27 Application of Geospatial Technology in Biodiversity Studies

Dr. Puneeta Pandey

 

1. Learning Objectives

 

The purpose of this module is to familiarize the reader with the biodiversity and the application of remote sensing (RS) and geographical information system (GIS) in conservation of biological diversity.

 

2. Introduction

 

Biological diversity or biodiversity has been defined by Convention on Biological Diversity (CBD) as “the variability among living organisms from all sources including, inter alia, terrestrial, marine and other aquatic ecosystems and the ecological complexes of which they are part”. This includes the diversity within species, between species and of ecosystems. Biodiversity can also be defined as the natural variety and variability within and among living organisms and the ecological complexes in which they occur naturally, as well as the ways of interaction among organisms and with that of physical environment (Noss, 1990). It is a multidimensional concept that includes different components (e.g. the genetic, population, species and community levels), and each of them has structural, functional and compositional attributes (e.g. size of population, species composition and distribution of alleles).

 

Due to the complex nature of biodiversity, it becomes very difficult to express and assess the biodiversity. It must be related to not only the variability of life forms, but also with the ecological complexes of which they are recognized as important components. Conservation has become an essential mean of interacting with the rapid degradation and conversion of ecosystem, which lead to serious impacts on biodiversity. As rates of habitat loss and species destruction continue to mount, the need for conserving biodiversity has become increasingly vital during the last decade (Wilson 1988; Kondratyev 1998). In order to design significant conservation strategies, comprehensive information on the species distribution, as well as the information regarding changes in distribution with time, is required.

 

Understanding biodiversity patterns distribution is very crucial so far as conservation strategies are concerned. Conservation of biodiversity is an indispensable issue due to increasing climate change and anthropogenic factors. Various rich biodiversity zones are under serious threat and have been degrading at an alarming rate. Thus it’s very important to preserve these zones and their habitats at local, regional and national levels. In order to implement conservation schemes for the sake of biodiversity conservation, comprehensive information on the distribution of species on a temporal basis are required. Biodiversity conservation has been put to the highest priority through Convention on Biological Diversity (CBD). It is expressed at different levels – genetic, species and landscape level. Although biodiversity is generally considered at the species level, the comprehension at the landscape level has been given priority worldwide as the interaction with the habitat part is very well understood in the latter.

 

Biological diversity is proximately associated with global environmental changes and global issues, such as climate change, land use and land cover (LULC) changes and sustainable developments (Nagendra et al., 2010). During the past several decades, human beings have caused serious impacts on ecosystems more rapidly due to rapid and large scale industrialization, urbanization and other activities. As a result, such activities posed serious threat to the survival of biodiversity and their natural habitat. This loss is further amplified by the lack of awareness, ethics, knowledge of biodiversity, especially of those communities living in close relationship with the ecosystem. The challenges with regard to biological diversity include inventories to determine the extent and location of biodiversity existence and its dynamics. Therefore, it becomes very important to link biodiversity and human interaction with respect to use of natural resources in order to sustain and preserve the biodiversity.

 

 

3 Geospatial Technologies

 

3.1 Remote Sensing (RS) literally means acquiring information about an object, area or phenomenon without coming in direct contact with it (Joseph et al., 2011).

 

According to White (1977), Remote Sensing includes all methods of obtaining pictures or other forms of electromagnetic records of Earth’s surface from a distance, and the treatment and processing of the picture data.

 

According to the United Nations (95th Plenary meeting, 3rd December, 1986), remote sensing (RS) means sensing of earth’s surface from space by making use of the properties of electromagnetic wave emitted, reflected or diffracted by the sensed objects, for the purpose of land use, natural resource management and the protection of the environment.

 

3.2 Geographical Information System (GIS) is a computer based information system which integrates a variety of qualities and characteristics to geographical location and helps in planning and decision making. In GIS system the map information supplemented with additional information, can be displayed and referenced using computers. It can provide spatial information with appropriate conventional statistics.

 

Burrough (1986) defined GIS as a set of tools for collecting, storing, retrieving at will, transforming and displaying spatial data from the real world for a particular set of purpose.

