8.0 LAND USE DYNAMICS in BNP

Land use Land cover (LULC) of Bannerghatta National park (BNP) is analysed using temporal remote sensing data to understand the status and land use changes. The land cover analysis reveals loss of vegetation cover from 85.78 to 66.37 % (1973-2015) and non- vegetative areas constitute 33.63% (2015). The land use analysis has been carried out in BNP  and in buffer region (5km). Land use changes within BNP region are minimal as compared to buffer region. The moist deciduous forest covered 50.4% (1973)and now 28.5 % (2015) due to anthropogenic pressure in BNP and its environs. Forests in Ragihalli, Manjunatha, Yelavantha, Bettahalli regions with good protection measures show minimal disturbance. However, implications of unplanned urbanization are evident in the buffer regions. Land use analyses in the buffer region (5 km) analysis highlights of urban sprawl in peri-urban regions has fragmented, dispersed urban patches in periphery accounting to 5462 ha(built-up area). The region has lost moist deciduous cover from 26.1 to 13.8 % with an increase in horticulture 8.5 to 11%(1973-2015). The region had lostthe large tracts of deciduous cover in Kanakapura taluk, Anekal taluk regions due to intensified horticulture activities and deforestation. Urbanization in the vicinity of ecologically sensitive national park in the form of housing layouts, etc. highlights the extent of unplanned senseless urbanization and also mirrors the extent of fragmented governance. This has further impacted agricultural tract in northern portion. Now, new agriculture lands are being created in common lands (gomala, revenue lands, etc.) of Kanakapura taluk, Anekal taluk. The mining of resources is another major threat to BNP  and estimate indicates that about 1538.7 ha is occupied by mining activities.Identification of localities for housing layouts, industrial complexes and commercial education institutions in the close proximity of NP further highlights lack of vision among regional planners and lack of appropriate acumen in the current breed of decision makers.  This analysis suggests that there has is a need to identify and restrict activities in buffer regions to protect ecologically sensitive national park. BNP is vital for Bangaloreans as it helps in moderating climate, sequester carbon, oxygen production and wide array of flora of medicinal importance. The conservation of this region requiresinventorying, mapping and monitoring of biological resources.
Ecologically Sensitive Regions (ESRs’) are the ‘ecological units’ that may be easily affected or harmed. It is a bio-climatic unit (as demarcated by entire landscapes) wherein human impacts would cause irreversible changes in the structure of biological communities (as evident in number/ composition of species and their relative abundances) and their natural habitats’ (Section 3 of the Environment (Protection) Act 1986 (EPA)). This approach of conservation or ecological planning considers spatially both ecological and social dimensions of environmental variables.The eco-sensitive regions (ESR) in the vicinity of BNP (buffer regions) are identified based on forest cover status, faunal distribution, human-elephant conflict regions, elephant migratory paths, etc. This would also help in minimizing human animal conflicts, conservation of biodiversity, etc.Regions were prioritized asESR 1 to ESR 4. Among these, ESR-1 and ESR-2 should be considered as no-go area without any major anthropogenic activities.ESR-1 represents zone of highest conservation and no further degradation be allowed. ESR-2 has potentiality to become as ESR-1 provided with strict regulations and improvement of forests and its environs by more protection. These regions have to be conserved to protect habitat of wild fauna, which helps in minimizing human animal conflicts and instances of wild fauna straying to the city. ESR-3 is a moderate eco-sensitive region, where controlled developmental activities are allowed and ESR-4 can be utilised for sustainable development. The region has 69 villages under ESR-1, 78 villages under ESR-2, 79 villages under ESR-3 and 176 villages under ESR-4.

INTRODUCTION
Land use Land cover (LULC) information provides insight to bio-geophysical processes and spatio-temporal changes due to anthropogenic pressures. The land cover is referred as biophysical attributes of the earth’s surface, while land use refers to the use of land for human purpose or usage of the biophysical attributes (Lambin et al., 2001; Ramachandra et al.; 2012a; 2012b). Land cover categories include forest, mountains, desert, water whereas, land use refers to the human induced changes in the land cover for agricultural, industrial, residential, recreational purposes. Forests support livelihood as grazing land for animals, etc. Land cover changes by anthropogenic activities such as illegal logging, mining and continued unsustainable exploitation of resources, etc. have been posing serious threats to the survival of ecosystems. The land management policies, population, agricultural production and urban expansion are considered as main drivers of LULC change. Deforestation, is the widespread phenomenon of land cover change resulted in the loss of more than a third of all forest cover worldwide over the past half century (Sexton et al., 2013; Ramachandra et al., 2014). Deforestation results with the degradation of forests, or the long term reduction of tree canopy cover below the 10% and thereby lower country’s economy, its capacity to supply products and services(FAO, 2009).Fragmented forests are likely to suffer from being smaller, more isolated with greater edges beyond the direct impacts of forest loss and expanding anthropogenic activities (Rands et al., 2010; Ramachandra et al., 2013a; 2013b).LULC changes alter the homogeneous landscape into heterogeneous mosaic of patches. This leads to the division of habitat into smaller and more isolated patches. The fragmentation results in the division of continuous forest area which alters the structure of the landscape affecting ecosystem functional abilities, evident from the decline of biodiversity, hydrology, etc. (Ramachandra et al, 2013a, 2013c). Uncontrolled LULC changes in a forested landscape will result in destruction and degradation of natural ecosystems, natural resources availability (Vinay et al., 2013), biodiversity (Bharath et al., 2014; Ramachandra et al., 2013b), induces change in local climate (Chase et al., 1999; Bharath et al., 2013; Ramachandra et al., 2015a: 2015 b) as well as to global climate (Yang et al., 1999). Unplanned urbanization leads to urban sprawl in the outer peripheral region gradually affecting the local ecology and environment (Ramachandra et al., 2012a; 2012b; 2012c; 2014).This type of transformation brings changes in the agricultural practices, policies, settlement structures, livelihood and industrial settings. The impact of deforestation in forest landscapes is evident from impaired hydrological processes, biochemical cycles soil erosion and water yield.LULC changes are prime factors for soil degradation (Ross et al., 2006) and reduced ecosystem services by affecting the ability of biological systems to support human needs.
LULC mapping and monitoring provide vital information of landscape and environmental status, distributions, and spatial patterns.LULC information also reflectsthe overall perspective of the landscape characteristics,changing economic and socialconditions in a region. The advancement of technologies in vegetation mapping has been providinga precise evaluation of the spatio-temporal patterns of forestdynamics andenvironmental consequences.For sustainable utilization of the forested ecosystems, it is essential to know thelimitations of various land uses, natural characteristics, quality, productivity, suitability.There is a growing awareness of LCLC change impacts on hydrologic, ecologic, climatic, and biologicprocesses over space and time. LULC change information at temporal scale helps the decision makers, planers to enumeratethe influence of human action on land surface conditions,ecosystem processesrequired for effective management of natural resources. Data acquired through space borne sensors (Remote sensing data)help in monitoring LULC change because of the repetitive coverage at short intervals. Remote Sensing (RS) with improvements in spectral, spatial andtemporal resolutions with Geographical Information System (GIS)techniques have been useful in monitoring land use changes of even inaccessible areas within a short span oftime.RS technique has proven to be a cost effective tool, which provides synoptic coverage of areas of interest and facilitatesto quantify LULCchange,and consequent impacts due to industrialisation, urbanisation and other developmental activities. These specifications of RS can therefore greatly contribute to local, regional as well as global mapping and monitoring of change in LULC.Objective of the current study is to assess the current status and trendsin spatio-temporal patterns of forest cover in and around BNP region during 1989 to 2015.

METHOD
LULC changes in BNP region has been analysed with the help of temporal remote sensing data (RS), ancillary data (collateral data compiled from government agencies) and field investigations. Multi resolution RS data acquired through the sensors of U.S. Geological SurveyEarth Observation Satellites (EOS), Indian remote sensing system (IRS) at temporal scale has been used for spatio-temporal analyses. Figure 1, outlines the method followed in the analysis. RS data used in the study are (i) Landsat MSS (1973), TM (1989, 1999), Landsat ETM+ (2009), downloaded from public domain (http://landsat.org), (ii) IRS p6L4X (2015) (http://nrsc.gov.in)) and online Google Earth portal (http://earth.google.com). The ancillary data is used to assist the interpretation of different land use types from remote sensing data. Topographic maps provided ground control points to rectify remotely sensed data and scanned paper maps (topographic maps). Survey of India (SOI) topo sheets (1:50000 and 1:250000 scales) and vegetation map of South India developed by French Institute (1986) of scale 1:250000 was digitized to identify various forest cover types and temporal analyses to find out the changes in vegetation. Pre-calibrated GPS (Global Positioning System - Garmin GPS unit) for field measurements. Ground control points are used to geometrically correct remote sensing data and verify the classified land use information.
Land cover analysis is done using NDVI (Normalized Difference Vegetation Index), given in equation 1. NDVI is the most commonly used vegetation index to distinguish healthy vegetation from others or from non-vegetated areas using red and near infrared reflectance values of RS data. NDVI provides information about the spatial and temporal distribution of vegetation communities, quality, biomass, and the extent of land degradation in various ecosystems (Reed et al., 1994).NDVI also known as a greenness index, value ranges between -1 to +1. NDVI is sensitive to the presence, density and condition of vegetation and is correlated with absorbed photo synthetically active radiation (PAR) and vegetation primary production.Based on grey scale corresponds to a pixel digital number dense green vegetation and non-vegetation features were separated.

