The present study examined the relationship among various diversified datasets using remote sensi... more The present study examined the relationship among various diversified datasets using remote sensing and GIS. About 72% of the total forest area of Chhattisgarh state (59,935 km2) has shown a trend of negative change between the periods (1982 and 2006). Around 50% of the total forest fires of the state were found in the two tehsils of Narayanpur and Bijapur with two major forest fire hotspots. Approximately 86% of the total forest fire event of the state occurred in the category of “tropical mixed deciduous and dry deciduous forests” whereas the intensity of forest fire events was found 2.2 times in the category “tropical lowland forests, broadleaved, evergreen, < 1000 m” when it was compared with the category of “tropical mixed deciduous and dry deciduous forests.” The highest poverty percent was found in the tehsil of Bijapur (65.9%) which retains a significantly high percentage of the tribal population (73.1%). The adaptive capacity of Raipur tehsil (state capital) is high whereas it reduces significantly towards north and south from the state capital. The climate anomaly data evaluation for the year 2030 showed variation such as reduction in rainfall and increase in temperature will significantly maneuver the forest fire regime in future is a matter of serious concern. The outcomes of the present study would certainly guide the policymakers of the state of Chhattisgarh to prepare a meaningful, transparent and robust plan for the betterment of people keeping in mind of future climate change impact.
Leśne Prace Badawcze / Forest Research Papers, 2019
Analysing the forest fires events in climate change scenario is essential for protecting the fore... more Analysing the forest fires events in climate change scenario is essential for protecting the forest from further degradation. Geospatial technology is one of the advanced tools that has enormous capacity to evaluate the number of data sets simultaneously and to analyse the hidden relationships and trends. This study has evaluated the long term forest fire events with respect to India's state boundary, its seasonal monthly trend, all forest categories of LULC and future climate anomalies datasets over the Indian region. Furthermore, the spatial analysis revealed the trend and their relationship. The state wise evaluation of forest fire events reflects that the state of Mizoram has the highest forest fire frequency percentage (11.33%) followed by Chhattisgarh (9.39%), Orissa (9.18%), Madhya Pradesh (8.56%), Assam (8.45%), Maharashtra (7.35%), Manipur (6.94%), Andhra Pradesh (5.49%), Meghalaya (4.86%) and Telangana (4.23%) when compared to the total country's forest fire counts. The various LULC categories which represent the forest show some notable forest fire trends. The category ‘Deciduous Broadleaf Forest' retain the highest fire frequency equivalent to 38.1% followed by ‘Mixed Forest' (25.6%), ‘Evergreen Broadleaf Forest' (16.5%), ‘Deciduous Needle leaf Forest' (11.5%), ‘Shrub land' (5.5%), ‘Evergreen Needle leaf Forest' (1.5%) and ‘Plantations' (1.2%). Monthly seasonal variation of forest fire events reveal the highest forest fire frequency percentage in the month of ‘March' (55.4%) followed by ‘April' (28.2%), ‘February' (8.1%), ‘May' (6.7%), ‘June' (0.9%) and ‘January' (0.7%). The evaluation of future climate data for the year 2030 shows significant increase in forest fire seasonal temperature and abrupt annual rainfall pattern; therefore, future forest fires will be more intensified in large parts of India, whereas it will be more crucial for some of the states such as Orissa, Chhattisgarh, Mizoram, Assam and in the lower Sivalik range of Himalaya. The deciduous forests will further degrade in future. The highlight/results of this study have very high importance because such spatial relationship among the various datasets is analysed at the country level in view of the future climate scenario. Such analysis gives insight to the policymakers to make sustainable future plans for prioritization of the various state forests suffering from forest fire keeping in mind the future climate change scenario.
An integrated approach was adopted to evaluate the three threats that are a forest fire, deforest... more An integrated approach was adopted to evaluate the three threats that are a forest fire, deforestation and forest fragmentation using remote sensing and GIS data with a synergistic approach for spatial assessment and analysis.
Fire events are an increasing phenomenon these days due to the climate change. It is responsible ... more Fire events are an increasing phenomenon these days due to the climate change. It is responsible for forest degradation and habitat destruction. Changes in ecosystem processes are also noticed. The livelihood of tribal population is also threatened. Geospatial technologies along with Remotely Sensed data have enormous capability to evaluate the various diversified datasets and to examine their relationship. In this analysis, we have utilized the long term fire events at district level for the Orissa state of India and forest fire hotspots were identified. The fire pattern was analyzed with respect to the existing vegetation types, tribal population and topography to understand its association/relationship. Furthermore, it was evaluated with future climate change data for better comprehension of future forest fire scenario. The study reveals that Kandhamal, Raygada and Kalahandi district have highest fire frequency representing around 38% of the total Orissa fire events. The vegetation type " Tropical mixed deciduous and dry deciduous forests " and " Tropical lowland forests, broadleaved, evergreen, <1000m " occupy the geographical area roughly 43% whereas they retain fire percent equivalent to 70%. Approximately 70% of forest fire occurred in the area where tribal population was high to very high. The 60% of forest fire occurred where elevation was greater than 500 meters whereas 48% of fire occurred on moderate slopes. Our observation of future climate change scenario for the year 2030 reflects the increase in summer temperature and irregular rainfall pattern. Therefore, forest fire intensity will be more in future in the state of Orissa whereas it's intensity will be more severe in few of the district such as Kandhamal, Raygada, Kalahandi and Koraput which have significantly high forest fire events in present scenario. The outcomes of the present study would certainly guide the policymakers to prepare more effective plan to protect the forest which is main source of livelihood to the tribal population keeping in mind of future climate change impact for prioritization of various districts of state of Orissa suffering from forest fires.
In the present study, we evaluated the long term MODIS fire counts with the grid spacing 1° × 1°... more In the present study, we evaluated the long term MODIS fire counts with the grid spacing 1° × 1° over the part of continent of Asia. The grid show high percent of fire events was assigned to high risk grid. The study further evaluated three selected 2 × 2 window representing the risk grid. We have analyzed the fire events along various vegetation types as well as country boundary. The climate data set is further analyzed and statistical analysis was performed to understand the relationship with fire events. The first selected 2 × 2 window grid roughly represents over region of Punjab and Haryana state of India show 83% of total fire in the month of October and November due to agricultural residues burning. The result of the analysis of vegetation types with fire events manifest the vegetation types dominated by shifting cultivation which occupies the geographical area of 8% whereas they retain fire percent equivalent of 30% of total fire events. Country based fire events analysis shows that Burma fire events per unit geographical area were found roughly 3.5 times higher when compared with India. The analysis of fire events and climate data from February to July in grids over a part of the Asian region (central part of India) exhibit the 50% fire events was in the month of March with maximum temperature (°C), precipitation (mm) and solar radiation (KJ/m2/day) with range of (26.7–35.9), (6–26) and (22680–24366) respectively. The evaluation of Crammer’s V coefficient (CVC) values of precipitation, mean maximum temperature and solar radiation are found in decreasing order and in the range of 0.77–0.31. The highest CVC value of precipitation (0.77) shows that among all other climatic parameters the precipitation has very strong relationship to fire events. Remote sensing data (fire and climate) when coupled with various analyses in GIS domain reflect better understanding of their relationship which will greatly help in management/planning/ making strategy on fire prevention/control.
