Geospatial Practices in Natural Resources Management

The advancements of the 1980s led to the creation of various important technologies, including GPS and satellite imagery, which allowed for the sustainable management of land resources. This must be done while preserving sustainable landuse systems and confronting concerns such as climate change, water scarcity, and the risk of increasing erosion and productivity due to extreme weather events. In several areas, geospatial Big Data analytics is transforming the way firms’ function. Although there are many research workson geographic data analytics and real-time data processing of massive spatial data streams in the literature, only a few have covered the entire geospatial big data analytics and geospatial data science project lifecycle. Because of the volume, pace, and variety of the data being analysed, big data analysis differs from typical data analysis. In comparison to conventional data analysis projects, geospatial data science initiatives are likely to be more difficult and require advanced technologies. The current study introduces a novel geographic big data mining and machine learning framework for geospatial data gathering, fusion, storage, management, processing, analysis, visualisation, and land resource modelling and evaluation. Any data science project that has a robust procedure for land resource data analysis and clear instructions for comprehensive analysis is always a positive. It also aids in estimating the amount of time and resources required early in the process to gain a good picture of the land resource challenges that must be overcome. Automation and the use of artificial intelligence (AI), the internet of things (IoT), drones, satellite imagers, and Big Data lay the foundation for a global “Digital Twin,” which will aid in the development of site-specific conservation and management practices that will boost incomes and ensure the long-term sustainability of land use/land cover systems.

Land Use and Climate change are interrelated to each other. Understanding the response of land use/land cover (LULC) change and climate change over highly urbanised area has become a priority issue for contemporary urban planning and management. This present study aimed to assess the LULC changes and predict future trends with relation to changing climate scenario at micro scale in Upper Catchment Area of Bagjola Canal, located within the Kolkata Urban Agglomeration. Land Use Change Simulations (MOLUSCE) model of Quantum GIS (QGIS) environment has been used here to detect land use/land cover changes. Future generated data from Model for Interdisciplinary Research on Climate 5 (MIROSC5) model is used for climate change analysis with the Coupled Model Intercomparison Project 5 (CMIP5). Representative Concentration Pathways (RCPs) 2.6, 4.5, 6 and 8.5 data are utilized for urban climate change impact on urban LULC. The analysis revealed that substantial growth of built-up areas in study area over the study period (1980–2028) resulted significant decrease in the area of water bodies, wetlands and open vacant land. However, the results show that urban sprawl direction is North and South-West to North and South-East. RCPs data revealed that study area will be more wormer and temperature will reach above 40 ºC. Increased rainfall intensity and number of extreme rainfall events will affect the geo-environment of the study area adversely. The impacts of climate change are more significant in study area. The outcomes of this study may help in developing sustainable urban planning and management policy, as well as assist authorities in making informed decisions to improve environmental and hydro-ecological conditions of Upper Catchment Area of Bagjola Canal which will increase the quality of life in an urban agglomeration environment.

Land capability classification (LCC) is useful to carry out scientific land evaluations and assess land suitability for agricultural use. In this study, the Sadoli Khalasa area of Karveer tehsil, Kolhapur District, Maharashtra, India has been selected to assess precise LCC at micro-scale (cadastral level) using field survey and advanced Geoinformatics approaches. For this purpose, 35 soil samples were collected from the entire area with geographical coordinates (x, y) using a handheld Global Positioning System (GPS) and empirically analyzed. Physical characteristics of soil, i.e. soil depth, texture, and structure were identified from analyzed soil samples and with the help of NBSS and LUP maps and soil grid database (250 m resolution) in Geographical information system (GIS) software. Regional relief, slope, contour, and drainage analysis were carried out from CartoDEM (30 m resolution), downloaded from https://​bhuvan.​nrsc.​gov.​in/​home/​index.​php, and its validations were carried out from 1:50,000 scale Survey of India (SOI) toposheet (47/L/2), and sample elevations points acquired by GPS. An Object based classification approach was implemented to prepare land use land cover (LULC) of study area in eCognition Developer software with agriculture, harvested land, built-up, lake, fallow land, and barren land classes using Resourcesat-2 LISS-IV data. Finally, all generated multi-layers are integrated with unique projections and intersect overlay operation was carried out to create the LCC of the area. The analysis reveals that Class II, III, IV, VI, and VII are observed in the study region of which Class II and III comprised about 50% area of the selected region. This result signifies that about 75% of land in the area is suitable for agriculture purpose, of which about 30% of land fall under Class II. The used Geoinformatics approach along with field investigations has proved satisfactorily for assessment of LCC in Sadoli Khalasa area in order to avail sustainable land development and can be used in other parts which have similar physio-pedological characteristics.

