Land use/land cover identification in an alpine and arid region (Nubra Valley, Ladakh) using satellite remote sensing

The remote sensing technology has been widely used for mapping the vegetation types in the tropical landscapes. However, in the temperate and alpine arid regions of India very few studies have been conducted using this technique. In the mountainous temperate arid conditions the vegetation is largely confined to marsh meadows, streams courses, river valleys and moist pockets close to snowfields. The ground truth collection in these zones are physically challenging due to tough terrain and restricted mobility. The detailed mapping of vegetation and other land use classes in these areas is therefore, extremely difficult. This paper describes the use of IRS-ID LISS III sensor for deciphering land cover details Nubra Valley, northern portion of Ladakh Autonomous Hill Council, Jammu & Kashmir (India). This analysis essentially emphasizes in bringing out various vegetation classes (speciallyHippophae rhamnoides and other medicinal plant communities) along the narrow river valleys.     

Analysis of population dynamics using satellite remote sensing and US census data

The population dynamics from 1991 to 2006 for the seven-county Twin Cities Metropolitan Area (TCMA), Minnesota, USA, was analysed in this study. Per cent impervious surface areas (%ISA) for 1991, 1999 and 2006 were derived from Landsat Thematic Mapper (TM) images and were modified using two different masking methods. The modified %ISA images of 1991 and 1999 were correlated with 1990 and 2000 census block group data of the ‘two highly developed counties’, ‘five suburban counties’ and ‘all seven counties.’ Populations of both years were then modelled, assessed and compared. Next, the statistical models based on the 1999 %ISA and 2000 census data were applied to the 2006 residential %ISA image to estimate the 2006 population. These 2006 estimates were compared with census county-level population projections for 2006. In comparison to Method A, which uses ‘adjusted %ISA images’ by masking out highway centrelines and areas that have greater than 75% imperviousness, Method B based on ‘pure residential %ISA image’ has higher coefficient of determination (R ²) and much lower, consistent mean absolute relative errors (MARE). For both methods, the strongest R ² and lowest MARE values between modelled population density and true density were found in the five-county model, followed by the seven-county model. The two-county model ranks last in terms of model performance for both years. In general, populations for the two highly developed counties were underestimated whereas the opposite was true for the five suburban counties. Population was most accurately estimated based on data from counties with the same or similar characteristics. By comparing the 1990/1991 and 1999/2000 models, we also found that the rate of population density per unit of impervious surface declined from 1991 to 1999. High accuracy was achieved when applying the 1999/2000 model to predict the 2006 population, suggesting that the relationship between per cent imperviousness and population density were relatively stable between 1999 and 2006.     

Analysis of geographical disparities in temporal trends of health outcomes using space–time joinpoint regression

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.     

GEODETIC LEVELLING IN KENYA

Abstract

Kenya-Topography. Kenya lies astride the Equator between latitudes 4°N and 4°S and extends from Lake Victoria to the Indian Ocean (34°E to 42°E). Between long. 36° and 36½°E it is traversed from north to south by the great Rift Valley, the surface of which is generally 2000-3000ft. lower than the level of the plateau on each side. The plateau culminates in the Aberdare Range (13,000 ft.) east of the Rift, and the Mau Forest (10,000 ft.) and Cherangani Hills (11,000ft.) west of the Rift. Together with the isolated mountain masses of Elgon (14,000 ft.), Kenya (17,000ft.) and Kilimanjaro (19,500ft.), this topography may be expected to cause considerable local distortion in the shape of the geoid. Gravity surveys in 1933-4 indicated a negative anomaly below the floor of the Rift Valley, suggesting that it had been forced down by over-riding pressure from both sides.     

Spectral Reflectance Characteristics of the Soils on Basaltic Terrain of Central Indian Plateau