Agroforestry provides the foundation for climate-smart agriculture to withstand the extreme weath... more Agroforestry provides the foundation for climate-smart agriculture to withstand the extreme weather events. The aim of the present study was to identify the land of Samastipur, Bihar, India for agroforestry, based on GIS modeling concept utilizing various ancillary (soil fertility) and satellite data (DEM, wetness, NDVI and LULC) sets. This was achieved by integrating various thematic layers logically in GIS domain. Agroforestry suitability maps were generated for the Samastipur district of Bihar, India which showed 48.22 % as very high suitable, 22.83 % as high suitable, 23.32% as moderate suitable and 5.63% as low suitable. The cross evaluation of agroforestry suitability with LULC categories revealed that the 86.4 % (agriculture) and 30.2% (open area) of land fall into a very high agroforestry suitability category which provides the huge opportunity to harness agroforestry practices if utilized scientifically. Such analysis/results will certainly assist agroforestry policymakers and planner in the state of Bihar, India to implement and extend it to new areas. The potentiality of Remote Sensing and GIS can be exploited in accessing suitable land for agroforestry which will significantly help to rural poor people/farmers in ensuring food and ecological security, resilience in livelihoods.
We have examined the climate and forest fire data using Remote Sensing and GIS in the state of Hi... more We have examined the climate and forest fire data using Remote Sensing and GIS in the state of Himachal Pradesh and Uttarakhand states of India. The significant high forest fire events were observed in district of Pauri Garhwal (22.4%) followed by Naini Tal (16.4%), Tehri Garhwal (8.5%), Almora (7.7%), Chamoli (5.8%), Dehra Dun (4.6%), Uttarkashi (4.3%), Champawat (4.2%), Haridwar (3.6%), Una (3.4%), Bageshwar (3.1%), Udham Singh Nagar (2.9%), Sirmaur (2.7%), Solan (2.3%), Kangra (2.1%), Pithoragarh (1.7%) and Shimla (1.2%). The LULC forest category “Deciduous Broadleaf Forest” occupied 17.2% of total forest area and retain significantly high forest fire percent equivalent to 44.7% of total forest fire events. The study revealed that 79% of forest fire incidence was found in the month of April and May. The fire frequency was found highest in the month of April (among all months) whereas it was spread over the five grids (in the count) where the fire frequencies were greater than 100. The average monthly analysis (from January to June) for maximum temperature (°C), precipitation (mm), solar radiation (MJ/m^2), wind velocity (meter/sec.), wet-days frequency (number of days) and evapotranspiration (mm/day) were found to be in the range of (9.90 to 26.44), (26.06 to 134.71), (11738 to 24119), (1.397 to 2.237), (1.46 to 5.12) and (3.96 to 8.46) respectively. Rapid climate/weather severities which significantly enhance the forest fire events were observed in the month of April and May. The analysis of the Pearson Correlation Coefficient (PCC) values of climate parameters showed a significant correlation with forest fire events. The analysis of predicted (2050) climate anomalies data (RCP-6) for the month of April and annual precipitation manifest the significant rise in April temperature and reduction in annual precipitation observed over large part of high forest fire grids will certainly impact adversely to the future forest fire scenario.
Geospatial evaluation of various datasets is extremely important because it gives a better compre... more Geospatial evaluation of various datasets is extremely important because it gives a better comprehension of the past, present and future and can therefore be significantly utilized in effective decision making strategies. This study examined the relationships, using geospatial tools, between various diversified datasets such as land use/land cover (LULC), long term Normalized Difference Vegetation Index (NDVI) based changes, long term forest fire points, poverty percentage, tribal percentage, forest fire hotspots, climate change vulnerability, agricultural vulnerability and future (2030) climate change anomalies (RCP-6) of Jharkhand state, India, for a better understanding and knowledge of its vegetation health, LULC, poverty, tribal population and future climate change impact. The long term NDVI (1982-2006) evaluation revealed negative change trends in seven northwest districts of Jharkhand state, these were: Hazaribag, Ramgarh, Palamu, Lohardaga, Chatra, Garhwa and Latehar. The forests as well as the agriculture of these districts have lost their greenness during this period. The forest fire frequency events were found to be more pronounced in the land use/land cover of "tropical lowland forests, broadleaved, evergreen, <1000 m" category, and were roughly twice the intensity of the "tropical mixed deciduous and dry deciduous forests" category. In the nine districts of Jharkhand it was found that 40 % of the population was living below the poverty line which is around twice the national average. The highest poverty districts, in percentage, were: Garwah (53.93), Palamu (49.24), Latehar (47.99) and Chatra (46.2). The southwest and south of Jharkhand state shows a tribal population density of more than 40%. The climate change vulnerability was found to be highest in the district of Saraikela followed by Pashchim Singhbhum, whereas agricultural vulnerability was found to be highest in the district of Pashchim Singhbhum followed by Saraikela, Garhwa, Simdega, Latehar, Palamu and Lohardaga. The temperature anomalies prediction for the year 2030 shows an increasing trend in temperature with values of 0.8°C to 1°C in the state of Jharkhand. The highest increases were observed in the districts of Pashchim Singhbhum, Simdega and Saraikela. Based on these evaluations we can conclude that a few of the districts of Jharkhand, such as Pashchim Singhbhum, Garhwa, Palamu and Latehar need to be prioritized for development on an urgent basis. The outcomes of this study would certainly guide the policymakers to prepare more robust plans when keeping in mind the future climate change impacts for the prioritization of various districts of Jharkhand which suffer from extreme poverty, diminished livelihood and insignificant agricultural productivity for the betterment of the people of Jharkhand based on their adaptive capacity.
Unfortunately, in the original publication of the article, in Abstract and Results and discussion... more Unfortunately, in the original publication of the article, in Abstract and Results and discussion some percent values are written incorrectly. In Abstract the 4th sentence was written as '
The dynamic changes of forest fire events are due to the swing of climate parameter. Geospatial t... more The dynamic changes of forest fire events are due to the swing of climate parameter. Geospatial technology has strong capability to analyze various thematic datasets towards visualization of spatial/temporal pattern and plays a vital role in fire management efforts. This paper aims to analyze the climate and forest fire trend using Geospatial technology in the state of Orissa of India. The 84.5% of forest fire events are observed in the month of March and April and it is significantly high in the south of Kandhamal, east of Kalahandi, north of Rayagada and north of Gajapati district. The parameters which favour the forest fire events in the month of March onwards were observed. The Maximum temperature is showing an increasing trend from February to June whereas the increase is significantly high during March and April. The solar radiation increased to 144% in the month of March when compared with preceding month whereas relative humidity was decreased to 64% in the same month. The evaluation of Cramer V coefficient values of minimum temperature, solar radiation, maximum temperature and relative humidity are found to be 0.302, 0.327, 0.366 and 0.482 respectively. The relative humidity shows strong relationship with fire events. Such data analysis would help in safeguarding the forest.