                  … (1)

Land use analyses involved (i) generation of False Color Composite (FCC) of remote sensing data (bands–green, red and NIR). This composite image helps in locating heterogeneous patches in the landscape, (ii) selection of training polygons by covering 15% of the study area (polygons are uniformly distributed over the entire study area) (iii) loading these training polygons co-ordinates into pre-calibrated GPS, (vi) collection of the corresponding attribute data (land use types) for these polygons from the field.  GPS helped in locating respective training polygons in the field, (iv) supplementing this information with Google Earth and (v) 60% of the training data has been used for classification, while the balance is used for accuracy assessment (Ramachandra et al., 2012b; 2012c). The land use analysis was done using supervised classification technique based on Gaussian maximum likelihood (GML) algorithm with training data (collected from field using GPS). GML is a widely used statistical classification method assigns a given pixel to a specific class based on the conditional probability. The likelihood for a given pixel with spectral value to be assigned to a class is determined using Bayes’s theorem and decision rule calculated by the natural logarithm or “discriminant function”. Each pixel is assigned to the class that has the highest probability (i.e., the maximum likelihood). If the highest probability is smaller than the specified threshold value, the pixel remains unclassified.GRASS GIS (Geographical Resources Analysis Support System, http://ces.iisc.ernet.in/grass), a free and open source software with the robust support for processing both vector and raster data has been used for analyzing RS data by using available multi-temporal “ground truth” information.



Figure 1: Method followed for LULC analysis
 

RESULTS AND DISCUSSION
The LULC analysis is carried out by using temporal remote sensing data. Temporal variations in NDVI values derived from satellite data helped to quantify spectrally distinct vegetation, non-vegetation features in land cover. The vegetation indices based analysis reveals the loss of vegetation cover from 85.78 to 66.37 % by 2015in BNP with 5km buffer (Table 1, Figure 2). The study area has witnessed large scale land cover transformation due to anthropogenic developmental activities from 1973 to 2015. The land cover analysis has shown considerable changes in vegetation cover and increase in non-vegetation features covering an area of 39559.26 ha by 2015 as compared with 1973 (16725.85 ha). The fast economic and social transformation in Bangalore metropolitan region has large scale impact on BNP and its environs. In the last few decades, the accelerated process of industrialisation and population growth had resulted greater impact on vegetation cover.
The land use analysis has carried out from 1973 to 2015  for (i) BNP region and (ii)  BNP region with 5km buffer. Figures3 and table 2  details land use changes in BNP region during 1973 to 2015.

Year
1973
1989
1999
2009
2015
Category
Ha
%
Ha
%
Ha
%
Ha
%
Ha
%
Vegetation
107087.77
87.98
104039.5
85.5
99992.21
82.2
94693.2
77.8
89419.0
73.46
Non-vegetation
14633.13
12.02
17681.5
14.5
21728.69
17.8
27027.6
22.2
32301.9
26.54
Total area
121720.9
Table 1: Land cover changes during 1973-2015.

Year
1973
1989
1999
2009
2015
Category
Ha
%
Ha
%
Ha
%
Ha
%
Ha
%
Dry deciduous forest
8966.2
34.4
9156.7
35.1
10442.5
40.1
10506.9
40.3
10600.5
40.7
Moist deciduous forest
13130.5
50.4
12253.4
47.0
8940.2
34.3
7879.9
30.2
7610.6
29.2
Grass/Scrub forest
1003.6
3.9
1113.1
4.3
1603.9
6.2
1867.6
7.2
2001.6
7.7
Water
81.0
0.3
109.5
0.4
120.7
0.5
126.0
0.5
195.4
0.7
Horticulture
239.3
0.9
565.0
2.2
569.1
2.2
530.5
2.0
483.2
1.9
Agriculture
1985.4
7.6
1990.9
7.6
3021.8
11.6
3536.8
13.6
3532.5
13.6
Urban
26.4
0.1
123.7
0.5
291.5
1.1
302.2
1.2
420.0
1.6
Barren land
609.7
2.3
681.3
2.6
775.7
3.0
1043.8
4.0
907.3
3.5
Forest plantations
9.3
0.0
57.6
0.2
74.8
0.3
163.1
0.6
195.5
0.8
Mining area
0.5
0.0
0.5
0.0
211.6
0.8
95.0
0.4
105.4
0.4
Total area
26051.87
Table 2: Land use changes in BNP region from 1973-2015.

BNP region had 50.4% of moist deciduous forest cover in 1973 and now left with 30.3 % by 2015 due to anthropogenic pressure. Though there is strict vigilance in forests of BNP grazing is the most disturbing factor of vegetation change and regeneration. The moist deciduous vegetation has transformed to dry deciduous forest in pockets such as Anekal, Harohalli, Marlawadi due to anthropogenic pressure. The dry deciduous forest covers 39.4 % of BNP region and scrub vegetation covers 7.7 %. The BNP region has increase in agriculture area from 7.62 to 13.6 % by 2015. The rural settlement, peri urban settlement and industrial areas are major driving forces acting in land use change of BNP. Disrupting forest cover of BNP can be witnessed in many villagesdue to intense deforestation, agriculture and population pressure. The new water bodies have been created in BNP for wild life covers an area of 195.36 ha. The forest cover with minimal changes is observed in Ragihalli, Manjunatha, Yelavantha, Bettahalli regions due to higher protection. The strict protection measures resulted in good regeneration of forests in Bannerghatta Wildlife Division (Ragihalli state forest) Harohalli, Kodihalli ranges, which is noticed during the field work.  The land use changes from 1989 to 2009 in southern part of BNP(which is not a part of BNP till 2011) were most prominent due to less protection, intense grazing and agriculture activities. The northern part of the park boundarysets a suburban landscape that is mainly an expansion of Bangalore city area (under BDA) with increasing built-up area, a dense roadnetwork and residential plots.
The BNP with 5km buffer region land use analysis reflects the impact of urban expansion and status of forest in the periphery of BNP. The buffer region is very important for maintaining wild life migration, refugee and grazing grounds for livestock. The western and eastern part of the BNP andbuffer region are composed of agricultural village communities. There is a predominance of sugar cane, ragi, eucalyptus in the eastern part; paddy, coconut and mango plantations in the western part. Figure 4 and table 3 reflects change in forest cover of BNP buffer region from 1973-2015. The large tracts of deciduous cover in Kanakapura taluk, Anekal taluk region are lost due to intensification of horticulture area in recent years and consequent land use changes. The region has lost moist deciduous cover from 26.1 to 13.8 % (1973-2015) and increase in horticulture 8.5 to 11 %. Large scale land use changes in the region are due to stone quarries, mining of sand and medium scale industries in the periphery of BNP, which hasalso led to increase in built-up area from 0.4 to 4.5 %. The analyses also highlights the implications of urban sprawl as peri-urban growth with fragmented new urban patches in periphery. Bangalore’s metropolitan growth has intrinsic relation with vegetation loss in peri urban landscape such as BNP buffer region (Bharath et al., 2012). The increase in population of Kanakapura taluk and Maralwadi town region resulted in more transition of forests to other land use. The encroachment in Kanakpura forests, revenue lands, gomala region has resulted in deforestation in buffer region, evident from Figures 5 and 6 by 2015. The changes in the form of suburban residential development, encroachment and illegal logging by communities,grazing animal population and illegal stone quarries, mining triggered a declining trend in forest cover. This change has aggravated human-animal conflict and many wild animals were killed in road accidents. When compared with 1999, therewas further loss in forest area (by 2015) with an increase in built-up area up to 4.5 % due to many residential layouts, educational institutions, industries. This has further impacted agricultural tract in northern portion and few new agriculture lands were created in gomala, revenue lands of Kanakapura taluk and Anekal taluk. The region has 9254.21 ha of scrub forests and which can be reforested for better protection of ecosystem in BNP.About 1538.7 ha land released for mining of resources is another major threat in BNP and its environs.

