Evaluation of multisensor data for delineating salt affected soils in arid rajasthan

The Landsat (MSS and TM), SPOT (PLA and MLA) and IRS (LISS-I and LISS-II) images of crop free period (April, May), rainfed crop (October) and rabi irrigated crop (January, February) have been evaluated for their capabilities of mapping (1) primary salt affected soils: (slightly, moderately and severely) (2) saline water irrigated saline soils, (3) sodic water irrigated sodic soils and (4) salt affected soils due to tank seepage in the arid region of Rajasthan. The moderately and severe salt affected soils could be mapped with Landsat, (IRS LISS-I) and SPOT, images of any season. However, the summer season imagery provided maximum extent of salt affected soils. The LISS-II imagery also provided delineation of slightly salt affected soils in addition to the moderate and severely salt affected soils. The delineation of saline and sodic water irrigated areas was possible by using Landsat False Colour Composite for the January month by their characteristic reflectance, existing cropping pattern and the quality of irrigation water being used in the area. The IRS (LISS-II) and SPOT PLA images for the May month were also used for mapping of saline and sodic water irrigated soils.     

Soil resource inventory of Punjab using remote sensing technique

Landsat MSS data in the form of BW imagery were used to generate Soil Map of Punjab convering an area of about 5 million ha. MSS bands 2 and 4 (L4) were interpreted singly and combined to form a compostie interpretetion map with which field check, was translated in terms of soils. The abstraction level attained was Great Groups of Soil Taxonomy. The distribution of soils of Punjab, with Aridisols in the SW through Inceptisols in the Central zone, to Alfisols in the NE sectors suggested a strong geographic bias in their evolution. The major soils of the aridic zone (SW sectors of the state) are: Camborthids, Calciorthids, Torripsamments and Torrifluvents and of the Ustic zone (Central Punjab) are Ustochrepts and Haplustalfs (the most productive soils of the State), Ustipsamments and Ustifluvents. The salt affected soils are found interspersed with these soils. In the udic zone (NE fringe), Hapludalfs, Eutrochrepts, Udifluvents, Udorthents and Hapludolls are the major soil formations. The soil map reveals that about one-third of the total area of the state suffers from various soil problems, such as soil salinity and sodicity, water logging, and soil erosion. For increasing agricultural production, these soils need to be brought under the plough. The study leads to conclude that for quick and precise macro level land use planning, the use of Landsat imagery is imperative.     

Monitoring of salt affected soils — A case study using aerial photographs,salyut‐7 space photographs,and landsat TM data

Soils of part of Ukai‐kakarapar Command area, Gujarat (India) have been mapped at 1:25, 000 scale using aerial photographs of December 1977. It was observed that about 36.3% of the area was affected by soil salinity/alkalinity. The test area has been remapped using Salyut‐7 space photographs taken during Indo‐Soviet joint flight in April, 1984. The area affected by soil salinity/alkalinity was found to be substantially higher (80.3%). The earlier mapping using aerial photographs was done when the soil surface was compartively moist (December 1977) as compared to date of Salyut‐7 photography (April 1984), when the soil surface was likely to be devoid of moisture and the salts moved to the surface. To have easy comparision with the map prepared by using aerial photographs, Landsat TM data of December, 1985 was used in which 45.7% of the total area was mapped as salt affected. The extent of area delineated using Landsat TM was higher than that of 1977 but much lesser than the area delineated using Salyut‐7 (MKF‐6M) photographs. This indicated that the increase in the extent of salt affected area in the map prepared using the MKF‐6M photographs might be partly due to actual increase in the salinity/alkalinity and partly due to the seasonal affects. Among the various bands of MKF‐6M, band ‐4 was found to be the best for delineating the salt affected soils. The boundaries were sharper in the FCC and band No.4 of MKF‐6M than in the aerial photographs.     

Environmental aspects in Dalli-Rajhara iron ore mine area,M.P. using digital image processing techniques

Landsat MSS (1982) and IRS LISS-II (1989) data have been used to study the land use/land cover changes in Dalli-Rajhara iron ore mine area. Supervised classification has been performed on the temporal data to generate land use/land cover maps. Land use/land cover categories generated from IRS LISS-II data of 36 m resolution has been resampled to 80 m and areal statistics have been computed for 2, 4, 8 and 10 km wide strips around Dalli-Rajhara iron ore mine. The environmental impact due to on-going mining activities in the area has been analysed. The results of this study indicate that due to increase in mine-related and agricultural activities, forests have been degraded and also forest areas have been reduced considerably.     

