Rapeseed-mustard acreage estimation using IRS LISS-II data

The present paper describes the remote sensing-based acreage estimation of rapeseed-mustard crop in Mehsana and Banaskantha districts of Gujarat, using four-band data and Maximum Likelihood classification. IRS LISS-II data of November 25, 1989 has been used to estimate the acreage of rapeseed-mustard. It is found that the data of November 25 is useful in discriminating rapeseedmustard from other rabi crops. Talukawise acreage estimation has also been done for three talukas of Mehsana and two talukas of Banaskantha district.     

Hydrogeomorphological mapping in ground water exploration using remotely sensed data — a case study in keonjhar district, orissa

Identification of fractures/lineaments and hydrogeomorphic units is prerequisite for undertaking ground water exploration and development in any terrain. Use of satellite remote sensing techniques coupled with aerial photo-interpretation greatly aid in planning ground water exploration, and pin pointing well sites In this study, airborne and space borne data was used for qualitative evaluation of ground water resources and a critical appraisal of such study in combination with hydrogeological and hydrogeophysical techniques for ground water exploration and development in Keonjhar district of Orissa. The study area has been divided into various geomorphic units based on visual interpretation of Landsat (TM) false colour composite on. 1:2,50,000 scale and the ground water potential of each of the units is qualitatively assessed. Digital image processing techniques such as principal component analysis and brightness index were used for generating classified outputs. The features like valley fills, pediments ete appeared clearly on the classified image. Directional filtering brought out minor fractures/lineaments crisply. The study has revealed the significance of different hydrogeomorptuc units and lineaments in Controlling ground water potential of the area. The findings were corroborated by resalts of drilling and resistivity soundings.     

LIDAR Data and Hydrological Applications at the Basin Scale

Digital elevation models (DEMs) resulting from LIDAR (light detection and ranging) surveys are now more available in the hydrology and hydraulics (H&H) community, not only for hydraulic applications in small areas close to river networks but also for hydrologic applications in whole basins. Several questions arise when trying to combine LIDAR data and hydrologic models. Despite the long processing time, LIDAR-derived DEMs can provide more accurate information that is useful for basin hydrogeomorphic characterization, in comparison with DEMs at resolutions commonly used in hydrologic applications (cell size 20-30 m). Of particular focus here are river network properties and the instantaneous unit hydrograph (IUH) framework. Two case studies, one in Italy and the other in the USA, are presented in which three DEMs are analyzed with differing resolutions as follows: "standard," i.e., a resolution commonly used in hydrologic applications (cell size 20-30 m), LIDAR (cell size 1-2.5 m), and LIDAR-resampled at the same resolution as the "standard" DEM. Results suggest that the higher spatial resolution LIDAR-derived data are preferable and can introduce more detailed information about basin hydrogeomorphic behavior.     

Influence of rock types and structures in the development of drainage network in hard rock area

Remote sensing techniques has proved to be an extremely useful tool in morphometric analysis and groundwater studies. Remote sensing techniques with an emphasis on lineament identifications can play a great role in groundwater prospecting in semi-arid hard rock areas of Purulia district. In the present study, morphometric analysis using remote sensing technique has been carried out in parts of Baghmundi block, Purulia district, West Bengal. The parameters worked out include Bifurcation ratio (R_b), Stream length (L_u), Form factor (R_c), Circulatory ratio (R_c), and Drainage density (D). The morphometric analysis suggests that fractured, resistant, permeable rocks cover the area, the drainage network not so affected by tectonic disturbances. Using satellite imageries of two dates of IRS, different hydrogeomorphological units have been delineated. Among different hydrogeomorphic units (i) very shallow weathered pediment and (ii) Structural hills/ residual hills/inselbergs have very poor ground water prospects, while moderately weathered pediplains and valley fills are good prospective zones for groundwater exploration.     

Analysis of Climate and Vegetation Characteristics along the Savanna-Desert Ecotone in Mali Using MODIS Data

MODIS data were used in conjunction with 600 ground survey points to create a 500 m resolution land cover product of Mali. It improves upon previously published land cover products for this region in resolution and accuracy. Of particular importance is the ability to detect small-scale, but important, wetland features such as rice cultivation areas. A combination of classical ground survey of vegetation type and structure, meteorological data, and remote sensing was used to quantify the relationship between vegetation and climate along the sensitive Sahel savanna—desert transition. The study demonstrates the effectiveness of using MODIS data for regional-scale studies.     

