Monitoring change in the extent of salt-affected soils in northern India

A large area of barren salt-affected soils has been reclaimed in recent years in the Ganges Plains or Uttar Pradesh, India, Increased canal irrigation in the area, on the other hand, is also leading to salinization of new areas. A study was conducted using aerial photographs and Landsat Thematic Mapper (TM) data to monitor change in the status of salt-affected soils in the Kanpur district of Uttar Pradesh. Old survey maps prepared using ground methods in 1956, showing large salt-affected soil blocks of more than 80 ha, were used as a basis for comparison. These maps were compared with the maps prepared using aerial photographs of 1972 and Landsat TM images of 1986. Aerial photographs on a 1:40 000 scale and standard Landsat TM false colour composite (FCC) image on 1:50000 scale provided a minimum delineation of 2 ha size, which was considered sufficient for change detection in the present case. The average increase in cultivation due to reclamation within the salt-affected soil blocks during 1956-86 was found to be 22 per cent. This increase was also corroborated by the increase in the rice area during the above period in the district since these soils are used mainly for rice cultivation. During 1972-86, an increase in the extent of salt-affected soils on the periphery of large blocks was also observed, which was limited to 3 per cent.     

Remote sensing technique for mapping salt affected soils

The salt affected soils of Etah, Aligarh, Mainpuri and Mathura districts have been mapped into S1: < 10 per cent of the area covered by salts, S2: 10–30 per cent, S3: 30–50 per cent, S4: 50–75 per cent and S5: > 75 per cent using an integrated approach of image interpretation. The dull white tone of salt affected and sandy soils have posed problems in their discrimination, on TM false colour composite, however, the problem of spectral similarity was solved through integration of interpretation of thermal data (10.4–12.5μm) with TM FCC (bands 2, 3, 4) interpretation. The discrimination of salt affected soils was significantly better on data between March and first week of April because of maximum contrast. Out of l-75m ha of the total geographical area, the salt affected soils account for 11–8 per cent. Another 16–2 per cent is likely to be affected with this problem if similar degraded conditions prevail there. The values of pH: 8–7 and ECe: 1–3 dsm^-1 of S1 soils group them into non saline and mildly alkali class. Similarly low ECe: 4–4dSm^-1 and high pH: 9–8 for S3 soils and high ECe: 24–0 dsm^-1 and very high pH: 10–7 of S4/S5 soils, placed the soils into alkali and sodic classes respectively. The gypsum requirement based on pH values varies from 1 to 15 tha^-1.     

Feasibility study in using multiband photography for studies in geomorphology,soils and land use

Remotely-sensed multiband imagery, covering 64 Km² between latitudes 18^° 28′ 30″-18^° 34′ 45″ N and longitudes 74^° 20′-74^° 23′ 15″ E, has been interpreted. The climate of the region studied is semi-arid tropical with an annual precipitation of 50 cm. The aerial photography, comprised of color infrared (CIR) and black-and-white infrared with 0.5 to 0.9 μm spectral band, and conventional panchromatic with 0.5 to 0.72 μm spectral band, was interpreted by conventional stereoscopic analysis based on tone, texture, pattern, shape, and size. The area was divided into 12 geomorphic units, confirmed from ground survey, and a soil map showing soil series associations was prepared and interpreted. The imagery was interpreted for the delineation of land use patterns. The I.R. false color and the black-and-white imagery on the scale of 1:25,000, with adequate ground surveys and checks, is useful for delineating second-order geomorphic units, soils at the level of association of series, and broad land-use classification.     

Remote sensing of soil salinity: potentials and constraints

Soil salinity caused by natural or human-induced processes is a major environmental hazard. The global extent of primary salt-affected soils is about 955 M ha, while secondary salinization affects some 77 M ha, with 58% of these in irrigated areas. Nearly 20% of all irrigated land is salt-affected, and this proportion tends to increase in spite of considerable efforts dedicated to land reclamation. This requires careful monitoring of the soil salinity status and variation to curb degradation trends, and secure sustainable land use and management. Multitemporal optical and microwave remote sensing can significantly contribute to detecting temporal changes of salt-related surface features. Airborne geophysics and ground-based electromagnetic induction meters, combined with ground data, have shown potential for mapping depth of salinity occurrence. This paper reviews various sensors (e.g. aerial photographs, satellite- and airborne multispectral sensors, microwave sensors, video imagery, airborne geophysics, hyperspectral sensors, and electromagnetic induction meters) and approaches used for remote identification and mapping of salt-affected areas. Constraints on the use of remote sensing data for mapping salt-affected areas are shown related to the spectral behaviour of salt types, spatial distribution of salts on the terrain surface, temporal changes on salinity, interference of vegetation, and spectral confusions with other terrain surfaces.As raw remote sensing data need substantial transformation for proper feature recognition and mapping, techniques such as spectral unmixing, maximum likelihood classification, fuzzy classification, band ratioing, principal components analysis, and correlation equations are discussed. Lastly, the paper presents modelling of temporal and spatial changes of salinity using combined approaches that incorporate different data fusion and data integration techniques.     

