Delineation of soil associations for a part of tamil nadu by digital processing of landsat multispectral data

The utility of Landsat multispectral data for small scale soil mapping has been demonstrated in this study. The scene used for the study has path-row number 153-054 of Landsat-1 dated 26th February, 1973 covering parts of Ramnad, Tirunelveli and Kanyakumari districts of Tamil Nadu. Associations of sub groups have been delineated on 1 : 250,000 scale using computer-aided multispectrcl data analysis system (M-DAS). Soil map prepared using the computer has been found to be camparable with the soil map prepared by conventional methods at the same scale. Apart from the soil associations, other land use/land cover classes like water bodies forest/scrub/hiliy areas, crcps etc. were also categorised in the colour coded soil map.     

Characteristics and morphogenesis of salt-affected soils in southeastern arid Rajasthan

Aerial photographs coupled with ground check and laboratory analysis have helped in mapping of four categories of salt affected soils located in the southeastern tract of arid Rajasthan. The categories are (1) Natural saline soils (2) Relict saline soils (3) Secondary salinized soils due to high water table and (4) Secondary salinised soils due to highly saline water use for irrigation Salinity in natural salt affected soils is mostly sodium chloride followed by sodium-calcium chloride and sodium-chloride-sulphate type. The distribution of the natural salt affected soils along the natural drainage or inconspicuous depressional areas suggest that their occurrence is due to insufficient surface drainage. Further, the pattern of distribution indicates that the origin of salt is within the catchment itself. Deep ploughing and application of organic material have reversed the upward flux of salts and improved the soils. This phenomenon also seems to explain the large occurrence of soils of relict salinity.     

Spectral reflectance characteristics of salt-affected arid soils of Rajasthan

The spectral reflectance characteristics of different types of natural and anthropogenic salt-affected soils have been studied under field conditions. The spectral reflectance value for non-saline and all types of salt-affected soils was maximum in near infra red region (800–1000 nm). The natural salt-affected soils having surface salt encrustation showed highest reflectance value followed by the sodic soils (formed due to high residual sodium carbonate water irrigation) natural saline soils and saline soils due to saline water irrigation. Soil texture, pH, CaC0₃ and organic matter together accounted for 29.6% variation in the maximum reflectance percentage value out of which only pH accounted for more than half (14.2% variation).     

Retrieval of soil physicochemical properties towards assessing salt-affected soils using Hyperspectral Data

The relationship between soil salinity parameters and their influence on soil spectral characteristics were analyzed using both satellite data (Hyperion) and reflectance data of soil samples collected from parts of Ahmedabad district of Gujarat, India. The soil spectral reflectance curves were assessed using absorption feature parameters by DISPEC software to identify suitable spectral band for salinity characterization. The Hyperion data of the study area were processed and classified into different classes by spectral angle mapper algorithm using spectral library generated from soil spectra. The results showed that among all the observed soil parameters Electrical Conductivity, Exchangeable Sodium Percentage, Cation Exchange Capacity and Mg⁺⁺ predictions can be made accurately based on partial least square regression models developed from selected wavelengths. Out of the total study area moderately saline-sodic, severely saline-sodic, severely saline and slightly saline soils occupy 23.5, 12.6, 10.9 and 0.04%, respectively.     

Mapping salt-affected soils in Sangrur district (Punjab) using aerial photo-interpretation technique

A detailed-reconnaissance soil survey of the Sangrur district was undertaken through systematic aerial photo-interpretation technique and a soil map on 1: 50,000 scale showing the association of soil series prepared. The salt-affected soils have been grouped into 4 soil associations and 8 soil series based on the diffrences in texture, drainge, profile development and degree of deterioration. The salt-affected soils are found both in plains and Channels. The piain unit without distinct parcelling (barren) white and fine textured tones represented the association of salic Natraqualfs (Ghabdan series) and Aquic Natruststalfs (Kaheru series). The piain units partly cultivated whitish-gray, fine to medium textured tones consisted of a association of Natraquic Calciorthids (Langrian and Narikc series) and Natraquic Camborthids (Isri Series). Lastly, the piain units with pattern of dark-tone and light mottles (mottled-iones,) distinct parceiling, cultivated consists of Typic Ustochrepts (Balewal series), Aquic Camborthids (Phaguwala series) and Natraquic Calciorthids (Marike series). The filled up Channels whitish-gray tones, concave relief, cultivated comprise wet soils (Jatwan series) which have been classified as Aeric Halaquepts. It is found that about 17% of the mapped area in Sangrur district is salt-affected, out of which 12% consisiing Ghabdan, Kaheru, Langrian and Isri series is severely salt-affected and rest 5% consisting, Phaguwala, Narike and Jatwan series is moderately to slightly affected.     

