A5087927767- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Remote Sensing and Land Use
- Conservation, Biodiversity, and Resource Management
- Oil Palm Production and Sustainability
- Smart Agriculture and AI
- Forest ecology and management
- Chaos-based Image/Signal Encryption
- Species Distribution and Climate Change
- Fire effects on ecosystems
- Remote-Sensing Image Classification
- Urban Heat Island Mitigation
- Wood and Agarwood Research
- Cloud Computing and Resource Management
- Advanced Computational Techniques and Applications
- Advanced Data Storage Technologies
- Geographic Information Systems Studies
- Tree Root and Stability Studies
- Cellular Automata and Applications
- Distributed and Parallel Computing Systems
- Leaf Properties and Growth Measurement
- Fungal Biology and Applications
- Fractal and DNA sequence analysis
- Plant and Biological Electrophysiology Studies
Southwest Forestry University
2015-2025
State Forestry and Grassland Administration
2023-2025
Yunnan Forestry Vocational and Technical College
2024
Mahidol University
2020
University of Oklahoma
2015-2018
Kunming University of Science and Technology
2012-2015
Dana (United States)
2012
The Erhai Lake Basin is an area with the active economic and social development of agriculture tourism, facing increasingly prominent environmental problems rapid urbanization. Assessing spatial–temporal changes in ecological environment quality objectively quantitatively a timely fashion crucial for protection policymaking. First, we selected high-quality Landsat imagery acquired at same time phase years 1999, 2004, 2009, 2014, 2019 respectively. Second, remote sensing-based index (RSEI)...
The accurate estimation of aboveground biomass (AGB) in rubber plantations is essential for predicting production and assessing carbon storage. Multispectral sensors mounted on unmanned aerial vehicles (UAVs) can obtain high spatiotemporal resolution imagery plantations, offering significant advantages capturing fine structural details heterogeneity. However, most previous studies primarily focused developing models using machine learning (ML) algorithms conjunction with feature selection...
Accurate and updated finer resolution maps of rubber plantations stand ages are needed to understand assess the impacts on regional ecosystem processes. This study presented a simple method for mapping plantation areas their by integration PALSAR 50-m mosaic images multi-temporal Landsat TM/ETM+ images. The L-band were used map forests (including both natural trees) non-forests. For those PALSAR-based forest pixels, we analyzed from 2000 2009. We first studied phenological signatures...
Accurate counting of Amorphophallus konjac (Konjac) plants can offer valuable insights for agricultural management and yield prediction. While current studies have primarily focused on detecting crop during the early stages low coverage, there is limited investigation into later high which could impact accuracy forecasting yield. High canopy coverage severe occlusion in pose significant challenges plant detection counting. Therefore, this study evaluated performance Count Crops tool a deep...
Abstract As farmland systems vary over space and time (season year), accurate updated maps of paddy rice are needed for studies food security environmental problems. We selected a wheat-rice double-cropped area from fragmented landscapes along the rural–urban complex (Jiangsu Province, China) explored potential utility integrating series optical images (Landsat-8, MODIS) radar (PALSAR) in mapping planting areas. first identified several main types non-cropland land cover then fields by...
Yuxi, located in China's central plateau of Yunnan, is grappling with ecological and environmental challenges as it continues to develop its economy. While quality assessment serves the foundation for protection, pivotal have reliable long-term methods assessing status support informed decision-making protection. Reliable order facilitate protection are applied. This study utilized Landsat data reconstruct four indices (greenness, wetness, dryness, heat) during vegetation growth Yuxi from...
Understanding post-fire vegetation recovery dynamics is crucial for damage assessment and planning, yet spatiotemporal patterns in complex plateau environments remain poorly understood. This study addresses this gap by focusing on Yunnan Province, a mountainous region with high fire incidence. We developed an innovative approach combining differenced Normalized Burn Ratio (dNBR) visual interpretation Google Earth Engine (GEE) to generate high-quality training samples from Landsat 5 TM/7...
This study aimed to accurately map burned forest areas and analyze the spatial distribution of fires under complex terrain conditions. integrates Landsat 8, Sentinel-2, MODIS data in western Yunnan. A machine learning workflow was developed on Google Earth Engine by combining Dynamic World land cover with official fire records, utilizing a logistic regression-based feature selection strategy an enhanced SNIC segmentation GEOBIA framework. The performance four classifiers (RF, SVM, KNN, CART)...
Forest fires are an important disturbance that affects ecosystem stability and pose a serious threat to the ecosystem. However, recovery process of forest ecological quality (EQ) after fire in plateau mountain areas is not well understood. This study utilizes Google Earth Engine (GEE) Landsat data generate difference indices, including NDVI, NBR, EVI, NDMI, NDWI, SAVI, BSI. After segmentation using Simple Non-Iterative Clustering (SNIC) method, were input into random (RF) model accurately...
The estimation of Above-Ground Biomass (AGB) in Amorphophallus konjac (Konjac) is essential for field management and yield prediction. While previous research has demonstrated the efficacy Unmanned Aerial Vehicle (UAV) RGB imagery estimating AGB monoculture crops, applicability these methods to Konjac remains uncertain due its distinct morphological traits prevalent intercropping practices with maize. Additionally, Vegetation Indices (VIs) Texture Features (TFs) obtained from UAV-based...
Forest fine fuels are a crucial component of surface and play key role in igniting forest fires. However, despite nearly 20 years long-term prescribed burning management on Zhaobi Mountain Xinping County, Yunnan Province, China, there remains lack specific quantification regarding the effectiveness fuel Pinus yunnanensis forests. In this study, 10 m × sample plots were established following one year growth after burning. The placed (PB) area an unburned control (UB) area. We utilized...
Forest mapping using remote sensing has made considerable progress over the past decade, but substantial uncertainties remain in complex regions, particularly where terrain and climate vary dramatically. Yunnan Province, China, represents such a challenging case, with its diverse climatic zones ranging from tropical to temperate topography spanning 6500 m elevation. These factors contribute variation vegetation types, complicating accurate identification of forest cover through sensing. This...
Carbon stock (CS) is an important indicator of the structure and function forest ecosystems, plays role in mitigating climate change, maintaining ecological system balance, promoting carbon trading, other socioeconomic values. Olea europaea L. a species high economic value, its excellent nutritional composition, strong drought tolerance, sustainable production characteristics, promotion agrodiversity make it guaranteeing food security. Accurately estimating CS offers reliable reference for...
Monoculture rubber plantations have been replacing tropical rain forests substantially in Southern China and Southeast Asia over the past several decades, which affected human wellbeing ecosystem services. However, to best of our knowledge on extent plantation expansion their stand ages is limited. We tracked spatiotemporal dynamics deciduous Xishuangbanna, second largest natural production region China, from 2000 2010 using time-series data Phased Array type L-band Synthetic Aperture Radar...
The rapid, accurate, and non-destructive estimation of rubber plantation aboveground biomass (AGB) is essential for producers to forecast yield carbon storage. To enhance the accuracy, an increasing number remote sensing variables are incorporated into development multi-parameter models, which makes its practical application potential impact on predictive precision challenging due inclusion non-essential or redundant variables. Therefore, this study systematically evaluated performance...
The increasing expansion of rubber plantations throughout East and Southeast Asia urgently requires improved methods for effective mapping monitoring. phenological information from was found in mapping. Previous studies have mostly applied rule-pixel-based phenology approaches mapping, which might result broken patches fragmented landscapes. This study introduces a new paradigm by combining with object-based classification to map Xishuangbanna. research first delineated the time windows...