LANDSAT (MSS) imagery interpretation: A new perspective tool aiding regional hydromorphic mapping for groundwater exploration

With the advent of Remote Sensing via Satellites, specially the LANDSAT providing a synoptic overview of our Earth, a powerful new tool aiding in regional terrain analysis for natural resources surveys is now available to earth scientistis. Many significant earth features identifiable on LANDSAT images help to update regional surveys. Sequential coverage is an added advantage. Based on terrain analysis using LANDSAT imagery, and utilising the principles of visual interpretation to develop satellite photo-analytical keys highlighting landforms, drainage features and the like it is possible to delineate hydromorphic units for groundwater studies on a regional scale. The paper highlights the utility of LANDSAT imagery interpretation in small scale hydromorphic mapping for groundwater studies by citing examples from North and Central India. The advantage of conjunctive use of satellite, aircraft ann ground data in enhancing survey results is mentioned. The known and expected hydrologic conditions in the different hydromorphic units mapped have been given. The study approach is relatively new in India, and can be very useful in planning regional groundwater exploration programmes. The method is speedy and economical. Possibilities of similar studies in a host of other areas of survey such as flood studies, erosion surveys add a new dimension to the study of our Earth.     

Evaluation of NDWI and MNDWI for assessment of waterlogging by integrating digital elevation model and groundwater level

Accurate information on the extent of waterlogging is required for flood prediction, monitoring, relief and preventive measures. The rule-based classification algorithms were used for differentiating waterlogged areas from other ground features using Resourcesat-2 AWiFS satellite imagery (Indian Remote Sensing Satellite with spatial resolution of 56 m). Two spectral indices normalized difference water index (NDWI) and modified normalized difference water index (MNDWI) were used for extracting waterlogged areas in Sri Muktsar Sahib district of Punjab, India. These indices extracted the waterlogged areas (cropped areas inundated with water) but the water features were less enhanced in the NDWI-derived image (when compared with MNDWI-derived image) due to negative values of NDWI and, mixing of water with built up features. The water features were more enhanced with MNDWI and the values of MNDWI were positive for water features mixed with vegetation. The overall accuracy of waterlogged areas extracted from the MNDWI image was 96.9% with the Kappa coefficient of 0.89. The digital elevation model (DEM) was extracted from ASTER-GDEM. The relationships among depth to the water table recorded before the incessant rain in the region, DEM and classified MNDWI images explained the differences in the extent of waterlogging in various directions of the study area. These results suggest that MNDWI can be used to better delineate water features mixed with vegetation compared to NDWI.     

A GIS for hydrological modelling in the semi-arid, HAPEX-Sahel experiment area of Niger, Africa

During the HAPEX-Sahel experiment (1991–94), water redistribution processes were studied at the meso-scale (10 000 km²) near Niamey, Niger. A project now under way at ORSTOM aims at modelling the regional water balance through a spatial approach combining GIS data organization and distributed hydrological modelling. The main objective is to extend the surface water balance, by now available only on a few, small (around 1 km²) unconnected endoreic catchments, to a more significant part of the HAPEX-Sahel square degree, a 1500 km² region called SSZ that includes most of the environmental and hydrology measurement sites. GIS architecture and model design consistently consider data and processes at the local, catchment scale, and at the regional scale. The GIS includes spatial and temporal hydrological data (rainfall, surface runoff, ground water), thematic maps (topography, soil, geomorphology, vegetation) and multi-temporal remote sensing data (SPOT, aerial pictures). The GIS supports the simulation of the composite effect at the regional scale of highly variable and discontinuous component hydrologic processes operating at the catchment scale, in order to simulate inter-annual aquifer recharge and response to climatic scenarios at the regional scale.     