 

 

4 Role of remote sensing (RS) and geographical information system (GIS) in Biodiversity

 

It is very difficult to acquire information regarding species distribution with respect to location and time simply on the basis of field assessment and monitoring (Heywood, 1995). In recent times, remote sensing and biodiversity communities have established cordial relationship to share their ideas, problems and their solutions on a single platform. Such relationships have been appreciably strengthened with the advancements of satellite remote sensing technology in past few decades. Consequently, the advancement has boosted the interdisciplinary research at local and regional scale with high temporal resolution to assess the changes in species distribution, loss of habitats, etc. Assessing and predicting ecosystem responses to global environmental climate change and subsequent consequences on humans are prime targets for scientific community. The management and conservation of wildlife and Biodiversity require a reliable and relevant data on the species distribution, abundance, habitats and threats as well. Different organizations and countries are being focused into the so-called information ‘super highway’. Reviewing the requirement for biodiversity information has been noticed and addressed by protected areas managers, decision makers, scientists, researchers and many others. The meeting of protected area managers at the Fourth World Parks Congress understood that individuals and organizations engaged in efforts of protected areas need better information for making decisions (IUCN, 1993). Dealing with biodiversity information, database need to be geographically based, and it must be able to predict where new populations of endangered species with a limited known range might be expected, specifying potential hot spots.

 

Therefore, Remote Sensing (RS) and Geographic information system (GIS) a modern day geo-spatial technology, helps in data (information) collection for biodiversity conservation management and planning.

 

The conventional methods for data collection on biodiversity have been found to be costly and time consuming. Comparatively, RS and GIS are the most efficient and cost effective ways for collection of information and subsequent management of our natural resources. It offers a systematic, synoptic view at regular time intervals, and has been considered as useful for this purpose (Debinski and Humphrey 1997; Innes and Koch 1998). Coupled with Geographical Information Systems (GIS), remotely sensed data can generate information about soil, temperature, rainfall, topography, landscape history and other climatic conditions, besides current habitat and soil coverage—factors on which species distribution depends (Noss, 1996). Relationships between remotely sensed/GIS data and species distribution patterns, can be used to predict the distribution of single or a set of species over an area (Debinski and Humphrey 1997). Between remote sensing science and conservation biology, the potential for synergies has been highlighted and acknowledged in the past by practitioners, researchers and data providers to better understand how remote sensing based studies can be utilized in monitoring and conservation of biodiversity (Duro et al., 2007; Gillespie et al., 2008).

 

GIS is a tool that can be used for monitoring biodiversity where it accommodates large varieties of spatial and attribute data. Embedded in a GIS, the information is used to target surveys and monitoring schemes. Data on species and habitat distribution from different dates allow monitoring of the location and the extent of change. Over the last few years, there has been a revolution in the availability of information and in the development and application of tools for managing information (Harrison, 1995). It can help in changing the very approach of wildlife management based more on current information and location oriented.

 

Turner et al. proposed two types of remote sensing (RS) approaches, viz. direct and indirect remote sensing approaches (Rapport et al., 1998). The former refers to the direct observation of individual organisms, group of species, or ecological communities from satellite sensors, such as high spatial resolution and hyper-spectral sensors (Directive, 1992). Indirect approaches are based on certain environmental parameters derived from remotely sensed data as proxies. For instance, habitat parameters, such as land cover, species composition, etc., regarded as a substitute for exact estimation of ranges and patterns of species and their richness (Gibbons et al., 2008).

 

Remote sensing provides consistent data of earth at various scales at all levels ranging from local to global. In addition to this, remote sensing does not require labour and it also save time when compared to ground-based observations. It covers a wide-scale terrestrial, atmospheric and oceanographic data collection as well as the monitoring of environmental changes at global-scale. Remote sensing plays a major role in monitoring changes in biodiversity and terrestrial, marine and freshwater ecosystems where it provides repetitive images on regular periodic intervals that make it predominantly appropriate for monitoring. It facilitates a vast amount of information for understanding and monitoring biodiversity and its dynamics. The RS monitors the changes in terrestrial ecosystems include changes in ecosystem extent, forest extent; health (e.g., by monitoring greenness, though estimating health can be a challenge). The RS provides a wide range of information that helps in estimating species distributions and in integration with models also estimates the overall biodiversity.

 

Wildlife and Biodiversity Management has stressed the requirement of having updated spatial information for (a) decision-making, and (b) implementation of plans. The updated spatial data information provided by RS need to be integrated with the conventional database. According to the IUCN (1996), “The main purpose of wildlife conservation is to maintain maximum plant and animal diversity through genetic traits, ecological functions and bio-geo-chemical cycles, as well as uphold aesthetic values.” Remote Sensing techniques play a vital role in wildlife and biodiversity management because of its exclusive characteristics of synoptic view, repetitive coverage, and uniformity. In forest management, the RS has a major role to play a revision and updating of working plan, wildlife management, forest fire control, soil and water conservation, land utilization studies, grazing management, mapping social forestry sites and for other important species of general afforestation programmes.

