Tree cover percent investigation with respect to geographical area, vegetation types, agro ecological regions and in agriculture landscape of India: a geospatial approach

Laxmi Goparaju,Firoz Ahmad 대한공간정보학회 2020 Spatial Information Research Vol.28 No.1

This study has utilized the remote sensing and GIS datasets such as tree cover, harmonized land cover, agriculture mask and ancillary source of India for better comprehension of tree cover percent distribution in geographical territory/vegetation classes/agro-ecological zones/agriculture landscapes. The study revealed in the year 2000 the forest area in India was 15.4% of the total geographical area. Furthermore, the total agriculture area in India (including single/double/continuous/rainfed area) for the year 2000 was found 63% of the total geographical area and approximately 10% of the agriculture land retains at least 10% of tree cover which is roughly one-fourth of the total global average. The mean tree cover distribution in various vegetation types was found highest (76.4%) in the category of ‘‘Tropical and sub-tropical mountain forests, broadleaved, evergreen [1000 m’’. The vegetation category ‘‘Tropical mixed deciduous and dry deciduous forests’’ occupied high area percent (14.4%) and showed significantly low mean tree cover percent (15.1%). The tree cover percent analysis in various agro-ecological zones of India showed high mean tree cover in those zones where the rainfall is significantly high and soil fertility is adequate such as the categories ‘‘North Eastern Hills’’ (62.5%), ‘‘Eastern Himalayas’’ (60.0%) and ‘‘Western Ghats and Coastal Plain’’ (30.70%).

Analyzing the risk related to climate change attributes and their impact, a step towards climate-smart village (CSV): a geospatial approach to bring geoponics sustainability in India

Laxmi Goparaju,Firoz Ahmad 대한공간정보학회 2019 Spatial Information Research Vol.27 No.6

The paper deals with various thematic parameters such as agriculture crop scenario (2000, 2010), water stress, precipitation trend and deficit, climate-induced risk towards crops, drought-prone area, suicide attributes of farmers, agro-ecological regions, prediction of future (2050) precipitation and temperature variation during kharif and rabi seasons of India and their spatial pattern were analyzed in GIS for better understanding of climate change. The analysis revealed about the need of synergic approach/strategies to address the impact of climate change. Few of the Climate-smart villages (CSVs) projects of India were discussed here based on their approach, achievement, and limitation. The CSV conceptual strategies are fully based on climate smart agriculture potentiality to achieve sustainability in food security, enhancing the livelihood, eradication of poverty and magnifying the farm household resilience. The climate-induced high and very high risk to the crops areas were found dominated in the arid and semi-arid regions which will be challenged in future due to water stress, inadequate irrigation facility, increasing trend of temperature and variation in precipitation pattern. The hotspot districts of farmer’s suicide were very significant in climate-induced very high risk zone and majority of them falls in the drought-prone areas/extremely high to high water-stressed areas which leads to crop failure. There is a need to formulate a concrete policy, legal, and institutional actions addressing the farmers problem significantly at country, state, district and village levels which will support investment/technology/guideline in and adoption of Climate-smart village (CSV) practices after seeing the socio-economic background (poverty/ tribes/backward class) of them.

Geospatial understanding of climate parameters within watershed boundaries of India

Firoz Ahmad,Laxmi Goparaju 대한공간정보학회 2020 Spatial Information Research Vol.28 No.6

We have analyzed the geospatial datasets such as precipitation, runoff, soil moisture, aridity, soil degradation, and future (2050) climate of India and investigated the spatial distribution pattern at the watershed level. Furthermore, we have investigated the long-term TerraClimate present decadal (2006–2015) trend with 20 years back decadal (1976–1985) data for evaluating temporal change in precipitation, runoff, and soil moisture at the watershed level of India. The long term decadal precipitations, as well as soil moisture deficit trend, are found very significant in the watersheds of the Ganga and Brahmaputra basin. The decadal runoff increase (%), when compared with 20 years back decadal runoff showed a high percent ([50%) increase in the majority of Sabarmati river basin in Gujarat state of India. The three villages Milkipur, Bikapur, and Bantikalan (Faizabad district of Uttar Pradesh) have shown a maximum reduction of soil moisture. The analysis of predicted (2050) temperature and precipitation anomaly showed the precipitation deficit in the majority of watersheds of Indus river basin and their subbasin. Similarly, the temperature increase in the year 2050 is found very significant in almost all watersheds of India with a range of 0.8 to 1.9 』C but it is more crucial for some of the northern parts of Indus river basin and Brahmaputra basin. Such analysis highlights the need for an adequate management plan with robust soil and water conservation at a watershed level for achieving sustainable development goals (SDGs).