In-situ spectral reflectance characteristics of soils were studied under field conditions with Multiband Ground Truth Radiometer covering 0.45?C0.52, 0.52?C0.59, 0.62?C0.68, and 0.77?C0.86 ??m spectral bands. Twenty-two surface soil samples were studied in laboratory for their spectral reflectance characteristics using ISCO Model S.R. Spectroradiometer in visible wavelength (450?C725 nm), with 25 nm bandwidth, and in infrared wavelength (750?C1550 nm), with 50 nm bandwidth. The Bidirectional reflectance factor representative of spectral reflectance varied from 3.78 to 11.3???m in band 1, 6.09 to 15.41???m in band 2, 8.05 to 19.41???m in band 3, and 12.18 to 31.2???m in band 4. In-situ spectral reflectance in general increases with the wavelength from visible to infrared bands for all the soils. Black soils have relatively lower reflectance as compared to red soils, which is attributed to the variation in the physicochemical properties of soils. Spectral reflectance, under laboratory conditions, for all the soils increases with wavelength from visible to infrared region except at 950 nm and 1200 nm, where reflectance decreased in all soils, due to weaker water absorption bands and also at 1350 nm, due to strong water absorption at this band. The spectral reflectance of red soils were higher, in-situ as well as under laboratory conditions, as compared to black soils, which is attributed to variation in soil colour, organic matter and clay content of soils. It is observed that the spectral reflectance decrease due to moisture content in soils in all the spectral bands because of darker appearance of soils at moist conditions. Laboratory reflectance measurements serve to define the extent to which intrinsic spectral information is available from soils as a consequence of their composition.     

A comparative study of different dielectric models—computation of representative dielectric profiles of black soils

The dielectric property of the soil is an important parameter for microwave remote sensing. Therefore an attempt is made to study and compare the models for the dielectric constant of moist soils by considering three soil types namely Haldi series (sandy loam), Hathiapathar series (silt loam) and Jambria series (clay) and at frequencies 1.4, 4.0 and 18.0 GHz. The semiempirical models of Wang et al. (1980) and Dobson et al (1985) predict more or les same results in the domain of their applicability. However, at lower frequencies below 1.0 GHz, the imaginary part of dielectric constant shows a decreasing trend with decreasing frequency for Wang et al (1980) model whereas it shows reverse trend for Dobson et al (1985) model. The soil texture and frequency dependence of dielectric constant have been investigated for Indian soils. Some of the representative dielectric profiles of black soils of Pune have been computed using semiempirical model of Dobson et al (1985) which are useful for the development of multifrequency models for the study of soil moisture.     

Microcomputer aided lineament analysis of Son-Mahanadi Valley coal basins,Central India from Landsat data

In the overall tectonic set up of various coal basins of the Peninsular India, the Son-Mahanadi Valley coal basins of Central India have a unique disposition. The coal measures sediments of Peninsular India are developed along well defined E-W and NW-SE trending linear narrow belts. The Son-Mahanadi Valley basins represent the tract where NW-SE trending Mahanadi Valley basins seemingly merge with the major east-west trending Damodar-Koel-Son-Satpura alignment. Landsat data of Son-Mahanadi Valley basins in the four spectral bands (0.5 to 1.1 Micrometers) were used to pick up the lineaments which are possibly of geologic origin. Detailed analysis of lineaments were carried out with the help of three softwares. Diglin (to produce rose diagram) and PLLIN (to plot digitized lineaments to produce a map on any scale) by a Hewlett Packard 45 series microcomputer equipped with graphics screen, plotter, digitiser and floppy disc unit. Detailed analysis revealed a pronounced direction roughly, N 70°E which is present in the northern half of the area while N 40°W direction is present alongwith N 70°E in the southern half. These trends correspond to the NW-SE trending Mahanadi Valley and to the E-W trending Damodar-Son Satpura belt. The above clearly brings out the striking parallelism between the lineament trends in the basement and the overlying coal bearing Gondwana Sediments. This parallelism is suggestive of a genetic relationship between the two.     

Mapping rates associated with polygons

Suppose that geographic data under investigation are rates associated with polygons. For example, disease incidence, mortality, and census undercount data may be displayed as rates. Spatial analysis of data of this sort can be handled very naturally through Bayesian hierarchical statistical modeling, where there is a measurement process at the first level, an explanatory process at the second level, and a prior probability distribution on unknowns at the third level. In our paper, we shall feature epidemiological data, specifically disease-incidence rates, and the “polygons” referred to in the title are typically states or counties.     