用基于知识的决策树方法分层提取矿区土地类型——以湖北大冶为例

以湖北大冶为研究区,采用多时相陆地卫星遥感图像,通过不同波段组合,以及ironoxide指数和归一化差异植被指数(NDVI)等,详细分析了各地表地物光谱特征和空间特征,建立了研究区分类知识库表,采用决策二叉树法进行分类,得到了高精度分类结果图。基于不同时相分类结果的变化检测,通过对研究区水体污染、矿区复垦、耕地变化等分析,认为从1986～2002年,研究区水质虽有一定改善,但矿区植被退化严重,耕地大量减少,停产矿区复垦仅为20%,为合理保护矿区生态环境和科学管理采矿企业提供了有用资料。     

Reclamation areas and their development studied by vegetation indices

Abstract

Large areas in the Czech Republic were used for open casts of brown coal mining. Many of them have been already closed. Reclamation of them and of their dumps is the next step intheir development. It is possible to divide used reclamations into the forest, hydrologic, agricultural and other ones – roads, etc. Their age varies from 45 years to as yet unfinished. Reclaimed areas are documented in reclamation projects. Information about age and land use determined groups of these areas to be evaluated by vegetation indices. 100 areas with forest type were evaluated. Eight vegetation indices (NDVI, DVI, RVI, PVI, SAVI, MSAVI, TSAVI and EVI) were calculated and their average value in each area in 1988, 1992 and 1998 Thematic Mapper data were compared. Changes over years showed close relation to precipitations of previous periods. This relation was confirmed by evaluation of forest areas situated near reclamation areas. Positive/negative changes of vegetation indices were different for different groups and different vegetation indices. An overview of results of vegetation indices is presented for individual areas whose land use comprised at least partly forest stand. Results in a 4-year period (1988–1992) were in many areas by many indices negative, changes in 10 years were in most areas by most vegetation indices positive. Changes, minimum values and maximum values in groups were compared. Evaluation of vegetation indices brought again various results. One vegetation index is not sufficient to prove improvement/deterioration of vegetation changes. Precipitation state before measurement should be controlled. Temporary shortage of precipitation can cause vegetation cover deterioration, which is also only temporary. The best development derived from vegetation indices evaluation was found at forest reclamation with mixed tree stand that was 10–20 years old. The method was derived as a tool for post-finishing control of vegetation development of reclamations performed in several year periods.     

Using Low‐Resolution Satellite Data to Quantify Terrestrial Carbon in Tropical Areas

Abstract

The ability to map and monitor terrestrial carbon is important in tropical regions where land conversion is intense and tropical moist forests store much of Earth's terrestrial carbon. The release of terrestrial carbon in the form of carbon dioxide could alter local, regional, and global weather, and enhance the greenhouse effect. This study analyzed the ability of coarse‐resolution Advanced Very High Resolution Radiometer (AVHRR) remote sensor data to quantify carbon stored in the Guaporé / Itenez River Basin in Bolivia and Brazil. This area was selected because of the amount of land conversion that has occurred there relative to other areas of the Amazon Basin. A supervised vegetation classification map was created with training sites acquired through fieldwork done in the area in summer 1998. Image pixels were classified as tropical moist forest, degraded tropical moist forest, cerrado, grasslands, degraded savanna, or bare ground. Estimated above and below‐ground carbon values of the different land cover types were applied to each class to calculate total carbon values. It was concluded that data such as AVHRR may be used to calculate the amount of carbon in terrestrial ecosystems in regional scale areas.     

Assessing ground cover at patch and hillslope scale in semi-arid woody vegetation and pasture using fused Quickbird data

The amount and distribution of vegetation and ground cover are important factors that influence resource transfer (e.g. runoff, sediment) in patterned semi-arid landscapes. Identifying and describing these features in detail is an essential part of measuring and understanding ecohydrological processes at hillslope scales that can then be applied at broader scales. The aim of this study was to develop a comprehensive methodology to map ground cover using high resolution Quickbird imagery in woody and non-woody (pasture) vegetation. The specific goals were to: (1) investigate the use of several techniques of image fusion, namely principal components analysis (PCA), Brovey transform, modified intensity-hue-saturation (MIHS) and wavelet transform to increase the spatial detail of multispectral Quickbird data; (2) evaluate the performance of the red and near-infra-red bands (NIR), the difference vegetation index (DVI), and the normalised difference vegetation index (NDVI) in estimating ground cover, and (3) map and assess spatial and temporal changes in ground cover at hillslope scale using the most appropriate method or combination of methods. Estimates of ground cover from the imagery were compared with a subset of observed ground cover estimates to determine map accuracy. The MIHS algorithm produced images that best preserved spectral and spatial integrity, while the red band fused with the panchromatic band produced the most accurate ground cover maps. The patch size of the ground cover beneath canopies was similar to canopy size, and percent ground cover (mainly litter) increased with canopy size. Ground cover was mapped with relative accuracies of 84% in the woody vegetation and 86% in the pasture. From 2008 to 2009, ground cover increased from 55% to 65% in the woody vegetation and from 40% to 45% in the pasture. These ground cover maps can be used to explore the spatial ecohydrological interactions between areas of different ground cover at hillslope scale with application to management at broader scales.     

