Geospatial modelling for identification of potential ecological corridors in Orissa

Development of forest connectivity and corridors are critical for biodiversity conservation and also ensures energy and genetic exchange across greater spatial extent. A model has been developed to geospatially identify the potential ecological corridors based on the vegetation type and land cover data in association with spatial disturbance profile. The model formulates the route of least impedance due to (1) disturbance (a function of fragmentation, juxtaposition, Interspersion & proximity to roads/settlements) and (2) vegetation type and land cover. This is because the movement of genetic information and materials follow the path of least resistance across a landscape. The paper explores the utility of the approach to spatially generate ecological corridors connecting 14 protected areas of Orissa. The model has been able to identify the potential route connecting the different protected regions with 85–87% of the corridor in the natural areas. Of the 14 protected areas, only 12 could be connected by the model as they confirm to the criteria for the corridor establishment.     

Identifying transit corridors for elephant using a long time-series

The role of corridors in mitigating the effects of landscape fragmentation on biodiversity is controversial. Recent studies have highlighted the need for new approaches in corridor design using long-term datasets. We present a method to identify transit corridors for elephant at a population scale over a large area and an extended period of time using long-term aerial surveys. We investigated environmental and anthropogenic factors directly and indirectly related to the wet versus dry season distribution of elephant and its transit corridors. Four environmental variables predicted the presence of elephant at the landscape scale in both seasons: distance from permanent water, protected areas and settlements and vegetation structure. Path analysis revealed that altitude and monthly average NDVI, and distance from temporary water had a significant indirect effect on elephant distribution at local scale in dry and wet seasons respectively. Five transit corridors connecting Tarangire National Park and the northern as well as south-eastern wet season dispersal areas were identified and matched the wildlife migration routes described in the 1960s. The corridors are stable over the decades, providing landscape connectivity for elephant. Our approach yielded insights how advanced spatial analysis can be integrated with biological data available from long-term datasets to identify actual transit corridors and predictors of species distribution.     

Landcover Classification in the Taieri River Catchment,New Zealand: A Focus on the Riparian Zone

Abstract

Riparian vegetation has a fundamental influence on the biological, chemical and physical nature of rivers. The quantification of riparian landcover is now recognised as being essential to the holistic study of the ecosystem characteristics of rivers. Medium resolution satellite imagery is now commonly used as an efficient and cost effective method for mapping vegetation cover; however such data often lack the resolution to provide accurate information about vegetation cover within riparian corridors. To assess this, we measure the accuracy of SPOT multispectral satellite imagery for classification of riparian vegetation along the Taieri River in New Zealand. In this paper, we discuss different sampling strategies for the classification of riparian zones. We conclude that SPOT multispectral imagery requires considerable interpretative analysis before being adequate to produce sufficiently detailed maps of riparian vegetation required for use in stream ecological research.     

Applying landscape-ecological concept and GIS modelling for assessing and mapping of ecological situation of mountainous landscapes (on the case of Syunik marz,Armenia)

Regional landscape-ecological studies have acquired a special topicality as they assure efficient environmental conservation and sustainable use of natural resources. A landscape-ecological analysis was performed based on four basic integral indices: (1) ecological potential, (2) ecological stability, (3) ecological load and (4) ecological tension. The values of basic integral indices of the landscape-ecological analysis were calculated as sums of respective factors expressed in scores and multiplied by their significance reflecting coefficients. In agreement with that rule, a formula was derived of calculation of basic indices of landscape-ecological analysis. Subsequently, those factors were integrated by ‘Model Builder’ in ArcGIS applying ‘Weighted Sum’ functions. Finally, through geographic information systems modelling, maps of basic indices of landscape-ecological analysis were produced. In conclusion – ecological potential, stability, load and tension are best indicators for the assessment of the landscape-ecological situation of the studied territory.     

基于生态重要性评价与最小累积阻力模型的重庆市生态安全格局构建

生态安全格局构建是保障生态系统稳定运行,实现区域生态安全的重要途径。本文以重庆市为例,基于生态服务功能和生态敏感性对重庆市进行生态重要性评价,将生态极重要区域与自然保护地共同作为生态源地。首先从生态本底和生态胁迫两个角度选取高程、坡度、土地利用类型、距道路距离、距水体距离、夜间灯光指数6个阻力因子构建了典型山地动物的生态阻力面,然后利用最小累积阻力模型（MCR）模拟潜在生态廊道,完成市域生态安全格局的构建。研究表明,重庆市生态源地30 751.11 km²,占全市总面积的37.32%,主要分布在渝东北与渝东南的山林地。将识别的73条潜在生态廊道、138个生态节点与生态源地进行叠加,结合重庆的山水格局,构建了"两区、三带、四核、多廊、多点"的多层次生态安全格局,为重庆市生态保护和修复工作提供科学参考。     

