The quantitative morphometry is useful in evaluating the river basins /watersheds. Morphometric parameters are the simple means by which geologic and geomorphic features can be best studied. The role of lithology and geologic structures in the development of stream network can be understood by studying nature, type of drainage pattern and also through quantitative morphometry. Measurement of linear and shape parameters envisages to understand basin morphology and to prioritize sub-watersheds (Biswas et. al., 1999). Advanced techniques like remotesensing and GIS have evolved as a powerful tools in efficient planning and management of watersheds. Landuse refers to the economic use to which land is put by man. On the other hand, LandCover refers to the vegetation, rocky outcrops, or other features that cover the land. Two land parcels may have similar landcover, but different landuse. Assessment of landuse accurately forms the basis for proper planning, management and monitoring of available natural resources. In the present work an attempt has been made to prioritize the sub- watersheds of Torehallawatershedbased on morphometric and landuse/landcover analysis making use of remotesensing and GIS techniques.
A watershed is the surface area drained by a part or the totality of one or several given water courses. It is an ideal unit for management of natural resources like land and water and for mitigation of the impact of natural disasters for achieving sustainable development. The watershed management concept recognizes the interrelationships among the linkages between uplands, low lands, landuse, geomorphology, slope and soil. Watershedprioritization is the key issue in watershed management while demarcating watersheds. Watershedprioritization is the ranking of different sub watersheds of a watershed according to the order in which they have to be taken for treatment and soil conservation measures. Integrated use of remotesensing and GIS techniques can be used for detailed morphometric analysis and landuse/landcover analysis for watershedprioritization studies. Remotesensing and GIS techniques are currently used for assessing various terrain and morphometric parameters of the drainage basins and watersheds, as they provide a flexible environment and a powerful tool for the manipulation and analysis of spatial information. In the present study , morphometric and landuse /landcover analysis has been carried out in Vazhichal watershed, falling in tiruvanathapuram district,Kerala usingremotesensing and GIS. An attempt has been made to prioritize sub- watersheds on the basis of morphometric and landuse /landcover analysis.
average elevation of 751 metres (2463 feet). The city is situated in the north-western parts of Karnataka and lies at the border of two states, Maharashtra and Goa on the Western Ghats (50 km from the Goa state border). The study area belongs to the Northern Dry zone and Northern Transition Zone. The annual rainfall ranges from 464.5- 785.7 mm and about 52 % of the annual rainfall is received during Rabi season. The elevation is between 450-900 m. The soils are shallow to deep black clay in major areas. The important crops grown here are Rabi jowar, Maize, Bajra, Groundnut, Cotton, Wheat, Sugarcane and Tobacco.12 watersheds covering Belgaum District was taken up for the study. The study area was extracted from LISS IV images as of February 2011. Sub watersheds were extracted by overlaying watershed boundary shapefiles. The details of the watersheds are as tabulated below
Land is the most important natural resources on which all activities are based. Landuse unlike geology, is seasonally dynamic and indeed is more changing. The increase in population and human activities are increasing the demand on the limited land and soil resources for agriculture, forest, pasture, urban and industrial land uses. Information on the rate and kind of changes in the use of land resources is essential for proper planning, management and to regularize the use of such resources. India is facing a serious problem of natural resource scarcity, especially that of water in view of population growth and economic development. As a result LanduseLandCover (LULC) change has become a topic of tremendous interest within the human dimensions of the Environmental change research community. Consequently, quantifying and understanding the extent and spatial distribution of LULC is a crucial importance to the study of Environmental change at various scales. Moreover this type of analysis provides a valuable tool to increase the efficiency of landuse and landcover, and to diminish the negative environmental and societal impacts related to LULC.