Land is essential component of nature for performing any type of economic activity but availability of land is limited and more or less fixed. Enormous population pressure on land is a contemporary phenomenon. So assessment of land suitability for different economic activity is a very imperative for natural resource management. The present study aims to determine suitability of land for agriculture, pasture, forestry and industry. GIS based Analytical Hierarchy Process (AHP) technique is used for land suitability classification. Versatile thematic components, namely soil-depth, soil-texture, river-buffer, MNDWI (Modified Normalized Differentiate Water Index), NDVI (Normalized Differential Vegetation Index), Groundwater, rainfall, landuse and landcover, curvature, slope and elevation are integrated in a GIS environment. It was produced based on weighted overly by using AHP technique. Land suitability of drought prone Gandheswari Watershed is divided into seven land suitability Classes, namely, Class-I: Highly suitable for agriculture [84 km²], Class-II: Moderately suitable for agriculture [81 km²], Class-III: Low to Moderately suitable for agriculture [76 km²]), Class-IV: Transitional zone-I, having less agriculture, agro-forestry and pasture [57 km²], Class-V: Suitable for Agro-forestry and pastureland [51 km²], Class-VI: Transitional zone-ii [26 km²], Class-VII: Suitable for industrialization (25 km²). The land suitability map of the study area has been validated by using present landuse and landcover ground truth point. Then, the Receiver Operating Characteristic (ROC) curve is prepared for validation of the methodology used in this work. The result of Area Under the Curve (AUC) is good indicating an accuracy of (0.72) 72%. The result of this Potential land suitability for economic activity can be helpful in sustainable land use and land cover development, land conservation planning and strategy formulation for management of land.

The rapid urbanization process has become a primary environmental concern due to environmental impacts, such as the drastic change in land-use/land-cover (LULC) and changes in the local climate. Rapidly growing areas such as Kolkata need to develop digital skills, which can be done easily with high-resolution remote sensing data. In this study an effort has been made to find out how changing trends of LULC and bio-physical indicators (NDVI, NDWI and NDBI) effects on Land Surface Temperature (LST) over the period of time. This study also attempts to make non-linear relationship among LST, LULC and bio-physical indicators which creates a significant output to know the exact factors those are affecting on micro-climatic change in Kolkata city. Landsat TM and OLI-TIRS image datawere utilized to extract information regarding land-use LST and biophysical indicators of Kolkata city between 1990, 2005, and 2019. In this study, GAM modelusing R programming has been used to analyze the relationship between Land Surface Temperature and bio-Physical indicators (NDVI, NDWI, and NDBI). LULC has dramatically changed in the city center as well as surrounding rural areas, resulting in a significant spatiotemporal impact on LSTs. Sustainable urban planning can be improved through these findings, as well as a reduction of the negative impacts of urbanization on the environment.

In eastern India, Durgapur is one of the fastest growing cities. The land cover and land use of Durgapur are shifting very hurriedly due to urbanization, which adversely impacts the local land resources there. This study was done from 1991 to 2021. To an attempt was made in this study to determine how the urban growth area grew over time. Aside from that, an attempt has been made to examine the pattern of urban expansion in Durgapur. Normalized Difference Vegetation Index and Normalized Difference Built up Index, Built up Index were analyzed to evaluate the urban expansion of Durgapur city from 1991 to 2021. According to the findings, vegetative area is decreasing in the city central areas (13.9–6.32%) while built-up area percentages are increasing in the central areas (78.42–84.75%). In 1991, the mean value of the built-up index in the study region was 0.04, which was transformed to 0.1 in 2021. Within a thirty-year time span, the degree of modification in the Built up area is perfectly visible.

