Article
Environmental Sciences
Marcelo Sacardi Biudes, Hatim M. E. Geli, George Louis Vourlitis, Nadja Gomes Machado, Vagner Marques Pavao, Luiz Octavio Fabricio dos Santos, Carlos Alexandre Santos Querino
Summary: Brazilian tropical ecosystems in the state of Mato Grosso have undergone significant land use and cover changes, which directly affect the mass and energy exchange near the surface and the process of evapotranspiration (ET). This study aimed to characterize the temporal and spatial patterns of ET using remotely sensed products and evaluate the accuracy of MOD16 ET in representing the ET patterns in Mato Grosso. The results showed that there was no significant difference between the MOD16 ET and the measured ET, indicating a good performance of MOD16 ET in this region. The spatial variation of ET was similar to the climatology of Mato Grosso, with higher ET in the wet period compared to the dry period. The study emphasizes the importance of studying ET in Mato Grosso due to land cover and climate change.
Article
Environmental Sciences
Eduarda M. O. Silveira, Volker C. Radeloff, Sebastian Martinuzzi, Guillermo J. Martinez Pastur, Luis O. Rivera, Natalia Politi, Leonidas Lizarraga, Laura S. Farwell, Paul R. Elsen, Anna M. Pidgeon
Summary: The study highlights the importance of integrating inter-annual and spatial variability data for biodiversity conservation, as areas with high spatial variability may have higher ecological resilience. Regions with low spatial variability and high inter-annual variability require increased management efforts, while areas with high spatial variability may be high priority candidates for protection.
REMOTE SENSING OF ENVIRONMENT
(2021)
Article
Environmental Sciences
Daniel Sousa, Christopher Small
Summary: Research conducted on the expansion of aquaculture in the Lower Ganges-Brahmaputra Delta revealed a rapid increase in standing water area, as well as a growing trend of aquaculture areas expanding over time. This expansion is primarily concentrated in the Sundarbans area of Bangladesh.
Article
Environmental Sciences
Wei Xue, Jonghan Ko, Ruyin Cao, Zhiguo Yu
Summary: This study proposes a simple yet effective Light and Temperature-Driven Growth model and Double Logistic function fusion algorithm (LTDG_DL) to predict the Landsat 5/7 EVI time series over cloud-prone, fragmented, and mosaic agricultural landscapes. The LTDG_DL algorithm calibrates the empirical EVI by adjusting crop growth using cloud-free Landsat EVI observations and assimilates ground daily solar radiation and air temperature to generate seasonal profiles of the empirical LAI and EVI. Compared to other interpolation functions and fusion algorithms, LTDG_DL algorithm demonstrates superior performance in predicting EVI increment slope, timing of peak EVI, and protecting key Landsat EVI observations.
Article
Environmental Sciences
Mahesh Palakuru, S. K. Khadar Babu, Nilima Rani Chaube
Summary: The development of satellite and remote sensing technology enables continuous monitoring and classification of rice crop phenological stages, as well as mapping production areas. Researchers can estimate rice yield through field visits and statistical analysis, with satisfactory results in mapping phenological stages.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2021)
Article
Geography, Physical
Murali Krishna Gumma, Prasad S. Thenkabail, Pranay Panjala, Pardhasaradhi Teluguntla, Takashi Yamano, Ismail Mohammed
Summary: Cropland products play a significant role in assessing water and food security in South Asia. This study aimed to produce three distinct products that would be useful overall in the region, including assessing irrigated versus rainfed croplands, identifying major crop types, and evaluating cropping intensity. By utilizing remote sensing data and machine learning algorithms, the study successfully generated accurate cropland products.
GISCIENCE & REMOTE SENSING
(2022)
Article
Forestry
Jingru Zhang, Xiaojuan Tong, Jinsong Zhang, Ping Meng, Jun Li, Peirong Liu
Summary: This study compared phenological metrics obtained from flux tower GPP with those derived from MODIS EVI and MCD12Q2, finding that MODIS EVI and MCD12Q2 are valuable for detecting vegetation phenological dynamics. Temperature plays a more crucial role in phenophase than precipitation.
FOREST ECOLOGY AND MANAGEMENT
(2021)
Article
Environmental Sciences
Monika A. Tomaszewska, Geoffrey M. Henebry
Summary: The study used higher spatial resolution land surface phenology modeling results to characterize patterns of phenometrics in highland pastures in Kyrgyz Republic. It found that terrain features and seasonal weather can modulate the influence of village proximity on phenology, and that aspect can attenuate negative impacts of dry conditions on seasonal peak values. The study also discussed limitations in previous and recent studies of pasture degradation.