Year
1973
1989
1999
2009
2015
Category
Ha
%
Ha
%
Ha
%
Ha
%
Ha
%
Dry deciduous forest
32415.6
26.6
31609.3
26.0
26433.6
21.7
24042.3
19.8
22729.9
18.7
Moist deciduous forest
31725.9
26.1
29694.3
24.4
25941.5
21.3
16916.1
13.9
16822.2
13.8
Grass/Scrub forest
4876.8
4.0
4500.4
3.7
4914.4
4.0
8967.2
7.4
9254.2
7.6
Water
377.8
0.3
922.5
0.8
1170.8
1.0
1251.6
1.0
1834.0
1.5
Horticulture
10361.3
8.5
11768.4
9.7
12707.1
10.4
13470.5
11.1
13363.2
11.0
Agriculture
36027.9
29.6
37222.3
30.6
40053.5
32.9
44975.1
36.9
45613.8
37.5
Urban
490.6
0.4
581.6
0.5
1934.9
1.6
3216.0
2.6
5462.1
4.5
Barren land
4461.8
3.7
4251.7
3.5
6833.9
5.6
6114.5
5.0
3536.6
2.9
Forest plantations
921.4
0.8
1060.5
0.9
1011.0
0.8
1533.1
1.3
1566.3
1.3
Mining area
61.8
0.1
109.9
0.1
720.3
0.6
1234.5
1.0
1538.7
1.3
Total area
121720.9
Table 3: Land use changes in BNP with 5km buffer during 1973-2015.


Figure 2: Land cover during 1973 to 2015 in BNP with 5km buffer.



Figure 3: Land use in BNP during 1973-2009.




Figure 4: Land use in BNP with 5km buffer during 1973-2009.



Figure5: Land use in BNP (2015).





Figure 6: Land use in BNP with 5km buffer (2015).

9. Eco-Sensitive Regions / Zones of BNP

Ecologically Sensitive Regions /Zones (ESRs’/ Zones) are the ‘ecological units’ that are susceptible to even small changes in the structure / integrity of the landscape (Ramachandra et al., 2013a; 2013b). It is a bio-climatic unit (as demarcated by entire landscapes) wherein human impacts have locally caused irreversible changes in the structure of biological communities (as evident in number/ composition of species and their relative abundances) and their natural habitats’ (Section 3 of the Environment (Protection) Act 1986 (EPA)). This approach of conservation or ecological planning considers spatially both ecological and social dimensions of environmental variables. Ecological sensitive regions with exceptional biotic and abiotic elements are being degraded or lost as a result of unplanned developmental activities. Landscapes sustainability as a basic goal for development requires comprehensive picture of the biophysical and socio-cultural information of a region and this approach provides an opportunities and constraints for decision-making and sustainable management of natural resources. Conservation by prioritisation of sensitive regions has been widely used to improve ecosystem by conservations practices(Ramachandra et al., 2013a; 2013b; 2013c). This study prioritizes the regions in the BNP buffer regions of 5 km, considering attributes (biological, Geo climatic, Social, etc.) as ESR1(Regions of highest sensitivity or Ecologically Sensitive Region 1), ESR2 (Regions of higher sensitivity), ESR3 (Regions of high sensitivity) and ESR4 (Regions of moderate sensitivity).
Unplanned rapid urbanisation in Bangalore during the last two decades has transformed the Bangalore landscape into concrete jungle (77% landscape covered with paved surfaces as on 2016), evident from 1005% urban growth with the loss of 88% vegetation cover and 79% water bodies during the last four decades (Ramachandra et al., 2012b; 2012c; 2014; 2015b). This has contributed to dispersed growth / urban sprawl in peri-urban regions of the city, apparent from senseless approvals for formation of housing layouts (in the immediate vicinity of BNP). This mirrors the extent of poor planning and lack of understanding in urban planning apart from complete disregard to human miseries due to frequent human-animal conflicts (Ramachandra et al., 2015a). Mushrooming housing layouts (authorized and unauthorized), information technologycorridors, express ways,peripheral ring road, satellite townships, etc. have made inroads into the green belt of BNP threatening the existence of BNP. The residential and commercial regions such as Jayanagar, Dorasani Palya, J.P. Nagar, Kalena Agrahara, Hulimavu, Gottigere are in close proximity within 10 km radius of park boundary. The BNP boundary has complex shape pattern with narrow width and surrounded by human settlements, agriculture fields restricting animal moment. BNP is one of the oldest habitat for many endemic faunal species such as elephants. BNP forms part of “Mysore Elephant Reserve”  constitute an important corridor for adjoining habitats like Cauvery wildlife sanctuary, Tali reserve forest, Kanakapura state forest, etc. The region is repository of exceptional plant and animal diversity. However, due to irresponsible regional planning involving the large scale land use changes in the immediate vicinity,  the region is prone to large-scale human-animal conflicts. The wildlife movement is hindered by traffic, people, mining and industries in and around BNP. This necessitates inventorying, mapping and sustainable management of eco-sensitive regions/ zones. Enrichment of the region with native vegetation and creation of water ponds  would provide better protection of wildlife and threatened flora.
The conservation of eco-sensitive regions would be an effective, ecological and economical method that is widely used to conserve wild taxa.The effective conservation and management of eco-sensitive regions will result in reduction of crop damage instances, human-animal conflict, illegal poaching, etc. Enrichment of region with native vegetation also act as carbon sink, while  improving regional hydrology and environment. The Union Ministry of Environment and Forests and Climate Change (MoEFCC) had set up Pronab Sen Committee in the year 2000 to identify parameters for designating Ecologically Sensitive Areas in the country to counter the rapid deterioration of the environment in India (MoEF, 2000). The committee has defined ecological sensitivity or fragility as permanent and irreparable loss of extant life forms from the world.
The inventorying and mapping of eco-sensitive zones / regions was carried out by examiningland cover status, wildlife habitats, elephant migratory path, elephant infested areas (crop damage)and native forest cover.Figures5 and 6 depict forest cover in 2015. Elephant infested or villages consistently affected due to elephant raids in and around BNP have been considered for identifying eco-sensitive zones, as elephant constitutes an indicator species of the park. The eco-sensitive regions have marked by zone of influence of elephant infested villages in and around BNP (details of these villages are included in Annexure 1).Forest regeneration initiatives through native vegetation and provision of water ponds would help in minimizing the instances of wild animals straying to the nearby villages. The eco-sensitive regionsalso aids as a national heritage of biological importance for the benefit of education. Eco-sensitive regions are treasuring more significant natural elements that could be degraded or lost as a result of uncontrolled or incompatible development. These regions are identified as being necessary to maintain the essential character and integrity of the existing environment, based on the quality, the scarcity and their role in the ecosystem and culture.The forest cover map has been created to mark the rich biodiversity regions (Figure 7). The BNP region hasvillages with major forest covers greater than 60 % and within buffer there are villages having forest cover > 45% in state forest areas, gomala lands, revenue lands. Human population is another important indicator in zonation, because land degradation results due to population pressure. Figure 8 shows villages near to Bangalore and highways have population density (PD) greater than 600 persons per sq.km. The villages in core area of BNP have PD less than 150 persons per sq.km and periphery of park has PD greater than 300. The faunal distribution in and around BNP maps were generated to categorize effective region for conservation. The faunal details were collected from earlier literature, field analysis, local stakeholders, interviewing forest watchers of all ranges of BNP. The region has rich faunal species such as elephant (Elephas maximus), Indian Sloth Bear (Melursus Ursinus), leopard (Panthera pardus fusca), tiger (Panthera tigris), spotted deer / chital (Axis axis), bison (Bos gaurus) etc. The villages in and around these regions are facing higher crop raid by wild fauna. Figures 9 and10 depict of elephant corridor and illustrates that BNP is located vitally at a terminal point on the northern side of Mysore Elephant Reserve. Figure 11 lists the villages wherein crops affected by elephants in BNP and Figure 12 lists the villages in BNP with 5kms buffer. Figures 13 to 17 shows various faunal species distribution, these maps imply the need for conservation, effective management to reduce human-animal conflict.
The eco-sensitive regions have been mapped based on forest cover, faunal details, elephant migratory path and elephant infested villages (human animal conflict areas). Each criterion is described by an indicator mapped to a value normalised between 10 to 1. The value 10 corresponds to very higher priority for conservation whereas 1 is converse to above. The value 7, 5 and 3 corresponds to high, moderate, low levels of conservation. The villages having forest cover greater than 50% is assigned weight as 10, less than 10% assigned as 1and 7, 5 and 3 corresponds intermediate ranges. The endangered species such as tiger, elephant distributed areas assigned weight as 10 and least concern has assigned as 3, other as 0. The villages with greater population density are assigned 0, intermediate values (3, 5, 7) for moderate and least PD were assigned as 10. The weightage metric score associated with each theme is generated. Interdisciplinary frameworks that incorporating individual as well as nonlinear feedback of various driving forces are critical to research that explicitly incorporates humans in ecosystems (Palmer et al. 2004).Developing a weightage metric score analysis requires combining knowledge from a wide array of disciplines (Termorshuizen & Opdam, 2009; Tooth et al., 2011), planning should acknowledge and actively integrate present and future needs for landscape. The approach has chosen a framework proposed by Beinat, 1997 for weightaging eco-sensitive regions because it provides an objective and transparent system for combining multiple data sets together to infer the significances. The weightage is defined as,


