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Remote sensing technology has revolutionized agriculture management and monitoring by providing valuable information on crop health, soil conditions, weather patterns, and overall land management. The reflectance data are progressively being exploited in agriculture with the momenta gained in ground-based, airborne, and satellite remote sensing. The agriculture systems when managed conventionally don’t facilitate the proper utilization of resources and productivity potential of the soil. However, taking the aid of remote sensing techniques helps in boosting the productivity potential of the soil and optimizing the inputs. This paper aims to review the potential applications of remote sensing in agriculture and its role in improving productivity, resource efficiency, and sustainability. The paper discusses various remote sensing techniques, including satellite imagery, aerial photography, and sensor-based data collection, and their integration with advanced data analysis methods. The applications explored include biomass estimation, yield estimation, global food demand, salinity stress detection, drought monitoring, soil moisture content assessment, and change detection. The paper highlights the benefits and challenges associated with each application and provides insights into future research directions and technology advancements in the field of remote sensing for agriculture.

Glacial landforms are pieces of evidence to comprehend the glaciological past and paleoclimatic conditions in the region. In paleo-glacial reconstructions, a critical geomorphological context is provided for determining glacial chronologies. The study provides a detailed geomorphological mapping and investigation of the Nehnar valley, NW Himalayas, Jammu and Kashmir, India. To map the glaciogeomorphological features, the study uses LISS-IV (5.8 m resolution) and Google Earth Pro (1 m resolution) images as well as morphological sketches and GPS data collected during field visits. The Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model (ASTER-DEM, 30m resolution) has also been used to enhance the morphological and elevation characterization of glacial features. A host of glacial features like lateral and terminal moraines, serrate, debris cones, moulins and outwash plains are among several others mapped in the study region. Using dating techniques, the spatial data on glacial landform features in the area can be used to guide the reconstruction of paleo-glaciological setups. This fills in some of the gaps in our knowledge about glaciation in the Kashmir Himalaya during the Pleistocene.

Climate change and variability has far reaching impacts on agriculture particularly in ecologically sensitive areas like the Himalayas. The present study attempts to understand the farmer’s perception and adaptation strategies to changing climate in Lidder watershed of Kashmir Himalayas, India. Based on a cross-sectional database of 266 farm operating families, the study adopts a bottom-up approach to investigate farmer’s perceptions of changes in climatic variables as well as various farm-level adaptation measures, determinants and barriers at the farm-household level. The results show that the majority of farmers have developed a perception of climate change and have engaged themselves in adaptive behaviour with regard to agricultural land use and planning. A weighted average index used to measure the most relevant adaptation strategies revealed that conversion of agricultural land to horticulture, improving irrigational facilities and water harvesting were the main adaptation methods implemented by farmers in the study area. Utilizing the logit regression model, the study confirmed that household characteristics such as land holding size, age of the farmer, years of schooling, farm experience and labour force highly influence household decisions to adapt to climate change. The study calls for policy intervention at the farm-household level to enhance the adaptive capacity of farmers in the region.

Successful management of the water resources directly depends on our understanding of the heterogeneity of changing climate and consequent response of annual and seasonal streamflows in different climatic regions. This study was undertaken to quantify the spatial and temporal variability of different climatic variables and their subsequent impacts on streamflows of river Jhelum and its tributaries during last more than three decades. Mann–Kendall trend statistic and Sen’s slope estimator test were used for assessing the trends and variability in climatic and streamflow variables. Data obtained from 11 hydrometric and 6 meteorological stations for different time intervals were used for analysis. The results pointed toward various significant trends in both hydrological and meteorological stations. Kashmir Himalayas witnessed rise in mean maximum temperature (+ 0.05 °C/year) and mean minimum temperature (+ 0.01 °C/year) with substantial reduction in precipitation (− 4.2 mm/year) from 1980 to 2015. Analysis of the streamflow trends revealed significant decreasing trends in all the hydrometric stations with the highest decrease in spring and summer seasons. Furthermore, the correlation analysis revealed a significant negative correlation between increase in temperature and streamflow, while strong positive correlation was realized with precipitation at both annual and seasonal scales.

Under changing global scenarios, assessment of land use/land cover change becomes necessary. Geospatial technologies have been used extensively in many areas of the world for generating valuable information on environmental monitoring. Kashmir valley is also witnessing large LULC changes due to the widespread lateral urbanization, favorable climate, fertile soils and improved infrastructure. This study aims to assess the LULC dynamics in North Kashmir Himalayas from 1992 to 2018 within a GIS environment. Results reveal that agricultural land, forest cover, snow and glaciers are showing a decreasing trend over the study period, while horticulture, built-up/urban area has increased over the same period. The study shows a high demand for the settlement class. Furthermore, an increase in population, climate variability and economic compulsions have been identified as major drivers of LULC change. The application of geospatial technologies to analyze LULC and related effects was clearly demonstrated.