黄河三角洲盐碱地遥感调查研究

土壤盐渍化是干旱、半干旱农业的主要的土地退化问题，有关盐碱地的性质、范围、面积、地理分布及盐渍程度等方面的实时、可靠的信息，对治理盐碱地防止其进一步退化和进行农业可持续发展规划至关重要，提出运用Landsat TM遥感数据来获取这些信息。基于地物光谱特征、野外调查建立的地物与影像之间的关系以及土壤和地下水监测数据的辅助，将常规监督分类法和改进的图像分类法两种方法相结合，提取了不同盐渍程度的盐碱地，即光板地14477．67hm^2，重度盐碱地52086．33hm^2，中度盐碱地86699．61hm^2，轻度盐碱地215001.7hm^2，占黄河三角洲总面积的近二分之一（47．4％），除此之外，水体，滩涂，非盐碱地等也作了区分。     

Hydrologic investigations in the north Chilean Altiplano using landsat ‐ MSS and ‐ TM data

In order to understand Late Glacial high lake levels in the dry Andes of Northern Chile, recent short ‐ to medium‐term fluctuations in the water budget of present lakes and brines (salars) and their relationship with the atmospheric circulation were investigated. A time sequence of four Landsat‐MSS images between November 1983 and August 1984 was analysed in terms of changing water surface and water volume of several lakes and salars. The variations of the open water bodies were interpreted as a result of the spatial pattern of summer and winter precipitation. Furthermore a method to determine water depth and water salinity of the very shallow salars and lakes by correlating field measurements and digital Landsat‐TM data is described. The resulting model to compute water depth was also applied to the MSS‐sequence, showing good results.     

Application of remote sensing and GIS to assess land use changes in Jhunjhunun district of arid Rajasthan

Over the last four decades exploitation of natural resources to meet increasing societal demands for land based products has caused significant changes in land use and land cover not only in nature’s best gifted regions but also environmentally sensitive arid regions. Through digital interpretation of IRS LISS-III data of 2004 supported with field survey, the present land use map of Jhunjhunun district of arid Rajasthan has been prepared. Agriculture is the dominant land use constituting 84% (including 38% irrigated cropland) area. The land use changes over time and space are worked out by comparing with Landsat 2 MSS data of 1975 and Land use/land cover map of 1988–89. These changes are correlated by analyzing historical land use and cropping pattern data from 1957–58 to 2004–05. The region witnessed record increase in irrigated area but sharply depleted ground water and rendered hectares of irrigated double cropland into dry land agriculture. Strategies and technologies are suggested for sustainable use and management of different category of land.     

Land use change detection based on multi‐date imagery from different satellite sensor systems

An empirical study was performed assessing the accuracy of land use change detection when using satellite image data acquired ten years apart by sensors with differing spatial resolutions. Landsat/Multi‐spectral Scanner (MSS) with Landsat/Thematic Mapper (TM) or SPOT/High Resolution Visible (HRV) multi‐spectral (XS) data were used as a multi‐data pair for detecting land use change. The primary objectives of the study were to: (1) compare standard change detection methods (e.g. multi‐date ratioing and principal components analysis) applied to image data of varying spatial resolution; (2) assess whether to transform the raster grid of the higher resolution image data to that of the lower resolution raster grid or vice‐versa in the registration process: and (3) determine if Landsat/TM or SPOT/ HRV(XS) data provides more accurate detection of land use changes when registered to historical Landsat/MSS data.

Ratioing multi‐sensor, multi‐date satellite image data produced higher change detection accuracies than did principal components analysis and is useful as a land use change enhancement technique. Ratioing red and near infrared bands of a Landsat/MSS‐SPOT/HRV(XS) multi‐date pair produced substantially higher change detection accuracies (～10%) than ratioing similar bands of a Landsat/MSS ‐ Landsat/TM multi‐data pair. Using a higher‐resolution raster grid of 20 meters when registering Landsat/MSS and SPOTZHRV(XS) images produced a slightly higher change detection accuracy than when both images were registered to an 80 meter raster grid. Applying a “majority”; moving window filter whose size approximated a minimum mapping unit of 1 hectare increased change detection accuracies by 1–3% and reduced commission errors by 10–25%.     