Where n is the number of data sets, Vi is the value associated with criterion i, and Wi is the weight associated to that criterion. The table expresses the theme wise decision variable considered and their significance. Each criterion is described by an indicator mapped to a value normalised between 10 to 1. The value 10 corresponds to very higher priority for conservation whereas 1 is converse to above. Based on the metric score the prioritisation map is prepared as ecologically sensitive regions (ESR) of 1, 2, 3 and 4 by combining all weights associated with different theme. Ecologically sensitive regions (ESRs) as proposed here intended at comprehensively attaining the biodiversity richness, more public participation in conservation and enrichment of their lively hood options.
Figure 18 shows69 villages(Table 5) represent ESR 1, 78villages(Table 6) represent ESR 2, 79villages (Table 7)represent ESR 3 and the rest 176villages(Table 8) represents ESR 4. The ESR 1 represents zone of highest conservation, no further degradation allowed. The ESR-1 reflects all villages within 1km of BNPwhich are to be treated as high sensitive region of conservation. ESR 2 represents a zone of transition for highest conservation and moderate conservation regions. ESR 3 represents moderate conservation region and only regulated development is allowed in these areas. ESR 4 represents least diversity areas and the developments are allowed as per the requirement by strict vigilance from regulatory authorities.
Table 9 lists the number of villages in the respective eco-sensitive zones.  All these regions are under various levels of degradation due to anthropogenic pressures and also due to senseless bureaucratic decisions (such as setting up housing layouts, sand and granite mining, etc.). These regions have scope for rejuvenation and sustainable management by involving all local stakeholders. Further developments should be refrained in ESR 2 and actions are to be taken to improve the native vegetation cover. The Community based Conservation (CBC) of ESR 2 & 3 is essential as conservation of biological diversity (or wildlife) depends on the extent of involvement of local communitiesin decision-making, monitoring and regular management. Local communitiesknowledge and experience of wildlife and their habitats, would be invaluable in conservation endeavors. This would also help the BNP administration in delineating the region for further usage by local communities on sustainable basis. The uncontrolled development should be discouraged in and around of pristine lakes, primeval forest patches, perennial water bodies. The village forest committees’ (VFCs) should be formed on priority for promoting conservation initiatives. The members should be involved for afforestation, wild life protection and controlling deforestation activities. Monitoring committee should be formed under the guidance of district forest officer (DFO) with powers conferred by subsection-3 of Environment Protection Act, 1986. The committee should include a representative from forest department, a representative from urban development (BDA), a representative of non-government organization, who are active in the field of conservation, an expert in forest ecology and environment, one of the village forest committee members (VFC), a representative from local stake holders.

Figure 7: Forest cover -BNP and 5 km buffer
Figure 8: Population density - BNP with buffer
Figure 9: Elephant migratory path across various forest divisions from Madikeri to BNP
Figure 10: BNP and Elephant migratory path
Figure 11: Crop infested regions due to elephants in BNP
Figure 12: Elephant crop infested villages of BNP and buffer region
Figure 13: Leopard siting distribution in BNP
Figure 14: Tiger distribution in BNP
Figure 15: Sloth bear distribution in BNP
Figure 16: Wild bison distribution in BNP
Figure 17: Spotted deer distribution in BNP.
Figure 18: Ecological sensitive regions of BNP (10 km buffer)
Figure 19: proposed layouts within 0.5 km of BNP
 
Table 4: Restricted and regulated activities in ESR -1, 2 3 & 4.
SNO
ACTIVITIES
ECOLOGICALLY SENSITIVE REGIONS
ESR-1
ESR-2
ESR-3
ESR-4
1
FORESTS
 
 
 
 
  • Land use change (Forest to non-forest usages)
  • Monoculture plantations
(for fuel wood requirement)
  • Extraction of medicinal plants (with strictregulations)
  • Forest improvement through VFCs and reforestation
  • NTFP collection
  • Encroachment of forests
  • Protection of hill slopes
  • Erection of new high tension power lines in forest area
  • Alteration of natural springs, lakes and wetlands
3
AGRICULTURE&HORTICULTURE
  • Agro forestry
  • Organic farming
  • Agro land use change / Encroachments
  • Genetically modified crops
  • Animal Husbandry
  • Establishment of large green houses and commercial ventures
  • Nitrogen and Phosphorus (N&P) fertilizers
(Dosage as prescribed by Agriculture department)
  • Endosulfan
5
INDUSTRIES (Larger scale)
  • Agro processing industries
  • Information Technology industries (IT)
  • Red category (Polluting) industries
  • Garment industries
  • New establishment of Industries
(Allowed only after critical review by local stake holders and experts)
  • Nonpolluting (Green) Industries
 
  • Petro chemical processing and gasoline pipes in forest land
6
INDUSTRIES (Small scale)
  • Garment industries
  • Domestic (Home based) industries
  • Papad
  • Fruit processing (Mango processing)
  • Milk products and processing
  • Bee keeping and bee nurseries
  • Pongamia plantations for biofuel (in private lands)
  • Bio pesticides manufacturing
  • Poultry farms and powdered eggs
  • Vegetable dyes; fruits and vegetables preservation
  • Aromatic plants and essential oil distillation; orchids and cut flowers harvesting industries
  • Nonpolluting (Green) Industries
7
TOURISM INDUSTRY
 
 
 
 
  • Ecotourism
  • Organic village and home stay
  • VFC managed tourism
  • Arts and handicrafts museum and trade center
8
MINING AND MINERAL EXTRACTION
(on sustainable basis)
  • Filter sand
  • Minerals
  • Stone quarries
 
(on sustainable basis)
9
WASTE DISPOSAL
 
 
 
 
  • Hazardous waste processing units
  • Solid waste disposal
(For composting and manure preparation)
  • Liquid waste discharge
(Treatment plants (STP) for processing)
  • Recycling and waste processing and units
 
(compliant with PCB)
  • Use of plastics
(compliant with PCB)
  • Medical and e-waste
(compliant with PCB)
10
TRANSPORTATION
(Allowed only after strict EIA)
  • Roads and express ways
  • Rail and freight corridors
Subject to EIA; Strict regulation and social audit
  • Up gradation of existing infrastructure
(Subject to
EIAs, strict regulation )
 
  • Vehicular moment at night
11
ENERGY
 
 
  • Solar (Roof top)
  • Wind power
  • Bio energy
  • Coal based (Thermal power)
  • Gas or liquid fuel based
  • Hydro power (No scope)
  • Nuclear power
Remarks
  • ESR1 represents zone of highest conservation, no further degradation allowed. ESR-2 has potentiality to become as ESR1 provided with strict regulations and improvement of forests and its environs by more protection. Small change in ESR-2 by unplanned activities will have more adverse impacts on  ESR1 (Ramachandra et al., 2013a; 2013b).
  • Senseless unplanned activities such as approving and formation of new residential layouts, large apartments and construction of shopping malls should not be allowed in ESR 1 & 2.
  •  Figure 19 lists the housing layout approved by BDA. Creation of these housing layout will only enhance the human animal conflicts and also threatens the survival of BNP.
  • There are several residential projects, layouts are farmed within 100-500 m of BNP boundary area (Figure 19), and also in gomala lands. Large scale residential layouts are in proposal state at Indlavadi, Bagganadoddi, Konasandra villages. Strict protection measures entails strict ban on any construction activity in ESR-1 & 2.
  • Forest Rights and wild life protection acts to be implemented in its true spirit by reaching out to local stake holders.
  • There are is a need for special protection in areas such as Keliginanath Gollahalli, Terubeedi,Gattigonda etc., villages suffering from rampant grazing. These promising forest patches should be protected (enclosures using barbed wire solar fencing and closed for any kind of exploitation). The natural regeneration should be promoted for at least five-year period. Thereafter these forests can provide more protection for free movement of wildlife and more such selected blocks are to be protected, similar to the actions taken under forest working plans. 
  • Monoculture plantations are not allowed in ESR1, 2, 3; existing exotics should be replaced by planting native species at the earliest.
  • Promote decentralized electricity, use of renewable energy sources such as (solar, wind power).
  • Implement eco-development programmes to meet the energy demand in decentralized way.  Local bio resource based industry should be promoted. All should be strictly regulated and be subject to social audit  (Ramachandra, et al., 2015a).
  • Quarrying, mining shall be banned in ESR 1, 2 immediately and no new licenses to be given for quarry and sand mining to minimize environmental and social impacts immediately.
  • The terrain is ideal for promoting eco-tourism based economy and scientific studies. Tourism Master Plan should be based on MOEF regulations (after taking into account social and environmental costs).
  • It is recommended that the state government should hand over all the revenue lands, gomala lands in BNP and within 1km buffer to the forest department for effective management.
  • The fodder farms should be created via VFCs/ women self-help groups in waste lands, gomala lands for controlling grazing in forest lands.
  • Environmental education and wild life awareness programs can be taken to involve local stakeholders for sensitising. Local educational and research institutions should be encouraged to take up these activities with the help forest department.
 