Stratification approach for forest cover type and landuse mapping using IRS-1A LISS-II data — A case study

Indian Remote Sensing Satellite-1A (IRS-1A) LISS-II data of 24th Nov., 1988 was analysed digitally to differentiate three density classes viz. dense/closed forest, open forest and degraded forest within each vegetation type in the district, Jalpaiguri, West Bengal. Stratification approach was used to classify separately forest cover into pure sal forests, mixed forests, riverine forests along with man-made sal/teak plantations. In this approach the forested and non-forested areas were classified separately through supervised classification techniques using maximum likelihood algorithm using VAX 11/780 based VIPS-32 Image Processing software. Later the two classified outputs were composited to provide entire area of the district. The forest cover of the district was 1420.89 sq. km, (22.82 percent). Other broad landuse/landcover dominant in the district include agricultural areas.(45.20 percent) and tea gardens (10.49 percent). The accuracy of the classified output was estimated to be 90 percent for forested areas and 85 percent in case of other landuse/landcover classes.     

机载LiDAR技术应用于茂密植被山区地质灾害调查

我国茂密植被山区地质灾害具有高位、高隐蔽性的特点,传统地质灾害排查手段在有效解决隐患的早期识别方面存在一定困难.机载雷达技术不仅可获取地面反射的三维激光点云,同时能够提供高分辨率、高精度的地形地貌二维影像.机载雷达的多次回波技术可"穿透"地面植被,通过滤波算法能够有效去除地表植被的影响,获取真地面高程数据信息,从而可获...     

Estimation of Wheat/Rice Residue Burning Areas in Major Districts of Haryana,India, Using Remote Sensing Data

Haryana has emerged as an important state for Rice & Wheat production in India contributing significantly in the central pool. Mechanized combine harvesting technologies, which have become common in Rice Wheat System (RWS) in India, leave behind large quantities of straw in the field for open burning of residue. Besides causing pollution, the burning kills the useful micro flora of the soil causing soil degradation. There is no field survey (Girdawari) data available with the Government for the areas where stubble burning is taking place. The present paper describes the methodology and results of wheat and rice residue burning areas for three districts of Haryana namely Kaithal, Kurukshetra and Karnal for the year 2010 using complete enumeration approach of multi-date IRS-P6 AWiFS and LISS-III data. In season ground truth was collected using hand held GPS and used to identify area of burnt wheat/rice residues, associated crops and land features. After geo-referencing the satellite images, district images were masked-out and multi-date image data stacks were created. Normalized Difference Vegetation Index (NDVI) of each date was generated and used at the time of classification along with other spectral bands. The non-agricultural classes in the image included: forest, wasteland, water bodies, urban/settlement and permanent vegetation etc. The vector of these non-agriculture classes were extracted from the land use, imported and mask was generated. During the classification non-agriculture area was excluded by using mask of these classes. From this the agricultural area could be separated out. The area was estimated by computing pixels under the classified image mask. In season multi-date AWiFS data along with available single-date LISS-III data between third week of April to last week of May are found to be useful for estimation of wheat residue burning areas estimation. The data between second week of October to last week of November is useful for estimation of rice residue burning areas estimation at district level.     

Ground filtering and vegetation mapping using multi-return terrestrial laser scanning

Discriminating laser scanner data points belonging to ground from points above-ground (vegetation or buildings) is a key issue in research. Methods for filtering points into ground and non-ground classes have been widely studied mostly on datasets derived from airborne laser scanners, less so for terrestrial laser scanners. Recent developments in terrestrial laser sensors (longer ranges, faster acquisition and multiple return echoes) has aroused greater interest for surface modelling applications. The downside of TLS is that a typical dataset has high variability in point density, with evident side-effects on processing methods and CPU-time. In this work we use a scan dataset from a sensor which returns multiple target echoes, in this case providing more than 70 million points on our study site. The area presents low, medium and high vegetation, undergrowth with varying density, as well as bare ground with varying morphology (i.e. very steep slopes as well as flat areas). We test an integrated work-flow for defining a terrain and surface model (DTM and DSM) and successively for extracting information on vegetation density and height distribution on such a complex environment. Attention was given to efficiency and speed of processing. The method consists on a first step which subsets the original points to define ground candidates by taking into account the ordinal return number and the amplitude. A custom progressive morphological filter (opening operation) is applied next, on ground candidate points using a multidimensional grid to account for the fallout in point density as a function of distance from scanner. Vegetation density mapping over the area is then estimated using a weighted ratio of point counts in the tri-dimensional space over each cell. The overall result is a pipeline for processing TLS points clouds with minimal user interaction, producing a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a vegetation density map and a derived Canopy Height Model (CHM). These products are of high importance for many applications ranging from forestry to hydrology and geomorphology.     