Nehnar glacier is located in the Sindh sub-basin of the Jhelum River in the Kashmir Himalayas. We studied the dynamic response of the glacier (area, snout, Equilibrium Line Altitude (ELA), specific...

Knowledge and up-scaling of status, availability, and distribution of soil micronutrients are hugely significant for enhancing crop productivity and profitability. However, regional database entailing spatial variability of key micronutrients for a major apple-producing region like the Kashmir Himalayan Region (KHR) is missing. We investigated 588 topsoil samples between 2016 and 2017 (to 30 cm depth) to estimate spatial variability of extractable Zn, Cu, Mn, and Fe; develop spatial maps; and delineate potential management zones (MZs) in apple orchards using geo-statistical methods. Soil sampling was performed post-harvest season. Principal component analysis and fuzzy c-mean clustering were performed to develop MZs. Results exhibited wide variation, with high coefficient of variation (%) for Mn and Cu (123.9 and 114.4, respectively) and low (71.6) and medium (104) variability for Fe and Zn. Mean concentrations followed the order: Fe > Mn > Cu > Zn, with deficiencies evident towards central and northern regions of the study area. The best-fitted model was exponential. The nugget/sill ratio values were 0.41, 0.08, 0.37, and 0.38 for Zn, Cu, Mn, and Fe, respectively, indicating strong spatial dependence for Cu and moderate dependence for Fe, Zn, and Mn. Correlations between elevation, slope, and soil pH with micronutrients were negative, whereas with soil organic carbon and electrical conductivity positive relationships were identified. Three principal components accounted for 67·18% data variance. Based on the fuzzy performance index and modified partition entropy, five MZs were delineated, which exhibited variations from each other. These MZs highlighted the need for specific supplemental provisions in increasing soil fertility and apple productivity.

Knowledge and up-scaling of status, availability, and distribution of soil micronutrients are hugely significant for enhancing crop productivity and profitability. However, regional database entailing spatial variability of key micronutrients for a major apple-producing region like the Kashmir Himalayan Region (KHR) is missing. We investigated 588 topsoil samples between 2016 and 2017 (to 30 cm depth) to estimate spatial variability of extractable Zn, Cu, Mn, and Fe; develop spatial maps; and delineate potential management zones (MZs) in apple orchards using geo-statistical methods. Soil sampling was performed post-harvest season. Principal component analysis and fuzzy c-mean clustering were performed to develop MZs. Results exhibited wide variation, with high coefficient of variation (%) for Mn and Cu (123.9 and 114.4, respectively) and low (71.6) and medium (104) variability for Fe and Zn. Mean concentrations followed the order: Fe Mn Cu Zn, with deficiencies evident towards central and northern regions of the study area. The best-fitted model was exponential. The nugget/sill ratio values were 0.41, 0.08, 0.37, and 0.38 for Zn, Cu, Mn, and Fe, respectively, indicating strong spatial dependence for Cu and moderate dependence for Fe, Zn, and Mn. Correlations between elevation, slope, and soil pH with micronutrients were negative, whereas with soil organic carbon and electrical conductivity positive relationships were identified. Three principal components accounted for 67·18% data variance. Based on the fuzzy performance index and modified partition entropy, five MZs were delineated, which exhibited variations from each other. These MZs highlighted the need for specific supplemental provisions in increasing soil fertility and apple productivity.

Horticulture plays a pivotal role in the economy of Jammu and Kashmir. Owing to favourable agro-climatic conditions, temperate horticulture is fast expanding in the state which is characterised by the increasing dominance of apple cultivation. In the present study, an attempt has been made to evaluate the long term trends in the productivity and areal expansion of apple cultivation in the state. It has been observed that area under apple cultivation has witnessed a considerable increase (326%) from year the 1975–1976 to the year 2015–2016. This trend is translated in the compound growth rates of both area and yield which has witnessed an increase at the rate of 0.69 and 3.09 respectively. The decomposition model analysis predicted that apple production is mainly contributed by area effect (65.73) followed by interaction effect (23.71) and yield effect (10.55). The rapid increase in the area under apple cultivation can be attributed to higher profitability. Climate change has also played a role in encouraging the shift in land use pattern in the state. The yield of apple is showing clear signs of stagnation and is hovering between 9 and 10 MT/ha during the last four decades. Therefore, policy intervention by the government along with the up-gradation of pre and post-harvest technology is the need of the hour to boost the productivity of this sector.