Table 9: Number of villages in ESR 1 to 4

Ecologically sensitive regions
AREA (Ha)
AREA (Sq. Km)
NO OF VILLAGES
ESR-1
63590.38
635.90
69
ESR-2
26436.21
264.36
78
ESR-3
30343.21
303.43
79
ESR-4
56477.6
564.78
176
Total
176847.4
1768.47
402
SNO
LOCATION
TALUK
HOUSE HOLDS
POPULATION_2011
FOREST %
ESR_STATUS
1
Ragihalli State Forest
Anekal
0
0
76.17
1
2
Thattekere
Anekal
303
1479
58.49
1
3
Kannaikana Agrahara
Anekal
528
2030
38.75
1
4
Bilwaradahalli
Anekal
324
1342
46.99
1
5
Bannerughatta
Anekal
930
3958
59.10
1
6
Bhoothanahalli
Anekal
393
1773
45.95
1
7
Mantapa
Anekal
270
1213
46.82
1
8
Begihalli
Anekal
221
911
24.99
1
9
Bukkasagara
Anekal
271
1258
19.57
1
10
Mahanth Lingapur
Anekal
500
2317
17.50
1
11
Ragihalli
Anekal
357
1590
34.69
1
12
Bagganadoddi
Anekal
95
474
37.53
1
13
Shivanahalli-Ragihalli
Anekal
359
1529
42.79
1
14
Indlavadiura
Anekal
113
569
39.69
1
15
Thammanayakanahalli
Anekal
432
2271
51.70
1
16
Gottikere
Bangalore South
2651
11201
25.39
1
17
Basavanapura
Bangalore South
495
1968
46.71
1
18
Thattaguppe
Bangalore South
453
2028
13.48
1
19
Vaddarapalya
Bangalore South
333
1537
20.27
1
20
Mallapur
Kanakapura
126
536
52.05
1
21
Muggur Forest
Kanakapura
2
9
92.28
1
22
Chikkamukodlu
Kanakapura
134
568
77.50
1
23
Honniganahalli
Kanakapura
116
528
82.46
1
24
Gullahalli Kaval
Kanakapura
163
815
65.38
1
25
Gottigehalli
Kanakapura
213
1091
28.56
1
26
Bilakanakuppe
Kanakapura
138
619
63.80
1
27
Attikuppe
Kanakapura
210
1050
43.61
1
28
Godur2
Kanakapura
337
1535
40.09
1
29
Kolalgundi
Kanakapura
124
575
59.13
1
30
Katrinatha
Kanakapura
36
182
60.47
1
31
Kallanakuppe
Kanakapura
512
2362
39.89
1
32
Elachavadi
Kanakapura
243
1216
53.29
1
33
Devarahalli
Kanakapura
286
1291
39.68
1
34
Bhimasandra
Kanakapura
29
120
68.94
1
35
Linganapura
Kanakapura
137
662
62.21
1
36
Therubeedi
Kanakapura
335
1518
78.48
1
37
Bantanalu
Kanakapura
4
17
83.32
1
38
Bachahalli
Kanakapura
59
228
66.16
1
39
Chlakanahalli
Kanakapura
425
1818
35.94
1
40
Bilikal Forest
Kanakapura
0
0
87.18
1
41
Kengalnath Gollahalli
Kanakapura
51
233
89.14
1
42
Kerelallusandra
Kanakapura
347
1424
41.85
1
43
Narayanapura
Kanakapura
201
819
46.50
1
44
Kebbre
Kanakapura
147
649
61.17
1
45
Gattigonda
Kanakapura
719
3631
52.48
1
46
Hanchiguli
Kanakapura
189
788
54.89
1
47
Chikkabettahalli
Kanakapura
182
770
59.27
1
48
Na1
Kanakapura
0
0
84.22
1
49
Kolagondanahalli
Kanakapura
706
3502
64.52
1
50
Halasuru
Kanakapura
127
503
44.95
1
51
Doddaguli
Kanakapura
340
1522
40.58
1
52
Arkere
Kanakapura
202
861
46.28
1
53
Tippuru
Kanakapura
237
1066
46.58
1
54
Bijhalli
Kanakapura
140
654
53.28
1
55
Manjilnatha
Kanakapura
0
0
97.66
1
56
Bommasandra1
Kanakapura
124
474
59.45
1
57
Bijjahalli
Kanakapura
276
1124
77.67
1
58
Hosadurga
Kanakapura
822
3653
59.02
1
59
Hunasanahalli
Kanakapura
648
2888
56.44
1
60
Ganganahalli
Kanakapura
189
799
70.85
1
61
Salbanni
Kanakapura
130
578
60.81
1
62
Tattikere
Kanakapura
211
851
56.48
1
63
Guddeveeranahosahalli
Kanakapura
166
785
59.37
1
64
Banimkodu
Kanakapura
481
2016
61.41
1
65
Kallakere
Kanakapura
150
659
42.43
1
66
Gollahalli4
Kanakapura
39
195
30.86
1
67
Jangalapalya
Kanakapura
109
420
27.95
1
68
Bannerughatta Kaval
Kanakapura
0
0
71.42
1
69
Byrappanahalli
Kanakapura
107
472
78.53
1
Table 5: Villages in  ESR – 1
SNO
LOCATION
TALUK
HOUSE HOLDS
POPULATION_2011
FOREST %
ESR_STATUS
1
Hullavalli
Anekal
468
2228
25
2
2
Sakalavara
Anekal
165
725
43
2
3
Bhujangadasana A. Kere
Anekal
92
325
56
2
4
Ramasandra
Anekal
55
260
43
2
5
Amani Bidarakere
Anekal
8
25
44
2
6
Harapanahalli
Anekal
233
929
10
2
7
Kallubalu
Anekal
194
815
16
2
8
Giddenahalli
Anekal
76
318
11
2
9
Kadujakkanahalli
Anekal
132
669
16
2
10
Indlavadi
Anekal
351
1730
16
2
11
Thimmasandra
Anekal
32
158
7
2
12
Chikkanahalli1
Anekal
56
285
10
2
13
Chikkahosahalli
Anekal
232
1187
13
2
14
Lakshmipura
Anekal
303
1456
33
2
15
Yalenahalli
Bangalore South
99
441
24
2
16
Kalenagrahara
Bangalore South
287
1482
21
2
17
Kammanahalli
Bangalore South
0
0
25
2
18
Gollahalli3
Bangalore South
623
2653
24
2
19
Pillaganahalli
Bangalore South
679
2772
0
2
20
Mylasandra
Bangalore South
488
2129
16
2
21
Badamanavarthekaval (P)
Bangalore South
0
0
65
2
22
Gulakamale
Bangalore South
394
1835
35
2
23
Alakabelalur
Bangalore South
4
17
8
2
24
Sunkadakatte
Bangalore South
29
125
19
2
25
Nettigere
Bangalore South
268
1340
10
2
26
Rayagodlu
Bangalore South
217
983
11
2
27
Kembathahalli
Bangalore South
245
1123
31
2
28
Pillaganahalli1
Bangalore South
679
2772
16
2
29
Hommadevanahalli
Bangalore South
290
1259
31
2
30
Tharalu
Bangalore South
303
1259
26
2
31
Yadamadu
Kanakapura
189
750
9.52
2
32
Kaggalahalli
Kanakapura
248
1130
8
2
33
Gabbadi
Kanakapura
352
1520
34
2
34
Kebbedoddi
Kanakapura
0
0
34
2
35
Godur1
Kanakapura
337
1535
0
2
36
Dyavsandra
Kanakapura
93
517
35
2
37
Konasandra
Kanakapura
170
832
41
2
38
T.Maniyambal
Kanakapura
67
296
36
2
39
Banavasi
Kanakapura
404
1844
37
2
40
Chikkamralavadi
Kanakapura
358
1636
33
2
41
Marasahalli
Kanakapura
149
646
35
2
42
Hosahalli2
Kanakapura
77
369
34
2
43
Thokasandra
Kanakapura
279
1223
30
2
44
Ajjegowdanavalse
Kanakapura
127
577
30
2
45
Virupasandra
Kanakapura
376
1754
17
2
46
Aralalu
Kanakapura
368
1657
19
2
47
Bekuppe
Kanakapura
466
2192
26
2
48
Tigalarahosahalli
Kanakapura
393
1780
25
2
49
Nidagallu Aralalusandra
Kanakapura
39
158
22
2
50
Nidagallu
Kanakapura
190
812
43
2
51
Kebbehalli
Kanakapura
372
1670
50
2
52
Yakkuli
Kanakapura
100
400
33
2
53
Galapur
Kanakapura
261
1222
0
2
54
Dodkaballi
Kanakapura
463
2057
27
2
55
Tattiguppe
Kanakapura
143
614
38
2
56
Ajjabasavanahatti
Kanakapura
53
251
33
2
57
Yeramgere
Kanakapura
262
1183
37
2
58
Balepura
Kanakapura
29
117
47
2
59
Kempalanatta
Kanakapura
102
449
59
2
60
Anekadaburu
Kanakapura
140
615
45
2
61
Balagondanahalli
Kanakapura
20
101
40
2
62
Muggur
Kanakapura
140
621
44
2
63
Kotnur
Kanakapura
0
0
16
2
64
Raghavanapalya
Kanakapura
44
171
29
2
65
Hullukasavanahalli
Kanakapura
33
159
33
2
66
Nallasandra
Kanakapura
128
614
31
2
67
Jakkasandra
Kanakapura
192
940
26
2
68
Huyalappanahalli
Kanakapura
169
839
28
2
69
Doddamaralavadi
Kanakapura
677
3191
40
2
70
Maniyambal
Kanakapura
373
1697
49
2
71
Mavathoor
Kanakapura
166
728
36
2
72
Herandyapanahalli
Kanakapura
664
3136
54
2
73
Galapur1
Kanakapura
261
1222
51
2
74
Halanatha
Kanakapura
371
1808
52
2
75
Na
Kanakapura
0
0
35
2
76
Kudigalani
Kanakapura
32
136
25
2
77
Vaderahalli1
Kanakapura
21
75
39
2
78
Yerahalli
Kanakapura
0
0
61
2
Table 6: Villages in ESR – 2.
SNO
LOCATION
TALUK
HOUSE HOLDS
POPULATION_2011
FOREST %
ESR_STATUS
1
Hullimangala
Anekal
450
2092
38.72
3
2
Bhingipura
Anekal
276
1246
32.71
3
3
Nanjapur
Anekal
88
442
47.65
3
4
Jigani
Anekal
1918
7871
13.36
3
5
Vaderamanchanahalli
Anekal
189
717
7.68
3
6
Konasandra1
Anekal
122
581
11.71
3
7
Bhingipura
Anekal
10
19
10.23
3
8
Dyavasandra
Anekal
65
295
9.38
3
9
Bommandahalli
Anekal
129
662
12.04
3
10
Nosenooru
Anekal
226
1037
10.65
3
11
Kadujakkanahalli1
Anekal
132
669
0.00
3
12
Nosenoorugollahalli
Anekal
82
400
20.00
3
13
Suragajakkanahalli
Anekal
187
912
10.33
3
14
Aduru
Anekal
115
636
11.13
3
15
Sonnayakanapura
Anekal
219
1046
15.91
3
16
Gowranahalli
Anekal
297
1635
11.55
3
17
Anekal
Anekal
7212
33506
9.93
3
18
Medihalli
Anekal
108
498
10.03
3
19
Agasathimmanahalli
Anekal
7
17
18.05
3
20
Sunnavara
Anekal
183
846
21.51
3
21
Pattangere Gollahalli
Anekal
43
201
47.32
3
22
Kalanaikanahalli
Anekal
47
239
38.10
3
23
Bidarakadahalli
Anekal
0
0
54.28
3
24
Koodlu
Bangalore South
1292
5201
14.41
3
25
Devar Chikkanahalli
Bangalore South
0
0
10.47
3
26
Dodda Kalsandra
Bangalore South
672
2700
15.81
3
27
Arkeri
Bangalore South
0
0
11.04
3
28
Uttarahalli Manavartha Kaval
Bangalore South
87
355
52.78
3
29
Chandrashekarapura
Bangalore South
40
178
15.04
3
30
Anjanapura
Bangalore South
529
2217
42.25
3
31
Vitasandra
Bangalore South
209
960
27.76
3
32
Bettadasanapura
Bangalore South
292
1391
12.64
3
33
Somanahalli
Bangalore South
747
3455
10.54
3
34
Nelaguli
Bangalore South
187
956
12.72
3
35
Shivanahalli
Kanakapura
629
2970
35.67
3
36
Vaderahalli
Kanakapura
236
1103
11.29
3
37
Gabbadi Kaval
Kanakapura
7
25
41.57
3
38
Hosakote
Kanakapura
126
651
34.39
3
39
Godur
Kanakapura
337
1535
0.00
3
40
Marasandra
Kanakapura
151
671
21.04
3
41
Chulakanakere Kaval
Kanakapura
31
145
53.58
3
42
Bheemasandra
Kanakapura
59
257
30.99
3
43
Gadaranahalli
Kanakapura
69
327
43.66
3
44
Rampura
Kanakapura
0
0
44.59
3
45
Anehosahalli
Kanakapura
153
708
33.98
3
46
Malligemetlu
Kanakapura
339
1532
31.06
3
47
Paduvanagere
Kanakapura
362
1557
43.96
3
48
Ballagere
Kanakapura
262
1105
35.77
3
49
Guthalahunase
Kanakapura
172
730
30.51
3
50
Anamanhalli
Kanakapura
227
1059
11.04
3
51
Aranakuppe
Kanakapura
190
852
10.40
3
52
Bardanahalli
Kanakapura
269
1058
21.43
3
53
Chakasandra
Kanakapura
228
1119
19.66
3
54
Kunur
Kanakapura
393
1931
43.82
3
55
Kodihalli
Kanakapura
1243
5895
31.79
3
56
Hosahalli
Kanakapura
220
1125
34.29
3
57
Nallahalli