According to the literature, soil erosion of a land surface is caused by various factors. These factors include topography (e.g., slope orientation, steep and length), soil cover (e.g., trees, grasses, water, bare soil and paved surface), soil character (e.g., soil mass, soil components and soil materials), and climate (e.g., rainfall amount and intensity, temperature and wind) [7, 12, 19]. In this study, we chose four different factors based on data availability to identify the potential risk areas of soil erosion in the Khlong Kui watershed. These factors are (1) slope, (2) LULC, (3) soil parent material and (4) rainfall. To construct the model, we executed two processes: (1) variable ranking and layer creation and (2) model development.
ABSTRACT: Geographical information system and remotesensing are proven to be an efficient tool for locating water harvesting structures by prioritization of Sub-Watersheds through morphometric analysis. In this study, the morphometric analysis and prioritization of seventeen Sub-watersheds of maniari watershed, situated in Lormi block of Mungeli District Chhattisgaarh State, India, was studied. For prioritization of sub-watersheds, morphometric analysis was utilized by using the Linear parameters such as Stream order, Stream length, Stream length ratio, Basin length, Bifurcation ratio, Mean bifurcation ratio, Drainage density, Stream frequency, Texture ratio, Length of overland flow and Shape parameters such as Form factor, Shape factor, Circulatory ratio, Elongation ratio, and Compactness constant. The different prioritization ranks were assigned after evaluation of the compound factor. So the entire study area has been further divided into 17 sub watersheds named 4G3F4n, 4G3F4p, 4G3F4q, 4G3F4r, 4G3F5a, 4G3F5b, 4G3F5c, 4G3F5d, 4G3F5f, 4G3F5g, 4G3F5h, 4G3F5j, 4G3F5k, 4G3F5m, 4G3F5n, 4G3F5p and 4G3F5s, ranging in geographical area from 39.57 km 2 to 112.78 km 2 and has been taken up for prioritizationbased on morphometric analysis usingGIS and remotesensing techniques. The drainage density of sub watersheds varies between 1.04 to 4.35 km/km 2 and low drainage density values of subwatershed 4G3F4n indicates that it has highly resistant, impermeable subsoil material with dense vegetative cover and low relief. The elongation ratio varies from 0.62 to 0.67 which indicates high relief and steep ground slope. The high value of circularity ratio for 4G3F5h subwatershed (0.69) indicates the late maturity stage of topography. This anomaly is due to diversity of slope, relief and structural conditions prevailing in this subwatershed. The compound parameter values are calculated and the subwatershed with the lowest compound parameter is given the highest priority. The subwatershed 4G3F5m has a minimum compound parameter value of 4.5 is likely to be subjected to maximum soil erosion and susceptible to natural hazards. Hence it should be provided with immediate soil conservation measures.
Soil erosion is a natural phenomenon, where environmental determinants such as climate, soil, topography, and vegetation affect the extent and magnitude of soil loss (Mutua et al., impacts on the natural system through deforestation, intensive land cultivation, uncontrolled grazing and construction activities are often (Thomas et al., 2018; 2000). The impact and extent of soil erosion is more severe in the developing world (Bayramin et al., 2003) where farmers are highly dependent on subsistence farming (Lulseged and Vlek, 2008). Soil erosion affects soil productivity and soil organic carbon (Quine and Zhang 2002; Cruse and Herndl 2009). Landuse/landcover change (LULC) recognized as an important driving factor of soil et al., 2017). Therefore, understanding the dynamics and trend of LULC changes based support to improve soil and land 04, Cotter et al., 2014). been demonstrated the stronger impacts of LULC change on soil erosion than rainfall variability (García-Ruiz 2014; Wijitkosum, 2012; Alkharabsheh 2013) and on the livelihood of the rural community LULC change and the associated been observed (Tadesse et al.,
Abstract: Landuse\Landcover is a vital component in understanding the interactions of the human activities with the environment and thus it is necessary to monitor and detect changes for the maintenance of sustainable environment. LanduseLandcover change analysis is executed as part of current study on Kanchinegalur sub-watershed of Dharma Watershed, Hangal Taluk, Haveri District. RemoteSensing and GIS Technologies are incorporated in the study. Classification based on LandUseLandcover is performed over the temporal resolution from 2003 to 2015 using Survey of India (SOI) toposheets, LANDSAT-7 (2003 & 2015) and IRS-P6-LISS-III (2012) dataset. Maximum Likelihood method is used in supervised classification algorithm of image classification technique. Thematic maps are prepared usingGIS software. Ground truth observations are used to validate the result of classification. Environmental impact assessment is essentially based on the efficient modelling and projection of landcover change. Exploitation of natural resources is increasing with the urban sprawl and has modified the pattern of landuse and landcover. Rapid urbanization has led to reduction of natural resources such as forest land, water bodies and arable land. Government of India (GOI) collaborated with Government of Karnataka (GOK) to undertake the project Integrated Watershed Management, for improvising the agricultural land, arable land, forest land and to work on provision of better living condition for the people settled in the watershed. Current study is presenting the positive impact of work carried out as part of the project Integrated Watershed Management in Kanchinegalur sub-watershed of Dharma Watershed, Hangal Taluk, Haveri District, based on LandUseLandcover change detection study.