Climate change over mountainous basins necessitates thorough understanding of present and future temperature and precipitation regimes for better water resource management, cryospheric resources, hydropower generation, natural hazard risk assessment, and ecosystem response. Global and regional climate models (GCMs/RCMs) do not represent valley/ridge scale interactions well. There are inherent model biases due to coarser reorientation of model forcings. The present study is an attempt to use the statistical downscaling model (SDSM) to calibrate and validate Canadian Earth System Model (CanESM2) outputs. The outputs have been compared with corresponding in situ observations available at six meteorological stations within the Kashmir basin in western Himalayas. Daily temperatures and precipitation records during present and future time slices have been considered. The three Representative Concentration Pathways (RCPs) were divided into three future time slices of 2030s, 2060s, and 2090s. Downscaled climate data reveals increase of the mean maximum temperature in the range of 0.3–2.3 °C and the mean minimum temperature increase from 0.3–1.9 °C under different RCPs when compared with the baseline period of 1980–2010. An increasing trend from 2 to 17% at different meteorological stations under different RCPs has been observed in precipitation. Seasonally, autumn shows the highest variability both in temperature and precipitation followed by spring.

The plant health is governed by many factors: soil playing a central role which exhibits huge variability in its characteristics. Micronutrients even though needed in small quantities by plants play an indispensable role in affecting the crop growth and development. The assessment of spatial variability of different soil parameters is incumbent for tackling the loss of crop productivity on account of non-receipt of desirable inputs. The present investigation centered on the spatial distribution of soil parameters and micronutrients was conducted to delineate management zones (MZs) in cold arid region (Kargil) of India for proficient micronutrient management. Overall 454 georeferenced representative soil samples at the depths of 0-15 cm were garnered. The soil samples were processed and analyzed for different soil parameters encompassing pH, EC (electrical conductivity), SOC (soil organic carbon), and available micro-nutrient (iron, manganese, zinc, copper and nickel) concentrations. The distinct variation in the soil properties including micronutrients was identified with coefficient of variation ranging as low as 5.62% to moderate (21.16 to 42.49%) and as high as 159.63%. Semivariogram analysis and ordinary kriging of soil variables under study revealed diverse spatial distribution exhibiting medium to high spatial dependence in the region. PCA (principal component analysis) and K-means clustering were expended for the delineation of MZs. Four principal components (PCs) having eigen values > 1 and accounting for 70% of the total variation were subjected to further analysis. The five potential MZs were demarcated on the basis of K-means cluster performance index, and heterogeneity in parameters was discerned. The results of study corroborate that the spatial variability analysis of different soil parameters for delineation/identification of MZs might be effectually employed for site-specific micronutrient management.

Agricultural soils form the backbone of the country’s economic development. The increased population has not only reduced this treasure but also has affected the global climate at an alarming rate. Among the GHGs, emission of N2O due to agricultural activities is nowadays a global concern. Agricultural industries have increased N2O and CH4 by 17% in the atmosphere since 1990, with an average emanation rate of around 60 MT CO2 equivalents per year. Crop production accounts for approximately 50% of N2O emissions stemming from the farming community and discharges of fertilizer-induced N2O, for the time being estimated by IPCC at 1.24% of the N used ranging from 0.76% (rice) to 2.77% (maize). The concentration of atmospheric N2O has increased (60 ppb) after the industrial revolution, at the pace of 0.73 ppb year−1. Besides, soil structure, temperature, moisture, denitrifying microbial population, pH, C:N ratio, and relief are the factors which significantly enhance the N2O levels into the atmosphere. N2O as a GHG has more potential towards global warming than CO2 and has a very long residence period (115 years) in the atmosphere. N2O emission is nowadays a core issue which needs to be mitigated so as to decline the levels of its production in agricultural soils. However, priority should be given to the organic farming, management of soil chemistry, and phytoremediation to reduce the addition of N2O into the ambient air. Furthermore, deployment of N2O reductase in agricultural soils increases the efficiency of converting N2O to inert N2 which is a valuable strategy to reduce N2O production.

Snowmelt makes an essential component of the hydrological system of Kashmir Himalayas. The present study was carried out to examine the status of Snow Cover Area (SCA) using Moderate Resolution Ima...

Climate change has emerged as an important issue ever to confront mankind. This concern emerges from the fact that our day-to-day activities are leading to impacts on the Earth’s atmosphere that has the potential to significantly alter the planet’s shield and radiation balance. Developing countries particularly whose income is particularly derived from agricultural activities are at the forefront of bearing repercussions due to changing climate. The present study is an effort to analyze the changing trends of precipitation and temperature variables in Kashmir valley along different elevation zones in the north western part of India. As the Kashmir valley has a rich repository of glaciers with its annual share of precipitation, slight change in the temperature and precipitation regime has far reaching environmental and economic consequences. The results from Indian Meteorological Department (IMD) data of the period 1980–2014 reveals that the annual mean temperature of Kashmir valley has increased significantly. Accelerated warming has been observed during 1980–2014, with intense warming in the recent years (2001–2014). During the period 1980–2014, steeper increase, in annual mean maximum temperature than annual mean minimum temperature, has been observed. In addition, mean maximum temperature in plain regions has shown higher rate of increase when compared with mountainous areas. In case of mean minimum temperature, mountainous regions have shown higher rate of increase. Analysis of precipitation data for the same period shows a decreasing trend with mountainous regions having the highest rate of decrease which can be quite hazardous for the fragile mountain environment of the Kashmir valley housing a large number of glaciers.