Kanakapura
947
4493
46.01
3
58
Mahimanahalli
Kanakapura
321
1502
40.10
3
59
Channasandra
Kanakapura
160
817
55.96
3
60
Hukkunda
Kanakapura
530
2759
30.95
3
61
Chikkakoppa
Kanakapura
112
511
49.07
3
62
Mullahalli
Kanakapura
477
2134
45.86
3
63
Madarahalli
Kanakapura
123
607
39.70
3
64
Doddakoppa
Kanakapura
234
1228
40.85
3
65
Gollahalli2
Kanakapura
239
1081
41.92
3
66
Purasagondanahalli
Kanakapura
72
325
38.03
3
67
Kottekoppa
Kanakapura
417
1832
48.84
3
68
Arekoppa
Kanakapura
411
1970
45.75
3
69
Bennagodu
Kanakapura
92
416
52.26
3
70
Begur
Kanakapura
2069
9237
18.70
3
71
Nyanappanahalli
Kanakapura
0
0
9.86
3
72
Hulimavu
Kanakapura
0
0
16.76
3
73
Vajarahalli
Kanakapura
516
2200
26.88
3
74
Alahalli
Kanakapura
1364
7137
23.28
3
75
Thippasandra
Kanakapura
111
487
25.13
3
76
Mallasandra
Kanakapura
8
38
44.73
3
77
Kaggalipura
Kanakapura
1532
6907
17.84
3
78
Obichudahalli
Kanakapura
196
906
26.36
3
79
Soluru
Kanakapura
92
493
37.41
3
Table 7: Villages in ESR – 3
SNO
LOCATION
TALUK
HOUSE HOLDS
POPULATION_2011
FOREST %
ESR_STATUS
1
Bangalore
Bangalore South
0
4301326
13.4
4
2
Hoskerehalli
Bangalore South
0
0
14.21
4
3
Halge Vaderahalli
Bangalore South
0
0
19.46
4
4
Kathreguppe
Bangalore South
0
0
5.43
4
5
Ittamadu
Bangalore South
0
0
4.13
4
6
Venkatapura
Bangalore South
0
0
14.5
4
7
Agara
Bangalore South
0
0
41.33
4
8
Jaksandra
Bangalore South
0
0
12.79
4
9
Karisandra
Bangalore South
0
0
8.97
4
10
Rupena Agrahara
Bangalore South
0
0
9.99
4
11
Kadarenahalli
Bangalore South
0
0
7.76
4
12
Chikka Kalsandra
Bangalore South
0
0
5.04
4
13
Arehalli
Bangalore South
698
2858
11.44
4
14
Haralakunte
Bangalore South
0
0
21.22
4
15
Sarakki
Bangalore South
0
0
12.35
4
16
Jarganahalli
Bangalore South
0
0
12.78
4
17
Bommanahalli
Bangalore South
0
0
4.22
4
18
Madivala
Bangalore South
0
0
8.68
4
19
Vaddara Palya1
Bangalore South
175
718
20.47
4
20
Marenahalli
Bangalore South
0
0
9.37
4
21
Gopanayakanahalli
Bangalore South
0
0
7.95
4
22
Uttarahalli
Bangalore South
0
0
13.9
4
23
Yellukunte
Bangalore South
0
0
8.23
4
24
Haralur
Bangalore South
296
1186
25.99
4
25
Nainappasettipalya
Bangalore South
0
0
6.35
4
26
Sarakki Agrahara
Bangalore South
0
0
10.12
4
27
Bilekhalli
Bangalore South
0
0
17.16
4
28
Channasandra
Bangalore South
0
0
24.27
4
29
Ganakallu
Bangalore South
556
2490
27.82
4
30
Kodichikkanahalli
Bangalore South
0
0
9.73
4
31
Bikaspur
Bangalore South
0
0
13.7
4
32
Yalachenahalli
Bangalore South
0
0
4.28
4
33
Sarakki Kere
Bangalore South
0
0
5.21
4
34
Subramanyapur
Bangalore South
1190
4817
14.57
4
35
Hongasandra
Bangalore South
0
0
6.66
4
36
Thurahalli
Bangalore South
187
838
37.4
4
37
Vasantpur
Bangalore South
565
2516
11.04
4
38
Puttenahalli
Bangalore South
0
0
20.47
4
39
Badamanavarthekaval1 (P)
Bangalore South
0
0
75.43
4
40
Konankunte
Bangalore South
3291
13316
8.43
4
41
Gabbalalu
Bangalore South
523
2147
22.86
4
42
Koodlu1
Bangalore South
1292
5201
13.4
4
43
Hemmigepura
Bangalore South
312
1658
39.42
4
44
Hemmigepura
Bangalore South
0
0
26.25
4
45
Choodasandra
Bangalore South
145
672
28.51
4
46
Badamanavarthe Kaval
Bangalore South
430
2060
55.31
4
47
Basapur
Bangalore South
133
604
22.94
4
48
Rajanamaduvu
Bangalore South
80
415
32.65
4
49
Devagere
Bangalore South
210
1179
34.07
4
50
Chikkathogaru
Bangalore South
127
575
27.42
4
51
Doddathogaru
Bangalore South
995
4087
18.54
4
52
Agara2
Bangalore South
781
3612
42.09
4
53
Gangasandra
Bangalore South
111
619
43.57
4
54
Vasanthanahalli
Bangalore South
284
1079
46.76
4
55
Chinnakurchi
Bangalore South
154
796
55.97
4
56
Saludoddi
Bangalore South
0
0
42.54
4
57
Uttari
Bangalore South
214
1038
31.11
4
58
Chudahalli
Bangalore South
184
998
12.63
4
59
Naganayakanahalli
Bangalore South
101
576
24.15
4
60
Hulugondanahalli
Kanakapura
365
1847
7.14
4
61
Harohalli
Kanakapura
2316
11338
26.38
4
62
Bannikuppe
Kanakapura
350
1651
7.67
4
63
Maralagere
Kanakapura
55
218
36.18
4
64
Devarakaggalahalli
Kanakapura
105
515
7.04
4
65
Jakkasandra1
Kanakapura
310
1938
23.88
4
66
Keeranagere
Kanakapura
126
629
34.35
4
67
Doddasadenhalli
Kanakapura
293
1488
32.14
4
68
Cheelur
Kanakapura
581
2739
19.5
4
69
Avaremala
Kanakapura
461
2247
42.93
4
70
Chikkasadenahalli
Kanakapura
136
632
29.84
4
71
Chikkadevarahalli
Kanakapura
59
299
36.17
4
72
T. Hosahalli
Kanakapura
293
1338
27.63
4
73
Mrasandra
Kanakapura
0
0
31.74
4
74
Agara1
Kanakapura
211
944
28.73
4
75
Ramapura
Kanakapura
232
1166
8.97
4
76
Rayasandra
Kanakapura
366
1645
28.96
4
77
Tungani
Kanakapura
393
1798
7.57
4
78
Ganalu
Kanakapura
423
1936
7.42
4
79
Aralalusandra
Kanakapura
290
1331
13.84
4
80
Banantimari State Forest
Kanakapura
0
0
53.55
4
81
Agrahara
Kanakapura
95
411
3.97
4
82
Kallahalli
Kanakapura
354
1627
8.36
4
83
Thammasandra
Kanakapura
454
2061
25.87
4
84
Kanakapura
Kanakapura
0
0
13.42
4
85
Hanumanahalli
Kanakapura
47
238
32.75
4
86
Virupasandra1
Kanakapura
376
1754
0
4
87
Seegekote
Kanakapura
290
1349
33.66
4
88
Acchalu
Kanakapura
496
2411
42.43
4
89
Horalagallu
Kanakapura
547
2557
45.17
4
90
Maralabekuppe
Kanakapura
964
4987
45.98
4
91
Sompura
Kanakapura
82
454
32.59
4
92
Singasandra1
Kanakapura
0
0
13.03
4
93
Raghuvanahalli
Kanakapura
126
627
28.72
4
94
Purappana Agrahara
Kanakapura
385
1584
16.46
4
95
Varahasandra
Kanakapura
89
479
31.09
4
96
Hosahalli1
Kanakapura
285
1242
14.98
4
97
Rayasandra1
Kanakapura
179
1019
36.67
4
98
Naganathapura
Kanakapura
279
1081
17.43
4
99
Lingadeeranahalli
Kanakapura
131
626
25.7
4
100
Gollahalli
Kanakapura
0
0
30.75
4
101
Thalaghattapura
Kanakapura
833
3607
20.8
4
102
Sreeramapura
Kanakapura
146
755
54.31
4
103
Doddanagamangala
Kanakapura
286
1360
16.83
4
104
Beratena Agrahara
Kanakapura
84
340
18.04
4
105
Dodda Tegur (P)
Kanakapura
0
0
4.15
4
106
Chikkanagamangala
Kanakapura
128
653
24.22
4
107
Konappana Agrahara
Kanakapura
2918
11038
14.81
4
108
Veerasandra
Kanakapura
620
2235
29.02
4
109
Hebbagodi
Kanakapura
114
557
18.32
4
110
Kammasandra
Kanakapura
620
2549
21.26
4
111
Maragondahalli
Kanakapura
799
4046
19.46
4
112
Gollahalli1
Kanakapura
427
1638
20.6
4
113
Andapura
Kanakapura
34
155
31.69
4
114
Bommasandra
Kanakapura
551
2194
22.89
4
115
Thirupalya
Kanakapura
802
2817
14.29
4
116
Seegehalli
Kanakapura
32
174
29.93
4
117
Yarandahalli
Kanakapura
588
2025
18.36
4
118
Vabasandra
Kanakapura
115
565
27.94
4
119
Kachanaikanahalli
Kanakapura
585
2231
24.41
4
120
Kithiganahalli
Kanakapura
578
2220
25.32
4
121
Kylasanahalli
Kanakapura
249
1151
14.43
4
122
Banahalli
Kanakapura
519
2071
11.81
4
123
Hosahalli3
Kanakapura
130
638
27.46
4
124
Bandenallasandra
Kanakapura
129
645
9.26
4
125
Hennagara
Kanakapura
373
1761
9.93
4
126
Rajapura
Kanakapura
143
730
8.14
4
127
Iggaluru
Kanakapura
327
1524
23.6
4
128
Hinnakki
Kanakapura
221
1078
9.46
4
129
Ramakrishnapura
Kanakapura
33
170
34.02
4
130
Marasuru
Kanakapura
395
1709
25.46
4
131
Haragadde
Kanakapura
842
3493
10.42
4
132
Seethanaikanahalli
Kanakapura
85
520
19.4
4
133
Lingapura
Kanakapura
130
746
8.22
4
134
Byagadadenahalli
Kanakapura
108
511
20.83
4
135
Doddaheggadde
Kanakapura
165
770
10.4
4
136
Koonmadivala
Kanakapura
64
326
12.38
4
137
Avadadenahalli
Kanakapura
90
513
16.26
4
138
Soppahalli
Kanakapura
91
450
9.89
4
139
Kumbaranahalli
Kanakapura
126
602
15.97
4
140
Channena Agrahara
Kanakapura
175
925
11.41
4
141
Kempavaderahalli
Kanakapura
47
201
12.87
4
142
Aravattigepura
Kanakapura
60
281
10.54
4
143
Chikkaheggadde
Kanakapura
117
650
8.94
4
144
Karapura
Kanakapura
252
1172
7.59
4
145
Hasarubani
Kanakapura
5
35
14.14
4
146
Honnakalasapura
Kanakapura
78
364
11.37
4
147
Kavala Hosahalli
Kanakapura
293
1238
13.35
4
148
Haladenahalli
Kanakapura
233
1031
11.63
4
149
Bidaragere
Kanakapura
174
900
2.92
4
150
Kurubarahalli
Kanakapura
1
4
7.07
4
151
Muthugatti
Kanakapura
427
1970
2.75
4
152
Sabmangala
Kanakapura
128
676
2.81
4
153
Choodenahalli
Kanakapura
116
558
13.75
4
154
Hompalaghatta
Kanakapura
99
536
7.37
4
155
Thelagarahalli
Kanakapura
119
626
10.81
4
156
Gudnahalli
Kanakapura
137
657
2.13
4
157
Geritiganabelu
Kanakapura
203
1049
2.69
4
158
Singasandra
Kanakapura
72
392
13.06
4
159
Menasiganahalli
Kanakapura
157
810
18.6
4
160
Vanakanahalli
Kanakapura
284
1283
20.62
4
161
Chikkanahatti
Kanakapura
3
11
3.45
4
162
Doddakuntanahalli
Ramnagara
56
283
53.67
4
163
Kodiyalkarenahalli
Ramnagara
523
2602
35.26
4
164
Chik Kuntanahalli
Ramnagara
112
566
41.21
4
165
Yerepalya
Ramnagara
6
37
15.77
4
166
Mandalahalli
Ramnagara
4
22
64.05
4
167
Bannigere
Ramnagara
349
1663
13.73
4
168
Hosur
Ramnagara
468
2107
13.82
4
169
Gollarapalya
Ramnagara
98
455
21.88
4
170
Byramangala
Ramnagara
624
2828
8.64
4
171
Allalasandra
Ramnagara
309
1509
9.39
4
172
Kanchugaranahalli
Ramnagara
240
1038
7.6
4
173
Kanchugaranahalli Kaval
Ramnagara
0
0
18.23
4
174
Kempalahnapalya
Ramnagara
487
2114
12.39
4
175
Muddenahalli
Ramnagara
231
1183
30.58
4
176
Medamaranahalli
Ramnagara
274
1283
19.21
4
Table 8: Villages in ESR –4.
Elephant infested villages in BNP area

