Sagara taluk (Figure 1) is located in the Shivamogga district of Karnataka state. Extending from 13.8549O N to 14.3427O N and 74.6259O E to 75.2955O E, Sagara taluk has an area of 1933 sq.km. Sagara taluk has numerous lakes and tanks (over 450) and streams which join either River Varada (Tungabhadra) or River Sharavathi (Figure 2).

Figure 1: Study area

Figure 2: Drainage network in sagara taluk

Rainfall (Figure 3) in Sagara taluk varies from as low as 2000 mm towards the plains to as high as over 4500 mm at the Ghats. Monthly rainfall variation in Sagara is as depicted in figure 4, indicating rainfall is due to the south west monsoons and over 85% occurring between June to September.

Figure 3: Annual Rainfall (1901 – 2010 average) in mm

Figure 4: Monthly Rainfall distribution
Temperature (Figure 5) varies from as low as 15 Degree Celsius during the months of December and January to as high as 32 degree Celsius in the months of March, April and May. Potential evapotranspiration (Figure 5) is high in the peak summers i.e., over 5 mm per day, and reduces to 3 mm per day during monsoon which is catered by the intercepted rainfall waters, and is almost constant during winter nearly 3.8 to 4 mm per day.

Figure 5: Temperature and PET dynamics in Sagara
Demographically, Sagara has a population of 206112 persons (2011 census) which has grown at a decadal rate of 2.55% since 2001.

Land use Analysis: Land use Land cover (LULC) dynamics is a major concern, as the abrupt changes has a negative impact on ecology, climate, hydrological regime, ecological flow, and also people’s livelihood in the region. LULC dynamics are specific to a region and vary from region to region. Land Cover refers to the observed physical cover on the earth’s surface. Land cover essentially distinguishes the region under vegetation with that of non-vegetation. Land use refers to use of the land surface through modifications by humans and natural phenomena. Land use can be classified into various classes such as water bodies, built up, forests, agriculture, open lands, sand, soil, etc. Land use modifications alter the structure of the landscape and hence the functional ability of the landscape. The modification includes conversion of forest lands, scrublands to agricultural fields, and cultivation lands to built-up, construction of storage structures for water bodies leading to submergence of land features that may vary from small scale to large scale.
Landscape is heterogeneous land area of interacting systems which forms an interconnected system called ecosystem. The functional aspects (interaction of spatial elements, cycling of water and nutrients, bio-geo-chemical cycles) of an ecosystem depends on its structure (size, shape, and configuration) and constituent’s spatial patterns (linear, regular, aggregated). The status of a Land use land cover can be visualized using the LULC information. Land use land cover information of a region provides a base for accounting the natural resources availability and its utilization. The information pertaining to LULC provides a framework for decision making towards sustainable natural resources management sensors.
Satellite remote sensing technology provide consistent measurements of landscape condition, allowing detection of both abrupt changes and slow trends over time for managing natural resources. Remote Sensing (RS) data with Geographic Information System (GIS) and Global Positioning System (GPS) helps in effective measure of landscape dynamics in cost effective manner.
Method involved in classification of a remotely sensed data using GIS is as depicted in Figure 6.  Data Acquisition involves collection of the remotely sensed satellite data, ancillary data include cadastral revenue maps (1:6000), the Survey of India (SOI) topographic maps (1:50000 and 1:250000 scales), vegetation map of South India developed by French Institute (1986) of scale 1:250000. Topographic maps provided ground control points (GCP’s) to rectify remote sensing data and scanned paper maps. French institute maps were delineated to identify the forest cover and used to classify the RS data. Other ancillary data includes land cover maps, administration boundary data, transportation data (road network), etc. Pre-calibrated GPS (Global Positioning System - Garmin GPS units) were used for field data collection, which were used for RS data preprocessing, classification as well as for validation. Satellite data of  1973 to 2012 were used to understand the landscape dynamics in Sagara taluk.

