDAR footprint. To evaluate the general versatility, we compared the created canopy height map with two different canopy height estimates on the basis of our original field study plots (799 plots located in eight study sites) and a previously developed canopy height map. The compared canopy height estimates were obtained by: (1) a stem diameter at breast height (D) – tree height (H) relationship specific to each site on the basis of our original field study, (2) a previously developed D–H model involving environmental and structural factors as explanatory variables (Feldpausch et al., 2011), and (3) a previously developed canopy height map derived from the spaceborne LiDAR data with different spatial modeling method and explanatory variables (Simard et al., 2011). As a result, our canopy height map successfully detected a spatial distribution pattern in canopy height estimates based on our original field study data (r = 0.845, p = 8.31 × 10−3) though our canopy height map showed a poor correlation (r = 0.563, p = 0.146) with the canopy height estimate based on a previously developed model by Feldpausch et al. (2011). We also confirmed that the created canopy height map showed a similar pattern with the previously developed canopy height map by Simard et al. (2011). It was concluded that the use of the spaceborne LiDAR data provides a sufficient accuracy in estimating the canopy height at regional scale. 相似文献
16.
The objective of this study was to investigate the entire spectra (from visible to the thermal infrared; 0.390–14.0 μm) to retrieve leaf water content in a consistent manner. Narrow-band spectral indices (calculated from all possible two band combinations) and a partial least square regression (PLSR) were used to assess the strength of each spectral region. The coefficient of determination (R2) and root mean square error (RMSE) were used to report the prediction accuracy of spectral indices and PLSR models. In the visible-near infrared and shortwave infrared (VNIR–SWIR), the most accurate spectral index yielded R2 of 0.89 and RMSE of 7.60%, whereas in the mid infrared (MIR) the highest R2 was 0.93 and RMSE of 5.97%. Leaf water content was poorly predicted using two-band indices developed from the thermal infrared (R2 = 0.33). The most accurate PLSR model resulted from MIR reflectance spectra (R2 = 0.96, RMSE = 4.74% and RMSE cross validation RMSECV = 6.17%) followed by VNIR–SWIR reflectance spectra (R2 = 0.91, RMSE = 6.90% and RMSECV = 7.32%). Using thermal infrared (TIR) spectra, the PLSR model yielded a moderate retrieval accuracy (R2 = 0.67, RMSE = 13.27% and RMSECV = 16.39%). This study demonstrated that the mid infrared (MIR) and shortwave infrared (SWIR) domains were the most sensitive spectral region for the retrieval of leaf water content. 相似文献
17.
Monitoring the spring green-up date (GUD) has grown in importance for crop management and food security. However, most satellite-based GUD models are associated with a high degree of uncertainty when applied to croplands. In this study, we introduced an improved GUD algorithm to extract GUD data for 32 years (1982–2013) for the winter wheat croplands on the North China Plain (NCP), using the third-generation normalized difference vegetation index form Global Inventory Modeling and Mapping Studies (GIMMS3g NDVI). The spatial and temporal variations in GUD with the effects of the pre-season climate and soil moisture conditions on GUD were comprehensively investigated. Our results showed that a higher correlation coefficient (r = 0.44, p < 0.01) and lower root mean square error (22 days) and bias (16 days) were observed in GUD from the improved algorithm relative to GUD from the MCD12Q2 phenology product. In spatial terms, GUD increased from the southwest (less than day of year (DOY) 60) to the northeast (more than DOY 90) of the NCP, which corresponded to spatial reductions in temperature and precipitation. GUD advanced in most (78%) of the winter wheat area on the NCP, with significant advances in 37.8% of the area (p < 0.05). GUD occurred later at high altitudes and in coastal areas than in inland areas. At the interannual scale, the average GUD advanced from DOY 76.9 in the 1980s (average 1982–1989) to DOY 73.2 in the 1990s (average 1991–1999), and to DOY 70.3 after 2000 (average 2000–2013), indicating an average advance of 1.8 days/decade (r = 0.35, p < 0.05). Although GUD is mainly controlled by the pre-season temperature, our findings underline that the effect of the pre-season soil moisture on GUD should also be considered. The improved GUD algorithm and satellite-based long-term GUD data are helpful for improving the representation of GUD in terrestrial ecosystem models and enhancing crop management efficiency. 相似文献
18.