Article
Environmental Sciences
Chang Fan, Jilin Yang, Guosong Zhao, Junhu Dai, Mengyao Zhu, Jinwei Dong, Ruoqi Liu, Geli Zhang
Summary: This study compared ground and satellite observations and found that the 30m Landsat/Sentinel-2 data was more consistent with ground observations in wetland vegetation phenology, indicating its advantage over the 500m MODIS data. The study also highlighted the complexity of wetland phenology and its role in global climate change.
Article
Remote Sensing
Avinash Kumar Ranjan, Amit Kumar Gorai
Summary: This study used MODIS-based EVI dataset to investigate the vegetation phenological trends in response to climate change in the Rajmahal Hills region of India from 2001 to 2019. The start of season (SOS) and end of season (EOS) were analyzed, and it was found that most vegetation types showed either an advancing or delaying trend, influenced by changes in precipitation and temperature patterns.
REMOTE SENSING LETTERS
(2022)
Article
Remote Sensing
Joanne Hall, Fernanda Argueta, Louis Giglio
Summary: The study finds that small fires are often underestimated in agricultural areas within global burned area and fire emission inventories. Current validation methods designed for larger wildfires are not suitable for small fires. An alternative approach using detailed field-level burned area reference maps was used to validate two global burned area products, revealing high omission and commission error rates.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Remote Sensing
Nanfeng Liu, Matthew Garcia, Aditya Singh, John D. J. Clare, Jennifer L. Stenglein, Benjamin Zuckerberg, Eric L. Kruger, Philip A. Townsend
Summary: Using the Snapshot Wisconsin trail camera network for plant phenology monitoring is efficient. There are differences in phenological offset between understory and overstory vegetation in different forest types, and factors influencing phenology are varied.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2021)
Article
Agronomy
Zewei Yue, Zhao Li, Guirui Yu, Zhi Chen, Peili Shi, Yunfeng Qiao, Kun Du, Chao Tian, Fenghua Zhao, Peifang Leng, Zhaoxin Li, Hefa Cheng, Gang Chen, Fadong Li
Summary: This study characterized the CO2 fluxes of a winter wheat-summer maize rotation cropland in different growing periods and identified the driving factors using long-term monitoring data. Leaf area index (LAI), photosynthetically active radiation (PAR), and soil water content (SWC) were found to be important drivers of CO2 fluxes in both wheat and maize seasons. The findings provide valuable insights into the carbon cycle of cropland ecosystems under climate change.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Environmental Sciences
Yijing Zhao, Xiaoli Wang, Yu Guo, Xiyong Hou, Lijie Dong
Summary: Crop phenology, especially winter wheat, is influenced by climate variables such as temperature and precipitation. In Shandong Province, China, the phenological changes of winter wheat show a spatial pattern and a trend of delay and advancement in some regions.
Article
Environmental Sciences
Denis Corte Vieira, Ieda Del 'Arco Sanches, Bruno Montibeller, Victor Hugo Rohden Prudente, Matthew C. Hansen, Antoine Baggett, Marcos Adami
Summary: This study investigates the dynamics of land use and land cover in Mato Grosso state, Brazil, focusing on cropland expansion and intensification. The results show an increase in both the extent and intensification of cropland in the state, with soy and corn prices playing a significant role in cropland expansion. However, deforestation in the humid tropical forest biome of Amazonia was not directly correlated with soy production. These dynamics are influenced by various factors, including conservation policies, market demand, climate, and technology, shaping Brazil's role as a global commodity crop producer.
REMOTE SENSING APPLICATIONS-SOCIETY AND ENVIRONMENT
(2022)
Article
Remote Sensing
Mariane Souza Reis, Luciano Vieira Dutra, Sidnei Joao Siqueira Sant'Anna, Maria Isabel Sobral Escada
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2020)
Article
Geography, Physical
Guiying Li, Longwei Li, Dengsheng Lu, Wei Guo, Wenhui Kuang
GISCIENCE & REMOTE SENSING
(2020)
Article
Environmental Sciences
Marinalva Dias Soares, Luciano Vieira Dutra, Gilson Alexandre Ostwald Pedro da Costa, Raul Queiroz Feitosa, Rogerio Galante Negri, Pedro M. A. Diaz
Article
Remote Sensing
Longwei Li, Nan Li, Zhuo Zang, Dengsheng Lu, Guangxing Wang, Ni Wang
Summary: Moso bamboo has unique characteristics such as fast growth rate, short harvesting cycle, and on/off-year phenomenon. This research used data from the VEN mu S micro-satellite to analyze the phenological features of Moso bamboo forests, determining sensitive spectral ranges for seasonal variation and identifying different phenological periods using the Red-edge Position Index (REPI).
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2021)
Article
Geography, Physical
Yaoliang Chen, Xiaotao Huang, Jingfeng Huang, Shanshan Liu, Dengsheng Lu, Shuai Zhao
Summary: The study successfully monitored the dynamics of desert vegetation in a dryland basin of Northwest China using MESMA method. Results showed areas of degradation, recovery, and greening, and analyzed different influencing factors, demonstrating the potential application of this method in semi-arid and arid regions.