Remote sensing of Red Mediterranean soils: a case study in the viticultural southern Rhone Valley using SPOT satellite imagery

The aim of this work was to map Red Mediterranean soils, for which no previous mapping approach exists, using optical multispectral satellite remote sensing data. This case study explores the use of SPOT XS images over the viticultural Southern Rhone Valley, France, to map exposed vineyard soils. Field spectral measurements were used to distinguish Red Mediterranean soil surfaces during Spring 1999. A supervised maximum likelihood classification was applied to sparsely vegetated and unvegetated surfaces of two spring images from 1995 and 1997, drawing on the field training set and available soil data. Similar global spatial segmentation was obtained despite different soil surface states on these dates. Classification performances were higher than 84% in both images. Mean classification accuracies of Red Mediterranean soils at seven reference surfaces were 60% in 1995 and 70% in 1997. This suggests that the direct use of optical remote sensing data at medium resolution can be useful for mapping bare Red Mediterranean soils.     

Fuzzy Based Approach for Moist Deciduous Forest Identification Using MODIS Temporal Data

Fuzzy based soft classification have been used immensely for handling the mixed pixel and hence to extract the single class of interest. The present research attempts to extract the moist deciduous forest from MODIS temporal data using the Possibilistic c-Means (PCM) soft classification approach. Temporal MODIS (7 dates) data were used to identify moist deciduous forest and temporal AWiFS (7 dates) data were used as reference data for testing. The Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI), and Transformed Normalized Difference Vegetation Index (TNDVI) were used to generate the temporal vegetation indices for both the MODIS and the AWiFS datasets. It was observed from the research that the MODIS temporal NDVI data set1, which contain the minimum number of images and avoids the temporal images corresponding to the highest frequency stages of onset of greenness (OG) and end of senescence (ES) activity of moist deciduous forest have been found most suitable data set for identification of moist deciduous forest with the maximum fuzzy overall accuracy of 96.731 %.     

Understanding the spatial distribution of elephant (Loxodonta africana) poaching incidences in the mid-Zambezi Valley,Zimbabwe using Geographic Information Systems and remote sensing

The objective of this study was to understand the factors that explain the spatial distribution of elephant poaching activities in the areas of the mid-Zambezi Valley, Zimbabwe using geographic information system (GIS) and remotely sensed data integrated with spatial logistic regression. The results showed that significant (α = 0.05) elephant poaching hot spots are located closer to wildlife protected areas. Results further demonstrated that resource availability (water and forage) are the main factors explaining elephant poaching activities in the mid-Zambezi Valley. For example, the majority of poaching activities were found to occur in areas with high vegetation fractional cover (high forage) and close to waterholes. The results also showed that poaching incidences were more prevalent during the dry season. The findings of this study highlight the significance of integrating GIS, remotely sensed data and spatial logistic regression tools for understanding and monitoring elephant poaching activities. This information is critical if poaching activities are to be minimized and it is also important for planning, monitoring and mitigation of poaching activities in similar protected areas across the sub-Saharan Africa.     

Determination of GPS orbits using double difference carrier phase observations from regional networks

Summary Carrier phase measurements are potentially the most precise observations available from theGPS satellite system, the formal precision being of the order of one centimeter per observation. If the so called double differences are used as the basic observable, the analysis is relatively simple, since satellite- and receiver-clocks may be represented by basic models. We investigate the feasibility of double difference phase observations for orbit determination using the material of the 1985 High Precision Baseline Test, where the coordinates of the so called fiducial points (Haystack, Ft. Davis Richmond and Mojave) are held fixed.TI-4100 andAFGL-receiver observations were used in the same orbit determination process. Although no surface weather data had been available to us, the orbit quality seems to be of the order of0.1 ppm. When we use these orbits to estimate the coordinates of the five “non-fiducial points” Owens Valley, Hat Creek Mammoth Lake, Austin and Dahlgren we get a repeatability of the order of5 cm for latitude and longitude and10 cm for height, if the observations of the first four days of the campaign are compared to those of the second four days. If we use our orbits estimated withTI andAFGL observations to process the Mojave—Owens Valley baseline (length245 km) measured by the twoSERIES-X receivers, we obtain day to day repeatabilities of1.6 cm (0.06 ppm) in length,2 cm (0.08 ppm) in latitude,4 cm (0.16 ppm) in longitude and7 cm (0.29 ppm) in height. Since there are indications that regional networks will be realized in the near future, the results presented here should encourage the realization of regional high precision orbit determination services.     

