Earth observations during space shuttle mission STS‐28 8–13 August 1989

Abstract

The paper presents a geospatial modeling approach for the assessment of plant richness in Barsey Rhododendron Sanctuary in Sikkim, a Himalayan State of India located in the “Indo‐Burma” biodiversity hotspot. Remotely sensed data from Indian Remote Sensing Satellite IRS‐1C Linear Imaging Self‐Scanner (LISS‐III) and field‐based methods were synergistically used to model plant richness on 1:50,000 scale. It was found that the sanctuary is dominated by East Himalayan Moist Temperate Forest (55.50%), followed by Rhododendron Forest (23.77%), Degraded Forest (6.66%) and Hemlock Forest (0.78%). The vegetation map prepared through digital interpretation of satellite imagery was subjected to landscape analysis and assessment of biotic disturbance in terms of disturbance index. The disturbance index together with species richness, ecosystem uniqueness, total importance value and terrain complexity was modeled to assess the plant richness in this unique sanctuary. Out of the 120 km² of the total geographical area of the sanctuary, 28.45 per cent was found to possess very high plant richness followed by high (50.84%), medium (6.96%) and low richness (13.75%). It was noted that plant richness assessment at ecosystem level presents a more realistic picture than at landscape level. The study demonstrated that remote sensing coupled with landscape analysis, ground inventory data and geospatial modeling holds good potential for rapid and operational assessment of plant richness.     

Geospatial modelling of biological richness in Sunderbans

The present study attempts to assess the biological richness in Sunderban Biosphere Reserve (SBR) using a three-pronged approach i.e. satellite image (IRS 1D LISS-III) for vegetation/land use stratification, landscape analysis for disturbance regimes assessment and the disturbance regimes together with the ecosystem uniqueness, species richness and importance value for biological richness modelling. The study showed that four mangrove categories, viz., Avicennia, Phoenix, mixed mangroves and mangrove scrub, cover 23.21 per cent of the total geographical area of SBR. The largest area is occupied by mixed mangroves (18.31%). The overall accuracy of the vegetation/land use map worked out to be 91.67 per cent. The disturbance analysis revealed that the vegetation types were not much disturbed. Shannon-Weaver’s index of diversity was highest in case of mixed mangrove. The results revealed that 75 per cent forest area has high biological richness.     

Forest Fire Burnt Area Assessment in the Biodiversity Rich Regions Using Geospatial Technology: Uttarakhand Forest Fire Event 2016

The hills of Uttarakhand witness forest fire every year during the summer season and the number of these fire events is reported to have increased due to increased anthropogenic disturbances as well as changes in climate. These fires cause significant damage to the natural resources which can be mapped and monitored using satellite images by virtue of its synoptic coverage of the landscape and near real time monitoring. This study presents burnt area assessment caused by the fire episode of April 2016 to the forest vegetation. Digital classification of satellite images was done to extract the burnt area which was found to be 3774.14 km², representing 15.28% of the total forest area of the state. It also gives an account of cumulative progression of forest fire in Uttarakhand using satellite images of three dates viz. 23rd, 27th May and 2nd June, 2016. Results were analyzed at district, administrative and forest division level using overlay analysis. Separate area statistics were given for different categories of biological richness, forest types and protected areas affected by forest fire. The burnt area assessment can be used in mitigation planning to prevent drastic ecological impacts of the forest fire on the landscape.     

Geo-spatial approach for phytodiversity characterization in Panna National Park (part), M.P. (India)

Panna National Park is situated in the north-central part of Madhya Pradesh, India. Landscape parameters like fragmentation, porosity, patchiness and jaxtaposition have been analysed for disturbance gradient characterization. Disturbance on biodiversity due to human activities has been studied both qualitatively and quantitatively. The species richness is highest in northern mixed dry deciduous forest followed by dry deciduous open scrub and southern tropical dry deciduous teak forest. Species richness of the open thorny dry deciduous forest with grasses is found to be the lowest. Disturbance analysis indicates that 22.02% of the southern slightly moist teak forests are highly disturbed whereas Anogeissus forest and Riverine forest have 17.04% and 12.41% of the area under high disturbance, respectively. A total of 88 field sample plots were laid to enumerate trees, shrubs, herbs, climbers, etc. Biological richness parameters such as Shannon-Wiener biodiversity index, biodiversity value, ecosystem uniqueness were derived from field data. High biological richness is found in northern mixed dry deciduous forest and mixed dry deciduous forest with bamboo. More than 99% of such areas are falling under medium to high biological richness. Nearly 55% of the gentle and flat to gentle, slope categories were found to have low biological richness. Phytosociological analysis of sampled field data indicated that the number of trees per unit area is the lowest in the Savannah. In inaccessible areas, the species richness and number of trees per unit area is very high. Main forces causing disturbance are search for diamonds, dams on river Ken, settlements in and around the park, grazing and resource utilization by villagers for fodder, animal grazing, fuel-wood, timber, etc.     