Due to rapid growth of population, urbanization, industry, the agricultural land is decreasing day by day. In small & large area in agriculture the information about Landcover/ use play are play an important role usingGIS& RemoteSensing Technique are support to take decision & planning in more effective &realistic . In Landcover there are a different factors of the earth are included like Mountain, Rocks, Water, Crop, Building, Trees, and Soil etc .Human can be useland for to produce food, developing area for their need . All countries economic growth & food security is dependent on agriculture. In many countries Agriculture is primary source to maintain the food requirement for everyone. The goal of every farmer and agricultural agencies are to production food in a cost-effective manner.
The impounded water bodies appear in light blue to dark blue tone (subject to shallow surface water spread, volume of water, turbidity etc.). The presence of weed/ vegetation contributes to patches of red tone amid them. They are small / medium to large with regular to irregular shapes, smooth to mottled in texture (subject to vegetation cover) non-contiguous and dispersed in pattern, except canals which show a linear pattern. Tanks occur in lowlands of plains, uplands and valleys. These are associated with agricultural lands, dam sites, built-up areas as a source for irrigation, power and supply of water for domestic and industrial consumption etc. The tanks occupy an area of about 0.67 km 2 in the watershed.
The empirical evidence is obtained by comparing the food produced and required especially, at the upper part of the catchment because of degraded land the gap is very wide. In most cases actual production of variety of crops per household per year was less than the amount of food crops needed to feed their family per year. In most cases, the actual production was lower than the required food crops by 16.6%, 4.1%, 4.2% and 5.0% per year, respectively (Table 4). By monetizing the agriculture output, the income generated from the land by individual household had a range from US $97 to US $1090/annum, with a mean income of US $630. As the result of this, many people in the watershed have to get income for living from other sources such as selling fire wood, cow dung and others that are obtained from exploitation of environmental resources. From the interview held be- cause of uneven distribution of income and lack of good management practices over the natural resources, poverty was prevalent, especially at the upper part of the catch- ment. Most respondents expressed insecurity of the ten- ure and rights over the land and better productivity can be achieved through secured ownership rights to the land holders.
Landuse and landcover (LULC) represent the ongoing challenge of envi- ronmental variation. The understanding of the level and process of its change is the basis for any environmental planning and management. In Morocco, as everywhere in the world, human population densities are constantly increas- ing on the coastal zones. This results in a continuous and rapid acceleration of the use of coastal space and an increase in pressures on ecosystems and the different species they contain. The purpose of this study is the analysis of the changes in LULC from 1985 to 2017 in the coastal area of Sebou estuary, si- tuated in the Northwest of the Moroccan Atlantic coast. The changes were identified and assessed after classifying a series of Landsat images taken dur- ing 1985, 2002 and 2017. The algorithm used for the classification is the Sup- port Vector Machine (SVM), which yielded results with accuracy higher than 85%. The results of the landuselandcover change describe phenomenal ur- banization and deforestation, as well as an evolution of the agricultural sector, indicating the impact of anthropization in this vulnerable environment.