On coalgebra of real numbers

We define the continuum up to order isomorphism (and hence homeomorphism) as the final coalgebra of the functor X·ω, ordinal product with ω. This makes an attractive analogy with the definition of the ordinal ω itself as the initial algebra of the functor 1;X, prepend unity, with both definitions made in the category of posets. The variants 1; (X·ω), X^o·ω, and 1;(X^o·ω) yield respectively Cantor space (surplus rationals), Baire space (no rationals), and again the continuum as their final coalgebras.     

Spatial analysis and delineation of ecological landtype phases for the Hoosier National Forest,Indiana, USA

The US Forest Service adopted the National Hierarchical Framework of Ecological Units in 1993 with the ecological landtype (ELT) and ecological landtype phase (ELTP) forming the lowest levels of the hierarchy. This study examines the potential of computer mapping ELTPs for the Hoosier National Forest (HNF) located in southern Indiana. ELTPs were sampled in 2001–2003 within four units of the HNF that are situated within the Brown County Hills and Crawford Upland subsections. A 10-m resolution USGS DEM and a soil survey map were used as source data layers. GIS layers were produced with ArcGIS tools using elevation, slope, aspect, curvature, and soil type. Statistical analysis was performed for those ELTPs that occupy sites similar in physiography but differing in vegetation and soils. A Kruskal–Wallis test of landform variable means indicated a statistically significant variation (p<0.05) among all ELTPs in elevation, aspect, slope, and profile curvature within both subsections. A pairwise Mann–Whitney test showed a significant difference (p<0.05) in elevation, general, and plane curvature among selected ELTPs. A χ² test of soil types derived from soil survey map units revealed a significant difference (p?0.05) in soil type constancy among selected ELTPs. An ELTP map was developed using physiographic characteristics defined in the classification and information from statistical testing. The resulting map provides the basis for management decisions and development of landtype associations (LTAs) using a “bottom-up” approach.     

Comparison of ERS-2 SAR and Landsat TM imagery for monitoring agricultural crop and soil conditions

Studies over the past 25 years have shown that measurements of surface reflectance and temperature (termed optical remote sensing) are useful for monitoring crop and soil conditions. Far less attention has been given to the use of radar imagery, even though synthetic aperture radar (SAR) systems have the advantages of cloud penetration, all-weather coverage, high spatial resolution, day/night acquisitions, and signal independence of the solar illumination angle. In this study, we obtained coincident optical and SAR images of an agricultural area to investigate the use of SAR imagery for farm management. The optical and SAR data were normalized to indices ranging from 0 to 1 based on the meteorological conditions and sun/sensor geometry for each date to allow temporal analysis. Using optical images to interpret the response of SAR backscatter (σ^o) to soil and plant conditions, we found that SAR σ^o was sensitive to variations in field tillage, surface soil moisture, vegetation density, and plant litter. In an investigation of the relation between SAR σ^o and soil surface roughness, the optical data were used for two purposes: (1) to filter the SAR images to eliminate fields with substantial vegetation cover and/or high surface soil moisture conditions, and (2) to evaluate the results of the investigation. For dry, bare soil fields, there was a significant correlation (r²=.67) between normalized SAR σ^o and near-infrared (NIR) reflectance, due to the sensitivity of both measurements to surface roughness. Recognizing the limitations of optical remote sensing data due to cloud interference and atmospheric attenuation, the findings of this study encourage further studies of SAR imagery for crop and soil assessment.     

