Application of remote sensing in wildlife mapping

 

Application of remote sensing in wildlife mapping

What is Remote Sensing?

Remote sensing refers to the process of detecting and monitoring an area’s physical characteristics ‘remotely’ by measuring the reflected and emitted radiation from its surface.

For instance, cameras on airplanes capture images of large areas of the Earth’s surface, sonar systems on ships map rugged topographies of the ocean floor, and satellite sensors study temperature variations in oceans.

Components and Steps Involved in Remote Sensing

Remote sensing technology primarily involves two components:

Platform: ‘Carriers’ for remote sensors.

Platforms can be of three types: ground-based platforms (hand-held devices, tripods, towers, moving vehicles, and total stations), aerial platforms (helicopters, low-altitude, and high-altitude aircrafts, unmanned aerial vehicles/drones), and spaceborne platforms (polar-orbiting satellites, sun-synchronous, and geostationary satellites).

Sensors: ‘Devices’ that collect data by detecting energy reflected from earth.

Sensors can be of the following types:

Active Sensors (emit, reflect, and detect energy produced by their own source) and Passive Sensors (detect the reflected sunlight or energy emitted by the object being studied). LiDAR and RADAR are “active” sensors, while radiometers and spectrometers are “passive”. Passive sensors are known to produce higher quality imagery than active ones.

 

Human induced undesirable changes such as land encroachments leading to wildlife habitat loss, pollution and introduction of invasive species pose serious threat to wildlife health and richness. Hence in order to restore wildlife habitat, fragmentation and to prevent further local and global extinction of any species, it is imperative to understand and carry out comprehensive study of the wildlife population and pattern. But most of the wildlife habitats are located in those areas where accessibility is not easy because of difficult terrain. Also the study of wildlife conservation and management including wildlife densities, living pattern, population and habitat with the help of conventional methods happens to be tough, time taking, risky and requires lot of resources. Also expressing and measuring biodiversity including study of organisms and their biotic and abiotic components happens to be intricate because of the versatile nature of biodiversity. Remote sensing can answer these problems as the number of strategies for wildlife studies including investigation of biodiversity, wildlife habitation mapping and animal movement modeling can be executed with the help of remote sensing and inventory database. Remote sensing is a computer based software application which obtains and processes geographic information from satellite or air born sensors. Remote sensing measures the reflected and emitted electromagnetic radiations from the objects. The spatial coverage provided by the remote sensing occurs across wide range of electromagnetic wavelength. Remote sensing is capable of providing uniform consistent spatial observation data at wide scale domain. The images and photographs obtained from the remote sensing helps greatly in the investigation of physical conditions. It can be further enhanced for better accuracy using remotely sensed data and field study (multi stage approach). Remote sensing can be classified based on either direct approach or indirect approach (Chambers et al., 2009). The direct approach suggests direct observation of spatial features, objects or communities using satellites or air born sensors using high resolution spatial sensors and hyperspectral sensors (Turner et al., 2003). The indirect parameters are dependent on the environmental parameters such as land use, land cover, species composition etc., obtained from remotely sensed data as surrogate for precise measurement of the potential species verities and patterns (Collingwood et al., 2009). Satellite Remote Sensing offers information on vegetation type, forest cover, and their changes at global, regional, national, or micro level studies (Roy et al. 1987, Unni at al. 1985, Porwal and Pant, 1986). Remote Sensing plays an important role in forest management with reference to wildlife management, fire control, grazing land management, soil and water conservation, mapping of sites suitable for social forestry and afforestation programmes.

Some of the areas where remote sensing can be useful for wildlife studies are:

o Revision and updating of stock maps

o Fire risk Zonation

o Planning response routes

o Protected area management

o Site suitability analysis for Afforestation

o Soil and water conservation

o Mapping wildlife corridors

o Habitat suitability Mapping

o Prediction Analysis

o Change Detection Analysis

o Mapping Required Resources for Wildlife

o Real time tracking

o Population Mapping

o Developing and updating Web Portal of particular Wildlife

Wide varieties of satellite data sets are available commercially including digital data sets obtained from LANDSAT-5 (Land Observation Satellite), TM (Thematic Mapper), LISS-3 (Linear Imaging and Self Scanning Sensor), IRSID (Indian Remote Sensing Satellite Series 1D), SPOT (Système Probatoire Pour l’Observation de la Terre) and XS (Multi-Spectra). TM sensors helps in availability of multi temporal data with replicated coverage of 16 days for examining temporal changes occurring in the wildlife habitat and communities. Latest series of Indian Remote Sensing Satellites and SPOT series (French satellites) come with the advantages of stereo data acquisition competence with ±26° off-nadir viewing potential of and higher spatial resolutions of 6 (IRS1C/IRSID PAN data) to 10m (SPOT PAN data). The sensors LISS-3 on board IRS1C/D satellites give multi-spectral data obtained in four bands of visible and the near infrared (VNIR) and short wave infrared (SWIR) zone. LISS-3 images contain region of 124/141 km for the VNIR bands (B2, B3, B4) and 133/148 km for the SWIR band (B5) perceived from an altitude of 817 km (IRS1C) to 780 km (IRS1D) with recurring coverage of 25 days. The VNIR bands have spatial resolution of 24m and SWIR has nearly 71m of resolution. The spatial resolution of LISS-3 of the IRS satellite series and XS of the SPOT satellite series are superior to LANDSAT- TM. In order to conserve and manage wildlife system, many countries maintain an inclusive forest account databases of protected areas. These vegetation inventory databases are important for the wildlife studies as they are extensive at comparatively larger spatial scales (example, 1:20,000), reduce the cost of production and they are generally allocated in convenient GIS format (McDermid et al., 2009). Generally different management and conservation strategies cover only particular species and protected areas, which happens to be only 5.19% (7.74 million km2 ) of the total earth’s land surface (WCMC 1992). Many of these biological reserves and protected areas are designed for aesthetic purpose and tourist attraction, rather than wildlife conservation purpose. In these areas, sometimes wildlife is exposed to unsuitable land use practices such as grazing livestock, agriculture, mining etc. Poaching of some species makes them vulnerable and sometimes some deceases and invasive species invade wildlife population (Prins 1996). Therefore thriving wildlife resource require up keeping of optimal conditions within wildlife reserve as well as outside it. The successful management and conservation of wildlife reserve can be carried out well if there is complete availability of information and relevant knowledge about the spatial and temporal distribution of wildlife population. The successful mapping of wildlife distribution can be accomplished using satellite remote sensing. Coral reef mapping of 9 reef classes was done with 37% accuracy with LANDSAT TM, 67% with aerial photography and 81% with an airborn CASI hyperspectral scanner by Mumby and his co workers (1998a). Thermal scanners have been used to measure the population of deer, elk, bison and moose in Canada by comparing ground counts with aerial count, as thermal scanners are known to determine the presence or absence of those species which are not easily observable during certain climatic conditions (Intera Environmental Consultants, 1976). Error can sometimes occur during thermal scanning because of sunlight heated objects and presence of non- target animals. Many of the species like earthworms and termites are known to cause interference because of the roughness caused either by their exoskeleton or by their impact to the soil surface. Certain species which readily modify their environment hamper the applicability of remote sensing satellite as the sensors are incapable to capture the impact of such species on the environment. In such conditions radar can be helpful to map such animals as it is sensitive to micro topography (Weeks et al. 1996; Van Zyl et al. 1991)

 

Application of Geographic Information System (GIS)

in wildlife mapping GIS is computer based system designed for capturing, managing, manipulating, analyzing, modeling and displaying spatially geo-referenced data and for solving complex management problems. GIS helps in easy management of natural and man- made resources at wider scales extending from local to global scale. GIS is capable of overlaying information from different thematic maps depending on user specific logic and derived map outputs. Because of the wide array of GIS application, task defined systems have been created which include engineering specific, land based information, generic thematic, statistical and property lot mapping, environmental planning systems and image processing systems related with remotely sensed data and landsat. In GIS, the attribute data are stored in relational database and geospatial data are saved in map layers, map themes and map coverages. These layers geographically referenced to one another happen to be the foundation of GIS. The gist of map layers refers to spatial as well as attributes data. GIS database sourced map coverages and GIS analysis based results can be displayed and printed in maps, tables and figures and shared various GIS software packages.

The increasing use of geospatial technology that involves the use of remote sensing, GIS and GPS have helped vastly in research pertaining to ecological domain. In the context of wildlife management, GIS is used for mapping, monitoring, analysing and modelling the nesting behaviour and habitats of wildlife populations; wildlife distributions; movement patterns; and to identify potential nesting habitats GIS easily helps in creating maps that cannot be created by using traditional cartographic method. Moreover GIS software packages offering modeling tools can easily create measurements and analyze attribute data. The information in GIS is stored digitally hence it is easily accessible for evaluation and analysis making it easy to be shared among wildlife managers and public. GIS particularly offer potential to enhance the accuracy and precision and long term inexpensive basic actions of wildlife management and conservation such as inventorying, analysis, monitoring, planning and communication. Wildlife management actions are ideally based on intimate information of natural landscape, land use and mass of interior and exterior threats to it. GIS and similar type of computer based technologies such as remote sensing provide means to acquire huge amount of geospatial data and offer powerful analysis tools for understanding linkages between different types of data and help in manipulating these data over larger areas for various development goals for wildlife. Geographic information on the population scattering of wildlife forms a basic source of data in wildlife management. Usually the distribution is derivative from observations on the ground. Radiotelemetry and satellite pathway have been used to evidence the distribution of a diversity of animal species. 

 

 

 

Aerial inspection process based on direct observation increased by use of photography have been used to map the distribution of a range mammals (Norton-Griffiths 1978), birds (Drewien et al. 1996; Butler et al. 1995) and sea turtles and marine mammals (Wamukoya et al. 1995). GIS mapping is progressively being used for wildlife density mapping and dispersion mapping derived from ground observation or aerial survey. Habitat studies based on GIS commonly merge information on vegetation type or different area descriptor, with other land feature reflecting the reserve base factors and other significant factors. A model for Florida scrub jay developed included vegetation type and soil drainage to differentiate primary habitation, secondary habitation and unsuitable areas (Breiniger et al., 1991). A GIs-based model was developed to categorize prospective nesting habitation for cranes in Minnesot.

 

 

 

 

 

 

 

 

 

GIS sometimes faces basic issues such as in case of determining if GIS is suitable for given situation, finding which data layer is essential and adequate to achieve the planned task. These basic problems need to be resolved before taking any action. constrictions and limitations of GIS applicability consist of the simplification of data for mixed areas due to inadequate scale resolution, data incoherence from integrating data from different sources without due regard to reliability of each source, and lack of quality data.