cover (LULC) changes play a major role in the study of global change. Landuse/landcover and human/natural modifications have largely resulted in deforestation, biodiversity loss, global warming and increase 2004). This environmental problems are frequently occurs related to LULC changes. So, available data is used in LULC changes. It can provide critical input to decision to make of environmental management and When growing population and ing socio economics are creates a LULC changes (Seto, 2002). The LULC alterations are generally caused by mismanagement of agricultural, urban, aquaculture pond and forest lands which lead to severe environmental problems such c. Remotesensing and Geographical Information Systems (GIS) are powerful tools to derive accurate and timely information on the spatial distribution of anges over large areas (Carlson et al., 2003) Past and present studies conducted by organizations and institutions around the world, mostly, has concentrated on the application of LULC changes. Remotesensing imagery is the most important data resources
The major LULC classes present in the study area are forest, farm on sand, farm on clay, fallow on sand, fallow on clay, woodyland, mixed woodland, grassland, burnt/wetland and natural water bodies. Farm and fallow on sandy and clay soils constitute the major land uses in the area, while mixed woodlands constitute the major landcover. This increase in cropping areas implies the overexploitation of natural resources on behalf of agriculture. This is confirmed by the decreasing areas of forest and also coincides with the vegetation cover decrease as indicated by NDVI from both images. This finding leads to accept the first hypothesis which stated that amount/degree of vegetation cover change is large enough to state that desertification occurs in the study area. Moreover, this finding leads to accept the second hypothesis which relates desertification process to change in land uses pattern. Remotesensing methods used in this study prove a high potential to illustrate vegetation cover changes. Therefore, the third hypothesis asking if remotesensing is a suitable tool for detection of vegetation cover change is accepted. However, results shows that vegetation cover in the southern part covered with clay soil type is more deteriorated in comparison with the northern part which is predominately covered with sandy soils. Hence, the fourth hypothesis stating that different soil types in the study area are related to different vegetation change patterns is accepted. Based on these results this study concludes the following: 1. Remotesensing techniques give reasonable classification for LULC in the study area.
With the dawn of civilization, humankind has been able to change landscapes in order to improve the amount, quality and security of natural resources critical to its well-being, such as food, freshwater, fiber and medicinal products. Through the increased levels of innovation, human population has, slowly at first, and at increasingly rapid pace later on, increased its ability to exploit resources from the environment, and expand its territory. The present paper aims at quantifying the land transformation in North Kashmir River catchment region. Since the study area is entirely mountainous, maximum change has occurred in the forest cover. The dense forests have shrunk by 112 Km 2 from 1992 to 2013. Horticulture and agricultural plantation are the fast changing landuse classes as minimum land is available for agriculture.
RemoteSensing (RS) technologies can be used to acquire spatially variable data for several applications. A number of these technologies can supply data to help to solve problems, and can often be accomplished at a lower relative cost than many other traditional methods. Remotesensing data of the earth's surface could be made readily available in digital format (Richards and Jia, 1998). These advantages have attracted great interest in the scientific and engineering community (Lyon, 1995). The reasons of remotesensing priorities over traditional methods are because of several unique aspects including the capability to measure spatial, spectral, and temporal information as opposed to point data, ability to assess the state of the earth’s surface over large areas, and to assemble long-term data sets and the capability to measure inaccessible areas; as the case in most arid regions (Qi et al., 1994; Ritchie and Rango, 1996). The “landscape-scale” requires methods to gather spatially distributed information and this requires repeated sampling of the variables of interest to acquire information over large areas. The costs and logistics of these actions can be high, and work is usually constrained by available resources. However, remotesensing is considered the most efficient technology to handle these problems and to observe the spatially distributed variables (Lyon, 1995). Integrating remotesensing images and other data in Geographic Information Systems (GIS) may provide a way to produce more accurate land-use and land-cover maps.
