DSpace Community:http://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/53242023-11-28T04:34:37Z2023-11-28T04:34:37ZForest type and health monitoring using Hyperion data for geoenvironmental planning of iron ore mining belt, Saranda forest, JharkhandKayet, Narayanhttp://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/63322021-12-21T10:16:28Z2021-12-07T00:00:00ZTitle: Forest type and health monitoring using Hyperion data for geoenvironmental planning of iron ore mining belt, Saranda forest, Jharkhand
Authors: Kayet, Narayan
Abstract: This study focuses on two major environmental aspects, i.e., assessment of impacts of mining on
forest health and intrusion of modern hyperspectral remote sensing technology to monitor forest
health for effective geo-environmental planning and management. This work emphasizes on four
objectives: (i) Forest health assessment for geo-environmental planning and management (ii)
Assessment of impact of mining activities on tree species and its diversity (iii) Foliar dust
estimation and mapping for environmental monitoring of forest surrounding mines and (iv)
Assessment and prediction of forest health risk (FHR) for effective planning and management of
mining-affected forest area. In this work, we had used narrow-banded vegetation indices (VIs) for
forest health assessment based on the VIs model. Also, we had classified forest health status
(healthy, moderated healthy, and unhealthy) based on tree spectral data analysis. Hyperspectral
data (Hyperion) used with VIs model shown better accuracy for forest health assessment (overall
accuracy 81.52%, kappa statistic 0.79) than spectral angle mapper (overall accuracy 79.99 %,
kappa statistic 0.75) as well as support vector machine (overall accuracy 76.53 %, kappa statistic
0.71).It was observed that the health assessment accuracy (SVM) achieved with hyperspectral
bands was significantly higher than multispectral Landsat-OLI data (overall accuracy 67.27 %,
kappa statistic 0.62). The result showed that healthy forest parts are found in the upper as well as
the lower hilly side of Kiriburu and Meghahatuburu mines. Furthermore, it also exhibits a
negative relation amongst different forest health class, distance from mines, and foliar dust
concentration. In the present study, we have classified the local tree species, and its diversity was
estimated based on hyperspectral remote sensing data at a fine-scale level as well as correlated
with foliar dust concentration and distance to mines. A total of 21 spectral wavebands were
selected by discrimination analysis (Wilk’s Lambda test). The SVM, SAM, and MD algorithms
were applied for tree species classification based on field trees spectra data. The hyperspectral VIs
were used to estimate species diversity based on field measured Shannon diversity index. The
result shows that NDVI705 (Red edge normalized difference vegetation index) is having the best
R
2
(0.76) and lowest RMSE (0.04) for species diversity estimation. The results portrayed a good
negative correlation between foliar dust concentrations; Shannon Index based species diversity,
and the distance from mines. The scope of this work is to estimate foliar dust concentration using
Hyperion and Landsat images, with the aid of eight different VIs and field-based laboratory
spectra. The healthy and dust contaminated areas were detected by vegetation combination
analysis using narrow banded VIs. Vegetation different (VI
diff
) based dust model used for this
estimation and mapping. The NDVI (Normalized difference vegetation index) showed an
excellent negative correlation (R
2
=0.89 for Hyperion and R
2
= 0.81 for Landsat). Amongst the
eight VIs, NDVI was selected as an optimal VI (RMSE = 0.06 g/m
2
for Hyperion and 0.11 g/m
for Landsat) based on both, the field measurement and satellite data for estimation of foliar dust
concentration. The result showed that maximum foliar dust was concentrated near the ore
transportation network, surrounding mining locations, tailing ponds, and mining dumps areas. It
also exhibits a negative correlation between foliar dust classes and average distances from mines.
This work focuses on forest health risk (FHR) assessment and prediction in mining-affected forest
regions using an AHP (Analytic hierarchy process) model based on the multi-criteria analysis. We
considered twenty-eight parameters, including climate, natural or geomorphology, forest,
topography, environment, and anthropogenic variables. Six parameters were also evaluated from
the predicted time frame (2030 and 2050). According to the predicted FHR maps, the very highrisk
class was found at and around Kiriburu and Meghataburu mines surrounding forest
compartments. The sensitivity analysis indicated that some parameters were more sensitive to
FHR. The correlation results between FHR and sensitive parameters have shown positive results.