ECOLOGICAL ASSESSMENT AND MAPPING FOR BALANCED REGIONAL DEVELOPMENT

A Russian geographer summarizes the results of a comprehensive study of modern landscapes and the mapping of diverse ecological situations. The procedure involves the development of a system of criteria and indices for the assessment of the properties of the environment, which provide a sound basis for comprehensive ecological mapping. The importance of an ecological assessment in the mapping of environmental problems and situations in support of the stable and balanced development of regions is demonstrated. Translated by Edward Torrey, Alexandria, VA from: Izvestiya Akademiya Nauk, seriya geograficheskaya, 1999, No. 1, pp. 81-87.     

Sentinel-2 red-edge spectral indices (RESI) suitability for mapping rubber boom in Luang Namtha Province,northern Lao PDR

Rubber (Hevea brasiliensis) tree cultivation is being continuously expanded northward by replacing evergreen forests and swidden-related regenerated vegetation across the uplands of mainland Southeast Asia (MSEA), e.g., Laos, a landlocked mountainous country. The non-native tree establishment in the northern tropical edge, or the non-traditional suitable planting area, provides stable supplies of natural latex, yet also leads to severe ecological degradation and environmental effects in water conservation, soil quality, rainforest fragmentation and biodiversity. Rubber plantations in the northern part of MSEA are normally characterized by periodic deciduous during the dry season, along with a lengthy defoliation-foliation duration, because of seasonal variations in temperature and precipitation. It thus lays a phenological and physiological base for dynamics monitoring with common multispectral (e.g., near-infrared and short-wave infrared bands) satellites, particularly Landsat. However, whether Sentinel-2 red-edge based algorithms are suitable for discriminating rubber plantations is not yet exclusively reported. Here, we developed a red-edge spectral indices (RESI) method through the normalization of three red-edge bands and applied it to identify and map rubber plantations in Luang Namtha Province of northern Laos, where a rubber boom begun in the mid-2000s. The RESI algorithm highlights the sensitivity of red-edge bands to the changes in moisture content and canopy density of rubber plantations. The area of mature rubber plantations was estimated to be 771.2 km² in this province bordering southwest China in 2018, which was nearly twice as much as that of 2011, with the overall accuracy and kappa coefficient up to 92.50% and 0.91, respectively. Our phenology-based RESI approach not only indicates that Sentinel-2 imagery holds significant potential for monitoring rubber plantations, but also improves the remotely-sensed methods of rubber boom mapping via introducing the red-edge channel.     

Detecting the changes in rural communities in Taiwan by applying multiphase segmentation on FORMOSA-2 satellite imagery

Agricultural activities mainly occur in rural areas; recently, ecological conservation and biological diversity are being emphasized in rural communities to promote sustainable development for rural communities, especially for rural communities in Taiwan. Therefore, since 2005, many rural communities in Taiwan have compiled their own development strategies in order to create their own unique characteristics to attract people to visit and stay in rural communities. By implementing these strategies, young people can stay in their own rural communities and the rural communities are rejuvenated. However, some rural communities introduce artificial construction into the community such that the ecological and biological environments are significantly degraded. The strategies need to be efficiently monitored because up to 67 rural communities have proposed rejuvenation projects. In 2015, up to 440 rural communities were estimated to be involved in rural community rejuvenations. How to monitor the changes occurring in those rural communities participating in rural community rejuvenation such that ecological conservation and ecological diversity can be satisfied is an important issue in rural community management. Remote sensing provides an efficient and rapid method to achieve this issue. Segmentation plays a fundamental role in human perception. In this respect, segmentation can be used as the process of transforming the collection of pixels of an image into a group of regions or objects with meaning. This paper proposed an algorithm based on the multiphase approach to segment the normalized difference vegetation index, NDVI, of the rural communities into several sub-regions, and to have the NDVI distribution in each sub-region be homogeneous. Those regions whose values of NDVI are close will be merged into the same class. In doing so, a complex NDVI map can be simplified into two groups: the high and low values of NDVI. The class with low NDVI values corresponds to those regions containing roads, buildings, and other manmade construction works and the class with high values of NDVI indicates that those regions contain vegetation in good health. In order to verify the processed results, the regional boundaries were extracted and laid down on the given images to check whether the extracted boundaries were laid down on buildings, roads, or other artificial constructions. In addition to the proposed approach, another approach called statistical region merging was employed by grouping sets of pixels with homogeneous properties such that those sets are iteratively grown by combining smaller regions or pixels. In doing so, the segmented NDVI map can be generated. By comparing the areas of the merged classes in different years, the changes occurring in the rural communities of Taiwan can be detected. The satellite imagery of FORMOSA-2 with 2-m ground resolution is employed to evaluate the performance of the proposed approach. The satellite imagery of two rural communities (Jhumen and Taomi communities) is chosen to evaluate environmental changes between 2005 and 2010. The change maps of 2005–2010 show that a high density of green on a patch of land is increased by 19.62 ha in Jhumen community and conversely a similar patch of land is significantly decreased by 236.59 ha in Taomi community. Furthermore, the change maps created by another image segmentation method called statistical region merging generate similar processed results to multiphase segmentation.     

