gandotra naina | University of Jammu, Jammu, Jammu and Kashmir, India (original) (raw)

Papers by gandotra naina

Annales Zoologici Fennici, Jan 1, 2002

Reunanen, P., Mönkkönen, M. & Nikula, A. 2002: Habitat requirements of the Siberian flying squirr... more Reunanen, P., Mönkkönen, M. & Nikula, A. 2002: Habitat requirements of the Siberian flying squirrel in northern Finland: comparing field survey and remote sensing data. -Ann. Zool. Fennici 39: 7-20.

… Conference on Remote Sensing, Jan 1, 1998

... computer based GIS provide the means to model the spatial habitat suitability effectively . .... more ... computer based GIS provide the means to model the spatial habitat suitability effectively . ... Epp.H., 1988 . application satellite data ad image analysis to wildlife habitat inventory. In Land/wildlife land Classification series No. ... 22 land conservation Branch . Canada wildlife service . ...

Global Ecology and …, Jan 1, 1999

monitoring system that uses both types of data. These problems need to be overcome if habitat and... more monitoring system that uses both types of data. These problems need to be overcome if habitat and 1. Britain is unusual in the quantity and quality of species data are to be used more effectively for species and habitat data available, at both national nature conservation in the wider countryside. and regional scales. This paper reviews the sources, 4. A more integrated system based on the concept coverage and quality of these data.

Tropical Ecology, Jan 1, 2002

Remote sensing and geographic information system (GIS) technologies have been used for gathering ... more Remote sensing and geographic information system (GIS) technologies have been used for gathering the information on physical parameters of the wildlife habitats and geospatial modeling for wildlife habitat evaluation. The results indicate definite advantage of remote sensing and GIS over conventional methods. Over time, the availability of better spatial data has made habitat evaluation and management more scientific and realistic. Many habitat evaluation procedures based on species-habitat relationship have been worked out. Basically, all models have tried to evaluate the carrying capacity of the wildlife habitat for a particular animal species.

Global Ecology and Biogeography Letters, Jan 1, 1998

JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, a... more JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact support@jstor.org.

Landscape and Urban Planning, Jan 1, 2003

In the face of human population growth that is transforming the Earth, scientists, land managers,... more In the face of human population growth that is transforming the Earth, scientists, land managers, and planners are working to prevent, mitigate, and reverse the consequent loss of species, ecosystems, and landscapes. Because of the need to act quickly with incomplete data, a number of shortcuts have been developed that rely on identifying key species for planning efforts. By developing conservation plans for a small set of carefully selected focal species, planners hope to create a protective umbrella for a wider array of species and functional landscapes. In an earlier paper, we described an approach for selecting a set of focal species. In this paper, we report a process for the rapid identification and verification of potential habitat for a focal species. Using the barred owl as an example, we present the process for a suburbanizing region of North Carolina, USA. The barred owl was selected to represent bottomland hardwood and forested wetland landscapes in the region. Using a geographic information system (GIS), we assembled data layers from readily available remotely sensed, conventional survey, and physiographic data to create a model of barred owl habitat. Barred owls occupy bottomland hardwood forests, which we identified using land cover, soils, and wetlands data. We eliminated from consideration bottomland forest habitat within 100 m of a road and within 60 m of open vegetative cover. Patches of the remaining bottomland forest larger than 86 ha in size were considered large enough to meet all barred owl habitat needs. Simple presence/absence surveys detected barred owls in approximately 65% of patches identified by our model as suitable habitat. We tested the barred owl's suitability as an umbrella for bottomland forest species using an existing database of rare and outstanding elements of natural diversity. Umbrella coverage for barred owl habitat (bottomland forest patches ≥ 86 ha) varied with taxa from 0% for invertebrate species to 75% for vertebrate species. However, umbrella coverage for all bottomland forest, including patches <86 ha, was at or near 100% for all taxa. The relatively simple modeling and verification processes we used can be carried out with a minimal amount of data and time, making it an attractive tool in situations where time and resources are in short supply.