The correlation results showed a good negative relationship between FHR and distance from
mines and foliar dust concentration. This work will provide a basis for effective geoenvironmental
planning
and management
in
the
mining-affected
forest
region.
22021-12-07T00:00:00ZEnvironmental impacts of inland shrimp farming in parts of Purba Medinipur district, West Bengal – A geospatial analysisOjha, Atanuhttp://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/63152021-12-10T10:07:08Z2021-10-11T00:00:00ZTitle: Environmental impacts of inland shrimp farming in parts of Purba Medinipur district, West Bengal – A geospatial analysis
Authors: Ojha, Atanu
Abstract: Shrimp farming (Penaeus monodon, Litopenaeus vannamei) plays a major important role
in Indian economy for earning huge foreign currency. In international market India
leads as one of the most active countries in shrimp farming sector for exporting large
quantity of shrimp. Although shrimp farming is an appreciable income generation
method at a short time but now a days it creates some adverse environmental
degradation which may be very dangerous in future scenario. Looking at the serious
matter of environmental affect, an attempt has been made to study the rapid growth of
commercial shrimp farming in major five coastal blocks of Purba Medinipur, West
Bengal, India to focus on its positive and negative impacts on the biophysical and socioeconomic
environment.
Several types of research on shrimp farming has been done in the last few decades and
different types of approaches has been introduce to properly study on it. But in recent
trends Remote Sensing (RS) and Geographical Information System (GIS) is considered to
be most accurate and reliable approach to study the shrimp farming as a birds eye. So in
this study RS and GIS techniques were used to hind cast assessment of previous years
shrimp farming areas in retrospective manner, as well as to generate a micro level spatial
database of shrimp farming. To quantify the changing pattern of shrimp farming from
the past years (2008, 2012 and 2016) at Block, Gram Panchayet and Plot level, change
detection method was used and the future scenario of year 2030 was also present by
using the Markov Chain method. In hind cast assessment shrimp farming area was
drastically increased from 2008 (4234.13 ha) to 2016 (5895.40 ha) whereas 1542.83 ha
(3.22%) area of agricultural land was converted to brackish water tanks/ponds. According
to future scenario study shrimp farming area will increase up to 8528.62 ha in 2030 from
5895.40 ha of 2016 (i.e. it will increase by 2634.22 ha) and agricultural land will be
decreased to 43084.29 ha where as in 2016 it was 46045.25 ha. The chapter on ‘Land use
and Land cover change detection’ covers the topic of changes of Land use and Land
cover in this study area due to shrimp farming. This topic attains the first two objectives
of the study which are generation of a micro level spatial database on inland waterbodies
of coastal blocks of Purba Medinipur District, West Bengal to develop
aquaculture/fisheries information system by using Remote Sensing and Geographic
Information System and identification, quantification and prediction of the Land use and
Land cover changes with a special focus on shrimp culture development. The rapid decrease of agricultural land and increase of shrimp farming not only affect
the agriculture sector but it also affects directly or indirectly on biophysical and socioeconomic
environment.
As
a
result
of
shrimp
farming,
salinity
level
of
soil
was
increased
and
soil
pH was also changed. Due to the seepage and leakage of brackish water to the
nearest agricultural land, the production of rice was hampered. The Land use and Land
cover change trajectories analysis, soil and water sample test, information gathering
from farmers, local people by using the preplanned questionaries’ were done and
intensity of impacts was also analysed by using the Leopold Matrix. As a result,
it is
clearly seen that the salinity and pH are high within 10 meter radius of shrimp pond
which cover to approximate 1185 ha area of agricultural land which was solely used for
rice production. Beside those, from the year of 2008 to 2016 total 31.45 ha vegetation
cover, 26.29 ha river/stream/canal, 18.09 ha freshwater tanks/ponds and 17.25 ha scrub
land was also affected as well as converted to brackish water tanks/ponds. On the other
hand on the perspective of income generation,
shrimp farming was found as the most
profitable activities, which was found approximate 12
th
time more profitable than rice
cultivation. Affect of shrimp farming on biophysical and socio-economic environment in
the study area is discussed in the chapter ‘Environmental Impacts’ which fulfills the
objective of pointing out the socio-economic as well as environmental impacts of shrimp
farming area’ in the present
study.