Presently, enormous expansions of the built-up environment have been going on at the fastest rate overtime to fulfill the demand of the world population. In this study, the Landsat satellite images of different times with various sensors were used. Various types of change detection methods like unsupervised, supervised classification, image differencing and discriminant function were used to measure the number of changes in land use/land cover with a spatio-temporal scale. Land use/land cover classes were detected by using the spectral reflectance signature. Results of the previous studies showed that built-up environment growth is at a rapid rate at the cost of agricultural land, fellow land, vegetation and water bodies. Climatic parameter like temperature gradually increases with the expansion of the built-up environment. On the other hand rainfall has decreased overtime at a spatial scale. So temperature and rainfall have also been influencing on depth to groundwater level. Continuous alteration of land use/land cover in an area for the purpose of regional development resulting alarming decrease in ground water level since the underlying surfaces have coverage by impervious materials that reduce the recharge of groundwater affect the cycling of groundwater. Spatial–temporal analysis of groundwater table fluctuation data indicates that it has been gradually declining in the groundwater level in respect to depth.

Citizen participation has recently become more common in water resource management and prevention, led to advances omnipresent and interactive technology. This scenario has provided a once-in-a-lifetime chance to capitalise on the efforts of large groups of volunteers. The importance of crowdsourcing in knowledge acquisition for water resource applications is the subject of this research. Our study compares crowdsourcing techniques created for water resource management and conservation, which can be used to optimise surface water and sustainable management procedures, using a systematic literature review. We present a road map for future water research that draws together fine-grained findings from previous crowdsourcing research to produce a high-level, macro-perspective of the crowdsourcing phenomena and its geopolitical significance, directed by our analysis.

The study focuses to understand spatial and seasonal variability of runoff and discharge across the Ganga River basin. To execute the study runoff and discharge data of 13 stations (5 stations on the Ganga River and other 8 are on the major tributaries) across the river basin had been used. The classification of season: monsoon (June–September), post monsoon (October-December), winter (January-March) and summer (April–May) had been considered as the base of seasonal variability analysis. The average runoff distribution reflectall major tributaries of the Ganga River have experienced high runoffwith respect to the stations on the Ganga River because the tributaries receive more direct runoff than the Ganga River and there is a decreasing trend in the amount of runoff from the up-stream to the down-stream of the Ganga River. In the post monsoon period Sasaram receives very lowrunoff probably because of low rainfall in the Son River basin during this time. Seasonal variability of runoff of all stations reflect that the tributaries receive more runoff than the Ganga. The construction of Farakka barrage play a significant role in the variability of runoff and discharge in downstream of the basin especially of Rajmahal, Jangipur and Nabadwip stations. The stations which are on the Ganga River receive high discharge and the stations on the tributaries get relativelylow discharge. This scenario is somehow reciprocal with the seasonal variability of average runoff of the basin.

The primary objective of the present research is to assess the effectiveness of geospatial studies in the spatial variation of groundwater quality. QGIS (version 3.14) software is used for geospatial analysis of water quality parameters. Spatial distribution maps of water quality parameters are extracted. Inverse distance weighted (IDW) technique is utilized for the spatial interpolation. Visual interpretation of these maps implies that most of the water quality parameters are well within the permissible limit as per Indian Standard 10,500 (2012): Drinking Water Standard. Weighted overlay map is created by overlaying spatial distribution layers of 13 water quality parameters. Calculated values of groundwater quality index (GWQI) at all stations are similarly interpolated and spatial distribution map of the same is derived. Major portions of the block of Golamunda, Koksara, Dharmagarh, Junagarh and Bhawanipatna the groundwater quality are very poor. The overall water quality ranges within good to medium for most of the regions of the district whereas some of the extreme northern parts of Bhawanipatna and central region of the Junagarh block exhibit excellent groundwater quality. Surprisingly close resemblance between water quality index map and weighted overlay map has been detected. The effectiveness of IDW interpolation is assessed by validating with root mean square error estimates and the value of RMSE is determined very close to 0 indicating that the IDW method has less estimation error. However, IDW over estimates the overall water quality for the present range of data sets.

Through a “geospatial strategy” for promoting Nature-Based Tourism (NBT) in the target region, the current article investigates the potential for tourism development at the site of the Maithon dam. The potential for creating leisure tourism at the dam site is tremendous. Since Damodar Valley Corporation's (DVC) primary focus is on flood control, irrigation, and water management, the site's recreational value is still underappreciated. The geospatial approach is used in the present study to determine the gradient suitability for scenic beauty and adventure depending on the tourist interest. The potential tourist places is generated in a GIS environment assigning weights to the existing environment based on detailed ground investigation. Topographical maps, ASTER data, LISS III satellite image, Google Earth image, and thematic maps are employed in the GIS environment to prepare the final layout.