International Journal of Remote Sensing, Jan 1, 2001

The tropical wetland environments of northern Australia have ecological, social, cultural and eco... more The tropical wetland environments of northern Australia have ecological, social, cultural and economic values. Additionally, these areas are relatively pristine compared to the many other wetland environments in Australia, and around the world, that have been extensively altered by humans. However, as the remote northern coastline of Australia becomes more populated, environmental problems are beginning to emerge that highlight the need to manage the tropical wetland environments. Lack of information is currently considered to be a major factor restricting the eVective management of many ecosystems and for the expansive wetlands of the Northern Territory, this is especially the case, as these areas are generally remote and inaccessible. Remote sensing is therefore an attractive technique for obtaining relevant information on variables such as land cover and vegetation status. In the current study, Landsat TM, SPOT (XS and PAN) and large-scale, true-colour aerial photographywere evaluated for mapping the vegetation of a tropical freshwater swamp in Australia's Top End. Extensive ground truth data were obtained, using a helicopter survey method. Fourteen cover types were delineated from 1:15 000 air photos (enlarged to 1:5000 in an image processing system) using manual interpretation techniques, with 89% accuracy. This level of detail could not be extracted from any of the satellite image data sets, with only three broad land-cover types identi ed with accuracy above 80%. The Landsat TM and SPOT XS data provided similar results although superior accuracy was obtained from Landsat, where the additional spectral information appeared to compensate in part for the coarser spatial resolution. Two diVerent classi cation algorithms produced similar results.

Ecology, Jan 1, 2006

Ecological ''niche modeling'' using presence-only locality data and large-scale environmental var... more Ecological ''niche modeling'' using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D 2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

Remote Sensing of …, Jan 1, 2008

Habitat distribution models have a long history in ecological research. With the development of g... more Habitat distribution models have a long history in ecological research. With the development of geospatial information technology, including remote sensing, these models are now applied to an ever-increasing number of species, particularly those located in areas in which it is logistically difficult to collect habitat data in the field. Many habitat studies have used data acquired by multi-spectral sensor systems such as the Landsat Thematic Mapper (TM), due mostly to their availability and relatively high spatial resolution (30 m/pixel). The use of data collected by other sensor systems with lower spatial resolutions but high frequency of acquisitions has largely been neglected, due to the perception that such low spatial resolution data are too coarse for habitat mapping. In this study we compare two models using data from different satellite sensor systems for mapping the spatial distribution of giant panda habitat in Wolong Nature Reserve, China. The first one is a four-category scheme model based on combining forest cover (derived from a digital land cover classification of Landsat TM imagery acquired in June with information on elevation and slope (derived from a digital elevation model obtained from topographic maps of the study area). The second model is based on the Ecological Niche Factor Analysis (ENFA) of a time series of weekly composites of WDRVI (Wide Dynamic Range Vegetation Index) images derived from MODIS (Moderate Resolution Imaging Spectroradiometer -250 m/pixel) for 2001. A series of field plots was established in the reserve during the summer-autumn months of 2001-2003. The locations of the plots with panda feces were used to calibrate the ENFA model and to validate the results of both models.

Ecological applications, Jan 1, 1999

Conservation …, Jan 1, 2002

We developed three black bear ( Ursus americanus ) habitat models in the context of a geographic ... more We developed three black bear ( Ursus americanus ) habitat models in the context of a geographic information system to identify linkage areas across a major transportation corridor. One model was based on empirical habitat data, and the other two (opinion-and literature-based) were based on expert information developed in a multicriteria decision-making process. We validated the performance of the models with an independent data set. Four classes of highway linkage zones were generated. Class 3 linkages were the most accurate for mapping cross-highway movement. Our tests showed that the model based on expert literature most closely approximated the empirical model, both in the results of statistical tests and the description of the class 3 linkages. In addition, the expert literature-based model was consistently more similar to the empirical model than either of two seasonal, expert opinion-based models. Among the expert models, the literature-based model had the strongest correlation with the empirical model. Expert-opinion models were less in agreement with the empirical model. The poor performance of the expert-opinion model may be explained by an overestimation of the importance of riparian habitat by experts compared with the literature. A small portion of the empirical data to test the models was from the pre-berry season and may have affected how well the model predicted linkage areas. Our empirical and expert models represent useful tools for resource and transportation planners charged with determining the location of mitigation passages for wildlife when baseline information is lacking and when time constraints do not allow for data collection before construction.