An automated and optimized approach for online spatial biodiversity model: a case study of OGC web processing service

An online spatial biodiversity model (SBM) for optimized and automated spatial modelling and analysis of geospatial data is proposed, which is based on web processing service (WPS) and web service orchestration (WSO) in parallel computing environment. The developed model integrates distributed geospatial data in geoscientific processing workflow to compute the algorithms of spatial landscape indices over the web using free and open source software. A case study for Uttarakhand state of India demonstrates the model outputs such as spatial biodiversity disturbance index (SBDI) and spatial biological richness index (SBRI). In order to optimize and automate, an interactive web interface is developed using participatory GIS approaches for implementing fuzzy AHP. In addition, sensitivity analysis and geosimulation experiments are also performed under distributed GIS environment. Results suggest that parallel algorithms in SBM execute faster than sequential algorithms and validation of SBRI with biological diversity shows significant correlation by indicating high R² values.     

Landscape characterisation of the forests of Himalayan foothills

Deforestation and degradation are important aspects of landscape dynamics and have global significance. Quantification of landscape pattern using landscape metrics help in characterisation of landscapes and thus overall health of the forest cover. Himalayan foothills are one of the most important and fragile landscapes. Developmental activities and depdendence on the forest resources have altered the spatial pattern of these natural landscapes to a great extent. These changes in the landscape were analysed using satellite data from 1990, 2001 and 2006. The vegetation type maps of Dehradun forest division were prepared by supervised classification technique in order to study the landscape dynamics. Patch density, edge density, shape index, cohesion index, interspersion and juxtaposition index, normalised entropy, and relative richness are some important landscape metrics used in the study for quantifying the characteristics of landscape. The landscape metrics analysis and transformation analysis show that the forested areas are getting degraded and physical connectedness between the patches have also decreased making them isolated. The study demonstrates the importance of geospatial tools for monitoring the impact of disturbances on the forest ecosystem health, which can further help in landscape management.     

Survey-gap analysis for botanical research using integrated approach through taxonomical data and geoinformatics

India is one of the 12 mega biodiversity countries in the world. There are still many areas where inadequate information on plant wealth is available. Gap area prioritization is of utmost concern to understand the species richness of different parts of India. In this context survey-gap analysis was carried out to assess exploration status and to prioritise areas using integrated approach through taxonomical data and geoinformatics. In order to highlight the gaps in botanical exploration in the country, the present case study was conducted in Adilabad district of Andhra Pradesh. A grid size of 5′×5′ has been prepared to analyse the exploration status. The results indicated that most parts of study area have been under-explored and unexplored. Of the 200 grids, only one grid has been well explored with species collections of above 100. The study brought to light that moist deciduous forests were not covered during floristic studies. Comparative analysis with disturbance index and biological richness maps evidently points out that explorations were undertaken only in high disturbed zones and areas of low to medium biological richness. This geospatial analysis clearly points the need for more attention to the exploration of tropical forests in India. There is a need of systematic botanical studies to prioritise the conservation strategies of varied natural ecosystems. It is recommended for national level survey-gap analysis as an important step to determine the floristic wealth, species representativeness and distribution.     

Assessment and validation of biological richness at Landscape Level in part of the Himalayas and Indo-Burma <Emphasis Type="Italic">Hotspots</Emphasis> using geospatial modeling approach

Validation is a necessary step for model acceptance and is defined as a comparison of the model’s predictions with real world to determine whether the model is suitable for its intended purpose. We have validated the biological richness index for three states generated in ‘Biodiversity Characterization at Landscape Level’ project under the aegis of Department of Biotechnology and Department of Space of the Government of India. Biological Richness (BR) index, described elsewhere as a cumulative property of ecological habitats and surroundings; was analyzed as an integrated ‘threetier modeling approach’ of (i) utilization of geospatial tools, (ii) limited field survey and (iii) landscape analysis.     

