Explanipedia

A practical method for deriving all-weather ET from remote sensing and meteorological data Open

Pengyu Hao, Liping Di, Liying Guo, Zhongxin Chen, Lynn Montgomery · 2025

Daily actual evapotranspiration (ET) is a crucial variable for efficient water resource management and irrigation planning, highlighting the need for timely and accurate ET products to support agricultural decision-making. This study prese…

Robust and timely within-season conterminous United States crop type mapping using Landsat Sentinel-2 time series and the transformer architecture Open

Hankui K. Zhang, Yu Shen, Xiaoyang Zhang, Junjie Li, Zhengwei Yang , et al. · 2025

Corrections to “In-Season Mapping of Sugarcane Planting Based on Sentinel-2 Imagery” Open

Hui Li, Liping Di, Chen Zhang, Li Lin, Liying Guo , et al. · 2025

This addresses errors in (1).

In-Season Mapping of Sugarcane Planting Based on Sentinel-2 Imagery Open

Hui Li, Liping Di, Chen Zhang, Li Lin, Liying Guo , et al. · 2024

Sugarcane is a significant crop in terms of annual biomass in the world. Timely and accurate mapping of sugarcane planting is important for food security and sustainability. However, accurately remote-sensing-based mapping sugarcane remain…

UAV detection technology research based on deep learning Open

Yu Wang, Xiaojun Bai, Liping Di, Shifeng Zhao · 2024

In the process of UAV target recognition, the target is small, the feature is not obvious, and the recognition accuracy is low, a UAV target detection method called YOLOv8-UD is proposed based on YOLOv8. This method replaces downsampling l…

Standardization of geospatial analysis ready data via OGC and ISO  Open

Liping Di, Genong Yu, Liying Guo, Patrick Quinn, Joshua Lieberman · 2024

Geospatial data are data with location information. Geospatial data are very diverse and widely used in various socioeconomic applications and decision makings. Typically, geospatial data obtained from data providers needs to go through a …

Modeling urban redevelopment: A novel approach using time-series remote sensing data and machine learning Open

Li Lin, Liping Di, Chen Zhang, Liying Guo, Haoteng Zhao , et al. · 2024

Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decision-makers to foster sustainable urban development. Traditional mapping methods heavily depend on field surveys and subjective questionnai…

In-Season Mapping of Sugarcane Planting Based on Sentinel-2 Imagery Open

Hui Li, Chen Zhang, Li Lin, Liying Guo, Ruopu Li , et al. · 2024

Phenology-Based Transfer Learning for Sugarcane Mapping in the U.S. And Brazil Open

Hui Li, Liping Di, Liying Guo, Ziao Liu, Bosen Shao · 2024

A Decision-Rule & Spatial Machine Learning-Based Approach for Automated Local Climate Zones (Lczs) Mapping Using Multi-Source Geospatial And Remote Sensing Data Open

Md Didarul Islam, Liping Di, Chen Zhang · 2024

A Decision Rule and Machine Learning-Based Hybrid Approach for Automated Land-Cover Type Local Climate Zones (LCZs) Mapping Using Multi-Source Remote Sensing Data Open

Md Didarul Islam, Liping Di, Chen Zhang, Ruixin Yang, John J. Qu , et al. · 2024

This article presents a streamlined, automated classification method to map land-cover-type local climate zones (LCZs). Using a two-phase hybrid approach, we first generated training samples through universal decision rules and subsequentl…

The Global Land Surface Temperature Change in the 21st Century—A Satellite Remote Sensing Based Assessment Open

Li Lin, Liping Di, Chen Zhang, Liying Guo · 2023

Changes in land surface temperature (LST) affect human society and the natural environment, especially for agricultural activities. In recent decades, satellite remote sensing has been used as an alternative approach to ground observation …

An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration Open

Haoteng Zhao, Liping Di, Liying Guo, Chen Zhang, Li Lin · 2023

Given the increasing prevalence of droughts, unpredictable rainfall patterns, and limited access to dependable water sources in the United States and worldwide, it has become crucial to implement effective irrigation scheduling strategies.…

Rapid Rice Yield Estimation Using Integrated Remote Sensing and Meteorological Data and Machine Learning Open

Md Didarul Islam, Liping Di, Faisal Mueen Qamer, Sravan Shrestha, Liying Guo , et al. · 2023

This study developed a rapid rice yield estimation workflow and customized yield prediction model by integrating remote sensing and meteorological data with machine learning (ML). Several issues need to be addressed while developing a crop…

Operational in-season rice area estimation through Earth observation data in Nepal - working paper Open

Faisal Mueen Qamer, Sravan Shrestha, Kiran Shakya, Birendra Bajracharya, Shib Nandan Shah , et al. · 2023

In an effort to adopt emerging technologies in food security assessment through a codevelopment approach, the Government of Nepal’s Ministry of Agriculture and Livestock Development (MoALD) and the International Centre for Integrated Mount…

Improving GEDI Forest Canopy Height Products by Considering the Stand Age Factor Derived from Time-Series Remote Sensing Images: A Case Study in Fujian, China Open