Effects of corn on C- and L-band radar backscatter: A correction method for soil moisture retrieval

This paper discusses the effects of vegetation on C- (4.75 GHz) and L- (1.6 GHz) band backscattering (σ^o) measured throughout a growth cycle at incidence angles of 15, 35 and 55°. The utilized σ^o data set was collected by a truck mounted scatterometer over a corn field and is supported by a comprehensive set of ground measurements, including soil moisture and vegetation biomass. Comparison of σ^o measurement against simulations by the Integral Equation Method (IEM) surface scattering model (Fung et al., 1992) shows that the σ^o measurements are dominated either by an attenuated soil return or by scattering from vegetation depending on the antenna configuration and growth stage. Further, the measured σ^o is found to be sensitive to soil moisture even at peak biomass and large incidence angles, which is attributed to scattering along the soil-vegetation pathway.For the simulation of C-band σ^o and the retrieval of soil moisture two methods have been applied, which are the semi-empirical water cloud model (Attema & Ulaby, 1978) and a novel method. This alternative method uses the empirical relationships between the vegetation water content (W) and the ratio of the bare soil and the measured σ^o to correct for vegetation. It is found that this alternative method is superior in reproducing the measured σ^o as well as retrieving soil moisture. The highest retrieval accuracies are obtained at a 35° incidence angle leading to RMSD's of 0.044 and 0.037 m³ m^− 3 for the HH and VV-polarization, respectively. In addition, the sensitivity of these soil moisture retrievals to W and surface roughness parameter uncertainties is investigated.     

盐化及钠质化对土壤物理性质的影响

对盐化土壤、钠质盐化土壤的概念及其参数进行了讨论 ,对盐化土壤的水分物理性质、渗透胁迫以及钠质化对土壤结构性能的影响 ,有机质对钠质化土壤结构性能的影响等方面的研究进行了综述     

Application of multitemporal Landsat data to monitor land cover changes in the Eastern Nile Delta region,Egypt

Due to the progressive increase in development of desert land in Egypt, the demand for efficient and accurate land cover change information is increasing. In this study, we apply the methodology of post‐classification change detection to map and monitor land cover change patterns related to agricultural development and urban expansion in the desert fringes of the Eastern Nile Delta region. Using a hybrid classification approach, we employ multitemporal Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images from 1984, 1990 and 2003 to produce three land cover/land‐use maps. Post‐classification comparison of these maps was used to obtain ‘from–to’ statistics and change detection maps. The change detection results show that agricultural development increased by 14% through the study period. The average annual rate of land reclamation during 1990–2003 (4511 ha a^?1) was comparable to that during 1984–1990 (4644 ha a^?1), reflecting a systematic national plan for desert reclamation that went into effect. We find that the increase in urbanization (by ca 21 300 ha) during 1990–2003 was predominantly due to encroachment into traditionally cultivated land at the fringes of urban centres. Our results accurately quantify the land cover changes and delineate their spatial patterns, demonstrating the utility of Landsat data in analysing landscape dynamics over time. Such information is critical for making efficient and sustainable policies for resource management.     

Modelling the impact of land-cover change on potential soil loss in the Taita Hills,Kenya, between 1987 and 2003 using remote-sensing and geospatial data

In sub-Saharan Africa, natural vegetation is being transformed into agricultural lands at a fast rate, endangering ecosystem services and increasing soil-loss potential, which may trigger land degradation. For the Taita Hills study area in Kenya, multi-temporal land-cover models of 1987, 1999 and 2003, derived from Satellite Pour l'Observation de la Terre (SPOT) imagery using a multi-scale segmentation/object relationship modelling (MSS/ORM) methodology and a rainfall layer, a digital elevation model (DEM) and a digital soil map were applied to model potential soil loss. Population growth in the area has led to a shortage of agricultural land and movement of people to the lowlands, evidenced by a 39% (9.3 km²) increase in croplands from 30% to 41% of the study area during the research time frame. Expansion took place mostly in surrounding foothills and lowlands, at the expense of natural shrubland and grassland, but also occurred in the hills. Universal soil-loss equation (USLE) model results showed a 60% (4 km²) increase in the area of very high potential soil loss, from 7% of the study area in 1987 to 12% in 2003, due mainly to very high soil-loss potential in croplands. Whilst the area of croplands as a whole increased, the relative proportion of very high soil-loss potential in croplands remained 20%, both in 1987 and in 2003, indicating that newly cleared agricultural lands with vulnerable soils are the most at-risk areas.     