Identifying Mangrove Species and Their Surrounding Land Use and Land Cover Classes Using an Object-Oriented Approach with a Lacunarity Spatial Measure

Accurate and reliable information on the spatial distribution of mangrove species is needed for a wide variety of applications, including sustainable management of mangrove forests, conservation and reserve planning, ecological and biogeographical studies, and invasive species management. Remotely sensed data have been used for such purposes with mixed results. Our study employed an object-oriented approach with the use of a lacunarity technique to identify different mangrove species and their surrounding land use and land cover classes in a tsunami-affected area of Thailand using Landsat satellite data. Our results showed that the object-oriented approach with lacunarity-transformed bands is more accurate (over-all accuracy 94.2% kappa coefficient = 0.91) than traditional per-pixel classifiers (overall accuracy 62.8% and kappa coefficient = 0.57).     

Applications of remote sensing and GIS to the assessment of riparian zones for environmental restoration in agricultural watersheds

Geographical design of riparian buffers with long-term vegetation cover for environmental restoration in agricultural watersheds needs to assess how much farmland is located in the buffers of a concerned watershed. Traditionally, this assessment was done by field surveying and manual mapping, which was a time-consuming and costly process for a large region. In this paper, remote sensing (RS) and geographical information system (GIS) as cost-effective techniques were used to develop a catchments-based approach for identifying critical sites of agricultural riparian buffer restoration. The method was explained through a case study of watershed with 11 catchments and results showed that only four of the catchments were eligible in terms of higher priority for riparian buffer restoration. This research has methodological contributions to the spatial assessment of farming intensities in catchments-based riparian buffers across a watershed and to the geographical designs of variable buffering scenarios within catchments. The former makes the catchments-based management strategy possible, and the latter provides alternative restoration scenarios to meet different management purposes, both of which have direct implementations to the environmental restoration of riparian buffers in the real world. This study, thus, highlights the great potential of RS and GIS applications to the planning and management of riparian buffer restoration in agricultural watersheds.     

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.     

Biodiversity Information System for North East India

Abstract

Biodiversity is the variety and variability of flora and fauna in an ecosystem. Articulated into genes, species, and ecosystem, it provides the biological plasticity needed by life on the earth to adapt changes. As we approach towards the forthcoming century, the earth's diversity of life is increasingly at risk through a combination of mostly human induced factors leading to erosion of genetic resources, extinction of species and collapse of ecological systems. Insitu conservation, biotechnology tools for conservation and prospecting, species habitat relationship and following evolutionary process of speciation are some of the challenges. India being one of the mega biodiversity centers of the world is also known for its traditional knowledge of conservation. The varied regions of the country, with unique floristic and faunal richness, their vastness, endemism, heterogeneity and also inaccessibility of large areas have necessitated creation of authentic baseline database on biodiversity. With the advent of Internet based Geographic Information System technology an effort is being made to harness the power of these technologies to facilitate biodiversity conservation.

The information system organizes the data base generated under the project on “Biodiversity Characterization at landscape level using remote sensing and Geographic Information System in North East India” of the Department of Biotechnology and Department of Space, Government of India. The entire database is organized in object oriented relational database using Oracle as Backend and Visual Basic, ASP as front end. The web enabling part comes through uploading the entire spatial and non‐spatial data at a common platform using ArcSDE and ArcIMS The spatial characterization of landscape structures and its linkages with attribute information on the floristic composition, economic valuation, endemism are presented in Biodiversity Information System on a sharable environment. It is a step to evolve with new a mechanism to conserve biological diversity at local, regional and national level.     