Sno
Village Name
Taluk
1
Bagganadoddi
Anekal
2
Bannerughatta
Anekal
3
Begihalli
Anekal
4
Bhoothanahalli
Anekal
5
Bilwaradahalli
Anekal
6
Bukkasagara
Anekal
7
Chikkahosahalli
Anekal
8
Indlavadiura
Anekal
9
Kadujakkanahalli
Anekal
10
Kadujakkanahalli1
Anekal
11
Mahanth Lingapur
Anekal
12
Mantapa
Anekal
13
Medihalli
Anekal
14
Ragihalli
Anekal
15
Ragihalli State Forest
Anekal
16
Shivanahalli-Ragihalli
Anekal
17
Thammanayakanahalli
Anekal
18
Thattekere
Anekal
19
Chudahalli
Bangalore South
20
Gulakamale
Bangalore South
21
Thattaguppe
Bangalore South
22
Vaddarapalya
Bangalore South
23
Acchalu
Kanakapura
24
Arekoppa
Kanakapura
25
Arkere
Kanakapura
26
Attikuppe
Kanakapura
27
Bachahalli
Kanakapura
28
Banimkodu
Kanakapura
29
Bannerughatta Kaval
Kanakapura
30
Bantanalu
Kanakapura
31
Bekuppe
Kanakapura
32
Bhimasandra
Kanakapura
33
Bijhalli
Kanakapura
34
Bijjahalli
Kanakapura
35
Bilakanakuppe
Kanakapura
36
Bilikal Forest
Kanakapura
37
Bommasandra1
Kanakapura
38
Byrappanahalli
Kanakapura
39
Chakasandra
Kanakapura
40
Chikkabettahalli
Kanakapura
41
Chlakanahalli
Kanakapura
42
Devarahalli
Kanakapura
43
Doddaguli
Kanakapura
44
Elachavadi
Kanakapura
45
Galapur
Kanakapura
46
Galapur1
Kanakapura
47
Ganganahalli
Kanakapura
48
Gattigonda
Kanakapura
49
Geritiganabelu
Kanakapura
50
Godur
Kanakapura
51
Godur1
Kanakapura
52
Godur2
Kanakapura
53
Gollahalli4
Kanakapura
54
Gottigehalli
Kanakapura
55
Guddeveeranahosahalli
Kanakapura
56
Gullahalli Kaval
Kanakapura
57
Halanatha
Kanakapura
58
Halasuru
Kanakapura
59
Hanchiguli
Kanakapura
60
Hosadurga
Kanakapura
61
Hosahalli2
Kanakapura
62
Hunasanahalli
Kanakapura
63
Kallanakuppe
Kanakapura
64
Katrinatha
Kanakapura
65
Kebbehalli
Kanakapura
66
Kebbre
Kanakapura
67
Kengalnath Gollahalli
Kanakapura
68
Kerelallusandra
Kanakapura
69
Kolagondanahalli
Kanakapura
70
Kolalgundi
Kanakapura
71
Kunur
Kanakapura
72
Linganapura
Kanakapura
73
Mahimanahalli
Kanakapura
74
Mallapur
Kanakapura
75
Mallasandra
Kanakapura
76
Manjilnatha
Kanakapura
77
Menasiganahalli
Kanakapura
78
Muggur Forest
Kanakapura
79
Nallahalli
Kanakapura
80
Narayanapura
Kanakapura
81
Salbanni
Kanakapura
82
Seegekote
Kanakapura
83
Shivanahalli
Kanakapura
84
Singasandra
Kanakapura
85
Soluru
Kanakapura
86
T.Maniyambal
Kanakapura
87
Tattikere
Kanakapura
88
Thelagarahalli
Kanakapura
89
Therubeedi
Kanakapura
90
Tippuru
Kanakapura
91
Vaderahalli
Kanakapura
92
Vaderahalli1
Kanakapura
93
Yadamadu
Kanakapura
 