RESULTS OF COMBINED ANALYSIS OF GROUND AND REMOTE SENSING INFORMATION IN THE STUDY OF MAJOR EARTHQUAKE CENTERS

Soil salinity is one of the most important problems affecting Egyptian soils. It is caused by: (1) a rising water table, or (2) the misuse of the irrigation water. Two Landsat images acquired in 1987 and 1999 were used to detect and monitor soil salinity over the Siwa Oasis, Western Desert, Egypt. DN values of these images were converted to percent reflectance. Inspection of Landsat images revealed that saline soils had an overall higher spectral reflectance in all spectral bands except the two MIR bands. The reflectance curves of saline soils show a strong relationship between the existence of salts in the soil and the difference between bands 4 and 5. A salinity index (SI) was calculated for both images. The majority of pixels in the 1987 image have salinity index values ranging between 0 and 0.2, whereas the values in the 1999 image histogram ranged between 0 and 0.4. These values indicate that soil salinity has increased twofold during the 12 years spanning the imagery. These values show a strong correlation with vegetation index images, in which the 1999 vegetation index image reveals the appearance of surface water lakes formed due to a rising water table. This study presents a model for the identification of soil salinity using remote sensing measurements in conjunction with piezometer readings taken during the time of image acquisition.     

基于3S技术的干旱区绿洲土壤盐渍化动态监测

选择生态环境脆弱的艾比湖地区绿洲为研究对象,采用1990年、2001年、2010年3期TM和ETM+影像为数据源进行土壤盐渍化分类,对研究区20 a土壤盐渍化动态变化进行了统计与分析。研究结果表明,非盐渍化土壤分布的面积最为广泛,但动态变化最为缓慢;轻度盐渍地经历了先增加后减少的过程,中度盐渍地在这20 a里一直呈现出下降的趋势;重度盐渍地在1990年分布面积最多,为366.35 km2;极重度盐渍地分布面积最少,但面积变化最为剧烈。     

Analysis of seasonal variation in the Niger River interior delta using satellite data∗

The Niger River is one of the most important sources of water supply for human consumption and agriculture in Western Africa. Two Landsat‐5 Multispectral Scanner (MSS) images, corresponding to the dry and wet seasons, over a selected area of the Niger River interior delta were classified to produce a land cover/land use map that reflects the geo‐hydrological units of this area. To classify the satellite data, training statistics were generated using a clustering algorithm with parameter values that maximize the separability among spectral classes. Both dry and wet season images are required to obtain an accurate classification for evaluation of hydrological parameters. The spatial resolution of the MSS proved to be adequate for this kind of work, since all the major cover types and geographic features were correctly recognized.     

Segregation of soilscapes using statistics in remote sensing

The use of remotely sensed data in the form of vertical aerial photographs has been in practice since several decades. Launching of Landsat satellites and their capability together multispectral scanner data afforded soil scientists enhanced capability for mapping soils. Technological advances in computer processing of Landsat MSS data coupled with ancillary information provided added advantages. Still difficulties exist in identifying the interference to vegetation and in segregation of narrowly defined soilscapes. Utility of statistical data, obtainable from computer analysis, and an aid in understanding the reflectance characteristics of various types of vegetation and soilscapes has been discussed in this paper. The final output obtained by computer processing compared with existing soil maps of the area registered more future prospects for utilisation of statistics in segregation of soilscapes and vegetation.     

Comparative evaluation of Indian remote sensing satellite and landsat thematic mapper data for geological and geomorphological applications

In order to evaluate the potentials of IRS‐1A Linear Imaging Self‐scanning Sensor (LISS‐I) data for geological and geomorphological applications and also to compare the IRS‐1A LISS‐I data with Landsat Thematic Mapper (TM) data, a study has been attempted for parts of Uttar Pradesh and Madhya Pradesh in Northern India. The first four spectral bands of Landsat TM sensor data which are similar and close to IRS‐1A LISS‐I senor have been utilised for the comparative evaluation. Various techniques employed for both the data set to derive the required geology and geomorphology related information include (i) band combination (ii) spectral response analysis (iii) principal component analysis (iv) supervised classification techniques and (v) visual observation of various outputs generated by the above methods. The Optimum Index Factor (OIF) method adopted for selecting suitable band combinations showed similar OIF rankings for IRS‐1A LISS‐I data and Landsat TM data. It has been visually observed that the band combination 1, 3 & 4 offers relatively better feature display. The spectral responses derived for various major geologic rock units such as Deccan Trap, Vindhyan Formation, Bundelkhand Granite and for a few landcovers such as surface water bodies and black soil show striking similarity in pattern for both LISS‐I and TM. The Principal Component (PC) analysis of both data sets suggested that the total scene brightness tends to dominate in the first PC. The percentage information contributed by PCs 1&2 as also by PCs 1,2 & 3 in both the LISS‐I and TM are comparable. It was observed from the classified image generated by performing supervised classification with a maximum likelihood algorithm that major geomorphic landforms were clearly distinguishable. Thus the qualitative and quantitative evaluation of both IRS‐1A LISS‐I and Landsat TM data showed that significant similarities exist between them. The study also revealed that IRS‐1A LISS‐I data can be effectively used for deriving geology and geomorphology related details.     