Study of coastal wetland classification based on decision rules using ALOS AVNIR-2 images and ancillary geospatial data

Wetlands play irreplaceable key roles in ecological and environmental procedures. To make effective conservation and management, it is essential to understand the wetlands’ distribution and changes. In this study, an approach based on decision rules algorithm in conjunction with maximum likelihood classification is proposed for coastal wetland mapping using multi-temporal remotely sensed imagery and ancillary geospatial data. As a case study, Multi-temporal Advanced Visible and Near Infrared Radiometer type 2 images acquired by Japanese Advanced Land Observation Satellite are analysed to investigate the seasonal change pattern of coastal wetlands in Washington State, USA. Geospatial data, including Digital Elevation Model and spatial neighbourhood knowledge, are further integrated to characterize wetland features and discriminate classes within a certain elevation ranges. The final result is a refined coastal wetland map with 15 land cover categories. Preliminary evaluation of the final result shows that the proposed approach is effective in coastal wetland mapping.     

GIS Methodology for Characterizing Historical Conditions of the Willamette River Flood Plain, Oregon

Recent environmental developments have stimulated an interest in conservation and restoration of the historical Willamette River flood plain, both to protect against flooding and to provide wildlife habitat. In order to best utilize scarce resources, we characterized historical and modern river channel and flood‐plain conditions to evaluate changes and help prioritize restoration sites. Using cartographic and photographic data sources, we developed a Geographic Information System (GIS) to map active channels, side channels, islands and tributaries for four separate dates, as well as riparian and flood‐plain vegetation characteristics for pre‐European settlement and modern time periods. Coverages based on flood records and other boundaries were used to partition the flood plain into spatial subsets for analysis. The GIS allowed comparisons between historical and present conditions for a variety of environmental factors. Much of the pre‐settlement channel complexity has been removed. Total channel length in 1995 was 26% less than in 1850, with almost 58% of the river's side channels disconnected from the system. In addition, we found a 72% loss of flood‐plain forest from 1850 to 1995, since it was converted to agricultural and urban land uses. Selected river and flood‐plain variables were made available for a spatial model to prioritize potential locations for flood‐plain restoration.     

Determining and Mapping Eco-Cultural Subregions Using GIS and Simos Procedure

Immovable cultural properties constituting cultural heritage centre upon regions that have the level of natural features required for basic human needs. Such regions constitute a space with characteristics of an eco-cultural subregion and they do not have any administrative or geographical boundaries. Aims of this study are to introduce the concept of eco-cultural subregion, which is the holistic expression of natural features together with cultural heritage, to the literature; to present a method in identifying geographical boundaries of subregions; and to formulate a classification system. The research was conducted in the Phrygian Valley, which is one of the most important centres of ancient Phrygians in Western Anatolia, using a method based on GIS-MCDM (Geographic Information System-Multiple Criteria Decision Making). The selected MCDM technique was Simos Procedure. Natural features and cultural heritage were considered together and the entire Phrygian Valley was approached as both an ecological and a cultural region. Ecological features were analysed using 7 main and 17 subfactors, while cultural heritage was analysed using 2 main factors and 15 subfactors. Simos Procedure was employed in the assignment of weight for main factors and subfactors. First 17 ecological subregions with similar characteristics under 4 levels were identified. Considering their cultural heritage values, a classification system was formulated and eco-cultural subregions were expressed in level/degree in this system. In consequence of this procedure boundaries of eco-cultural subregions were drawn and mapped. This classification also enabled to identify the concept of eco-cultural subregion which is not found in the literature. It is expected that eco-cultural subregions will provide to discuss ecological features and cultural heritage holistically in conservation and planning studies.     

Strategies for Watershed Management planning using remote sensing technique

‘Watershed Management’ has assumed urgency for planned development of land and water resources and to arrest land degradation process to preserve environment and ecological balance. Decision support to such management planning requires scientific knowledge of resources information, expected runoff and sediment yield, priority classification of watersheds for conservation planning, monitoring of watershed for environmental impact assessment and technologies of GIS for data base creation, scenario development and appropriate decision making. Remote sensing technique is ideally suited to evolve such a management strategy. Scientific basis of this approach is explained.     