Full article can be read using the given below link....
https://rdcu.be/YMfM
Agroforestry has tremendous potential for poverty alleviation, alternate food security instrument... more Agroforestry has tremendous potential for poverty alleviation, alternate food security instrument and attempts to improve quality of fallow and abandoned land. Nonetheless, with advent of new technologies the practices of agroforestry can be scaled up as technology potentially predicts areas which have relatively higher suitability. Satellite data harnessed through remote sensing and maneuvered through GIS offers a better decision support system and prioritization of forest area for higher productivity. The present study aims for identification of suitable area for agroforestry projects towards maximizing the outcome in terms of agriculture output and carbon sequestration capacity by generating integrated maps for Chakardharpur sub-division, West Singhbhum district of state of Jharkhand. A weight matrix was derived based upon field data and related research works to produce nitrogen, phosphorous, potassium mapping along with soil pH, organic carbon and sulphur content. Later, it was superimposed with remote sensing imageries/images, topographic maps and climatic datasets for integrated mapping in GIS to develop agroforestry suitability. It was found that 21.6 % areas have high suitability and within watersheds 22 sample points corresponding to some village was generated for making buffers. It was done to establish relationship of nearness of watershed areas with high suitability. The study highlighted the scope of geo-spatial technology agroforestry practices and in estimating prominent factors for its optimal productivity. It demands for diversions of forestry projects of areas which plunge in high suitability zones to optimize the outcome. The use of ancillary data in GIS domain can have gigantic potential to map the land and emerging as one significant dimension in food security and carbon sequestration targets.
In view of climate change scenario, the increasing population, higher food demand and deteriorati... more In view of climate change scenario, the increasing population, higher food demand and deteriorating land productivity are the key issues which need to be addressed in present time frame because it will be more critical in the future. The scientific evaluation of land for agroforestry is a step towards sustainability for achieving the socio-economic and environmental goal of the community. The objective of the present study was to investigate the suitability of land use/land cover of Lohardaga district of state of Jharkhand, India for agroforestry use based on FAO land suitability criteria utilizing Landsat-8 images (NDVI/wetness), ASTER DEM (elevation/slope/drainage and watershed), ancillary data source (rainfall/organic carbon/pH and nutrient status). The analysis of our study for agroforestry suitability reveals that 50.5% area as highly suitable (S1), 28.2% area as moderately suitable (S2), 20% area as marginally suitable (S3) and 1.3% area as not suitable (NS). Only 2.9% of the total land area is dominated by two season crop which is a matter of serious concern. The statistical analysis of the results reveals that the lands have huge potentiality for harnessing agroforestry crops if utilized scientifically. Such results will greatly help to the state level policymakers for achieving the national agroforestry policy goal for extending it to the new areas in the districts of Jharkhand.
Agroforestry system has the enormous capacity to achieve social, economic, and environmental goal... more Agroforestry system has the enormous capacity to achieve social, economic, and environmental goals by optimizing land productivity. The aim of the present study was to evaluate the land potentiality in India for agroforestry based on FAO land suitability criteria utilizing various land, soil, climate, and topographic themes. This was achieved in GIS Domain by integrating various thematic layers scientifically. The analysis of land potentiality in India for agroforestry suitability reveals 32.8% as highly suitable (S1), 40.4% moderately suitable (S2), 11.7% marginally suitable (S3), and 9.1% not suitable (NS). About 52% of land of India is under the cropland category. In addition, it revealed that the 46% of these cropland areas fall into high agroforestry suitable category “S1,” and provide huge opportunity for harnessing agroforestry practices. Furthermore, agroforestry suitability mapping in broad ecosystem and in different agroecological regions will assist various projects in India at the regional level. Such results will also boost the various objectives of the National Agroforestry Policy (2014, http://www.cafri.res.in/NAF_Policy.pdf) and policymakers of India where they need to extend it. The potential of geospatial technology can be exploited in the field of agroforestry for the benefit of rural poor people/farmers by ensuring food and ecological security, resilience in livelihoods, and can sustain extreme weather events such as droughts and climate change impact. Such type of research can be replicated in India at village level (local level) to state level (regional level) utilizing the significant themes which affect the agroforestry suitability. This will certainly fetch better results on ground and will significantly assist the management programs.
Background: The environment and habitat are the important aspects of the forest ecosystem. The co... more Background: The environment and habitat are the important aspects of the forest ecosystem. The continuous changes in the environment due to natural phenomenon or human actions have degraded the forest and wildlife habitat thus causing a decline in their population. Therefore it is important to study wildlife habitat in order to ensure their survival. In this regard, application of Remote Sensing and Geographic Information System has been widely accepted as a tool which has immense significance in wildlife habitat suitability modeling and mapping. Maps derived from analysis of remote sensing data and modeling in GIS are highly useful in making the strategies in wildlife management and conservation planning. Objectives: The objectives of the study are to identify the suitable habitat for wild life and conservation hotspot grids were delineated which require immediate attention. Methods/Statistical analysis: The wildlife habitat suitability parameter based on forest cover, agriculture with settlement, forest fires, roads, streams and mines were analyzed. The statistical method such as pairwise comparison was used to evaluate the weightage of each parameter which helped to determine the wildlife habitat suitability modeling and mapping. Findings: The study of wildlife habitat suitability mapping in Saranda forest division reveals 42% of the grid equal to 1898 has very high suitability for wild life. The conservation hotspot reserve grid based on contiguous patch was identified within the very high wildlife suitability habitat was found to be 925 (49%). Application/Improvements: Conservation effort can be focused based on the above study and will assist in policy related decision making.
Aerial imagery have long been used for forest Inventories due to the high correlation between tre... more Aerial imagery have long been used for forest Inventories due to the high correlation between tree height and forest biophysical properties to determine the vertical canopy structure which is an important variable in forest inventories. The development in photogrammetric softwares and large availability of aerial imagery has carved the path in 3D mapping and has accelerated significantly the use of photogrammetry in forest inventory. There is tremendous capacity of 3D mapping which has been recognized in research, development and management of forest ecosystem. The aim of this article is to provide insights of 3D mapping (photogrammetry including Lidar) in forest-related disciplines. We utilizing the satellite stereo pair and LiDAR point cloud as a case study for producing the anaglyph map and Canopy Height Model (CHM) respectively. The study also revealed the area verses canopy height graph. Present study has some strength because it was demonstrated the use of advance software module of ARC/GIS and Erdas Imagine for 3D mapping using Photogrammetry and LiDAR data sets which is highly useful in forest management, planning and decision making. .
This study has analysed the Landsat 8 OLI data (December 2016) to delineate the various land use/... more This study has analysed the Landsat 8 OLI data (December 2016) to delineate the various land use/land cover classes of the
area which will be submerged by the proposed Daudhan/Greater Gangau Dam, which is part of the proposed Ken Betwa
River Link Project (in the Madhya Pradesh state of India) and also the area likely to be submerged in the Panna Tiger Reserve
(PTR). The proposed area of submergence was computed at various full reservoir lengths (FRL), 278 m, 283 m, 288 m, 289 m
and 293 m. Similarly the area of submergence for the Panna Tiger Reserve was computed at the mentioned FRLs. It was
concluded that a large part of the Panna Tiger Reserve would be submerged and habitat of various animals and plants would
be under threat. In comparison with the figures given in the Environmental Impact Assessment certain serious discrepancies
and weaknesses were detected and it was felt that they should have been addressed. The results were compared with the EIA
– EMP report of the Ken-Betwa link project, Phase 1, prepared by Agricultural Finance Corporation Limited for the National
Water Development Agency (Ministry of Water Resources, River Development and Ganga Rejuvenation, Government of India).