Landscape analysis in Fambong Lho wildlife sanctuary,East district,Sikkim, India using remote sensing and GIS techniques

The high biological diversity and rich genetic forest resources of the state of Sikkim are to be conserved due to their sensitiveness to environmental degradation through continued human interference. The conservation of bioprospecting zones in natural forests as well as in protected areas is considered important for up keeping genetic resources and their germplasm. Keeping this in view, ‘Fambong Lho’ wildlife sanctuary in East district, Sikkim, has been selected to characterize different communities in the dominant vegetation type of Tropical Broad Leaved Hill Forest and to assess biodiversity controls in respect of different topographical features, such as altitude, slope, and aspects and use these inputs for prioritizing the protected area into different Bioprospective zones for conservation and planning. An altitude above 2000 m, having a slope in the range of 1–5 percent facing south east aspect are the ideal environmental conditions conducive to have high species richness. The analysis of fragmentation indicates that the forests are under stress along the fringes as they are closely associated with the habitations. The biological richness is recorded reasonably within the limits in the core area of the park but further prioritizing of such areas for conservation is necessary in view of impending danger of frequent interaction of human habitation with in the sanctuary for forest resources.     

Application of landscape ecology and remote sensing for assessment,monitoring and conservation of biodiversity

Landscape ecology, inter alia, addresses the question as to how altered landscape patterns affect the distribution, persistence, and abundance of a species. Landscape ecology plays an important role in integrating the different scales of biodiversity from habitat patch to biome level. Satellite remote sensing technology with multi-sensor capabilities offers multi-scale information on landscape composition and configuration. Advances in geospatial analytical tools and spatial statistics have improved the capability to quantify spatial heterogeneity. Globally, landscape level characterization of biodiversity has become an important discipline of science. Considering the vast extent, heterogeneity, and ecological and economic importance of forest landscapes, significant efforts have been made in India during the past decade to strengthen landscape level biodiversity characterization. The generic frame work of studies comprises preparation of national databases providing information on composition and configuration of different landscapes using multi-scale remote sensing techniques, understanding the landscape patterns using geospatial models to elicit disturbance and diversity patterns and application of this information for bioprospecting and conservation purposes. Studies on hierarchical linkage of multi-scale information to study the processes of change, landscape function, dynamics of habitat fragmentation, invasion, development of network of conservation areas based on the understanding of multi-species responses to landscape mosaics, macro-ecological studies to understand environment and species richness, habitat and species transitions and losses, landscape level solutions to adaptation and mitigation strategies to climate change are a few of the future challenges. The paper presents the current experiences and, analyses in conjunction with international scenario and identifies future challenges of Indian landscape level biodiversity studies.     

近40年长株潭生态景观的人为干扰过程分析

以长株潭主城区为研究对象,综合考虑卫星遥感数据、土地利用数据以及地理国情普查数据特点建立长株潭用地类型分类系统,应用土地利用转移矩阵和景观人为干扰测度模型获取主城区用地转移矩阵和人为干扰度指数时空分布,探讨长株潭主城区生态景观与人为干扰之间的关系。结果表明:从土地利用变化角度,1978—2015年长株潭主城区耕地、园林地、建设用地发生了显著变化,耕地总体上呈持续下降趋势,从3 544.67 km~2下降到2 571.18 km~2,园林地呈现先下降后升高的变化趋势,总体下降177.89 km~2;建设用地呈持续上升趋势,从80.56 km~2增加到1 252.85 km~2;在1994—2000年和2010—2015年长株潭主城区土地利用变化两个典型阶段,建设用地的增加主要通过占用耕地和园林地的方式实现。景观人为干扰指数时空分析表明:1978—2015年长株潭主城区景观人为干扰指数高值区主要集中在中心城市和其周边地区,在人类活动的影响下,中心城区以耕地、园林地向建设用地转移为主,周边地区主要以耕地和园林地的相互转移为主;随着城市化进程持续加快,人类活动对主城区生态景观的影响总体呈加强趋势,且受人类活动干扰主要集中在中心城区。     

Development of National Database on Long-term Deforestation in Sri Lanka

Sri Lanka is one of the biodiversity hotspots of the world. This study has utilized satellite remote sensing and GIS techniques to generate a nation-wide database on forests, forest types and land use/land cover of Sri Lanka. Spatial assessment of forest cover changes was carried out for the periods 1976–1985, 1985–1994, 1994–2005 and 2005–2014. The landscape fragmentation analysis has carried out to calculate the spatial and temporal patterns of forest. Land use/land cover map was prepared representing seven classes in 2014. The plantations occupy a large area (34.2%) followed by forests (33.4%) and agriculture (26.1%) in 2014. During the period of 1976–2014, the forest has been decreased by 5.5%. From 1976 to 1985 forest recorded a loss at an annual rate of 0.49%. This annual rate decreased to 0.01% during 2005–2014 indicates declining trend of deforestation and effective conservation measures. The study found deforestation hotspots in south east and northern most parts of the Sri Lanka. Total number of patches estimated has increased from 15193 in 1976 to 16136 in 2014. The study has found that main causes of deforestation in Sri Lanka were due to expansion of agriculture and plantations. The extent of change detected in the study through geospatial techniques has significance to the forest ecology and management of natural landscapes in Sri Lanka.     