The Watershed management project is dedicated to soil and water conservation as well as livelihood development. This paper summarizes the importance of MGNREGA in watershed management. This is an observational study based on the review of papers and field level experience. Various watershed management structures can be set up under Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), which are extensively discussed here, considering the ridge to valley treatment method. So many natural resource management (NRM) schemes have been included in the guidelines of permissible work for MGNREGA, but some have a less significant impact on watershed management. This paper discusses those schemes which have a high impact on watershed management. The participatory approach of planning and the preparation of a detailed planning report (DPR) for micro watersheds have been conferred here. Impact of “Ushar Mukti Project” in watershed management has been analyzed as a case study. It is identified that the main obstacles to watershed management planning are communication gaps, insufficient Participatory Rural Appraisal (PRA) material, selection of schemes irrespective of land types, etc. The possible solutions to those problems are active participation of the community in the planning process and cooperation between the government and civil society organizations.

Droughts occur due to scarcity of water. Meteorological drought is result of the impacts of lower than usually occurring rains and the agricultural drought is the result of impacts of non availability of sufficient water on the crops. The drought can be viewed as moisture deficit that can generate social, environmental or economic impacts. For quantifying intensity of drought a number of drought indices were developed. These indices were calculated on selected locations where the rainfall data was observed or there was some method to assess the water needs of the crops. The long term averages of rainfall played important role in computing the values of these indices. The method of deciles developed by Gibbs (Gibbs WJ, Maher JV (1967) Rainfall deciles as drought indicators. Bureau of Meteorology Bulletin No 48, Commonwealth of Australia) could define the onset, strength and cession of the drought by comparing the actual rainfall with the rainfall below deciles value. The Palmer Drought Severity Index (PDSI) was developed keeping in view the water needs of crops. Many more indices were developed using the point station data. Estimation of hydro-meteorological variables through remote sensing could help in estimating the spatial distribution of the drought indices and thus the drought intensities. The development of Normalised Difference Vegetation Index (NDVI) could help in assessing the vegetation health on large regions. Further development of a series of drought indices based on the remote sensing of other parameters combined with NDVI resulted in ability to monitor, analyse and predict droughts. The drought monitoring systems are used to get information for a country or a region or the entire globe. The objective of this chapter is meteorological and agricultural drought monitoring with emphasise on the use of remote sensing.

Ever increasing anthropogenic activities and, changes in geological, hydrological and climate factors has increased the occurrence of disaster events such as floods. Floods has caused debilitating effects worldwide by affecting people physically, emotionally and financially by virtue of displacements, lost of livelihoods, spread of water borne diseases and mortality of both humans and several wildlife species. Many environmental, geological, and anthropogenic factors shape the susceptibility of different areas. Flood conditioning factors such as slope, TWI, elevation, soil texture, LULC, Geomorphology and Drainage Density affects the flood susceptibility. With the advancement of GIS tools and ease of access to remote sensing data, flood susceptibility mapping is increasingly being used to demarcate high flood prone areas and to understand the relative effect of each flood conditioning factor on occurrence of floods. East Vidarbha region which has faced high intensity floods in recent past has been chosen to investigate the influence of all these flood conditioning factors using Analytical Hierarchy Process (AHP). AHP is a multi-criteria decision analysis technique, used in range of applications to assess the relative weight of each conditioning factor for the susceptibility mapping. Our results show that, most of the study area falls under moderate flood susceptibility i.e., 91.28%. However, looking at the poor socio-economic status of people living in the East Vidarbha region, the vulnerability to moderate flood susceptibility could be very high. This study stands helpful to decision makers to install prevention structures in areas with high flood susceptibility and socio-economically backward areas with moderate flood susceptibility. The study will also be helpful to mark the high flood susceptible areas and preparing the villagers in these areas to make suitable actions to mitigate the risks arising from future floods.

