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MAPPING RICE CROPPING SYSTEM IN THE LOWER GANGETIC PLAIN USING LANDASAT 8 (OLI) AND MODIS IMAGERY

A. Maiti, P. Acharya • The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences (2018)

The Indo-Gangetic basin is one of the productive rice growing areas in South-East Asia. Within this extensive flat fertile land, lower Gangetic basin, especially the south Bengal, is most intensively cultivated. In this study we map the ric...

DOAJ Open Access (DOAJ) DOI: 10.5194/isprs-archives-XLII-5-271-2018

A long-term daily 500 m snow cover extent product over China (1981–2000)

Yanlong Shen, Xiaoyan Wang, Ruixiang Zhu, Shi Liang et al. • Big Earth Data (2026)

Due to the limitations of early satellite sensors in terms of spatial resolution, temporal resolution, and time series availability, there is currently a lack of long-term daily snow cover extent (SCE) products with 500 m spatial resolution...

DOAJ Open Access (DOAJ) DOI: 10.1080/20964471.2026.2648197

Data for: Terrain units, land use/cover, and gross primary productivity of the largest fluvial basin in the Brazilian Amazonia/Cerrado ecotone: The Araguaia River Basin

Antonio Couto, Junior, Pedro Martins, Edson Sano, Eder Martins et al. • Data in Brief (2021)

Integrity of most of tropical wetlands is threatened because they are often considered freely available resources of land and water. The Araguaia River Basin is one of the Brazilian basins most influenced by tropical seasonal floods, in add...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.dib.2020.106636

Assessment of the response of tropical dry forests to El Niño southern oscillation

Lidong Zou, Sen Cao, Zaichun Zhu, Arturo Sanchez-Azofeifa • Ecological Indicators (2021)

Tropical Dry Forests (TDFs) in the Americas are significantly affected by drought related to El Niño Southern Oscillation (ENSO). The analysis builds upon two drought indices: the MODIS-derived Vegetation Condition Index (VCI) and Temperatu...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ecolind.2021.108390

Prior Season Crop Type Masks for Winter Wheat Yield Forecasting: A US Case Study

Inbal Becker-Reshef, Belen Franch, Brian Barker, Emilie Murphy et al. • Remote Sensing (2018)

Monitoring and forecasting crop yields is a critical component of understanding and better addressing global food security challenges. Detailed spatial information on crop-type distribution is fundamental for in-season crop condition monito...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs10101659

SnowMapPy: An automated GEE Python tool for snow cover mapping and monitoring in the Moroccan Atlas Mountains

Haytam Elyoussfi, Hatim Bechri, Mostafa Bousbaa, Salwa Belaqziz et al. • SoftwareX (2026)

SnowMapPy is an open-source Python-based package developed to streamline the collection, processing, and analysis of MODIS snow cover data from Terra and Aqua satellites. By automating essential steps, including data clipping, reprojection,...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.softx.2026.103006

Using different computing systems to solve the automatic cloud classification problem according to MODIS satellite data by probabilistic neural network

Aleksey Viktorovich Skorokhodov, Sergey Vladimirovich Aksenov, Andrey Vladimirovich Aksenov, Dmitriy Nikolaevich Laykom • Известия Томского политехнического университета: Инжиниринг георесурсов (2017)

The relevance of the research is caused by the necessity to develop algorithms and software to classify the cloud types based on single-layer cloud on the satellite images received from MODIS spectral radiometer used in Terra and Aqua remot...

DOAJ Open Access (DOAJ)

MATCHA, a novel regional hydroclimate-chemical reanalysis: System description and evaluation

C. Roychoudhury, R. Kumar, C. He, W. Y. Y. Cheng et al. • Earth System Science Data (2026)

We present MATCHA (Model for Atmospheric Transport and Chemistry in Asia), a 17-year (2003–2019) regional hydroclimate-chemical reanalysis for Asia (58–140° E, 4– 40° N) at 12 km resolution. MATCHA couples the Weather Research and Forecasti...

DOAJ Open Access (DOAJ) DOI: 10.5194/essd-18-5209-2026

Aerosol Optical Depth Retrieval from MODIS Using a Physically Informed Machine Learning Framework

Tianchen Liang, Linqing Zou, Qiaoning He, Lin Sun • Remote Sensing (2026)

Retrieving aerosol optical depth (AOD) over land remains challenging because the relatively weak aerosol signal in top-of-atmosphere (TOA) observations must be separated from strong and spatially heterogeneous surface reflectance. Here, we ...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs18172862

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Amanuel Kumsa Bojer, Muluneh Woldetsadik Abshare, Fitsum Mesfin, Ayad M. Fadhil Al-Quraishi • Scientific Reports (2025)

Abstract Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spati...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-03493-8

A satellite-derived, ground-measurement-independent monthly PM2.5 mass concentration dataset over China during 2000 - 2015

Ying Zhang, Zhengqiang Li, Yuanyuan Wei, Zongren Peng • Big Earth Data (2021)

Following the accelerated development of urbanization and industrialization, atmospheric particulate matter has become a significant threat to public health globally. Environmental health studies usually use the mass concentration of fine p...

DOAJ Open Access (DOAJ) DOI: 10.1080/20964471.2021.1918908