Habitat Suitability Assessment of <Emphasis Type="Italic">Ardeotis nigriceps</Emphasis> (Vigors) in Great Indian Bustard Sanctuary,Maharashtra (India) Using Remote Sensing and GIS

Ardeotis nigriceps, commonly known as Great Indian Bustard (GIB), is a Critically Endangered, Evolutionary Distinct and Globally Threatened (EDGE) and endemic species to the Indian subcontinent. GIB is under tremendous threat in its last strongholds and sliding inextricably towards extinction. The GIB sanctuary in Maharashtra (India) is one of the last refuges of the bird constituting an area of 8496 km² spread over in seven talukas of Solapur and Ahemednagar districts. Major portion of the sanctuary (94.3 %) consists of privately owned lands under a variety of economic vocations and large number of villages and townships. In view of the legal restrictions relating to Protected Area under the Wildlife (Protection) Act of India 1972, the inhabitants of villages and townships faced a very difficult situation regarding use of their lands, development of properties and deriving benefits from planned local and regional development. This created conflict between local people and the forest department over the use of land, which necessitated the rationalization of the sanctuary. The objective of the present study was to map the suitable habitat of GIB in GIB Wildlife Sanctuary as an input for the realignment of the GIB Sanctuary by identifying areas that are important for the GIB. Main parameters considered for the habitat suitability assessments are, habit and habitat of GIB, slope, minimum patch size and disturbance sources. Based on the criteria derived for the ecological and biological requirements of GIB, binary deductive habitat suitability modeling has been done using remote sensing and GIS and prioritized the potential habitats of GIB. The net area of important suitable habitat of GIB in GIB sanctuary is 2304.99 km² out of 8496.44 km². The output of the present study has been used as an input by the committee (set by Honorable Supreme court of India) on rationalization of the GIB Sanctuary and the sanctuary has been rationalized with an area of 1222 km².     

Efficient,simultaneous detection of multi-class geospatial targets based on visual saliency modeling and discriminative learning of sparse coding

Automatic detection of geospatial targets in cluttered scenes is a profound challenge in the field of aerial and satellite image analysis. In this paper, we propose a novel practical framework enabling efficient and simultaneous detection of multi-class geospatial targets in remote sensing images (RSI) by the integration of visual saliency modeling and the discriminative learning of sparse coding. At first, a computational saliency prediction model is built via learning a direct mapping from a variety of visual features to a ground truth set of salient objects in geospatial images manually annotated by experts. The output of this model can predict a small set of target candidate areas. Afterwards, in contrast with typical models that are trained independently for each class of targets, we train a multi-class object detector that can simultaneously localize multiple targets from multiple classes by using discriminative sparse coding. The Fisher discrimination criterion is incorporated into the learning of a dictionary, which leads to a set of discriminative sparse coding coefficients having small within-class scatter and big between-class scatter. Multi-class classification can be therefore achieved by the reconstruction error and discriminative coding coefficients. Finally, the trained multi-class object detector is applied to those target candidate areas instead of the entire image in order to classify them into various categories of target, which can significantly reduce the cost of traditional exhaustive search. Comprehensive evaluations on a satellite RSI database and comparisons with a number of state-of-the-art approaches demonstrate the effectiveness and efficiency of the proposed work.     

Utilization of Landsat data to quantify land-use and land-cover changes related to oil and gas activities in West-Central Alberta from 2005 to 2013

Land use and land cover (LULC) change detection associated with oil and gas activities plays an important role in effective sustainable management practices, compliance monitoring, and reclamation assessment. In this study, a mapping methodology is presented for quantifying pre- and post-disturbance LULC types with annual Landsat Best-Available-Pixel multispectral data from 2005 to 2013. Annual LULC and land disturbance maps were produced for one of the major conventional oil and gas production areas in West-Central Alberta with an accuracy of 78% and 87%, respectively. The highest rate of vegetation loss (178 km²/year) was observed in coniferous forest compared to broadleaf forest, mixed forest, and native vegetation. Integration of ancillary oil and gas geospatial data with annual land disturbances indicated that less than 20% of the total land disturbances were attributable to oil and gas activities. In 2013, approximately 44% of oil and gas disturbances from 2005 to 2013 showed evidence of vegetation recovery. In the future, geospatial data related to wildfire, logging activities, insect defoliation, and other natural and anthropogenic factors can be integrated to quantify other causes of land disturbances.     