A proper evaluation of the negative impacts would help when making relevant decisions and appropriate steps to ensure that
the loss is kept to a minimum. Safeguarding the biodiversity of forests and wildlife habitats should be the priority as their loss
is irreplaceable. Geospatial technology helps in studying the overall spatial view of the proposed submergence area and the
visualization gives a clear picture of the likely scenario in the future. It would assist in decision making and mitigation measures.
Crime is a social stigma which needs to be addressed beyond
talks. In developed country Geospatia... more Crime is a social stigma which needs to be addressed beyond talks. In developed country Geospatial technology has become well established within the criminology and forensic fields in recent past. In order to achieve this proper database of various crimes (state/ district level) should be available for decision making. The present study was an attempt made to study the district wise crime data (IPC crime registered) for murder, rape, kidnapping, dacoity, burglary, theft and riots of state of Jharkhand for the year 2013 to understand the crime trend. We have generated various maps including crime density map of Jharkhand based on crime types using ARC/ GIS Software and MS EXCEL. The crime density such as murder, rape, kidnaping and riots were found in the range of (2.2 to 17.8), (1.6 to 12.6), (2.3 to 10.4) and (1.0 to 17.5) respectively. Murder crime density was highest in Gumla district whereas it was found to be lowest in Gridih district. Sahebganj district has high crime density for rape and kidnapping. Palamu district had low crime density in rape, whereas Ranchi district recorded low crime density in kidnapping. Crime density for riots was found lowest for district Simdega whereas highest for Koderma. The Indian police and law enforcement departments has not yet exploited the GIS aspect which will fetch better result as far as crime control is considered.
Monitoring and management of forest fire is imperative in India where 50% of forest cover is pron... more Monitoring and management of forest fire is imperative in India where 50% of forest cover is prone to the fire. The study aims for applying the geospatial technology towards forest fire characterization and evaluation of relationship with meteorological thematic layers. Spatial analysis of forest fires in the state of Arunachal Pradesh was carried out based upon the decadal (2008–2016) forest fire count datasets, which was assessed for spatial variability over the known Himalayan biodiversity hotspot in diverse geographical and socio-economic gradients. Result suggested that Kameng districts had maximum fire incidences (25.2%) whereas it has 15.2% of state forest, established the districts as ‘forest fire hotspot’ in the state. Maximum number of incidences (88%) occurred in areas of low elevation (< 1500 m). There was high correlation with socio-economy where 42.3% forest fire points falls in high poverty index areas and 73% of fire incidences in the areas having population density 6–50. All districts showed high fire incidences, therefore an urgent intervention is greatly required by the policy makers towards conservation and management of forest fire prevention and control by adopting focused intervention, strategic allocation of limited resources in potent areas in order to safeguard Himalayan region of highest biodiversity.
Forest fires are a major threat to the existence of forests these days due to climate change and ... more Forest fires are a major threat to the existence of forests these days due to climate change and global warming scenario. The present study utilizes geospatial techniques to analyze the incidences of forest fires events from the year 2005 to 2016 in the Jharkhand state of India. Forest fire hotspot areas within the state were identified. The analysis of the datasets reveals that approximately 89% of the forest fires occur in the month of March and April. From 1 st March to 10 th March the fire starts in North East part of Jharkhand forest because of high wind speed and it continues till the end of March. Later, it intensifies to the south of Jharkhand in Paschim (west) Singhbhum district from 11 th to 20 th March. From 21 st to 31 st March the forest fire starts in North West part of Jharkhand in Palamu district which it continues along with Paschim (west) Singhbhum district till the end of April. Three major locations were identified in Jharkhand forest as forest fire hotspot. Statistical analysis (Cramer's V coefficient) was performed to test the scale / magnitude of association of forest fire with driving factor (meteorological parameters). The range of CVC value varied between 0.74 to 0.32 whereas rainfall retain the highest value 0.74 means it is one of the strongest driving factor among all other environmental parameter contribute to forest fire events. The study of forest fire event analysis, its correlation of trend and its interrelationship with environmental/meteorological parameters gives better comprehension for forest fire events thus helps in mitigation, control and prevention to safeguard our precious forest and the environment.
The present study examined the relationship among various diversified datasets using remote sensi... more The present study examined the relationship among various diversified datasets using remote sensing and GIS. About 72% of the total forest area of Chhattisgarh state (59,935 km2) has shown a trend of negative change between the periods (1982 and 2006). Around 50% of the total forest fires of the state were found in the two tehsils of Narayanpur and Bijapur with two major forest fire hotspots. Approximately 86% of the total forest fire event of the state occurred in the category of “tropical mixed deciduous and dry deciduous forests” whereas the intensity of forest fire events was found 2.2 times in the category “tropical lowland forests, broadleaved, evergreen, < 1000 m” when it was compared with the category of “tropical mixed deciduous and dry deciduous forests.” The highest poverty percent was found in the tehsil of Bijapur (65.9%) which retains a significantly high percentage of the tribal population (73.1%). The adaptive capacity of Raipur tehsil (state capital) is high whereas it reduces significantly towards north and south from the state capital. The climate anomaly data evaluation for the year 2030 showed variation such as reduction in rainfall and increase in temperature will significantly maneuver the forest fire regime in future is a matter of serious concern. The outcomes of the present study would certainly guide the policymakers of the state of Chhattisgarh to prepare a meaningful, transparent and robust plan for the betterment of people keeping in mind of future climate change impact.
Leśne Prace Badawcze / Forest Research Papers, 2019
Analysing the forest fires events in climate change scenario is essential for protecting the fore... more Analysing the forest fires events in climate change scenario is essential for protecting the forest from further degradation. Geospatial technology is one of the advanced tools that has enormous capacity to evaluate the number of data sets simultaneously and to analyse the hidden relationships and trends. This study has evaluated the long term forest fire events with respect to India's state boundary, its seasonal monthly trend, all forest categories of LULC and future climate anomalies datasets over the Indian region. Furthermore, the spatial analysis revealed the trend and their relationship. The state wise evaluation of forest fire events reflects that the state of Mizoram has the highest forest fire frequency percentage (11.33%) followed by Chhattisgarh (9.39%), Orissa (9.18%), Madhya Pradesh (8.56%), Assam (8.45%), Maharashtra (7.35%), Manipur (6.94%), Andhra Pradesh (5.49%), Meghalaya (4.86%) and Telangana (4.23%) when compared to the total country's forest fire counts. The various LULC categories which represent the forest show some notable forest fire trends. The category ‘Deciduous Broadleaf Forest' retain the highest fire frequency equivalent to 38.1% followed by ‘Mixed Forest' (25.6%), ‘Evergreen Broadleaf Forest' (16.5%), ‘Deciduous Needle leaf Forest' (11.5%), ‘Shrub land' (5.5%), ‘Evergreen Needle leaf Forest' (1.5%) and ‘Plantations' (1.2%). Monthly seasonal variation of forest fire events reveal the highest forest fire frequency percentage in the month of ‘March' (55.4%) followed by ‘April' (28.2%), ‘February' (8.1%), ‘May' (6.7%), ‘June' (0.9%) and ‘January' (0.7%). The evaluation of future climate data for the year 2030 shows significant increase in forest fire seasonal temperature and abrupt annual rainfall pattern; therefore, future forest fires will be more intensified in large parts of India, whereas it will be more crucial for some of the states such as Orissa, Chhattisgarh, Mizoram, Assam and in the lower Sivalik range of Himalaya. The deciduous forests will further degrade in future. The highlight/results of this study have very high importance because such spatial relationship among the various datasets is analysed at the country level in view of the future climate scenario. Such analysis gives insight to the policymakers to make sustainable future plans for prioritization of the various state forests suffering from forest fire keeping in mind the future climate change scenario.