The influence of morphophysiological variation at different growth stages on the performance of vegetation indices for estimating plant N status has been confirmed. However, the underlying mechanisms explaining how this variation impacts hyperspectral measures and canopy N status are poorly understood. In this study, four field experiments involving different N rates were conducted to optimize the selection of sensitive bands and evaluate their performance for modeling canopy N status of rice at various growth stages in 2007 and 2008. The results indicate that growth stages negatively affect hyperspectral indices in different ways in modeling leaf N concentration (LNC), plant N concentration (PNC) and plant N uptake (PNU). Published hyperspectral indices showed serious limitations in estimating LNC, PNC and PNU. The newly proposed best 2-band indices significantly improved the accuracy for modeling PNU (R2 = 0.75–0.85) by using the lambda by lambda band-optimized algorithm. However, the newly proposed 2-band indices still have limitations in modeling LNC and PNC because the use of only 2-band indices is not fully adequate to provide the maximum N-related information. The optimum multiple narrow band reflectance (OMNBR) models significantly increase the accuracy for estimating the LNC (R2 = 0.67–0.71) and PNC (R2 = 0.57–0.78) with six bands. Results suggest the combinations of center of red-edge (735 nm) with longer red-edge bands (730–760 nm) are very efficient for estimating PNC after heading, whereas the combinations of blue with green bands are more efficient for modeling PNC across all stages. The center of red-edge (730–735 nm) paired with early NIR bands (775–808 nm) are predominant in estimating PNU before heading, whereas the longer red-edge (750 nm) paired with the center of “NIR shoulder” (840–850 nm) are dominant in estimating PNU after heading and across all stages. The OMNBR models have the advantage of modeling canopy N status for the entire growth period. However, the best 2-band indices are much easier to use. Alternatively, it is also possible to use the best 2-band indices to monitor PNU before heading and PNC after heading. This study systematically explains the influences of N dilution effect on hyperspectral band combinations in relating to the different N variables and further recommends the best band combinations which may provide an insight for developing new hyperspectral vegetation indices. 相似文献
19.
This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 − 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = −1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08–0.12 and 0.1–0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = −0.019 m3 m−3, ubRMSE = 0.062 m3 m−3 for the IGBP-based calibration; against R = 0.54, bias = −0.034 m3 m−3 and ubRMSE = 0.070 m3 m−3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product. 相似文献
20.
This paper is a comprehensive review of the potential for remote sensing in exploring for geothermal resources. Temperature gradients in the earth crust are typically 25–30 °C per kilometer depth, however in active volcanic areas situated in subduction or rift zones gradients of up to 150 °C per kilometer depth can be reached. In such volcanic areas, meteoric water in permeable and porous rocks is heated and hot water is trapped to form a geothermal reservoir. At the Earth's surface hot springs and fumaroles are evidence of hot geothermal water. In low enthalpy systems the heat can be used for heating/cooling and drying while in high enthalpy systems energy is generated using hot water or steam. In this paper we review the potential of remote sensing in the exploration for geothermal resources. We embark from the traditional suite of geophysical and geochemical prospecting techniques to arrive at parameters at the Earth surface that can be measured by earth observing satellites. Next, we summarize direct and indirect detection of geothermal potential using alteration mineralogy, temperature anomalies and heat fluxes, geobotanical anomalies and Earth surface deformation. A section of this paper is dedicated to published remote sensing studies illustrating the principles of mapping: surface deformation, gaseous emissions, mineral mapping, heat flux measurements, temperature mapping and geobotany. In a case study from the La Pacana caldera (Chili) geothermal field we illustrate the cross cutting relationships between various surface manifestations of geothermal reservoirs and how remotely sensed indicators can contribute to exploration. We conclude that although remote sensing of geothermal systems has not reached full maturity, there is great potential for integrating these surface measurements in a exploration framework. A number of recommendations for future research result from our analysis of geothermal systems and the present contributions of remote sensing to studying these systems. These are grouped along a number of question lines: ‘how reproducible are remote sensing products’, ‘can long term monitoring of geothermal systems be achieved’ and ‘do surface manifestations link to subsurface features’? 相似文献