Murali K. Gumma

Orcid: 0000-0002-3760-3935

According to our database1, Murali K. Gumma authored at least 19 papers between 2009 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2024
Dryland cropping in different Land uses of Senegal using Sentinel-2 and hybrid ML method.
Int. J. Digit. Earth, December, 2024

Spatial Distribution of Cropping Systems in South Asia Using Time-Series Satellite Data Enriched with Ground Data.
Remote. Sens., August, 2024

A framework for disaggregating remote-sensing cropland into rainfed and irrigated classes at continental scale.
Int. J. Appl. Earth Obs. Geoinformation, February, 2024

2022
Identifying Suitable Watersheds across Nigeria Using Biophysical Parameters and Machine Learning Algorithms for Agri-Planning.
ISPRS Int. J. Geo Inf., 2022

2020
Characterizing and mapping cropping patterns in a complex agro-ecosystem: An iterative participatory mapping procedure using machine learning algorithms and MODIS vegetation indices.
Comput. Electron. Agric., 2020

2019
Monitoring Changes in the Cultivation of Pigeonpea and Groundnut in Malawi Using Time Series Satellite Imagery for Sustainable Food Systems.
Remote. Sens., 2019

Mapping cropland extent of Southeast and Northeast Asia using multi-year time-series Landsat 30-m data using a random forest classifier on the Google Earth Engine Cloud.
Int. J. Appl. Earth Obs. Geoinformation, 2019

2018
Surface Freshwater Limitation Explains Worst Rice Production Anomaly in India in 2002.
Remote. Sens., 2018

2017
Nominal 30-m Cropland Extent Map of Continental Africa by Integrating Pixel-Based and Object-Based Algorithms Using Sentinel-2 and Landsat-8 Data on Google Earth Engine.
Remote. Sens., 2017

Urban Sprawl and Adverse Impacts on Agricultural Land: A Case Study on Hyderabad, India.
Remote. Sens., 2017

Spectral matching techniques (SMTs) and automated cropland classification algorithms (ACCAs) for mapping croplands of Australia using MODIS 250-m time-series (2000-2015) data.
Int. J. Digit. Earth, 2017

2016
Priority regions for research on dryland cereals and legumes.
F1000Research, 2016

Mapping rice-fallow cropland areas for short-season grain legumes intensification in South Asia using MODIS 250 m time-series data.
Int. J. Digit. Earth, 2016

2014
Mapping Asian Cropping Intensity With MODIS.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2014

2013
Selection of Hyperspectral Narrowbands (HNBs) and Composition of Hyperspectral Twoband Vegetation Indices (HVIs) for Biophysical Characterization and Discrimination of Crop Types Using Field Reflectance and Hyperion/EO-1 Data.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2013

2011
Mapping Irrigated Areas of Ghana Using Fusion of 30 m and 250 m Resolution Remote-Sensing Data.
Remote. Sens., 2011

2010
A Holistic View of Global Croplands and Their Water Use for Ensuring Global Food Security in the 21st Century through Advanced Remote Sensing and Non-remote Sensing Approaches.
Remote. Sens., 2010

2009
Irrigated Area Maps and Statistics of India Using Remote Sensing and National Statistics.
Remote. Sens., 2009

A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing.
Int. J. Appl. Earth Obs. Geoinformation, 2009


  Loading...