On urban heat island of Beijing based on landsat TM data

Land surface temperature (LST) of Beijing area was retrieved from Landsat TM thermal band data utilizing a radiative transfer equation and the urban heat island (HUI) effects of Beijing and its relationship with land cover and normalized difference vegetation index (NDVI) were discussed. The result of LST showed that the urban LST was evidently higher than the suburban one. The average urban LST was found to 4. 5°C and 9°C higher than the suburban and outer suburban temperature, respectively, which demonstrated the prominent UHI effects in Beijing. Prominent negative correlation between LST and NDVI was found in the urban area, which suggested the low percent vegetation cover in the urban area was the main cause of the urban heat island.     

A comparative evaluation of IRS-1A LISS-II and landsat MSS images using computer-aided lineament data analysis

Lineament patterns detected from remotely sensed data provide useful information to geoscientists, specially in the study of basement tectonics, groundwater targetting and mineral exploration. Improvements in the spatial resolution of satellite images have resulted in the detection of short and faint lineaments which have hitherto gone unnoticed The IRS-1A LISS-II data offers a significant improvement in spatial resolution as compared to the Landsat MSS. A set of computer programmes developed for analysis of lineaments were used to study the parameters such as lineament frequency, length and density in order to quantify the added information derived using IRS-1A LISS-II images. The incremental contribution of LISS-II images are of the order of 100 per cent for lineament frequency and about 60 per cent for total line kilometers of lineaments detected.     

An evaluation of landsat thematic mapper data for reforestation monitoring in British Columbia

Renewal of forests is important for continued wood supply and for other benefits. Consequently, restocking of forest cut-overs is a major forest management activity. Effective planning and successful implementation of reforestation programmes require efficient techniques for obtaining timely and accurate information regarding restocking status over clearcut forest lands. The purpose of this paper is to investigate the potential of Landsat Thematic Mapper (TM) data for reforestation monitoring. B-distance, a multivariation distance measure, has been used to measure spectral separability. Attempt has been made to discriminate five restocking classes (with percent canopy classes of 0,10 -12,15 -18, 43 - 47 and 100). Finally selection has been made for the optimum multiband subset from the six reflective TM bands. The results indicate that the combinations of TM bands 3-4-5, 4-5-7,1-4-5, and 2-4-5 were most useful for discriminating various restocking classes. Overall classification accuracies are estimated to be approximately 90 percent using these three-band subsets.     

Verification of net primary production estimation method in the Mongolian Plateau using landsat ETM+data

We plan to estimate global net primary production (NPP) of vegetation using the Advanced Earth Observing Satellite-II (ADEOS-II) Global Imager (GLI) multi-spectral data. We derive an NPP estimation algorithm from ground measurement data on temperate plants in Japan. By the algorithm, we estimate NPP using a vegetation index based on pattern decomposition (VIPD) for the Mongolian Plateau. The VIPD is derived from Landsat ETM+multi-spectral data, and the resulting NPP estimation is compared with ground data measured in a semi-arid area of Mongolia. The NPP estimation derived from satellite remote sensing data agrees with the ground measurement data within the error range of 15% when all above-ground vegetation NPP is calculated for different vegetation classifications.     

基于TRMM降雨数据的中国黄淮海地区干旱监测分析

热带降雨测量卫星(tropical rainfall measuring mission,TRMM)的降雨数据覆盖范围广,时间分辨率高,是区域干旱监测的一种有效数据源。将0.25°空间分辨率的TRMM 3B43数据降尺度处理成0.05°空间分辨率数据,用以构建降水量距平百分率(Pa指数)和Z指数,对黄淮海地区2010年冬季到2011年春季的干旱时空演化特征进行监测与分析,并计算同期的标准化降水指数(standardized precipitation index,SPI)对监测结果进行验证。研究结果表明,降尺度数据具有较高的可靠性,与实测数据的拟合结果 R20.76;Pa指数突出降水盈亏程度,能够有效监测区域尺度干旱,但缺乏空间分布规律;Z指数以Person-Ⅲ型分布拟合降水量,能够很好地监测干旱的时空演化特征,但干旱等级划分相对困难;利用Pa指数对Z指数干旱等级划分进行修正,其结果与SPI相关程度R20.75,表明Pa和Z指数用于干旱监测的有效性,为区域尺度干旱监测提供了一种切实可行的方法。     

Soil resource survey of silent valley and its environ using landsat MSS data

This paper presents a case study of the utility of Landsat MSS imagery for soil resoruces mapping in Silent Valley and its environs covering about 33,000 sq. km. area. A collective approach involving monoscopic visual interpretation of Landsat imagery in conjunction with the lithological and topographical information supported by limited field check has been followed to prepare a soil map on 1:250,000 scale showing sub-groups/association of sub-groups. Future prospect of using spaceborne data for soil mapping has also been discussed.     