Geoinformatics as a tool for the assessment of the impact of ground water quality for irrigation on soil health

Secondary salinisation is the most harmful and extended phenomenon of the unfavourable effects of irrigation on the soil and environment. An attempt was made to study the impact of poor quality ground water on soils in terms of secondary salinisation and availability of soil nutrients in Faridkot district of Punjab of northern India. Based on physiographic analysis of IRS 1C LISS-III data and semi-detailed soil survey, the soil map was finalized on a 1:50,000 scale and digitized using Arc Info GIS. Georeferenced surface soil samples (0–0.15 m) from 231 sites were collected and analyzed for available phosphorus (P) and potassium (K). Interpolation by kriging produced digital spatial maps of available P and K. Ground water quality map was generated in GIS domain on the basis of EC (electrical conductivity) and RSC (residual sodium carbonate) of ground water samples collected from 374 georeferenced tube wells. Integration of soil and ground water quality maps enabled generating a map showing degree (high, moderate and low) and type (salinity, sodicity and both) of vulnerability to secondary salinization. Fine-textured soils have been found to be highly sensitive to secondary salinisation, whereas medium-textured soils as moderately sensitive to secondary salinisation. The resultant map was integrated with available P and K maps to show the combined influence of soil texture and ground water quality on available soil nutrients. The results show that available P and K in the soils of different physiographic units were found in the order of Ap1 < Ap2 < Ap3. The soils of all physiographic units had sizeable area having high content of P (>22.5 kg / ha) and medium available K (135–335 kg ha⁻¹) in most of the test sites when irrigated with saline, sodic or poor quality water.     

Landsat TM versus MSS data for forest type identification

Landsat Thematic Mapper (TM) and Multispectral Scanner (MSS) data were digitally analyzed for forest type identification in the Kisatchie Ranger District, Kisatchie National Forest, Louisiana. Ground‐verification maps were produced from field surveys and interpretation of 1.12,000 and 1: 58,000 color‐infrared (CIR) aerial photography of nine compartments. Stand boundary and soils maps were input to a digital Geographic Information System (GIS) with the Landsat and ground‐verification data.

‐ Unsupervised classifications of the Landsat data did not identify the above cover types well. Supervised classifications were tested by stand agreement to the ground verification. The highest four‐class agreement was obtained for the TM classification (76 percent). Three‐class (open, pine, and hardwoods) stand agreements (81 (MSS) and 85 (TM) percent) were not significantly different as tested by analysis of variance (alpha level 0.1).     

Relative performance of landsat MSS,TM and IRS LISS-I data for acreage estimation of Rabi sorghum

Acreage estimation of Rabi sorghum crop in Ahmadnagar, Pune and Solapur districts of central Maharashtra has been attempted using synchronously acquired Landsat MSS and TM data of 1987–88 season and IRS LISS-I data of 1988–89 season; in conjuction with near-synchronous ground truth data. The remote-sensing-based acreage estimations for the districts were compared with the respective estimates by Bureau of Economics and Statistics (BES). As the acreages were underestimated with the classification of standard four-band MSS data, the atmospheric correction of fourband MSS data and normalised differencing (ND) of the atmospheric-corrected MSS data were attempted. The main observations are: (1) the use of Landsat MSS data results in underestimation of sorghum acreage in comparison with BES estimation, (2) the atmospheric correction and ND transformation of MSS data are necessary for bringing acreage estimates in agreement with BES estimates, (3) Mid-IR data in band 1.55 to 1.75 μm are useful in improving the separability of land-use classes, and (4) remote sensing data with radiometric sensitivity comparable to LISS-I or Landsat TM and Signal-to-Noise ratios comparable to LISS-I data are suitable for accurate acreage estimation of sorghum.     