Fluoride contamination in groundwater is a major environmental issue, mostly in the developing world, due to the extensive negative impact that it has on human health. Excessive consumption of fluoride-contaminated water causes dental fluorosis and, in extreme cases, skeletal fluorosis. An estimated 200 million people all over the world, 62 million from India in almost 17 out of 29 states, which includes 6 million children, suffer from fluorosis due to consumption of water with high fluoride concentration. Natural sources such as weathering of rocks bearing fluoride rich minerals, volcanic eruptions are the major sources of fluoride, although anthropogenic sources are also present. Major chemical controlling factors responsible for fluoride contamination of groundwater are dissolution, hydrolysis, precipitation, adsorption, ion exchange and biochemical reactions. Five major fluoride affected belts have been delineated globally. In India, many districts of states such as Rajasthan, Tamil Nadu, Andhra Pradesh, Telengana and West Bengal show high fluoride in groundwater. Determining factors causing fluoride contamination in groundwater are Rock type, Tectonics, Physico-Chemical properties of water, Soil type and weathering.

A crucial step in understanding the issue of land resource management is to perform the morphometric analysis of a river basin in order to determine changing pattern of the river and its basin characteristics. Geospatial techniques (RS and GIS) have recently arisen as vital tools for evaluating environmental issues and ensuring the complete advancement of a river basin area. Both these tools are combinedly used to determine the numerical account of river basin morphometry in an undistinguishable articulate manner. In this venture, basin morphometric methods have been employed to comprehend the type of soil erosion impending in the study area. The present study considers the river basin of Debnala (located in Purba Singbhum District, Jharkhand). River Debnala is a south bank non-perennial tributary of Dulung River which was invented in Jharkhand at an elevation of over 134 m. In the study, different morphometric parameters (Linear, Areal, and Relief) along with DEM alignment have been derived at grid level (1 km² × 1 km²) over the basin. Finally, all the morphometric parameters have been combined and a weighted score has also been assigned to find the precedence of soil dispassion rate in the study area. The result shows that 1st order stream shows that the fourteen (14) Sub-basin are very high soil erosion potential zone. As a whole in the study area, forty (40) sub-basins recorded very remarkable erosion potential capacity to produce sediments which needs special attention. The result of morphometric analysis-based prioritization shows that soil erosion and sediment production rate are inversely proportional to each other.

Quantification of drainage network with special reference to climatic conditions, geo-tectonic uniqueness, lithological configuration, geomorphic characteristic features etc. It extends conspicuous evidences of drainage evolution, hydro-geomorphic specialties and denudational features of the area over which the drainage does flow along with its tributaries as well as distributaries. The present paper will throe focus on the satellite-image based analysis of digital elevation model that entails the drainage basin of river Kangshabati in selected portion of the western forested track of Bankura District. Along with the morphometric techniques, the impacts of fluvial Morphometry over the hydro-geomorphicfeatures have also been studied in the current paper. Drainage density, dissection Index, study of slope features and nature of relief have been corroborated with all minute details in this research work. The shape features show that the drainage basin is extended towards north and south and the highest fourth order stream Kangshabati has drained the entire region. Lots of fingertip as well as the First order channels are developed over the area and after their joining with each other, a good number of second order streams have also been originated. Gradually with the increase in order, the occurrence of higher order streams has got reduced gradually. With chromatic variations, the higher-magnitude areas with special regards to drainage density, relief feature, gradient characteristics have been delineated clearly and the result of such high occurrences have been explained as well with respect to their connections to topography. In the analysis with adequate inputs from the Geographical information system, the zones of high, moderate and low regions of drainage density, relative relief, average slope, dissection index etc. have been manifested through the map layouts and some prospective studies are also done over here from the present situation of the drainage and relief.

This work aims to deal with the morphometric analysis of the Panzara River Basin (PRB) watershed, a tributary of the Tapi River in Maharashtra, India. In this study, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Digital Elevation Model (DEM) and Survey of India (SOI) toposheets have been used along with various parameters like linear, areal, and relief aspects in Geographical Information System (GIS) environment. Out of total 293 number of streams in the watershed, 226, 54, 12, and 1 are of first, second, third and fourth orders respectively. PRB watershed is of 4th order and less elongated in shape, having lower peak flows of longer duration with dendritic pattern and having coarse drainage texture. The bifurcation ratio lies between 6 and 7, indicating that geological structure doesn’t have more influence on drainage patterns. The area forms a rugged topography having an elevation range from 123 to 1199 m above Mean Sea Level (MSL). Variables like Stream Frequency and Drainage Density shows impermeable surface of PRB watershed which causes higher water discharge volume and speed in the basin so that the probability is maximum for frequent floods. The results indicates that PRB is having high slope in SW part as compare to NE part and having very low gradient ratio. These variables also shows a temporal variation in the water flowing speed in the stream when the flood reaches its peak. The outcomes of this work can suggest and recommend a better mechanism for proper watershed management in the PRB.