Directional morphological image transforms for lineament extraction from remotely sensed images

Morphological image transforms find their basis in the notions of mathematical morphology. An attempt is made to develop morphological transforms for enhancement of directional edges and lineaments from satellite imagery. Geostructural features are generally oriented in preferred directions. This information has been utilized in designing structuring elements for morphological transforms. Several shapes and sizes of structuring elements have been designed and applied to delineate lineaments in different litho-environments of the same study area. Top hat transform has been applied using the directional structuring elements for edge image at 0^o, 30^o, 60^o, 90^o, 120^o and 150^o. Geological lineaments such as faults could be easily identified on an edge image obtained using top hat transformation followed by an image superimposition technique. The lineament map was developed using directionally enhanced edge images and the results have been verified.     

Comparing Sentinel-2 MSI and Landsat 8 OLI in soil salinity detection: a case study of agricultural lands in coastal North Carolina

This study presents the first comparison of Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) in identifying soil salinity using soil physiochemical, spectral, statistical, and image analysis techniques. By the end of the century, intermediate sea level rise scenarios project approximately 1.3 meters of sea level rise along the coast of the southeastern United States. One of the most vulnerable areas is Hyde County, North Carolina, where 1140 km² of agricultural lands are being salinized, endangering 4,200 people and $40 million USD of property. To determine the best multispectral sensor to map the extent of salinization, this study compared the feasibility of OLI and MSI to estimate electrical conductivity (EC). The EC of field samples were correlated with handheld spectrometer spectra resampled into multispectral sensor bands. Using an iterative ordinary least squares regression, it was found that EC was sensitive to OLI bands 2 (452 nm – 512 nm) and 4 (636 nm – 673 nm) and MSI bands 2 (457.5 nm – 522.5 nm) and 4 (650 nm – 680 nm). Respectively, the R²_Adj and Root Mean Square Error (RMSE) of 0.04–0.54 and 1.15 for OLI, and 0.05–0.67 and 1.17 for MSI, suggests that the two sensors have similar salinity modelling skill. The extracted saline soils make up approximately 1,703 hectares for OLI and 118 hectares for MSI, indicating overestimation from the OLI image due to its coarser spatial resolution. Additionally, field samples indicate that nearby vegetated land is saline, indicating an underestimation of total impacted land. As sea levels rise, accurately monitoring soil salinization will be critical to protecting coastal agricultural lands. MSI’s spatial and temporal resolution makes it superior to OLI for salinity tracking though they have roughly equivalent spectral resolutions. This study demonstrates that visible spectral bands are sensitive to soil salinity with the Blue and Red spectral ranges producing the highest model accuracy; however, the low accuracies for both sensors indicate the need of narrowband sensors. The HyspIRI to be launched in the early 2020s by NASA may provide ideal data source in soil salinity studies.     

Long‐term monitoring of land cover changes based on Landsat imagery to improve hydrological modelling in West Africa

The spatial and temporal variability of land cover changes is a fundamental parameter to integrate when modelling water resources in order to reproduce the relations between rainfall and surface flow more precisely. This is particularly important in West Africa, where the land cover has been changing for more than 40 years under the combined impact of climatic effects and human activities. In this study, we evaluated the potential of Landsat imagery to monitor the vegetation cover in the upper Niger watershed (120 000 km²) using archive images from MSS, TM and ETM+ sensors covering three periods of time around 1975, 1985, and 2000. Because of the heterogeneity of the acquisition dates, the spatial and spectral resolution of the images, and the scale of analysis, we chose a simple system of classification. Pretreatments were applied to reduce variations between the images. Vegetation indices (NDVI) were then calculated and subsequently thresholded using the same land‐cover classification system. The thresholds were then optimized by automated recursive calculations of confusion matrices and control parcels. Our results revealed that although the accuracy was not perfect, it was nevertheless possible to estimate changes using an unconventional spatio‐temporal scale. The resulting changes were characterized by a moderate trend to deforestation with a corresponding increase in bare soils, soils with sparse vegetation, and shrublands. The spatial layers produced were then combined with a soil map to incorporate changes in surface conditions in the hydrological modelling of the Niger River.     

