Nirajan Luintel

ORCID: 0000-0002-9653-1572
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About
Contact & Profiles
Research Areas
  • Remote Sensing and Land Use
  • Climate variability and models
  • Remote Sensing in Agriculture
  • Land Use and Ecosystem Services
  • Precipitation Measurement and Analysis
  • Urban Heat Island Mitigation
  • Automated Road and Building Extraction
  • Agricultural Economics and Practices
  • Rice Cultivation and Yield Improvement
  • Climate change impacts on agriculture
  • Meteorological Phenomena and Simulations
  • Building Energy and Comfort Optimization
  • Agriculture Sustainability and Environmental Impact
  • Advanced Image Fusion Techniques
  • Hydrology and Drought Analysis
  • Solar Radiation and Photovoltaics
  • Agriculture, Water, and Health
  • Smart Agriculture and AI
  • Remote-Sensing Image Classification

TU Wien
2024

Science Hub
2023

Institute of Tibetan Plateau Research
2019-2021

Kathmandu University
2021

Chinese Academy of Sciences
2021

University of Chinese Academy of Sciences
2019

Understanding the spatial and temporal variation of precipitation is important to identify its driving potential extreme events that impact on socio-economic conditions at national provincial scales. This study presents related in scale using 143 rain-gauge stations across Nepal during 2001–2016. The results show differences distribution, with highest Province 4 (Bagmati) lowest 6 (Karnali). decreasing trend scale, expect for 6. distribution shows wettest (Lumle) driest (Manang Mustang)...

10.12691/aees-8-2-4 article EN Applied ecology and environmental sciences/Applied ecology and environmental science 2020-04-17

Land surface temperature (LST) is an important variable for assessing climate change and related environmental impacts observed in recent decades. Regular monitoring of LST using satellite sensors such as MODIS has the advantage global coverage, including topographically complex regions Nepal. In order to assess climatic changes, daytime nighttime trend analysis from 2000 2017 Terra-MODIS monthly datasets at seasonal annual scales over territory Nepal was performed. The magnitude quantified...

10.1080/16742834.2019.1625701 article EN cc-by-nc Atmospheric and Oceanic Science Letters 2019-05-29

Droughts may have severe impacts on the environment and economy, particularly in regions with high water demand low annual precipitation. Central Europe is one such region, where droughts reportedly led to losses crop yield biodiversity, disruptions transport, shortages of drinking water, among others. To mitigate these impacts, national weather environmental agencies region developed drought monitoring tools. The tools enable early warning, support planning policymaking, foster resilience....

10.5194/egusphere-egu25-14666 preprint EN 2025-03-15

Precipitation plays vital roles in the global water cycle, knowledge of spatial and temporal variation precipitation is essential to understanding extreme environmental phenomena such as floods, landslides, drought. In this paper, integrated characteristics during 1980–2016 over Nepal along with seasonal elevation dependency were examined for three different regions country using Multi-Source Weighted-Ensemble (MSWEP) product. The distribution mean annual varies significantly highest...

10.3126/jalawaayu.v1i1.36446 article EN Jalawaayu 2021-04-21

Sustainable agricultural management requires knowledge of where and when crops are grown, what they are, for how long. However, such information is not yet available in Nepal. Remote sensing coupled with farmers’ offers a solution to fill this gap. In study, we created high-resolution (10 m) seasonal crop map cropping pattern mountainous area Nepal through semi-automatic workflow using Sentinel-2 A/B time-series images farmer knowledge. We identified areas iterative self-organizing data...

10.3390/geomatics3020017 article EN cc-by Geomatics 2023-04-06

Monitoring paddy rice cultivation is essential for ensuring food security and land resource management in agrarian countries of South Asia. In this presentation, we investigate the spatial temporal variation cultivated area phenological metrics Nepal between 2003 2018 using time series MODIS data PhenoRice algorithm (Luintel et al., 2021). Comparisons outputs with ancillary show that implementation can be used long-term change analysis cultivation. Results on distribution illustrate...

10.5194/egusphere-egu24-5834 preprint EN 2024-03-08
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