Built-up and vegetation extraction and density mapping using WorldView-II

This study demonstrates the use of high resolution WorldView-II satellite data in extraction of built-up land and vegetation using normalized index techniques. The PCA 1 and NIR 2 bands-based built-up index was proposed for extracting built-up land, which exhibit high accuracy. The normalized difference vegetation index based on Red Edge and NIR 2 bands of WorldView-II produced high accuracy inthe estimation of vegetation compared to the use of Red and NIR bands. The grid technique used in estimating built-up and vegetation density from precisely classified images provided better and accurate assessment of built-up and vegetation density in heterogeneous landscape of urban areas. This shows areas of very high to high built-up density are located in the central, western and southern parts, which are primarily devoid of vegetation. This study indicates possibilities of utilizing high resolution satellite data in urban landscape characterization using a grid-based technique.     

Vegetation analysis and study of its dynamics in Chandaka Wildlife Sanctuary (Orissa) using aerospace remote sensing

Changes brought in habitat conditions due to increasing human influences on natural areas have posed serious threat to wildlife. Remote Sensing has probably omerged as one of the most viable techniques to assess and monitor habitat conditions. Comparative analysis of maps of two-time period can provide authentic data with respect to changes brought in the habitat conditions. Chandaka Wildlife Sanctuary, covering an area of 213.71 sq. km in Orissa is one of the natural reserves of elephants which has undergone serious changes brought in through anthropogenic activities of urban areas of Cuttack and Bhubaneshwar lying within the proximity of the sanctuary. The natural reserve, an ideal habitat for elephants, was connected to neighbouring extensive forest belts. These connections have been either degraded or deforested over the years. The present study analyses the types of habitat available in the sanctuary using remote sensing data (aerial and satellite). Vegetation-type maps of 1975 have been prepared from B/W aerial photographs of 1:25,000 scale. For assessing the current vegetation types, maps have been prepared from Indian Remote Sensing Satellite (LISS II) false colour composite on 1:50,000 scale. Comparative evaluation of the maps indicates changes in the vegetation pattern, increase in mining and agriculture areas within the sanctuary. Stratified field sampling of vegetation types provide structural characteristics of the vegetation. Bamboo has been found to extend in the valleys and side slopes of the sanctuary area during past 15 years. An analysis on response of vegetation in all major vegetation types mapped have been made in the context of the invasion of Eupatorium odoratum. Finally, bamboo biomass has been assessed through stratified random sampling as it constitutes a major elephant food source.     

自然资源生态空间现状与适宜性分析评价 ——以上海市金山区为例

本文以上海市金山区为例,利用地理国情普查和监测数据,从生态空间规模水平、生态空间稳定水平、生态空间保障度等角度出发,在常规基础评价指标之外,结合生态空间景观格局指数、生物丰富度指数的综合评价模型方法,对金山区各街镇的生态空间适宜性进行了评价。其技术方法与路线,可为相关部门开展生态环境评价、统筹各类规划的空间要求及强化土地用途管制等提供一定的技术支撑。     

Characterizing urban area dynamics in historic city of Kurukshetra,India, using remote sensing and spatial metric tools

Abstract

Developing countries like India are an urbanization hotspot with many upcoming towns and cities. Growth in small and medium sized towns and cities have been unnoticed and growing without appropriate urban planning. Utilizing the available medium resolution satellite data and geospatial platforms, the growth dynamics of Kurukshetra city was analysed over a period of 24 years. The study employed a combination of change detection technique and spatial metrics (six each of class and landscape levels) analysis to delineate the growth track of the city and its environs. A significant increase in urban built up (dense 237%; open 1038%) is seen majorly at the cost of open area (70%) and tree clad (58%). Phases of city’s aggregation and diffusion are observed using class and landscape level spatial metrics. Understanding and monitoring of land use changes in and around city limits using integrated spatial tools provide better decision making capability.     

无人机低空摄影测量在城市测绘保障中的应用前景

无人机低空摄影测量具有高清晰、大比例尺、小面积、高现势性的优点,是卫星遥感与普通航空摄影不可缺少的补充。可为大比例尺影像地图生产、重点地区正射影像制作、高精度DEM格网和DLG产品提供高分辨率清晰影像数据源,满足城市信息化建设对大比例尺基础地理空间数据的需求,为城市建设提供有效的测绘保障。通过高分辨率测绘产品支持、应急测绘保障、三维数字建模和重点区域动态监测等多个方面对无人机低空摄影测量在城市测绘保障中的应用前景进行论述展望。