 | Up a level |
Gumma, M K and Panjala, P and Dubey, S K and Ray, D K and Murthy, C S and Kadiyala, D M and Mohammed, I and Takashi, Y (2024) Spatial Distribution of Cropping Systems in South Asia Using Time-Series Satellite Data Enriched with Ground Data. Remote Sensing(TSI), 16 (15). pp. 1-18. ISSN 2072-4292
Gumma, M K and Panjala, P and Teluguntla, P (2024) Dryland cropping in different Land uses of Senegal using Sentinel-2 and hybrid ML method. International Journal of Digital Earth, 17 (1). pp. 1-18. ISSN 1753-8947
Gumma, M K and Nukala, R M and Panjala, P and Bellam, P K and Gajjala, S and Dubey, S K and Sehgal, V K and Mohammed, I and Deevi, K C (2024) Optimizing Crop Yield Estimation through Geospatial Technology: A Comparative Analysis of a Semi-Physical Model, Crop Simulation, and Machine Learning Algorithms. AgriEngineering, 6 (1). pp. 786-802. ISSN 2624-7402
Panjala, P and Reddi, V R M and Gumma, M K and Deevi, K C and Gupta, S K (2023) Identifying prospects and potential areas for introducing pearl millet stress-tolerant cultivars in Rajasthan, India: A geospatial analysis. Smart Agricultural Technology, 6. pp. 1-10. ISSN 2772-3755
Park, T and Gumma, M K and Wang, W and Panjala, P and Dubey, S K and Nemani, R R (2023) Greening of human-dominated ecosystems in India. Communications Earth & Environment, 4. pp. 1-11. ISSN 2662-4435
Mandapati, R and Gumma, M K and Metuku, D R and Bellam, P K and Panjala, P and Maitra, S and Maila, N (2023) Crop Yield Assessment Using Field-Based Data and Crop Models at the Village Level: A Case Study on a Homogeneous Rice Area in Telangana, India. AgriEngineering, 5 (4). pp. 1909-1924. ISSN 2624-7402
Bellam, P K and Gumma, M K and Panjala, P and Mohammed, I and Suzuki, A (2023) Mapping Shrimp Pond Dynamics: A Spatiotemporal Study Using Remote Sensing Data and Machine Learning. AgriEngineering, 5 (3). pp. 1432-1447. ISSN 2624-7402
Gumma, M K and Panjala, P and Deevi, K C and Bellam, P K and Dheeravath, V and Mohammed, I (2023) Impacts of irrigation tank restoration on water bodies and croplands in Telangana State of India using Landsat time series data and machine learning algorithms. Geocarto International, 38 (1). 01-19. ISSN 1010-6049
Gumma, M K and Takashi, Y and Panjala, P and Deevi, K C and Inthavong, V and Bellam, P K and Mohammed, I (2022) Assessment of Cropland Changes Due to New Canals in Vientiane Prefecture of Laos using Earth Observation Data. Smart Agricultural Technology, 4. 01-11. ISSN 2772-3755
Panjala, P and Gumma, M K and Ajeigbe, H A and Badamasi, M M and Deevi, K C and Tabo, R (2022) Identifying Suitable Watersheds across Nigeria Using Biophysical Parameters and Machine Learning Algorithms for Agri–Planning. International Journal o f Geo-Information, 11. 01-17. ISSN 2220-9964
Gumma, M K and Thenkabail, P S and Panjala, P and Teluguntla, P and Yamano, T and Mohammed, I (2022) Multiple agricultural cropland products of South Asia developed using Landsat-8 30 m and MODIS 250 m data using machine learning on the Google Earth Engine (GEE) cloud and spectral matching techniques (SMTs) in support of food and water security. GIScience & Remote Sensing, 59 (1). pp. 1048-1077. ISSN 1943-7226
Mwema, C M and Wangari, C and Anitha, S and Muendo, C and Nyaga, Simon and Siambi, M and Gumma, M K and Panjala, P and Kane-Potaka, J (2021) Measuring and Influencing Behavior Change in Dietary Intake: Integrated Photovoice Approach in Nutrition Interventions in Eastern Kenya. Ecology of Food and Nutrition (TSI), 61 (2). pp. 215-234. ISSN 1543-5237
Gumma, M K and Kadiyala, M D M and Panjala, P and Ray, S S and Akuraju, V R and Dubey, S and Smith, A P and Das, R and Whitbread, A M (2021) Assimilation of Remote Sensing Data into Crop Growth Model for Yield Estimation: A Case Study from India. Journal of the Indian Society of Remote Sensing (TSI). ISSN 0255-660X
Gumma, M K and Desta, G and Amede, T and Panjala, P and Smith, A P and Kassawmar, T and Tummala, K and Zeleke, G and Whitbread, A M (2021) Assessing the impacts of watershed interventions using ground data and remote sensing: a case study in Ethiopia. International Journal of Environmental Science and Technology (TSI). ISSN 1735-1472
Panjala, P and Gumma, M K and Teluguntla, P (2021) Machine Learning Approaches and Sentinel-2 Data in Crop Type Mapping. In: Data Science in Agriculture and Natural Resource Management. Studies in Big Data, 96 . Springer, Singapore, pp. 161-180. ISBN 2197-6503
Yamano, T and Gumma, M K and Panjala, P and Haq, N U and Fahad, M and Sato, N and Arif, B W and Saeed, U (2024) Applying Spatial Analysis to Assess Crop Damage: A Case Study of the Pakistan 2022 Floods. Working Paper. ADB publications, Philippines.
Gumma, M K and Panjala, P and Mohammed, I and Pyla, V and Bellam, P (2022) Strengthening Food Security Post-COVID-19 and Locust Attacks: Supporting crop insurance in Pakistan. Project Report. ICRISAT, Hyderabad.
Gumma, M K and Panjala, P and Mohammed, I and Pyla, V and Bellam, P (2021) Strengthening Food Security Post-COVID-19 and Locust Attacks. Project Report. ICRISAT, Hyderabad.
Murali Krishna, G and Panjala, P and Ismail, M and Pyla, V (2020) Crop type mapping using high-resolution Sentinel-2 Satellite Data– A case study on Gujarat State. Project Report. ICRISAT.
Gumma, M K and Kadiyala, M D M and Panjala, P and Mohammed, I (2020) Pilot studies on GP Crop yield estimation using Technology (Kharif 2019) using SENTINEL- 2 satellite data (in Andhra Pradesh, Telangana and Odisha States (Five Districts)) for Groundnut, Chickpea, Maize and Rice. Project Report. ICRISAT, Patancheru, India.