Above Ground Forest Phytomass Assessment in Southern Gujarat

Spectral modeling of above ground biomass (AGB) with field data collected in 48 field sites representing moist deciduous forest in Surat district is reported. Models were generated using LISS-III and MODIS data. The plot-wise field data was aggregated to MODIS pixel (250 m) using area weightages of forest/vegetation. The study reports that above ground phytomass varied from 6.13 t/ha to 389.166 t/ha while AGB phytomass estimated using area-weights for sites of 250×250 m, ranged from 5.534 t/ha to 134.082 t/ha. The contribution of bamboo in AGB has been found very high. The analysis indicated that the highest correlation between AGB phytomass and red band (R) of MODIS satellite data of October was (R²=0.7823) and R²=0.6998 with both NDVI of October data as well as NDVI_max. High correlation (R²=0.402) with IR band of February month was also found. The phytomass range obtained by using MODIS data varies from 0.147 t/ha to 182.16 t/ha. The mean biomass is 40.50 t/ha. Total biomass is 31.44 Mt. The mean Carbon density is 19.44 tC/ha in forest areas. The study is validation of region-wise spectral modeling approach that will be adopted for mapping vegetation carbon pool of the India under National Carbon Project of ISRO-Geosphere Biosphere Programme.     

Landsat时序数据支持下的藏东南植被时空变化监测

本文利用GEE平台和1990—2019年巴宜区Landsat遥感影像,采用像元二分模型、相关性分析等方法分析了巴宜区植被覆盖度的时空变化特征与驱动力。研究结果表明:①1990—2019年巴宜区植被覆盖度总体呈稳中有增的趋势,其中,河谷区域增加明显,而高海拔区域相对稳定;②1990—2019年巴宜区气温呈显著升高,降水略有下降,总体呈"暖干化",气温较降水量对植被覆盖变化更明显,但气候变化对植被覆盖变化影响总体不明显;③1990—2019年巴宜区植被覆盖变化与人类活动有很好的相关性,其中,低、中低、中、中高植被覆盖区域,呈显著的负相关,而高植被覆盖区域呈正相关。本文基于遥感大数据和地理云计算的植被覆盖监测动态监测和定量分析方法,能对高山峡谷区生态评估和演替分析提供一定的技术支撑和科学数据。     

Applying Landsat Imagery for Groundwater Development in Egypt

Landsat Thematic Mapper data over the Nile Valley and Delta were analyzed to assist in various phases of groundwater development in Egypt. Land surface features were identified and located in combination with other data stored in a Geographic Information System for input to the final hydrogeological map of this area. Simple vegetation indices were used to delineate the extent of vegetation cover and related to groundwater recharge. Supervised classification techniques were used to separate features such as sabkhas which are areas of high evaporative losses. Detection of upward groundwater seepage at the surface in the winter season was used to calibrate regional groundwater flow models. Possible future applications include estimation of evapotranspiration, determination of irrigation water needs, and improvement of the existing network of groundwater observation wells for water quality purposes.     

一种改进的PolInSAR PCT方法反演植被垂直结构

针对传统PCT方法中“相干相位-幅度联合反演算法”的缺点,采用RVOG模型,利用改进的非线性迭代算法反演植被高、地表相位.改进的非线性迭代算法不仅充分利用不同极化方式对应的复相干系数,同时兼顾复相干系数的先验统计误差,提高参数解算的可靠性,进而提高PCT结果的反演精度.最后,采用两景德国E-SAR数据进行实验,实验结果表明：文中提出的方法能较好地反映植被的垂直结构信息;植被冠层对应的平均相对反射率函数近似服从高斯分布;反演的相对反射率值与植被的种类、密度存在一定关联.