Caractérisation de formations végétales mediterranéennes à partir de données ‘Thematic Mapper’ Une étude de cas en Andalousie (Espagne)

Abstract

The study is focused on the characterization of vegetation formations in a Mediterranean area (943 km²) located in southern Spain: herbaceous canopies (rangelands), shrubby vegetation (‘matorral’) and complex woody/herbaceous formations (‘dehesa’). Vegetation formations (physiognomical units) have been characterized by their spectral responses in the six reflective TM channels and by vegetation indices. From the ratio index TM4/TM3 there has been derived a map displaying seven classes (water, bare soil and five biomass levels reflecting the hierarchy of vegetation formations). Channels TM3, TM4 and TM5 have been considered for a supervised classification into nine land-cover categories (seven vegetation formations, bare soil and water). The proportion of correct classification of vegetation formations is about 78 per cent when considering test areas. Classification made from three principal components gives similar results.     

Colour additive viewing techniques for small-scale soil mapping in an area of Karimnagar district,Andhra Pradesh,India

Multi-spectral imagery from Landsat relating to the Karimnagar district of Andhra Pradesh, in South India was analysed using colour additive viewing techniques. The results were correlated with an existing soil association map prepared from aerial photo-interpretation with adequate ground truth. The four landscapes and their subdivisions that were identified on the soil map also could be identified on the Landsat map. An overall classification performance of 83·9, 82·4, 80·9 and 95·7 percent respectively has been achieved for rugged (R), undulating hummocky (U), very gently sloping (V) and river alluvium (A) landscapes. The best class performance was in the order of 95·7, 97·6, 81.8 and 95·7 percent and that of the lowest class performance of 50·5, 57·3, 70·1 and 95·7 percent for R, U, V and A landscapes, respectively. The overall combined performance of 85·7 percent has been achieved with respect to soilscape boundary delineations for all the four landscapes. The Student's t-test of significance revealed that for units R₄, U₄ and V₂ the differences were significant and the rest were found to be nonsignificant. This study has demonstrated the usefulness of colour additive viewing techniques in the analysis of Landsat-MSS data for small-scale soil mapping and the same could be used for the preparation of small-scale soil maps of the States and the country.     

Circularly polarized stacked patch antenna array with enhanced bandwidth for S‐band applications

In this article, a circularly polarized coupled slot 1 × 4 stacked patch antenna array with enhanced bandwidth is proposed for S‐band applications. Initially, a patch antenna radiating at 2.79 GHz is designed and maximum energy from feedline to patch element is coupled using two rectangular slots. Whereas, a parallel feedline structure is designed to provide polarization flexibility by creating 0, 90 , and 180^o phase differences. Then, a truncated patch element is vertically stacked in the design to achieve broader bandwidth of 600 MHz over frequency range from 2.4 to 3.0 GHz. Finally, a coupled slot 1 × 4 array stacked antenna array having feedline line structure to provide 90^o phase difference for circular polarization is designed and fabricated for measurements. It is observed that the final design achieved target specification having impedance matching (|S₁₁ | (dB) < ?10 dB over 2.4 to 3.0 GHz, broad band circular polarization, and 11.5 dBic total gain. Overall, a good agreement between simulated and measurement results is observed.     

新疆奎屯123团土壤砷污染研究

土壤砷污染是一种十分严重的环境问题。80年代初,新疆奎屯垦区发现了中国大陆第一个地方性砷中毒病区。本文主要以奎屯123团为研究区域,通过对该地区土壤中砷含量的测定,分析该地区土壤中砷的污染状况,砷的主要来源,探讨砷在土壤中的分布特征。结果表明奎屯123团0~20 cm土壤中砷的含量范围在8.36~39.63mg kg-1,算术平均值为16.67mg kg-1,高于全国的平均水平。土壤中砷的来源主要受自然因素的影响,同时也受到高砷地下水灌溉以及含砷农药、化肥等诸多人为因素的影响,砷在该地区土壤中的垂直变化没有呈现出统一的规律。     

Product category description for web-shopping in e-commerce

In this paper, we focus on the web-shopping activity and on ways to improve the quality of the information available to consumers. We describe a tool, called a product space map, for the presentation of information about a product category which can help consumers in making purchasing decisions. Using this tool we first provide a clustering or segmentation of a product line, that is, 27-inch televisions, into price categories such as low end, moderate and high end. Once having this partitioning we then use the idea of linguistic summaries to describe the properties of each category with respect to relevant features. An example of such a summary is “Most TV's in the high price category provide extremely high resolution.” With the aid of such information it becomes much easier for consumers to understand the product line, see what they are getting for their money, and more easily and confidently locate products that are of particular value for the money. Considerable use is made of fuzzy set technology to provide the ability to describe the information in a way, using linguistic expressions, that is particularly consumer friendly. © 2001 John Wiley & Sons, Inc.