Though it is a most profitable business strategy but it gradually hampered our
environment. So potentially shrimp farming site selection is essential to maintain both
shrimp farming as well as sustainable management of environment. On this study
potential shrimp farming site identification and prioritization are done on the basis of
the analytical hierarchy approach. It is observed that approximately 4% of the study area
that is 3289.8 ha is suitable for shrimp culture without having any issues. This 4% area is,
particularly within the coastal region. The highest potential area is detected in the
Desopran block that is 1175.29 ha. It constitutes almost 6.4% area of the block. The
potential site selection for shrimp farming has been discussed in the chapter
‘Identification of potential sites for shrimp culture’. This topic attains the objective of
identification and prioritization of the potential sites for sustainable shrimp culture using
Remote Sensing and GIS techniques in this study.
The changes of the Land use and Land cover detected due to shrimp farming revealed
that there is an appreciable development due to coastal shrimp culture. However, it is not a sustainable development undoubtedly. The information and collected data point
directly to the future threat of shrimp farming on the physical environment. Now the
burning question is that whether to focus on economic growth with shrimp farming or
to save our environment by taking some suitable measures to control the future
environmental degradation.2021-10-11T00:00:00ZPhysiographic micro zonation of Purba Medinipur district for sustainable agro-natural resources management: An appraisal of remote sensing and GISKaran, Tanmoyhttp://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/62572021-09-23T10:15:56Z2021-09-01T00:00:00ZTitle: Physiographic micro zonation of Purba Medinipur district for sustainable agro-natural resources management: An appraisal of remote sensing and GIS
Authors: Karan, Tanmoy
Abstract: Agro-natural resources management is one of the important key for sustainable development.
Sustainable development is a systematic approach and continuous process for growth and
development in which natural, produced and social capital is managed for the welfare of own
and the future generations. At present, in every country sustainable process is very much
essential for development. Therefore, this concept has been repeatedly emphasized in various
national and international conferences which are held in different countries of the world.
Sustainable agro-natural resources management is a system in a sustainable way that is
directed based on understanding the environment, economy and society. The main intention
of agro-natural resource management activities is to maintain the long-term ecological and
biological integrity of natural resources by increasing productivity in agriculture and proper
utilization of agricultural products. In this context, now the study of physiographic micro
zonation of Purba Medinipur district for sustainable agro-natural resources management is
most important. Here, the major agro-natural resources are agriculture, fishery and
vegetation. The study illustrates the village wise distribution of agro-natural resources and its
pattern and related problems in the district. This study reveals the village wise amount of
cultivated land, various crop cultivated area, cropping pattern such as cropping intensity, crop
combination and crop diversification of the district. Characteristics of agriculture and its
types and methods practiced in the district have also been described. In this study, seasonal
nature of uses of agricultural land has been analyzed. In this context, the amount of non
ploughed arable land has been determined during three crop season in an agriculture year
such as kharif, rabi and zaid crop season and which reveals that the amount of non ploughed
arable land in most of the villages of the district is highest in rabi crop season and then in zaid
crop season. But in kharif crop season almost all agricultural land is used for cultivation in all
the villages. Spatial distribution of vegetation in the district has been analyzed and also highlighted the nature of forest and its types. There are two types forest like forestry planted
by farmer and forestry planted by government or semi-government organization. The study
also discussed the distribution of inland fishery of the district. The important analysis of the
study is to determine the conversion of land into fishery. The analysis reveals that day to day
agricultural land and forest land is converted into fishery. It is estimated that the amount
fishery was 17107.2 hectares in 2013, it increased to 35832.69 hectares in 2019. Another
important analysis is the different physical properties of the district such as, nature of soil
salinity, soil pH, nature of inundated tidal water salinity, tidal water influence zone, drainage
types, drainage density and some other socio-economic analysis such as population density,
distribution of different worker population, transport system and transport density of the
district. In addition, it is important to highlight how those resources are currently being used.