9.1. SAFE PASSAGE FOR ELEPHANTS
India has approximately more than 50% of wild elephants of the world and acting as a last remaining stronghold of the Asian elephants. India has 26,000 elephants in the wild and 3500 elephants in captive distributed across 18 states /union territories. South India supports around 10,000 elephants in the wild and it is estimated that their geographic range has shrunk by 70% since 1960s (GAJAH, 2011). Bannerghatta National Park (BNP) is the confluence point of the Western and Eastern Ghats for Asiatic elephants. BNP connects to the forest tracks of the Cauvery Wildlife Sanctuary eventually joining the Nilgiri Biosphere Reserve of Western Ghats forest at Nilgiris, stretching through Malaimahadeshwara hills, Biligiri Ranga Temple Sanctuary, Kollegal Forest Division and Sathyamangala Forests. The elephants are distributed in the entire park area. Within the habitat, the elephants seem to have preferences to some locations such as Ragihalli, Harohalli range, which are characterized by thick vegetation cover, shade and proximity to water sources with least human pressure. BNP is one of the oldest habitats of Asian elephants, supporting 100-150 population and large number of 200-300 migratory population also noticed from adjoining Tali reserve forest and Kaveri wild life sanctuary. Asper census population the stable population of BNP elephants are 148 (Bhaskaran et al. 2007) and as per forest department records the number exceeds 200. This number gets doubled with the migratory elephants moving in during the cropping season.
The disturbance in the park appears to be prominent and more crucial. The forest department records reveal that encroachment of forest land in the park is one of the major disturbances to the elephant’s in the park with as many as 300 cases being registered as on 2008. Some local residents are involved in the illegal mining of sand along the watercourses inside the park. Sandalwood poaching (about 35 cases were registered as on April 2008 in the forest department offence register) and incidences of illicit fuel wood collection and timber smuggling are common in the park (Singh 2008), resulting in the formation of more open patches and degradation of the forest whilst reducing the effective area available for elephants use (Gopalakarishna et al., 2008). Despite best efforts of the forest department, state and central governments the elephant conservation still remains a difficult task. There are numerous challenges such as habitat loss, fragmentation, human-elephant conflict, legal and illegal capturing of elephants and poaching etc. The coordinated and determined effort is needed from public and regulatory bodies to effectively address the challenges. The bottle necks for safe movements are identified based on field investigation and it is recommended the forest department to acquire the lands for better connectivity, based on existing width of forest boundary, available forest area and  gomala lands. The boundary of BNP is having highly irregular shape and it measures about 59 km in length and the width varies from 0.2 km to 13.8 km. These regions should be fenced and enriched with native species. Table 10 lists the areas (with spatial extent) to be acquired for better connectivity of BNP. Figure 20 lists identified regions for effective elephant moment with in BNP area. Figure 21 (a, b, c, d, e, f, g) shows the polygon current land form as shown in Google earth. The Forest department should undertake flowing on priority to minimize human animal conflicts.


Figure 20: Bottleneck regions – to be acquired and enriched with fodder crops
Figure 21 (a, b, c, d, e, f, g):  Regions (areas) to be acquired (Violet color represents BNP boundary)
Table 10: Proposed connectivity for elephants

S.NO
Polygon name
Villages covered
Area (Ha)
Current land form
Reason
1
E1
Bhoothanahalli, Gulakamale, Uttarahalli Manavartha Kaval, Bilwaradahalli, Badamanavarthekaval (P), Kannaikana Agrahara, Agrahara-2
2196.97
Forest (degraded)
& Gomala land, Agriculture
Earmarked based on existing forest cover that support diverse fauna (Ex. Leopard etc.) and Elephant crop ride information. Thottikallu falls also present in this region.
2
E2
Katrinatha
31.03
Agriculture
To increase the width (to 1 km) of BNP for effective and safe passage of elephants.
Existing width is only 313 m.
3
E3
Elachavadi-1
12.60
Forest;
Agriculture
To increase the width (to 0.45 km) of BNP for effective and safe passage of elephants.
Earlier width existing only 173 m.
4
E4
Elachavadi-2
22.68
Forest
Connecting disconnected BNP boundary with in between agriculture area.
5
E5
Bhimasandra Lingapura
28.93
Forest;
Agriculture
Connecting existing disconnected BNP boundary with acquiring agriculture land.
6
E6
Maniyambal, Bachahalli
343.79
Forest
Connecting with existing
7
E7
Gattigonda
113.62
Agriculture
Connecting existing BNP boundary between Kolagondanahalli, Kengalnath Gollahalli villages
 
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