疟疾发病的空间格局和时空演化分析

疟疾是一种具有复杂地理空间分布特征的地方性疾病,研究疟疾的空间格局,掌握疟疾发病的时空演化规律,为疟疾的防治提供科学决策具有十分重要的科学意义。本文以湖南省105个市、县级行政区1983～1992年疟疾发病的历史资料为例,运用空间自相关分析方法对湖南省疟疾发病的空间格局和时空演化规律进行分析、探测和识别。研究结果表明：湖南省各市县疟疾发病地域差异明显,整体呈现＂南高北低＂的空间格局,且主要集中在湘南和湘中经济相对落后的地区。在这期间,湖南省的疟疾发病经历了一个从＂南低北高＂到＂南高北低＂的时空演化过程。     

Satellite remote sensing of forest type and landcover in the subalpine forest region,Kananaskis Valley,Alberta

Landsat Thematic Mapper (TM) imagery and a digital elevation model (DEM) of the Kananaskis Valley in southwestern Alberta have been used to separate three forest types and eight landcover classes with mapping accuracies up to 76% overall. Image transformations based on a principal components analysis (PCA) were used to distinguish vegetation type and separate surface features in visual interpretations, and to reduce the 10 channel data set (TM 1–7, elevation, slope and incidence) to a more manageable 7 channel data set (PCA 1–4, elevation, slope and incidence). The DEM was shown to be critical in providing explanation of surface cover variability even though the original model was produced from medium scale aerial photography on a relatively coarse 100 metre grid. Discrimination increased up to 50% for pure stands of Lodgepole Pine (Pinus contorta Dougl.) and Englemann Spruce (Picea englemanii Parry) based on analysis of 100 pixels in test areas. Overall increases in map accuracy were between 2 and 11%. Success at this level of classification is required prior to detailed ecological study and modelling of mountain vegetation productivity at the community level using current satellite and aerial remote sensing technology.     

REMOTE SENSING METHODS IN THE STUDY OF SOILS IN BELARUS'

Applications of remote sensing in the study of soils of Belarus' are investigated. The focus is upon ascertaining relationships between phototone of cultivated soils and various soil characteristics (humus content, texture, etc.); upon ensuring the best times for imaging; on the revision of existing soil maps from remote sensing imagery; and on determinations of humus content from spectral reflectance values. Translated by Edward Torrey, Alexandria, VA 22308 from: G. V. Dobrovol'skiy and V. L. Andronikov, eds., Aerokosmicheskiye metody v pochvovedenii i ikh ispol'zovaniye v sel'skom khozyaystve: sbornik nauchnykh trudov [Remote Sensing Methods in Soil Science and Their Utilization in Agriculture: A Collection of Scientific Works]. Moscow: Nauka, 1990, pp. 109–116.     

Visual interpretation of computer transformed Landsat imagery for salt affected areas of part of Haryana

In the present study an attempt has been made to interpret visually the computer transformed, FCC, PC₁-PC₂ and Δ method products, landsat imagery of different seasons and with different crop cover, of salt affected areas of part of Haryana. FCC and PC₁-PC₂ of moist hot climate (10 October, 1972) was found better for physiographic interpretation than other seasons and bands, Δ method (October. 1972) and FCC of hot-dry season were good only for interpreting salt affected areas whereas other landform features were suppressed. Not much additional information was gained by way of PC₁-PC₂ and Δ method transformation over FCC (bands 4, 5, 7). It was possible to delineate different classes of salt effected soils based on the areal extent of the hazard.     

环境小卫星S波段SAR监测土壤水分变化应用分析

通过IEM正演模型的模拟数据，发展了一种用S波段(3.0GHz)、VV极化数据反演土壤含水量相对变化的算法；选择典型的土壤含水量、地表粗糙度及入射角变化范围，模拟出两幅SAR图像，并把该算法应用到模拟图像中，对算法进行验证和改进； 将结果与输入值对比，结果表明，该算法能较好地提取土壤含水量时间和空间变化信息。     