An integrated approach was adopted to evaluate the three threats that are a forest fire, deforest... more An integrated approach was adopted to evaluate the three threats that are a forest fire, deforestation and forest fragmentation using remote sensing and GIS data with a synergistic approach for spatial assessment and analysis.
Fire events are an increasing phenomenon these days due to the climate change. It is responsible ... more Fire events are an increasing phenomenon these days due to the climate change. It is responsible for forest degradation and habitat destruction. Changes in ecosystem processes are also noticed. The livelihood of tribal population is also threatened. Geospatial technologies along with Remotely Sensed data have enormous capability to evaluate the various diversified datasets and to examine their relationship. In this analysis, we have utilized the long term fire events at district level for the Orissa state of India and forest fire hotspots were identified. The fire pattern was analyzed with respect to the existing vegetation types, tribal population and topography to understand its association/relationship. Furthermore, it was evaluated with future climate change data for better comprehension of future forest fire scenario. The study reveals that Kandhamal, Raygada and Kalahandi district have highest fire frequency representing around 38% of the total Orissa fire events. The vegetation type " Tropical mixed deciduous and dry deciduous forests " and " Tropical lowland forests, broadleaved, evergreen, <1000m " occupy the geographical area roughly 43% whereas they retain fire percent equivalent to 70%. Approximately 70% of forest fire occurred in the area where tribal population was high to very high. The 60% of forest fire occurred where elevation was greater than 500 meters whereas 48% of fire occurred on moderate slopes. Our observation of future climate change scenario for the year 2030 reflects the increase in summer temperature and irregular rainfall pattern. Therefore, forest fire intensity will be more in future in the state of Orissa whereas it's intensity will be more severe in few of the district such as Kandhamal, Raygada, Kalahandi and Koraput which have significantly high forest fire events in present scenario. The outcomes of the present study would certainly guide the policymakers to prepare more effective plan to protect the forest which is main source of livelihood to the tribal population keeping in mind of future climate change impact for prioritization of various districts of state of Orissa suffering from forest fires.
In the present study, we evaluated the long term MODIS fire counts with the grid spacing 1° × 1°... more In the present study, we evaluated the long term MODIS fire counts with the grid spacing 1° × 1° over the part of continent of Asia. The grid show high percent of fire events was assigned to high risk grid. The study further evaluated three selected 2 × 2 window representing the risk grid. We have analyzed the fire events along various vegetation types as well as country boundary. The climate data set is further analyzed and statistical analysis was performed to understand the relationship with fire events. The first selected 2 × 2 window grid roughly represents over region of Punjab and Haryana state of India show 83% of total fire in the month of October and November due to agricultural residues burning. The result of the analysis of vegetation types with fire events manifest the vegetation types dominated by shifting cultivation which occupies the geographical area of 8% whereas they retain fire percent equivalent of 30% of total fire events. Country based fire events analysis shows that Burma fire events per unit geographical area were found roughly 3.5 times higher when compared with India. The analysis of fire events and climate data from February to July in grids over a part of the Asian region (central part of India) exhibit the 50% fire events was in the month of March with maximum temperature (°C), precipitation (mm) and solar radiation (KJ/m2/day) with range of (26.7–35.9), (6–26) and (22680–24366) respectively. The evaluation of Crammer’s V coefficient (CVC) values of precipitation, mean maximum temperature and solar radiation are found in decreasing order and in the range of 0.77–0.31. The highest CVC value of precipitation (0.77) shows that among all other climatic parameters the precipitation has very strong relationship to fire events. Remote sensing data (fire and climate) when coupled with various analyses in GIS domain reflect better understanding of their relationship which will greatly help in management/planning/ making strategy on fire prevention/control.
Agroforestry provides the foundation for climate-smart agriculture to withstand the extreme weath... more Agroforestry provides the foundation for climate-smart agriculture to withstand the extreme weather events. The aim of the present study was to identify the land of Samastipur, Bihar, India for agroforestry, based on GIS modeling concept utilizing various ancillary (soil fertility) and satellite data (DEM, wetness, NDVI and LULC) sets. This was achieved by integrating various thematic layers logically in GIS domain. Agroforestry suitability maps were generated for the Samastipur district of Bihar, India which showed 48.22 % as very high suitable, 22.83 % as high suitable, 23.32% as moderate suitable and 5.63% as low suitable. The cross evaluation of agroforestry suitability with LULC categories revealed that the 86.4 % (agriculture) and 30.2% (open area) of land fall into a very high agroforestry suitability category which provides the huge opportunity to harness agroforestry practices if utilized scientifically. Such analysis/results will certainly assist agroforestry policymakers and planner in the state of Bihar, India to implement and extend it to new areas. The potentiality of Remote Sensing and GIS can be exploited in accessing suitable land for agroforestry which will significantly help to rural poor people/farmers in ensuring food and ecological security, resilience in livelihoods.
We have examined the climate and forest fire data using Remote Sensing and GIS in the state of Hi... more We have examined the climate and forest fire data using Remote Sensing and GIS in the state of Himachal Pradesh and Uttarakhand states of India. The significant high forest fire events were observed in district of Pauri Garhwal (22.4%) followed by Naini Tal (16.4%), Tehri Garhwal (8.5%), Almora (7.7%), Chamoli (5.8%), Dehra Dun (4.6%), Uttarkashi (4.3%), Champawat (4.2%), Haridwar (3.6%), Una (3.4%), Bageshwar (3.1%), Udham Singh Nagar (2.9%), Sirmaur (2.7%), Solan (2.3%), Kangra (2.1%), Pithoragarh (1.7%) and Shimla (1.2%). The LULC forest category “Deciduous Broadleaf Forest” occupied 17.2% of total forest area and retain significantly high forest fire percent equivalent to 44.7% of total forest fire events. The study revealed that 79% of forest fire incidence was found in the month of April and May. The fire frequency was found highest in the month of April (among all months) whereas it was spread over the five grids (in the count) where the fire frequencies were greater than 100. The average monthly analysis (from January to June) for maximum temperature (°C), precipitation (mm), solar radiation (MJ/m^2), wind velocity (meter/sec.), wet-days frequency (number of days) and evapotranspiration (mm/day) were found to be in the range of (9.90 to 26.44), (26.06 to 134.71), (11738 to 24119), (1.397 to 2.237), (1.46 to 5.12) and (3.96 to 8.46) respectively. Rapid climate/weather severities which significantly enhance the forest fire events were observed in the month of April and May. The analysis of the Pearson Correlation Coefficient (PCC) values of climate parameters showed a significant correlation with forest fire events. The analysis of predicted (2050) climate anomalies data (RCP-6) for the month of April and annual precipitation manifest the significant rise in April temperature and reduction in annual precipitation observed over large part of high forest fire grids will certainly impact adversely to the future forest fire scenario.