Abstract - The structure, functions and dynamics of most landscapes across the world are mainly determined by their landuse and landcover. Mapping landuse/ landcover changes at regional scale is essential for wide range of applications, including landslides, erosion, land planning, global warming etc. Rapid and extensive modifications of landuse/ landcover due to accelerated human activities have largely resulted into changes which have wider ramifications due to the sensitiveness of these fragile ecosystems of mountainous areas. The study area is environmentally fragile region facing tremendous and undue pressure on its natural resources. Watershed as a resource region clearly reveals the impact of developmental activities. The watershed is therefore an ideal spatial management unit for analyzing land dynamics as well as integrated development of natural resources potentialities of these sensitive systems. RemoteSensing satellite IRS P6 LISS III (2012) data have been used in this study along with information collected from the field for preparing the landuse / landcover classes. Suitable ground control points were selected for ground truthing and validation of data. Varied landuse/ landcover classes were identified ranging from moderate to dense forests to orchards to snow cover. An important element of this research paper has been advanced and improved data products and data collection systems. The thrust of the present research in mountainous areas revolve around better understanding of landuse/landcover analysis and suitable resource management in the Hamal Watershed of Kashmir.
Abstract: LandUse and LandCover development is mutually supportive and is highly complicated activity. Most of the LandUse and LandCover issues lie with land related activities as land is a scarce and highly valuable commodity. GIS is a useful and powerful analytical tool for LandUse, LandCover and urban management. This is reflected even in the field of LandUse and LandCover development of the study area. The main purpose of this study is to venture out the possibilities of GIS application in LandUse and LandCover with respect to land safety and sustainable management. The satellite data of 1998 and 2015 are being used with a spatial resolution of 23.5 m and topographic data of 1970 Survey of India (SOI) top sheets with the scale of 1:50,000. In the present study, supervised digital classification method was proved to be very much useful for making landuse and landcover interpretations. The results indicate the presence of five landuse classes with due weightage on agricultural land. An extreme change of landuse and landcover was recorded during the last 15 years of time i. e. (1998-2015). In 1998, an area of 916.98 Sq. Km. of the land was under agricultural practice, which has been decreased to 866.33 Sq. Km. in 2015. This shows 50.65Sq. K m .reduction in agricultural land during the last 15 years. The results confirm that the main reason for the drastic change in landuse and landcover change might be due to the increase in the waste land and population growth and also due to the relocation of resources to urban areas from the rural areas of Akola Taluka.
The initial LISS-III (2007) and Landsat TM (2013) imageries were subjected to a classification zones. Visual image interpretation was utilized to classify the images to different landuse categories. In order to classify the rectified images, five classes were delineated in the images namely, agriculture, fallow land, scrub land, industry and built up. The overall testing accuracy for the classification of Landsat TM (2013) was 85.3%, while it was 87.5% for IRS IC LISS III image (2007). The landuse map prepared for the year 2007 and 2013 are shown in figure 2 and 3 respectively.
Landuse and landcover studies could be a ground survey and made by Satellite imagery. These approaches may be used either independently or jointly, each having its own advantages and disadvantages. Generally multi-level approach is a very expensive. The approach, however, will ultimately depend upon the size and nature of the study area and the availability of the data. Careful section of techniques are important as it must suit the satellite data and more over, different changes in the techniques may highlight different types of Landuse and Landcover change. The Satellite landcover change information provides an inventory level of data indicating location, nature and extent of change. In order to obtain this information and to contribute effectively to sustain development strategies, it must be integrated into a database in which the process, effects and inter-actions of change with the surrounding environment that can be identified and assessed. Descriptive data on natural and socio-economic components accruing in the study area, including Remotely Sensed data, are collected in a GIS. In many previous investications in landuse and landcover related. There is the United States geological survey has devised a landuse and landcover classification, as per the report (Anderson et al., 1976). *Corresponding author: email@example.com