Figure 6: Method - land use analysis

Pre-processing of data: The remote sensing data is checked for radiometric errors and geometric errors.  The radiometric errors are rectified through radiometric correction, and the image is geometrically rectified by geo-referencing the image. Geo-registration of remote sensing data has been done using ground control points collected from the field using pre calibrated GPS  and also from known points (such as road intersections, etc.) collected from geo-referenced topographic maps published by the Survey of India. The geo-referenced image is cropped to the study area. Vector data of the district, taluk, river basins and village boundaries, drainage network, water bodies (lakes, ponds) were digitized from the Survey of India topographic maps, cadastral maps and digital elevation models. Population census and taluk wise village boundaries were collected from the Directorate of Census Operations (http://censuskarnataka.gov.in). 
Land use classification and accuracy assessment: The method involves i) generation of False Colour Composite (FCC) of remote sensing data (bands – green, red and NIR). This helped in locating heterogeneous patches in the landscape ii) selection of training polygons covering 15% of the study area and 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, iv) Supplementing this information with Google Earth/Bhuvan. Land use classification was done using supervised pattern classifier - Gaussian maximum likelihood algorithm based on various classification decisions using probability and cost functions Land uses during the different period were computed using the temporal remote sensing data through open source GIS: GRASS- Geographic Resource Analysis Support System (http://ces.iisc.ernet.in/grass). The land use was classified into five major categories such as Built up, Water, Agriculture, Plantation, Forest. 60% of the derived signatures (training polygons) were used for classification and the rest for validation. Statistical assessment of classifier performance based on the performance of spectral classification considering reference pixels is done which include computation of kappa (κ) statistics.
Land use dynamics of Sagara taluk is presented in table 1 and figure 7. Land use analysis shows that the forests have reduced from 57.3%in 1973 to 42.57% in 2013 due to intense agriculture and horticulture activities.

Table 1: Land use dynamics of Sagara (all units in %)

Status of Forest in Sagara indicating various land use categories as per the French institute maps (Pascal 1982) is depicted in Figure 8. In addition to the land use analysis using temporal medium resolution satellite imageries, Google earth was use to map kan boundaries according to the cadastral maps. These cadastral maps were rectified for geometric errors considering various prominent points on the ground as well as on the maps. The rectified maps were converted to Keyhole Markup Language files (KML files) and encroachments were delineated for Sagara kans (selected kans from Forest Working plan of Sagara division 2001-11). The results of encroachment areas are depicted in Table 2.

Figure 7: Land use dynamics in Sagara

Figure 8: French Institute map of Sagara Taluk

Table 2: Status of Kan forest in Sagara division

OBSERVATIONS
Presence of Lakes in the upstream of the well keeps the ground water table intact during all seasons with deviation of less than 0.6m (2ft) with respect to mean.
Presence of forests kept the lakes perennial. Kans with less variability and nonforests had higher variability in lake dynamics across months. 
Forest plays major role in the maintaining hydrological status during post monsoons that can be observed by the Ground water (< 1.2 metre variation on an average), well maintained quantity of water in the lake and almost constant flow post monsoon.
Degradation of forest have led to deterioration of water sources, this could be observe in Lavigere lake when compared to Baruru lake (deviation is higher in Lavigere Lake compared to Baruru Lake).
Similarly comparing Kanle, Bilisiri, Varadamoola, Yennehole and Hulkodu shows presence of higher pristine forests in the area, higher quantity of water available in the post monsoons i.e., over 5 times.
During field visits (April 2014 to April 2016), large scale degradation of forest in Lavigere, Baruru, Huttadimba, Hosgunda, Masuru, and other due to anthropogenic activities (agriculture, timber, etc).
Of all the observed Lakes in Sagara, encroachments were found to be common followed by bad quality of water (where in DO is less than 2) due to complete macrophytes and other floral cover (see Common flora found in lakes of sagara), and siltation.
Some of the lakes in Sagara are well maintained by the village lake committees.

COMMON FLORA FOUND IN LAKES OF SAGARA

Trapa	Polygonum
Salvinia	Nymphaea
.
Ludvigia	Nymphaea/Lily
Nymphaea	Nelumbos
Nelumbos	Nelumbos

 Birds in Sagara

Flora of Sagara Kans and forests