Geospatial evaluation of various datasets is extremely important because it gives a better compre... more Geospatial evaluation of various datasets is extremely important because it gives a better comprehension of the past, present and future and can therefore be significantly utilized in effective decision making strategies. This study examined the relationships, using geospatial tools, between various diversified datasets such as land use/land cover (LULC), long term Normalized Difference Vegetation Index (NDVI) based changes, long term forest fire points, poverty percentage, tribal percentage, forest fire hotspots, climate change vulnerability, agricultural vulnerability and future (2030) climate change anomalies (RCP-6) of Jharkhand state, India, for a better understanding and knowledge of its vegetation health, LULC, poverty, tribal population and future climate change impact. The long term NDVI (1982-2006) evaluation revealed negative change trends in seven northwest districts of Jharkhand state, these were: Hazaribag, Ramgarh, Palamu, Lohardaga, Chatra, Garhwa and Latehar. The forests as well as the agriculture of these districts have lost their greenness during this period. The forest fire frequency events were found to be more pronounced in the land use/land cover of "tropical lowland forests, broadleaved, evergreen, <1000 m" category, and were roughly twice the intensity of the "tropical mixed deciduous and dry deciduous forests" category. In the nine districts of Jharkhand it was found that 40 % of the population was living below the poverty line which is around twice the national average. The highest poverty districts, in percentage, were: Garwah (53.93), Palamu (49.24), Latehar (47.99) and Chatra (46.2). The southwest and south of Jharkhand state shows a tribal population density of more than 40%. The climate change vulnerability was found to be highest in the district of Saraikela followed by Pashchim Singhbhum, whereas agricultural vulnerability was found to be highest in the district of Pashchim Singhbhum followed by Saraikela, Garhwa, Simdega, Latehar, Palamu and Lohardaga. The temperature anomalies prediction for the year 2030 shows an increasing trend in temperature with values of 0.8°C to 1°C in the state of Jharkhand. The highest increases were observed in the districts of Pashchim Singhbhum, Simdega and Saraikela. Based on these evaluations we can conclude that a few of the districts of Jharkhand, such as Pashchim Singhbhum, Garhwa, Palamu and Latehar need to be prioritized for development on an urgent basis. The outcomes of this study would certainly guide the policymakers to prepare more robust plans when keeping in mind the future climate change impacts for the prioritization of various districts of Jharkhand which suffer from extreme poverty, diminished livelihood and insignificant agricultural productivity for the betterment of the people of Jharkhand based on their adaptive capacity.
Unfortunately, in the original publication of the article, in Abstract and Results and discussion... more Unfortunately, in the original publication of the article, in Abstract and Results and discussion some percent values are written incorrectly. In Abstract the 4th sentence was written as '
The dynamic changes of forest fire events are due to the swing of climate parameter. Geospatial t... more The dynamic changes of forest fire events are due to the swing of climate parameter. Geospatial technology has strong capability to analyze various thematic datasets towards visualization of spatial/temporal pattern and plays a vital role in fire management efforts. This paper aims to analyze the climate and forest fire trend using Geospatial technology in the state of Orissa of India. The 84.5% of forest fire events are observed in the month of March and April and it is significantly high in the south of Kandhamal, east of Kalahandi, north of Rayagada and north of Gajapati district. The parameters which favour the forest fire events in the month of March onwards were observed. The Maximum temperature is showing an increasing trend from February to June whereas the increase is significantly high during March and April. The solar radiation increased to 144% in the month of March when compared with preceding month whereas relative humidity was decreased to 64% in the same month. The evaluation of Cramer V coefficient values of minimum temperature, solar radiation, maximum temperature and relative humidity are found to be 0.302, 0.327, 0.366 and 0.482 respectively. The relative humidity shows strong relationship with fire events. Such data analysis would help in safeguarding the forest.
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Agroforestry has tremendous potential for poverty alleviation, alternate food security instrument... more Agroforestry has tremendous potential for poverty alleviation, alternate food security instrument and attempts to improve quality of fallow and abandoned land. Nonetheless, with advent of new technologies the practices of agroforestry can be scaled up as technology potentially predicts areas which have relatively higher suitability. Satellite data harnessed through remote sensing and maneuvered through GIS offers a better decision support system and prioritization of forest area for higher productivity. The present study aims for identification of suitable area for agroforestry projects towards maximizing the outcome in terms of agriculture output and carbon sequestration capacity by generating integrated maps for Chakardharpur sub-division, West Singhbhum district of state of Jharkhand. A weight matrix was derived based upon field data and related research works to produce nitrogen, phosphorous, potassium mapping along with soil pH, organic carbon and sulphur content. Later, it was superimposed with remote sensing imageries/images, topographic maps and climatic datasets for integrated mapping in GIS to develop agroforestry suitability. It was found that 21.6 % areas have high suitability and within watersheds 22 sample points corresponding to some village was generated for making buffers. It was done to establish relationship of nearness of watershed areas with high suitability. The study highlighted the scope of geo-spatial technology agroforestry practices and in estimating prominent factors for its optimal productivity. It demands for diversions of forestry projects of areas which plunge in high suitability zones to optimize the outcome. The use of ancillary data in GIS domain can have gigantic potential to map the land and emerging as one significant dimension in food security and carbon sequestration targets.
In view of climate change scenario, the increasing population, higher food demand and deteriorati... more In view of climate change scenario, the increasing population, higher food demand and deteriorating land productivity are the key issues which need to be addressed in present time frame because it will be more critical in the future. The scientific evaluation of land for agroforestry is a step towards sustainability for achieving the socio-economic and environmental goal of the community. The objective of the present study was to investigate the suitability of land use/land cover of Lohardaga district of state of Jharkhand, India for agroforestry use based on FAO land suitability criteria utilizing Landsat-8 images (NDVI/wetness), ASTER DEM (elevation/slope/drainage and watershed), ancillary data source (rainfall/organic carbon/pH and nutrient status). The analysis of our study for agroforestry suitability reveals that 50.5% area as highly suitable (S1), 28.2% area as moderately suitable (S2), 20% area as marginally suitable (S3) and 1.3% area as not suitable (NS). Only 2.9% of the total land area is dominated by two season crop which is a matter of serious concern. The statistical analysis of the results reveals that the lands have huge potentiality for harnessing agroforestry crops if utilized scientifically. Such results will greatly help to the state level policymakers for achieving the national agroforestry policy goal for extending it to the new areas in the districts of Jharkhand.