Xiaocheng Zhou, Youzhuang Hao, Liping Di, Xiaoqin Wang, Chongcheng Chen , et al. · 2023

Forest canopy height plays an important role in forest resource management and conservation. The accurate estimation of forest canopy height on a large scale is important for forest carbon stock, biodiversity, and the carbon cycle. With th…

RiceMapEngine: A Google Earth Engine-Based Web Application for Fast Paddy Rice Mapping Open

Zhiqi Yu, Liping Di, Sravan Shrestha, Chen Zhang, Liying Guo , et al. · 2023

Mapping rice area is a critical resource planning task in many South Asia countries where rice is the primary crop. Remote-sensing-based methods typically rely on domain knowledge, such as crop calendar and crop phenology, and supervised c…

Evaluating contributions of urbanization and global climate change to urban land surface temperature change: a case study in Lagos, Nigeria Open

Liying Guo, Liping Di, Chen Zhang, Li Lin, Fei Chen , et al. · 2022

Near-real-time MODIS-derived vegetation index data products and online services for CONUS based on NASA LANCE Open

Chen Zhang, Zhengwei Yang, Liping Di, Genong Yu, Bei Zhang , et al. · 2022

Crop-CASMA: A web geoprocessing and map service based architecture and implementation for serving soil moisture and crop vegetation condition data over U.S. Cropland Open

Chen Zhang, Zhengwei Yang, Haoteng Zhao, Ziheng Sun, Liping Di , et al. · 2022

Spatio-Temporal Responses of Precipitation to Urbanization with Google Earth Engine: A Case Study for Lagos, Nigeria Open

Alamin Molla, Liping Di, Liying Guo, Chen Zhang, Fei Chen · 2022

Lagos, Nigeria, is considered a rapidly growing urban hub. This study focuses on an urban development characterization with remote sensing-based variables for Lagos as well as understanding spatio-temporal precipitation responses to the ch…

WaterSmart-GIS: A Web Application of a Data Assimilation Model to Support Irrigation Research and Decision Making Open

Haoteng Zhao, Liping Di, Ziheng Sun · 2022

Irrigation is the primary consumer of freshwater by humans and accounts for over 70% of all annual water use. However, due to the shortage of open critical information in agriculture such as soil, precipitation, and crop status, farmers he…

Bibliometric Analysis of OGC Specifications between 1994 and 2020 Based on Web of Science (WoS) Open

Mingrui Huang, Xiangtao Fan, Hongdeng Jian, Hongyue Zhang, Liying Guo , et al. · 2022

The Open Geospatial Consortium (OGC) is an international non-profit standards organization. Established in 1994, OGC aims to make geospatial information and services FAIR-Findable, Accessible, Interoperable, and Reusable. OGC specification…

Validation and refinement of cropland data layer using a spatial-temporal decision tree algorithm Open

Li Lin, Liping Di, Chen Zhang, Liying Guo, Yahui Di , et al. · 2022

Refined Cropland Data Layer (R-CDL) Open

Li Lin, Liping Di, Chen Zhang · 2022

A decision tree algorithm was employed to refine Cropland Data Layer (CDL) using spatial and temporal information. The Refined Cropland Data Layer (R-CDL) could be used as an alternative to researchers as it provides more accurate cropland…

Refined Cropland Data Layer (R-CDL) Open

Li Lin, Liping Di, Chen Zhang · 2022

A decision tree algorithm was employed to refine Cropland Data Layer (CDL) using spatial and temporal information. The Refined Cropland Data Layer (R-CDL) could be used as an alternative to researchers as it provides more accurate cropland…

Refined Cropland Data Layer (R-CDL) Open

Li Lin, Liping Di, Chen Zhang · 2022

A decision tree algorithm was employed to refine Cropland Data Layer (CDL) using spatial and temporal information. The Refined Cropland Data Layer (R-CDL) could be used as an alternative to researchers as it provides more accurate cropland…

Near-real-time MODIS-derived vegetation index data products for CONUS (sample data) Open

Chen Zhang, Zhengwei Yang, Liping Di, Genong Yu, Bei Zhang , et al. · 2022

This is a Near-Real-Time (NRT) Vegetation Index (VI) data set for the Conterminous United States (CONUS) based on MODIS data from Land, Atmosphere Near-real-time Capability for EOS (LANCE), an openly accessible NASA near-real-time EO data …

Near-real-time MODIS-derived vegetation index data collection for CONUS (sample) Open

Chen Zhang, Zhengwei Yang, Liping Di, Genong Yu, Bei Zhang , et al. · 2022

This is a Near-Real-Time (NRT) Vegetation Index (VI) data set for the Conterminous United States (CONUS) based on MODIS data from Land, Atmosphere Near-real-time Capability for EOS (LANCE), an openly accessible NASA near-real-time EO data …

Refined Cropland Data Layer (R-CDL) Open

Li Lin, Liping Di, Chen Zhang · 2021

A decision tree algorithm was employed to refine Cropland Data Layer (CDL) using spatial and temporal information. The Refined Cropland Data Layer (R-CDL) could be used as an alternative to researchers as it provides more accurate cropland…

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