基于Landsat长时间序列数据估算树高和生物量

以Landsat长时间序列数据为研究对象,旨在以光谱序列信息反演森林参数为视角,应用Landtrendr算法从时间序列数据中提取森林扰动变量,使用随机森林计算方法建立扰动变量、反射率和GLAS激光点森林参数之间的关系模型,获取树高和生物量的空间分布信息。为多源遥感数据反演森林参数提供参考,研究证明基于Landsat长时间序列数据获得的森林扰动变量能够增强反射率和森林参数之间的相关性,可提高预测精度。     

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.     

Identification and delineation of saline soils using aerial photographs in Yamuna Alluvial plain,Haryana

Salinity is creating great problems in the Yamuna Alluvial Plain. State Government is taking steps for reclaiming these lands to increase agricultural production. Impeded drainage, excess canal irrigation, topography parent material, shallow depth and bad quality of ground water are the main factors which are responsible for the genesis of saline soils in the alluvial plains of Haryana. On the arial photographs tonal differences on account of salt concentration in the soil are clearly seen. These differences are aslo associated with physiography and soil conditions which can be easily delineated. The information thus; collected can be used for reclamation of saline soils.     

银川平原湿地时空变化信息的可视化分析

针对在湿地动态变化监测中,经典的土地利用转移矩阵无法实现湿地类型变化信息的定位可视化表达的问题,提出了一种新的时空变化信息的可视化分析方法。利用由空间单元和时序单元集成的时空复合单元建立转移图谱单元分类体系,较好地记录每一个图谱单元湿地类型的起始和终止状态,实现了湿地时空变化信息的定位表达;基于遥感制图和地学图谱的湿地空间演变规律特征图谱,采用图表和图谱的形式展示湿地类型变化的数量及空间位置变化信息,实现了湿地时空变化的可视化表达。基于银川平原湿地的实验结果表明:该方法能够清晰、直观地显示1999—2013年期间银川平原湿地的时空变化,能够为该地区合理利用湿地资源提供科学的理论依据。     

Glacial mapping using landsat thematic mapper data: A case study in parts of gangotri glacier, NW himalaya

Glacial mapping is difficult and hazardous because of the remoteness and inaccessibility of the terrain. In this context, remotely-sensed data from satellites provide valuable information on glaciers and the associated landforms. It is important to note that judicious selection of spectral bands is critical in mapping the glacial features. Glacial landforms in parts of Gangotri glacier, NW Himalaya, have been delineated using selected bands of Landsat Thematic Mapper Data. Digital image processing of Landsat data has helped in identifying the major features of the Gangotri glacier such as accumulation and ablation zones, and glacial moraines. The study shows that Thematic Mapper bands 4, 5 and 7 are more useful in snow mapping because of their distinct spectral discriminability in identifying the glacial features.     

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.     

Modelling urban growth in the Indo-Gangetic plain using nighttime OLS data and cellular automata

The present study demonstrates the applicability of the Operational Linescan System (OLS) sensor in modelling urban growth at regional level. The nighttime OLS data provides an easy, inexpensive way to map urban areas at a regional scale, requiring a very small volume of data. A cellular automata (CA) model was developed for simulating urban growth in the Indo-Gangetic plain; using OLS data derived maps as input. In the proposed CA model, urban growth was expressed in terms of causative factors like economy, topography, accessibility and urban infrastructure. The model was calibrated and validated based on OLS data of year 2003 and 2008 respectively using spatial metrics measures and subsequently the urban growth was predicted for the year 2020. The model predicted high urban growth in North Western part of the study area, in south eastern part growth would be concentrated around two cities, Kolkata and Howrah. While in the middle portion of the study area, i.e., Jharkhand, Bihar and Eastern Uttar Pradesh, urban growth has been predicted in form of clusters, mostly around the present big cities. These results will not only provide an input to urban planning but can also be utilized in hydrological and ecological modelling which require an estimate of future built up areas especially at regional level.