塔里木盆地周边地区土地退化的遥感研究

以20世纪70年代陆地卫星MSS和90年代ETM图像为基础,通过分析对比,并配合野外检查验证,快速提取了塔里木盆地周边地区4种程度土地沙化类型的分布信息.根据获取的两个时期4种程度的土地沙化类型分布信息,编制了全区土地沙化程度及范围变迁图.该图客观地反映了区内近30a来土地退化的实际情况,为干旱-半干旱地区的土地退化研究提供了遥感技术应用实例.     

三峡库区近30年土地利用时空变化特征分析

利用三峡库区1975年、1987年、1995年、2000年和2005年的遥感影像数据,提取各期土地利用图。以各期土地利用图为基础图件,利用G IS技术,分析了三峡库区各期土地利用类型的数量、空间分布及变化趋势,分析表明库区的耕地、林地和草地都在减少,库区近30年建设用地和河流水面的增加最为明显。同时引入土地利用变化的景观特征指数、土地利用变化速度、土地利用程度指数来总结三峡库区近30年来土地利用变化的主要时空变化特征。采用多种特征指数相结合的研究方法,有利于了解三峡库区土地利用变化的特征,可以进一步指导库区的土地利用规划,为库区的生态环境保护提供参考。     

Remote sensing and GIS in identification of soil constraints for sustainable development in Bhilwara district,Rajasthan

Soil is an integral part of ecosystem nurturing the biological system. Sustainable management of soil resources based on the consideration of constraints is the key to check land degradation and maintain productivity of biological system. To meet the objective remote sensing and GIS technology has been employed for identification of soil constraints in resource potential Bhilwara district. IRS LISS-III FCC images were interpreted for soil constraints using physiography soil approach, verified through field checking and laboratory analysis. On IRS LISS-III FCC images the salt affected soils of Kotri and Taswaria appeared in bright white to light grey tone, smooth texture with white mottles. These were also verified during ground truth and soil analysis for salinity (EC 2.90–3.32 dS m⁻¹) and sodicity (pH 9.50–9.86 and ESP 17.60–19.05). Similarly on the LISS III FCC, constraints due to water erosion near Bir, Sareri and Vijaypura soil series were apparent in light grey to whitish tone, intercepted by medium grey streaks indicating streams and exposed sub-soil. The constraints due to shallow depth associated with rock out crops and hilly areas of Balda and Delwara series appeared in greenish grey tone and coarse texture. There was close relationship between image characteristics, field observation and analytical data.     

Recognition of arid zone soil features from Landsat imagery

Usefulness of Landsat imagery in discerning major arid zone soils has been studied. Results are based on analysis of Band 7 coverage and Band 5 and 7 for a limited area followed by a comparison of these with the known soil distribution as seen in Bikaner, Jodhpur and part of Jalore, Pali and Nagaur districts. Results show that at Band 7 the dominant course loamy Typic Camborthids in association with dunes could be recognised. Vegetation was found non-interfering though surface soil moisture variation of the period immediately following monsoon months (Sept.–Dec.) appeared to do so. Hardpan soils were identifiable largely by their associated features than by soil characteristics proper. Fine loamy typic Camborthids could not be recognised at series level and as a group also these could be identified only in post-monsoon period when the land is devoid of much of its vegetation cover. Saline areas could be recognised but those occurring in South-eastern tract were largely inseparable from adjoining shallow soils. For these, Band 5 image of monsoon months was quite satisfactory. For all other soils, Band 7 was better than Band 5. Though light brown sandy soils in association with dunes are the dominant formations, past evolutionary history and source rock variability have given considerable heterogeniety to the soil cover of the arid zone. Natural resource survey activity over the years has provided ground information for nearly 30 percent of Westren Rajasthan and this incidentally covers major soils of the area albeit with few exceptions. With the Landsat imagery now becoming accessible, it was thought befitting to see how far soil variations as recognised in the course of above surveys could be discerned from the Landsat. Some encouraging reports on the use of the Landsat or similar data in small cale soil mapping are available in literature (Kristof and Zachary, 1970; El-Baz, 1978; Everitt and Gerbermann 1977). In our own country also usefulness of this tool has been demonstrated by Krishnamurthy and Srinivanan (1973) and Hilwig (1975). Recently Bhandariet al; (1976) while working in northern part of arid zone have shown that soil salinity mapping could be attempted with the help of Landsat data.