The world has seen the development and growth of urban areas at a faster pace. The rapid urban growth and development have resulted in the increase in the share of India’s urban population from 79 million in 1961 that was about 17.92 percent of India’s total population to 388 million in 2011 that is 31.30 percent of India’s total population. This fast rate of increase in urban population is mainly due to large scale migration of people from rural and smaller towns to bigger cities in search of better employment opportunities and better quality of life. Urban sprawl has resulted in loss of productive agricultural lands, open green spaces and loss of surface water bodies. Hence, there is a dire need to study, understand and quantify the urban sprawl. In this study, an attempt has been made to monitor land use/land cover of part of Dehradun city over two periods of time i.e., from 2004 to 2014 for change detection analysis and to assess urban sprawl using IRS P-6 data and topographic sheets, in GIS environment for better decision making and sustainable urban growth.

Landslides are one of the major natural hazards that are experienced in hilly terrains all over the world and Himalayas are no exception to this. Though primarily attributed to natural causes, landslides are increasing in frequency and magnitude due to anthropogenic disturbances. This has resulted in enormous damage to both life and property. Hence, identification of landslide prone areas is essential for safer strategic planning of future developmental activities. A landslide hazard zonation (LHZ) map is generated by multi-criteria evaluation (MCE) of various responsible factors like slope, drainage, land use and land cover, lithology, soil and aspect which are weighted on the basis of their relative contribution to the occurrence of landslides. These weights are normalized such that the sum of normalized weights is equal to unity. The study area is divided into five zones based on the deciles of the normalized weights. The results reveal that 40% of the area falls under high LHZ which needs immediate engineering and agronomic measures. The MCE model presented in this study could be utilized for other mountainous regions in general and Himalayas in particular.

The economy of the Jammu and Kashmir state depends mostly on traditional forms of occupation. Unaffected and unaltered by modern day industrial developments and changing times, the indigenous traditional occupations of farming, animal husbandry and horticulture forms the backbone of the state economy. But in the last few decades, Agriculture in the state as well as the study area is receiving a set back and Horticulture is flourishing leaps and bounds. The present study aims to analyze various determinants responsible for this change. Climatic as well as field data was thoroughly analyzed to comprehend the situation. A Mann–Kendall test was done on the climatic data to support the hypotheses. It was observed that initially changing climatic trends proved to be the triggering factor supporting this change, but in due course of time, the determinants took an economic and psychological turn. The perusal of Indian Meteorological Data reveals an increasing trend of annual mean maximum temperature from 16.78 °C in 1985 to 17.58 °C in 1995 and an increase from 5.30 °C to 7.00 °C in the annual mean minimum temperature, and as such acting as a triggering factor for the land use conversion. Further, the mean annual rainfall shows a decrease from 100.75 mm in 1981 to 79.43 mm in 1991. The greater economic returns from horticulture as well as the changing behavioral patterns of people over the time further cemented its growth. The farmers have since persisted with the horticulture activity as it has proven to be an economically a much better lucrative enterprise.

This study is an attempt to analyze and highlight the present state of land use/land cover in Lolab watershed of Kashmir valley in western Himalayan environment. Land use/land cover determines the structure, functions and dynamics of most landscapes. The rampant changes in land use/land cover at regional watershed scale have wider ramifications on the environment. The land use/land cover is under tremendous anthropogenic pressure. Rapid and extensive modifications of land use/land cover due to accelerated human activities especially in fragile mountainous ecosystems like Kashmir valley have wider environmental ramifications. Watershed is an ideal spatial management unit for analyzing land dynamics and for initiation of holistic integrated conservation strategies. The present study carries out the land use/land cover change detection studies were from the year 2002 to 2014. A total of seven categories were delineated and during the study period, the forests showed a decrease from 45.31 percent in 2002 to 44.61 in 2014 i.e., 0.7 percent decrease while as horticulture showed an increase from 8.05 percent in 2002 to 9.91 percent in 2014, thus registering an increase of 1.86 percent. Agriculture has decreased to 1.04 percent during the study period. The overall, scenario presented by the study reveals that the land use/land cover change is quite visible throughout the study area.