A History and Analysis of Mapping Urban Expansion in the Kathmandu Valley,Nepal

Abstract

There have been numerous efforts over many years to map or delineate urban locations and features in the Kathmandu Valley of Nepal. This study acquired 27 land useland cover maps for the Valley or the urban portions of the Valley. Those maps vary greatly in their mapping parameters. The objectives of this study were to first conduct a cartographic comparison of the differences in the creation and content of the maps and then do an analysis of the urban changes in the Valley based upon the maps. The maps for the Valley have differed in their source materials, the amount of field work involved, scale and minimum mapping units, classifications used, definitions of classes and coordinate systems. Source materials have included various scales and formats of aerial photography and different satellite systems. The most difficult issue in comparing the maps is the varied classification systems and definitions. The same feature will be classified differently from map to map. This is particularly an issue for institutional features such as temples, palaces, educational facilities, open public space and governmental sites. Definitions of residential areas are also not consistent. Even with the differences in mapping parameters, considerable useful information can be obtained by comparing these maps. These include a simply documentation of the urban extent and the generally resulting loss in agricultural lands. There was an increase in urban extent from 22 to 83km² between 1955 and 2000. Urban expansion has also changed from occurring on the upland river terraces or tars to the floodplains. Finally, while not directly documented in these maps, the tremendous pace of urban growth has resulted in multiple infrastructure and environmental challenges.     

利用AVHRR植被指数数据集分析中国东部季风区的物候季节特征

利用ＮＯＡＡ／ＮＡＳＡＰａｔｈｆｉｎｄｅｒＡＶＨＲＲ陆地数据集,建立了中国东部季风区（１０８°－１２３°Ｅ,２１°－４５°Ｎ）的１９８６年归一化植被指数（ＮＤＶＩ）距平图像序列。对此数据集进行主成分分析（ＰＣＡ）,前２个主成分的时间序列和空间场展示了中国东部季风区植被物候季节性特征和地域差异。南岭一五夷山以南的华南地区,植被生长季的物候季节性变化不明显。在南岭－五夷山以北地区,植被生长季的物候季节性特征明显,可以比较清晰地确定生长季的变化过程。以淮河流域为界,植被生长季的物候季节性特征又存在明显差异。华北平原表现出强烈的双峰植被物候过程。淮河以南地区,虽然也存在这种双峰物候过程,但比较华北平原的植被,还具有持续性的植被生长特征。淮河流域构成一条区分南北物候季节特征差异的过渡带。     

Biomass allometric equation and expansion factor for a mountain moist evergreen forest in Mozambique

Background

Worldwide, forests are an important carbon sink and thus are key to mitigate the effects of climate change. Mountain moist evergreen forests in Mozambique are threatened by agricultural expansion, uncontrolled logging, and firewood collection, thus compromising their role in carbon sequestration. There is lack of local tools for above-ground biomass (AGB) estimation of mountain moist evergreen forest, hence carbon emissions from deforestation and forest degradation are not adequately known. This study aimed to develop biomass allometric equations (BAE) and biomass expansion factor (BEF) for the estimation of total above-ground carbon stock in mountain moist evergreen forest.

Methods

The destructive method was used, whereby 39 trees were felled and measured for diameter at breast height (DBH), total height and the commercial height. We determined the wood basic density, the total dry weight and merchantable timber volume by Smalian’s formula. Six biomass allometric models were fitted using non-linear least square regression. The BEF was determined based on the relationship between bole stem dry weight and total dry weight of the tree. To estimate the mean AGB of the forest, a forest inventory was conducted using 27 temporary square plots. The applicability of Marzoli’s volume equation was compared with Smalian’s volume equation in order to check whether Marzoli’s volume from national forest inventory can be used to predict AGB using BEF.

Results

The best model was the power model with only DBH as predictor variable, which provided an estimated mean AGB of 291?±?141 Mg ha^?1 (mean?±?95% confidence level). The mean wood basic density of sampled trees was 0.715?±?0.182 g cm^?3. The average BEF was of 2.05?±?0.15 and the estimated mean AGB of 387?±?126 Mg ha^?1. The BAE from miombo woodland within the vicinity of the study area underestimates the AGB for all sampled trees. Chave et al.’s pantropical equation of moist forest did not fit to the Moribane Forest Reserve, while Brown’s equation of moist forest had a good fit to the Moribane Forest Reserve, having generated 1.2% of bias, very close to that generated by the selected model of this study. BEF showed to be reliable when combined with stand mean volume from Marzoli’s National Forestry Inventory equation.

Conclusion

The BAE and the BEF function developed in this study can be used to estimate the AGB of the mountain moist evergreen forests at Moribane Forest Reserve in Mozambique. However, the use of the biomass allometric model should be preferable when DBH information is available.