 

 

4.1 Forest Management

 

4.1.1 Forestry Conversion Studies: With the population explosion and urbanization, the forest lands are being converted at a rapid rate which causes a serious damage to the forest biodiversity. The forest cover distribution and its change is a crucial issue so far as forest management is concerned. Also to develop the methods for estimating and evaluating the extent of forest resource and its changes to support the policy makers to take a decision that may ensure and maintain the rich biodiversity of forest resource. Monitoring of the changes in the forest cover has been quite important task because of its significant impact on climatic change. The RS technique and GIS coupled with ground survey can be reliable in providing information on spatial distribution of forests and its changes. With the rapid destruction of forests and encroachment the use of multi-temporal satellite data using data analysis procedure provide a way to generate maps based on spatial changes by image differencing methods and logical operations. Such maps would help in assessing the extent of conversion of forest land based on multi-temporal satellite data.

 

4.1.2 Forest Fire Damage: Fire is one of the natural or man-made disasters causing damage to the forest biodiversity and the ecosystem worldwide, which ultimately have adverse effects on soil, forests and humans. During the process of forest burning, the soil nutrients are reduced and the soil is left bare making it more prone to soil and water erosion. Therefore, it is very essential to have precise and timely information of the total area burned, topography, type of forest etc. It is very difficult to manage fires effectively without any information related to the distribution and dynamics of forest fires. RS and GIS can play a crucial role in detecting burnt forest and developing a spatial model to forecast and assess the forest fire and subsequent impacts on forest biodiversity. The use of multi-mission IRS data has been implemented to identify forest ground fire damaged areas with the combined use of IRS 1A and IRS 1B.

 

4.2 Wildlife Management

 

Wildlife distribution and protection are the prime focus area of wildlife management. So far as the management is concerned the geospatial technology is very effective in analyzing, managing and visualizing wildlife data. GIS enables analysis and mapping of distribution of wildlife, their movements and pattern of habitat use, which can provide precious information for the development of wildlife management strategies (Gibson et al., 2004). In recent times, the rapid technological improvements in GIS, as well as in remote sensing techniques have significantly increased their accessibility and efficacy in ecological management and research (Guisan and Zimmermann 2000).

 

4.3 Management of Grasslands: Grasslands are the world’s most wide-ranging terrestrial ecosystem, and are considered as major feed sources for livestock. Global Positioning System (GPS) and other ground-based sensor technologies have been recognized as valuable tools for grassland and herd management. With the availability of space-borne remote sensing data, it becomes possible to assess and monitor grassland ecosystems, based on the data related to their status about biomass, productivity level, quality, phenological stage, species composition and change, their biophysical parameters and management characteristics (i.e. degradation, grazing intensity).

 

4.4 Agricultural biodiversity: Agricultural biodiversity is a broad term that consists of all components of biodiversity related to food and agriculture, and all components of biodiversity that constitute the agricultural ecosystems, which are essential to sustain crucial functions of the agro-ecosystem, its structure and processes. The term Agro-bioinformatics is application of Informatics for  management, presentation, discovery, exploration and analysis of Agriculture and related issues. Agro-bioinformatics is a type of electronic documentation of biographical, taxonomical and ecological aspects related to agriculture. It may consider a multidimensional database in which information stored in digital form, using RS and GIS. Furthermore spatial analysis significantly helps to understand agriculture biodiversity constraints.

 

The combination of multi-spectral and multi-temporal remote sensing data along with local knowledge and simulation models has been effectively verified as a valuable approach to identify and monitor a wide range of agriculturally related characteristics (Oliver et al. 2010). The Spatial variability in crops creates a need for precision agriculture. The identification of such spatial variability is possible through the use of geospatial technology (remotely sensed images of the crops and GIS modeling approach). The spatial variability in crop yield can be assessed through RS and other geospatial techniques (Taylor et al., 1997). In recent times, aerial images have been broadly used for crop yield prediction before harvest (Senay et al., 1998). Vegetation analysis and change detection in vegetation patterns are significant for management and monitoring of natural resource, such as crop vigor analysis (Thiam and Eastman 1999). Spectral bands such as visible red, green, and blue band and near-infrared (NIR) regions of the electromagnetic spectrum have been used effectively to monitor crop health, crop cover, soil moisture, crop yield and nitrogen stress (Magri et al., 2005). There are different spectral indices which are used to estimate crop distribution, crop yield, crop cover etc. These indices include: (a) normalized difference vegetation index (NDVI), based on red and near-infrared (NIR) spectral bands (b) green vegetation index (GVI), based on green and NIR (c) soil adjusted vegetation index (SAVI), based on red and NIR (d) perpendicular vegetation index (PVI), based on red and NIR spectral bands.

 

5. Conclusions

 

At the end of the module, the reader would have gained an insight into the role of remote sensing and GIS in the studies pertaining to biodiversity. Besides, the reader would also have gained an insight into the applications of remote sensing and GIS in management of forest, wildlife and grasslands, besides assessing agricultural diversity.

 

6. References

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