The present study on fluoride contamination in surface water and groundwater in and around Attappady tribal area of Palghat district, Kerala State, India reveals that fluoride dispersal is controlled by country rocks and their structures along with hydrogeomorphology and drainage network. The leaching of F⁻ in groundwater is also controlled by semi-arid climate, which is the result of very less rainfall (936 mm) in the area. Total 42 samples including both surface water and groundwater have been collected during both pre-monsoon and post-monsoon periods and have been analyzed for fluoride apart from other chemical parameters. High fluoride (>1.50 mg/L) in groundwater has been observed in major parts of the Attappady area. The surface water contain fluoride within the range of 1.22–2.86, whereas groundwater in phreatic aquifers have the range of 2.18–2.56 mg/l and deeper fractured aquifers have the fluoride range of 3.20–4.20 mg/l during pre-monsoon and post-monsoon periods, respectively. Maximum fluoride concentration (4.20 mg/L) is recorded in the east-central part of Attappady. Low rainfall and high rate of evaporation promote the dissolution of fluorine-bearing minerals and help in increasing the F⁻ content in groundwater. Fluoride contamination is geogenic in nature and major contribution is made by the hornblende-gneiss formation (1.67 mg/l).

The Sundarban ecosystem bears a unique biodiversity of its own and hosts livelihoods of millions of people. Because of its typical virtues the Sundarban as a whole and many of its parts at the same time, have attracted various researchers and academicians gaudily since a long past. Though individual island in the south eastern parts of the Indian Sundarban in general and Marichjhapi Island in particular are comparatively less studied. Thus, long term variation of land and vegetation-area of Marichjhapi Island was studied with remotely sensed data. In the study it is found that the island lost an estimated land-area of ~4.42 km² over the period 1972–2022 with an erosion-rate of 0.18 km²/year over last 25 years, while the mangrove cover decreased by 1.39 km² in last 50 years against an increase by 1.24 km² during 1972–1997 and decrease by 2.63 km² over the period 1997–2022. Over the period 1972–2022, the mangroves in the island encountered massive structural changes in terms of greenness-density. The area of denser mangroves decreased by 36 km² between 1972 and 1977, by 31 km² between 1979 and 1997, while increased by 39 km² between 1997 and 2022, and the overall greenness-impact was calculated to be 1.50:1.10:1.00:1.12 in the year 1972, 1979, 1997 and 2022. However, such transformations may be attributed mainly to various natural forces like frequent cyclonic storms, tidal and sea current-surges etc.

A widely used method is to estimate crop water requirements using reference evapotranspiration and crop coefficient. The crop coefficients can be estimated using a relationship between satellite-derived vegetation index and crop coefficient values for efficient and timely agricultural water management strategies. In the present decade several remotesensing based vegetation indices are applied to simulate crop coefficients but almost all are based on linear relationship. The relationship between the NDVI and K_c was established by using both a traditional regression method and ANN model. Given the complex meteorological and biophysical phenomena related with crop coefficients and satellite-derived vegetation index, a linear relationship between these two variables is insufficient to extract the non-linearity and non-stationarity between them. Therefore in this study widely applied feed forward back propagation Artificial neural networks (FFBP-ANN), a soft computing techniques for mapping complex input and output relationship, was applied. Performance of FFBP-ANN for mapping crop coefficients with NDVI was also compared with traditional regression method. It was found that FFBP-ANN can be applied to accurately estimate crop coefficient values using the remote sensing derived NDVI values. This advancement in calculating crop coefficient using free satellite images is a significant step forward in the development of agricultural irrigation demand models. As a result, this research paves the way for near-real-time irrigation decision-making systems.