Agroforestry system has the enormous capacity to achieve social, economic, and environmental goal... more Agroforestry system has the enormous capacity to achieve social, economic, and environmental goals by optimizing land productivity. The aim of the present study was to evaluate the land potentiality in India for agroforestry based on FAO land suitability criteria utilizing various land, soil, climate, and topographic themes. This was achieved in GIS Domain by integrating various thematic layers scientifically. The analysis of land potentiality in India for agroforestry suitability reveals 32.8% as highly suitable (S1), 40.4% moderately suitable (S2), 11.7% marginally suitable (S3), and 9.1% not suitable (NS). About 52% of land of India is under the cropland category. In addition, it revealed that the 46% of these cropland areas fall into high agroforestry suitable category “S1,” and provide huge opportunity for harnessing agroforestry practices. Furthermore, agroforestry suitability mapping in broad ecosystem and in different agroecological regions will assist various projects in India at the regional level. Such results will also boost the various objectives of the National Agroforestry Policy (2014, http://www.cafri.res.in/NAF_Policy.pdf) and policymakers of India where they need to extend it. The potential of geospatial technology can be exploited in the field of agroforestry for the benefit of rural poor people/farmers by ensuring food and ecological security, resilience in livelihoods, and can sustain extreme weather events such as droughts and climate change impact. Such type of research can be replicated in India at village level (local level) to state level (regional level) utilizing the significant themes which affect the agroforestry suitability. This will certainly fetch better results on ground and will significantly assist the management programs.
Background: The environment and habitat are the important aspects of the forest ecosystem. The co... more Background: The environment and habitat are the important aspects of the forest ecosystem. The continuous changes in the environment due to natural phenomenon or human actions have degraded the forest and wildlife habitat thus causing a decline in their population. Therefore it is important to study wildlife habitat in order to ensure their survival. In this regard, application of Remote Sensing and Geographic Information System has been widely accepted as a tool which has immense significance in wildlife habitat suitability modeling and mapping. Maps derived from analysis of remote sensing data and modeling in GIS are highly useful in making the strategies in wildlife management and conservation planning. Objectives: The objectives of the study are to identify the suitable habitat for wild life and conservation hotspot grids were delineated which require immediate attention. Methods/Statistical analysis: The wildlife habitat suitability parameter based on forest cover, agriculture with settlement, forest fires, roads, streams and mines were analyzed. The statistical method such as pairwise comparison was used to evaluate the weightage of each parameter which helped to determine the wildlife habitat suitability modeling and mapping. Findings: The study of wildlife habitat suitability mapping in Saranda forest division reveals 42% of the grid equal to 1898 has very high suitability for wild life. The conservation hotspot reserve grid based on contiguous patch was identified within the very high wildlife suitability habitat was found to be 925 (49%). Application/Improvements: Conservation effort can be focused based on the above study and will assist in policy related decision making.
Aerial imagery have long been used for forest Inventories due to the high correlation between tre... more Aerial imagery have long been used for forest Inventories due to the high correlation between tree height and forest biophysical properties to determine the vertical canopy structure which is an important variable in forest inventories. The development in photogrammetric softwares and large availability of aerial imagery has carved the path in 3D mapping and has accelerated significantly the use of photogrammetry in forest inventory. There is tremendous capacity of 3D mapping which has been recognized in research, development and management of forest ecosystem. The aim of this article is to provide insights of 3D mapping (photogrammetry including Lidar) in forest-related disciplines. We utilizing the satellite stereo pair and LiDAR point cloud as a case study for producing the anaglyph map and Canopy Height Model (CHM) respectively. The study also revealed the area verses canopy height graph. Present study has some strength because it was demonstrated the use of advance software module of ARC/GIS and Erdas Imagine for 3D mapping using Photogrammetry and LiDAR data sets which is highly useful in forest management, planning and decision making. .
This study has analysed the Landsat 8 OLI data (December 2016) to delineate the various land use/... more This study has analysed the Landsat 8 OLI data (December 2016) to delineate the various land use/land cover classes of the
area which will be submerged by the proposed Daudhan/Greater Gangau Dam, which is part of the proposed Ken Betwa
River Link Project (in the Madhya Pradesh state of India) and also the area likely to be submerged in the Panna Tiger Reserve
(PTR). The proposed area of submergence was computed at various full reservoir lengths (FRL), 278 m, 283 m, 288 m, 289 m
and 293 m. Similarly the area of submergence for the Panna Tiger Reserve was computed at the mentioned FRLs. It was
concluded that a large part of the Panna Tiger Reserve would be submerged and habitat of various animals and plants would
be under threat. In comparison with the figures given in the Environmental Impact Assessment certain serious discrepancies
and weaknesses were detected and it was felt that they should have been addressed. The results were compared with the EIA
– EMP report of the Ken-Betwa link project, Phase 1, prepared by Agricultural Finance Corporation Limited for the National
Water Development Agency (Ministry of Water Resources, River Development and Ganga Rejuvenation, Government of India).
A proper evaluation of the negative impacts would help when making relevant decisions and appropriate steps to ensure that
the loss is kept to a minimum. Safeguarding the biodiversity of forests and wildlife habitats should be the priority as their loss
is irreplaceable. Geospatial technology helps in studying the overall spatial view of the proposed submergence area and the
visualization gives a clear picture of the likely scenario in the future. It would assist in decision making and mitigation measures.
Crime is a social stigma which needs to be addressed beyond
talks. In developed country Geospatia... more Crime is a social stigma which needs to be addressed beyond talks. In developed country Geospatial technology has become well established within the criminology and forensic fields in recent past. In order to achieve this proper database of various crimes (state/ district level) should be available for decision making. The present study was an attempt made to study the district wise crime data (IPC crime registered) for murder, rape, kidnapping, dacoity, burglary, theft and riots of state of Jharkhand for the year 2013 to understand the crime trend. We have generated various maps including crime density map of Jharkhand based on crime types using ARC/ GIS Software and MS EXCEL. The crime density such as murder, rape, kidnaping and riots were found in the range of (2.2 to 17.8), (1.6 to 12.6), (2.3 to 10.4) and (1.0 to 17.5) respectively. Murder crime density was highest in Gumla district whereas it was found to be lowest in Gridih district. Sahebganj district has high crime density for rape and kidnapping. Palamu district had low crime density in rape, whereas Ranchi district recorded low crime density in kidnapping. Crime density for riots was found lowest for district Simdega whereas highest for Koderma. The Indian police and law enforcement departments has not yet exploited the GIS aspect which will fetch better result as far as crime control is considered.