A geospatial analysis of climate variability and its impact on forest fire: a case study in Orissa state of India

Firoz Ahmad,Laxmi Goparaju 대한공간정보학회 2018 Spatial Information Research Vol.26 No.6

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.

LULC analysis of urban spaces using Markov chain predictive model at Ranchi in India

Firoz Ahmad,Laxmi Goparaju,Abdul Qayum 대한공간정보학회 2017 Spatial Information Research Vol.25 No.3

Monitoring of land use and land cover (LULC) change is one important drivers of global change, which plays a decisive role on the management and sustainable developmental planning for urban spaces. The study aims to develop series of LULC maps of urban areas of Ranchi, India and was studied during the years 1989 and 2015. It predicts LULC changes using geospatial tools such as remote sensing and GIS. Various satellite imagery datasets such as Landsat TM, ETM? and Landsat 8 OLI of years 1989, 2002 and 2015 were used to analyze urban LULC, which was later used to predict for 2015 and 2028 using Markov transition matrix and was cross-validated with true LULC of 2015. The urban area growth was found 11% more than the predicted value. Slope map was also generated from digital elevation model and urban expansion in 2015 was 67% and with respect to roads it was 60% within 1 km road buffer in 2015 over 2002. Regression equation was developed over decadal population of 1961–2011 to estimate it for years 1989, 2002, 2015 and 2028. The population has increased 102% in 2015 over 1989. However, Markov predicted 43% more urban expansion for year 2028 over 2015. Coarse resolution temporal satellite data can be effectively harnessed to assess LULC change whereas prediction can be done with accuracy as high as 89.02% based on Markov transition matrix. An effective coordination between governments agencies are solicited to achieve sustainable development to be implemented systematically.

Himalayan forest fire characterization in relation to topography, socio-economy and meteorology parameters in Arunachal Pradesh, India

Firoz Ahmad,Laxmi Goparaju,Abdul Qayum 대한공간정보학회 2018 Spatial Information Research Vol.26 No.3

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.

Geo-spatial perspective of vegetation health evaluation and climate change scenario in India

Firoz Ahmad,Laxmi Goparaju,Abdul Qayum 대한공간정보학회 2019 Spatial Information Research Vol.27 No.5

Vegetation health of any ecosystem and changes in it are vital in global change in ecology and it is delicately linked to climate change. This study evaluated the spatial patterns of significant negative change trend using composite NOAA-AVHRR data time series (1982–2006), long term forest fire point data, invasive hotspot data and predicted climate anomalies data over the different harmonized landcover categories of India. Around 65% of Indian forest shows the trend of negative change. Significant negative change were found to be highest (203,026 km2) over ‘Tropical mixed deciduous and dry deciduous forests’ category, followed by ‘Tropical lowland forests, broadleaved, evergreen’ (81,555 km2) and ‘Evergreen shrubland & regrowth/Abandoned shifting cultivation/Extensive shifting cultivation’ (55,811 km2). Around 85% of Indian biodiversity hotspot showed the negative change. The analysis of forest fire revealed the ‘Tropical mixed deciduous and dry deciduous forests’ retained the highest forest fire percentage (40%). The prediction of temperature anomalies for the year 2030 using RCP 4.5 model showed the increase in the temperature in the range of 0.58–1.32 C and was found highest in northern part of India. Similarly, the rainfall prediction for the year 2030 showed rainfall deficit in several states of India. The outcomes of the present study would help in prioritization of various vegetation types suffering from anthropogenic and natural disturbances and will guide the policymakers to safeguard, prioritized forest areas for effective conservation, scientific protection and climate change mitigation endeavors.

Analysis of forest health and socioeconomic dimension in climate change scenario and its future impacts: remote sensing and GIS approach

Firoz Ahmad,Md Meraj Uddin,Laxmi Goparaju 대한공간정보학회 2019 Spatial Information Research Vol.27 No.4

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.

Geospatial application for agroforestry suitability mapping based on FAO guideline: case study of Lohardaga, Jharkhand State of India

Firoz Ahmad,Md Meraj Uddin,Laxmi Goparaju 대한공간정보학회 2018 Spatial Information Research Vol.26 No.5

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.