Use of multi-temporal Landsat images for analyzing forest transition in relation to socioeconomic factors and the environment

Recently there have been reports of forest regrowth occurring in different regions across the world. There is also a growing recognition of the potential beneficial impact that secondary forests may have on the global environment: providing crucial ecosystem services such as soil conservation, stabilization of hydrological cycles, carbon sequestration, and support for forest dependent communities. Consequently, there is a growing awareness of the need to recognize that landscapes are complex shifting mosaics wherein forest clearing and reforestation take place. In this study, the rates of reforestation, deforestation, forest regrowth and degradation were measured using multi-temporal Landsat images of Danjiangkou, China. Landsat data from 1990, 1999 and 2007 were (1) classified as dense forest, open forest and non-forest areas and (2) compared between years to identify forest cutting, regeneration and degradation. The results showed that there was a net gain of 29,315 ha of forest area (including dense and open forest) from 1990 to 2007, showing a clear trend of reforestation in the study area. Forest modification (degradation and regrowth) and change categories (deforestation and reforestation) occurred simultaneously during the observation time period. Socioeconomic data from public statistics and environmental attributes allowed the assessment of the socioeconomic factors and the environmental conditions that caused these changes using non-metric multidimensional scaling (NMDS). The research showed that the socioeconomic factors due to different policies were major driving forces of forest transition, whereas environmental attributes of the underlying landscape constrained forest cover changes. These findings have led to a better understanding of forest transition at a local scale in our study region. Comprehensive knowledge of these relationships may be useful to reconstruct past forest transitions and predict future changes, and may help to enhance sustainable management practices aimed at preserving essential ecological functions.     

基于植被指数模型的淡水湖泊湿地景观信息提取

高邮湖湿地是江苏省重要湿地之一,对生态、环境控制、调节气候和保护生物多样性具有重要意义。采用2007年的LandsatTM影像作为遥感信息源,选择影像的光谱特征和比值植被指数(RVI)、差值植被指数(DVI)、归一化植被指数(NDVI)、归一化差异绿度指数(NDGI)、土壤调节植被指数(SAVI)和最佳土壤调节植被指数(OSAVI)6种植被指数做了光谱特征分析,从而确定出最佳指数模型,并基于决策树方法,实现研究区景观信息的遥感分类。研究结果表明,决策树分类法易于综合多种特征进行遥感影像分类,植被指数参与到决策树分类中能够提高分类的总体精度,其总体精度达到79.58%,Kappa系数为0.721 0,分类结果理想且人工参与灵活。     

Remote sensing of scattered Natura 2000 habitats using a one-class classifier

Mapping of habitats with relevance for nature conservation involves the identification of patches of target habitats in a complex mosaic of vegetation types not relevant for conservation planning. Limiting the necessary ground reference to a small sample of target habitats would greatly reduce and therefore support the field mapping effort. We thus aim to answer in this study the question: can semi-automated remote sensing methods help to map such patches without the need of ground references from sites not relevant for nature conservation? Approaches able to fulfill this task may help to improve the efficiency of large scale mapping and monitoring programs such as requested for the European Habitat Directive.In the present study, we used the maximum-entropy based classification approach Maxent to map four habitat types across a patchy landscape of 1000 km² near Munich, Germany. This task was conducted using the low number of 125 ground reference points only along with easily available multi-seasonal RapidEye satellite imagery. Encountered problems include the non-stationarity of habitat reflectance due to different phenological development across space, continuous transitions between the habitats and the need for improved methods for detailed validation.The result of the tested approach is a habitat map with an overall accuracy of 70%. The rather simple and affordable approach can thus be recommended for a first survey of previously unmapped areas, as a tool for identifying potential gaps in existing habitat inventories and as a first check for changes in the distribution of habitats.     

Cotton Crop Discrimination Using Fuzzy Classification Approach

Crop growth information represented through temporal remote sensing data is of great importance for specific agriculture crop discrimination. In this paper, the effect of various indices was empirically investigated using temporal images for cotton crop discrimination. Five spectral indices SR (Simple Ratio), NDVI (Normalized Difference Vegetation index), TNDVI (Transformed Normalized Difference Vegetation Index), SAVI (Soil-Adjusted Vegetation Index) and TVI (Triangular Vegetation Index) were investigated to identify cotton crop using temporal multi-spectral images. Data used for this study was AWIFS (coarser resolution) for soft classification and LISS-III (medium coarser) data for soft testing from Resourcesat-1 (IRS-P6) satellite. The mixed pixel (i.e. multiple classes within a single pixel) problem had been handled using soft computing techniques. Possibilistic fuzzy classification approach is used to handle mixed pixels for extracting single class of interest. The classification results with respect to various indices were compared in terms of image to image fuzzy overall classification accuracy. It was observed that temporal SAVI indices database with data set-2 outperformed other temporal indices database for cotton crop discrimination. Temporal SAVI indices database gave highest fuzzy overall accuracy of 93.12% with data set-2 in comparison to others.