The study also explains the growth rate of different agro-natural products for the past few
years, i.e., 2003-04 to 2013-14. The study describes about the various types of agro-based
industries that have developed based on the local resources. Different environmental
problems arising from fishery are also described here. Another important focus of the study is
to develop the methodological process for sustainable management of agro-natural resources,
like physiographic micro zonation, land suitability for agriculture and fishery. The district has
been divided into 8 physiographic micro zone based on drainage basin area for management
and development of agro-natural resources from grass root level. Apart from, all the villages
of the district is divided into 14 categories based on salinity level of soil and inundated tidal
water which help in selecting the suitable crop for cultivation. Suitability of villages for
development of fishery has been determined considering the location factors of the district.
All the analysis is crucial for policy making and formulation and decision making in agro-
natural resources management. Village wise agricultural data from all block of the district has
been used for the analysis of different crops area distribution, cropping pattern and nature of agricultural landuse. To extract the vegetation cover area and fishery, Sentinel-2 image, June
2019 has been used. Four years LANDSAT-8 OLI satellite data like April 2013, March 2015,
April 2017 and May 2019 has been used to show the changing agricultural land into the
fishery. Field data has been collected for the analysis of soil salinity, soil pH, nature of
inundated tidal water salinity, tidal water influence zone and environmental problems arising
from fishery. Others secondary data has been collected from different offices and website for
different analysis. Crop combination of J.C Weaver’s (1954), Gibbs-Martin Index of
Diversification (1962) is used for the analysis of cropping pattern. Normalized Difference
Water Index (NDWI) for water body extraction, supervised image classification technique for
vegetation mapping is used in the study. Remote sensing and GIS is most powerful technique
for this analysis. Some statistical methods related to analysis are also been applied.2021-09-01T00:00:00ZApplication of Remote Sensing and Geographical Information Systems in Ecotourism Development in Sustainable Manner: A Case Study of the Hugli Estuary and its EnvironsSultana, Farhinhttp://inet.vidyasagar.ac.in:8080/jspui/handle/123456789/58852021-02-25T05:01:47Z2020-10-11T00:00:00ZTitle: Application of Remote Sensing and Geographical Information Systems in Ecotourism Development in Sustainable Manner: A Case Study of the Hugli Estuary and its Environs
Authors: Sultana, Farhin
Abstract: The immense pressure of the mass tourism in the sensitive coastal region can damage
the environment and ecosystems. To protect the coastal resources and to control the inflow of
the tourists in the destination sites there is need an alternative form of tourism. In this present
work the study reveals a qualitative and quantative research in the coastal region by
ecotourism practices in a sustainable manner with the help of geospatial techniques. The
study assessing the potentialities, Beach Quality index, Tourism Climate Index, SWOT and
Sustainability of the each destination sites after the monitoring field survey, literature review
and remote sensing data uses on temporal basis. The results shows that GIS data base
management of several indicators can identify the problems and further improve the
destinations. The assessment of the potentialities of the each tourism destination sites reveals
that some destinations have the high potentiality to develop the ecotourism infrastructure and
some have the moderate to low potentialities in the region to develop the ecotourism
infrastructure. The assessment of the Beach Quality Index in the destination sites analysis the
beach quality on the basis of Environmental Quality and Human Welfare and Health. The
assessment is again consider the four (4) sub factor of Environmental Quality and remaining
four (4) sub factor of Human Welfare and Health in the present study. The results shows that
the Environmental Quality and Human Welfare and Health are excellent in some places but
some destinations are need some management strategies to conserve the natural habitats and
the coastal ecosystems. The estimation of the Tourism Climate Index in the coast al
destinations also shows that the November, December, January and February are the
favourable month for the tourist’s recreational activit ies. The month of May to July is
acceptable weather condition for the tourists to playing recreational activities in the coastal
region. The assessment of the SWOT analysis shows that the strengths, weaknesses,
opportunities and threats of the each destination sites. The results also analysis the main
hindrance of the each destination and develop the opportunities for promote the tourism
industry. Finally assessment the sustainability of the each destination sites by using the
sustainable indicators and allow the stakeholders and the other authority to practice the
environment friendly ecotourism under the strict coastal regulations of the region. The
present study also suggests some recommendation approach for further develop the
ecotourism infrastructure and continuation of tourism process in a restricted manner in the
sensitive fringed region.2020-10-11T00:00:00Z