Forest is the most imperative piece of the environment to maintain ecological balance in any region and it also support the economy of the neighbouring populace. India is a country where forest resource is very much limited; still, some of its states holding the baton to improve the situation and the state Sikkim is one of it. Sikkim is the north-eastern state of India situated in the Himalayan region, which has accounted the forest cover of about 82.31% of its geographical vicinity. In the current effort, the spatio-temporal dynamics of forest health of Sikkim were analyzed using the Moderate Resolution Imaging Spectroradiometer (MODIS) [16-day products (MOD13Q1) of 250 m spatial resolution] satellite data. The Normalized difference vegetation index (NDVI), Enhanced vegetation index (EVI), Leaf area index (LAI), Optimized soil adjusted vegetation index (OSAVI), Infrared percentage vegetation index (IPVI) and Renormalized difference vegetation index (RDVI) have been employed to generate diverse vegetation indices to estimate the temporal variations of forest health from 2000 to 2020. Apart from the appliance of geospatial techniques, the Analytical Hierarchy Process (AHP) method is employed on a GIS platform to recognize the dynamics of forest health pattern to cover the research gap of the earlier studies. It reveals form the outcome of the study that, the forest health of the South and West districts of Sikkim is most affected during the study period. It also found that the very high category of vegetation cover gradually decreased; while the low vegetation cover are comparatively increased. The present investigation provides forest health database, which will definitely help in forest planning and management and the outcomes obtained from this study will aid forest recovery and mitigate the negative effects of forest health deterioration on biodiversity and ecosystem services in the region.

Rainfall-runoff soil erosion is the most frequent form of land degradation. Soil erosion and sediment yield assessment are essential to develop suitable land and water resource management practices. Siltation impact assessment plays a major part in the choice of sustainable development projects for watershed management and can be thus a base to plan appropriate strategies for decision-makers to avoid soil erosion risks and consequently lengthen dams’ life. The current study aims to estimate annual sediments deposit in the Abdelmomen dam, Morocco, using the Previsioni Interimento Serbatoi Artificiali (PISA) model integrated with GIS. Various geospatial layers were used, including ALOS Digital Terrain Model (DTM), historical climate data, high-resolution ESRI land use land cover (LULC) map, etc. The PISA-based model results reveal an average annual degradation of 1044,71m³/km²/yr is estimated, which is equivalent to a soil erosion rate of about 14.62 t/ha/yr, and to a total annual potential soil loss of 1,900,600 (t y⁻¹). These results are significantly higher than that measured in situ by a bathymetric survey (Er), where the ratio Y(PISA)/E(Er) is about 1.24. This model overestimates soil erosion in the study area, as well as for other studies, areas in the Greater Maghreb. In general, the application of the PISA-based model has until now not provided very satisfying results for the prediction of soil loss for large-sized catchments and still encounters severe problems. This model allows an indirect assessment of water erosion and the scope of degradation and soil loss on the siltation of the dam lake. Further, a moderate hazard of water erosion was found throughout the study area. Moreover, the highly eroded areas, which are quite frequented over the study area, require delineation and immediate action. These findings can help the water resource managers to develop a new insight from a multi-scale approach and a new model for delineation of vulnerable areas to water erosion, especially, in mountain regions.

Air pollution and meteorological monitoring are an integral part of the mitigation strategies that need to be adopted for curbing air pollution. Geospatial techniques are used to integrate research and development for the geographic mapping of the earth. The major geospatial techniques include Geographic Information Systems (GIS), Remote Sensing, Global Positioning System (GPS), Geodatasets, and Internet Mapping Technologies like Google earth. Using GIS and remote sensing data for air pollution monitoring is a very beneficial tool as the ground-based monitoring of air pollutants at all locations is not feasible. Integrating geospatial techniques along with various artificial intelligence techniques for air quality and weather prediction and monitoring is a key factor in bringing about effective measures for mitigation of air pollution. Geospatial technologies are emerging technologies used to integrate research and development in the geographic mapping and analysis of the Earth.

Geospatial technology empowered by its own modern tools has contributed a lot for the benefit of humankind and society. In real world, geospatial technologies intersect with digital technologies for enabling many processes in several applications. Geospatial technologies and digital technologies although are self-driving but the cross linkages can help in solving many complex problems. The empowerment of geospatial technologies in conjunction with key Information and Communication Technologies (ICT) has not been widely pondered over. This paper discusses the influence and significance of geospatial technology and digital technologies in conjunction with one another. The paper is also one of the pioneers in discussing conjunction of all key digital technologies with geospatial in single work. Hardware founded technologies like Internet of Things (IoT), Wireless Sensor Networks (WSN), Robotics and Unmanned Aerial Vehicle (UAV) and software based technologies like Artificial Intelligence (AI), Machine Learning (ML), Data Science and Data Analytics are deliberated in this paper. Other than providing introduction to processes of these technologies, coalition of location parameter and related tools is discussed. The discussions of conjunction are further supported by well-established real life implementations in government or business sector.