Monitoring and management of forest fire is imperative in India where 50% of forest cover is pron... more Monitoring and management of forest fire is imperative in India where 50% of forest cover is prone to the fire. The study aims for applying the geospatial technology towards forest fire characterization and evaluation of relationship with meteorological thematic layers. Spatial analysis of forest fires in the state of Arunachal Pradesh was carried out based upon the decadal (2008–2016) forest fire count datasets, which was assessed for spatial variability over the known Himalayan biodiversity hotspot in diverse geographical and socio-economic gradients. Result suggested that Kameng districts had maximum fire incidences (25.2%) whereas it has 15.2% of state forest, established the districts as ‘forest fire hotspot’ in the state. Maximum number of incidences (88%) occurred in areas of low elevation (< 1500 m). There was high correlation with socio-economy where 42.3% forest fire points falls in high poverty index areas and 73% of fire incidences in the areas having population density 6–50. All districts showed high fire incidences, therefore an urgent intervention is greatly required by the policy makers towards conservation and management of forest fire prevention and control by adopting focused intervention, strategic allocation of limited resources in potent areas in order to safeguard Himalayan region of highest biodiversity.
Forest fires are a major threat to the existence of forests these days due to climate change and ... more Forest fires are a major threat to the existence of forests these days due to climate change and global warming scenario. The present study utilizes geospatial techniques to analyze the incidences of forest fires events from the year 2005 to 2016 in the Jharkhand state of India. Forest fire hotspot areas within the state were identified. The analysis of the datasets reveals that approximately 89% of the forest fires occur in the month of March and April. From 1 st March to 10 th March the fire starts in North East part of Jharkhand forest because of high wind speed and it continues till the end of March. Later, it intensifies to the south of Jharkhand in Paschim (west) Singhbhum district from 11 th to 20 th March. From 21 st to 31 st March the forest fire starts in North West part of Jharkhand in Palamu district which it continues along with Paschim (west) Singhbhum district till the end of April. Three major locations were identified in Jharkhand forest as forest fire hotspot. Statistical analysis (Cramer's V coefficient) was performed to test the scale / magnitude of association of forest fire with driving factor (meteorological parameters). The range of CVC value varied between 0.74 to 0.32 whereas rainfall retain the highest value 0.74 means it is one of the strongest driving factor among all other environmental parameter contribute to forest fire events. The study of forest fire event analysis, its correlation of trend and its interrelationship with environmental/meteorological parameters gives better comprehension for forest fire events thus helps in mitigation, control and prevention to safeguard our precious forest and the environment.
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area which will be submerged by the proposed Daudhan/Greater Gangau Dam, which is part of the proposed Ken Betwa
River Link Project (in the Madhya Pradesh state of India) and also the area likely to be submerged in the Panna Tiger Reserve
(PTR). The proposed area of submergence was computed at various full reservoir lengths (FRL), 278 m, 283 m, 288 m, 289 m
and 293 m. Similarly the area of submergence for the Panna Tiger Reserve was computed at the mentioned FRLs. It was
concluded that a large part of the Panna Tiger Reserve would be submerged and habitat of various animals and plants would
be under threat. In comparison with the figures given in the Environmental Impact Assessment certain serious discrepancies
and weaknesses were detected and it was felt that they should have been addressed. The results were compared with the EIA
– EMP report of the Ken-Betwa link project, Phase 1, prepared by Agricultural Finance Corporation Limited for the National
Water Development Agency (Ministry of Water Resources, River Development and Ganga Rejuvenation, Government of India).
A proper evaluation of the negative impacts would help when making relevant decisions and appropriate steps to ensure that
the loss is kept to a minimum. Safeguarding the biodiversity of forests and wildlife habitats should be the priority as their loss
is irreplaceable. Geospatial technology helps in studying the overall spatial view of the proposed submergence area and the
visualization gives a clear picture of the likely scenario in the future. It would assist in decision making and mitigation measures.
talks. In developed country Geospatial technology has become
well established within the criminology and forensic fields in
recent past. In order to achieve this proper database of various
crimes (state/ district level) should be available for decision
making. The present study was an attempt made to study
the district wise crime data (IPC crime registered) for murder,
rape, kidnapping, dacoity, burglary, theft and riots of state of
Jharkhand for the year 2013 to understand the crime trend. We
have generated various maps including crime density map of
Jharkhand based on crime types using ARC/ GIS Software and
MS EXCEL. The crime density such as murder, rape, kidnaping
and riots were found in the range of (2.2 to 17.8), (1.6 to 12.6),
(2.3 to 10.4) and (1.0 to 17.5) respectively. Murder crime density
was highest in Gumla district whereas it was found to be lowest
in Gridih district. Sahebganj district has high crime density for
rape and kidnapping. Palamu district had low crime density in
rape, whereas Ranchi district recorded low crime density in
kidnapping. Crime density for riots was found lowest for district
Simdega whereas highest for Koderma. The Indian police and
law enforcement departments has not yet exploited the GIS
aspect which will fetch better result as far as crime control is
considered.
Full article can be read using the given below link....
https://rdcu.be/YMfM
area which will be submerged by the proposed Daudhan/Greater Gangau Dam, which is part of the proposed Ken Betwa
River Link Project (in the Madhya Pradesh state of India) and also the area likely to be submerged in the Panna Tiger Reserve
(PTR). The proposed area of submergence was computed at various full reservoir lengths (FRL), 278 m, 283 m, 288 m, 289 m
and 293 m. Similarly the area of submergence for the Panna Tiger Reserve was computed at the mentioned FRLs. It was
concluded that a large part of the Panna Tiger Reserve would be submerged and habitat of various animals and plants would
be under threat. In comparison with the figures given in the Environmental Impact Assessment certain serious discrepancies
and weaknesses were detected and it was felt that they should have been addressed. The results were compared with the EIA
– EMP report of the Ken-Betwa link project, Phase 1, prepared by Agricultural Finance Corporation Limited for the National
Water Development Agency (Ministry of Water Resources, River Development and Ganga Rejuvenation, Government of India).
A proper evaluation of the negative impacts would help when making relevant decisions and appropriate steps to ensure that
the loss is kept to a minimum. Safeguarding the biodiversity of forests and wildlife habitats should be the priority as their loss
is irreplaceable. Geospatial technology helps in studying the overall spatial view of the proposed submergence area and the
visualization gives a clear picture of the likely scenario in the future. It would assist in decision making and mitigation measures.
talks. In developed country Geospatial technology has become
well established within the criminology and forensic fields in
recent past. In order to achieve this proper database of various
crimes (state/ district level) should be available for decision
making. The present study was an attempt made to study
the district wise crime data (IPC crime registered) for murder,
rape, kidnapping, dacoity, burglary, theft and riots of state of
Jharkhand for the year 2013 to understand the crime trend. We
have generated various maps including crime density map of
Jharkhand based on crime types using ARC/ GIS Software and
MS EXCEL. The crime density such as murder, rape, kidnaping
and riots were found in the range of (2.2 to 17.8), (1.6 to 12.6),
(2.3 to 10.4) and (1.0 to 17.5) respectively. Murder crime density
was highest in Gumla district whereas it was found to be lowest
in Gridih district. Sahebganj district has high crime density for
rape and kidnapping. Palamu district had low crime density in
rape, whereas Ranchi district recorded low crime density in
kidnapping. Crime density for riots was found lowest for district
Simdega whereas highest for Koderma. The Indian police and
law enforcement departments has not yet exploited the GIS
aspect which will fetch better result as far as crime control is
considered.