GISCIENCE & REMOTE SENSING
(2021)
Article
Biodiversity Conservation
Dengqiu Li, Dengsheng Lu, Yan Zhao, Mingxing Zhou, Guangsheng Chen
Summary: This study developed a new framework to assess habitat fragmentation by integrating spatial patterns of vegetation coverage and its change in the giant panda habitat ecosystem of China. The results revealed that most disturbed areas experienced negative abrupt vegetation change, while undisturbed areas mainly showed an increase in vegetation. By identifying spatial clusters and outliers, the study pinpointed areas in need of careful management to reduce habitat fragmentation.
ECOLOGICAL INDICATORS
(2021)
Article
Geography, Physical
Wenke Lin, Yagang Lu, Guiying Li, Xiandie Jiang, Dengsheng Lu
Summary: This study compares the performance of LS-CHM and L-CHM for FGSV modeling and explores the advantages of using the hierarchical Bayesian approach when sample size is small. The results show that L-CHM provides better predictions overall using the same modeling approaches, but LS-CHM-based variables produce better modeling accuracy than L-CHM-based variables in a specific range of FGSV. The HBA based on stratification of both forest type and slope aspect provides the best FGSV estimation.
GISCIENCE & REMOTE SENSING
(2022)
Article
Environmental Sciences
Mengzhuo Fan, Kuo Liao, Dengsheng Lu, Dengqiu Li
Summary: Examining the characteristics and spatial patterns of vegetation change under different protection levels can provide a scientific basis for national park protection and management. The study analyzed the vegetation change in Wuyishan National Park using Landsat EVI data from 1986 to 2020 and the WBS approach. The results showed that the highest percentage of area without abrupt change was in the strictly protected area, while the non-protected area had the lowest percentage. The study also found that the vegetation coverage generally improved in the park, with higher positive percentage in the protected areas. However, the non-protected area had a higher mean greenness change. The study highlighted the importance of protection level in determining vegetation change and spatial patterns in the national park.
Article
Environmental Sciences
Kuo Liao, Yunhe Li, Bingzhang Zou, Dengqiu Li, Dengsheng Lu
Summary: This study compared the accuracy of tree height measurements using different methods and the influence of allometric models on tree volume estimation accuracy. The results showed significant impacts of different measurement methods on tree volume calculations, and incorporating UAV Lidar data with DBH field measurements can effectively improve tree volume estimation accuracy.
Article
Environmental Sciences
Yi Zhang, Dengsheng Lu, Xiandie Jiang, Yunhe Li, Dengqiu Li
Summary: In this study, the 3-PG model was optimized and calibrated using survey and UAV lidar data at the sample plot scale and applied at the forest sub-compartment scale. The results show that both survey forests age data and remote-sensing-derived forest age data can accurately estimate eucalyptus plantation parameters. The simulation results based on remote-sensed forest age data are significantly better than the ones based on survey data, providing an important reference for future studies using remote sensing-derived forest age data in large spatial scales.
Article
Remote Sensing
Ruoqi Wang, Guiying Li, Yagang Lu, Dengsheng Lu
Summary: This research compared the advantages of using object-based GSV modeling approach with traditional grid-based approaches for poplar GSV estimation. The results showed that the object-based approach was more accurate in estimating GSV and solving the mixed plot problem in the striped forest distribution areas.
GEO-SPATIAL INFORMATION SCIENCE
(2023)
Article
Environmental Sciences
Yongpeng Ye, Dengsheng Lu, Zuohang Wu, Kuo Liao, Mingxing Zhou, Kai Jian, Dengqiu Li
Summary: This study developed a framework based on multi-source high-resolution satellite images to analyze vertical characteristics of mountainous vegetation distribution. The results showed distinct differentiation of vegetation types along elevation gradients in Wuyishan National Park, with significant differences in distribution patterns under different human protection levels.
Article
Remote Sensing
Willian Vieira de Oliveira, Luciano Vieira Dutra, Sidnei Joao Siqueira Sant'Anna
Summary: In land-cover classification using remote sensing images, methods that solely analyze the spectral information of individual pixels often generate noisy results. Incorporating spatial contextual information into classification can effectively reduce noise and improve accuracy. However, existing contextual methods may oversmooth certain classes, causing the loss of important spatial structures. To address this issue, a strategy called Meta-CTX is proposed, which allows for a trade-off between noise smoothing and the preservation of small spatial details.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Article
Forestry
Shiyun Pang, Guiying Li, Xiandie Jiang, Yaoliang Chen, Yagang Lu, Dengsheng Lu
Summary: This research aims to explore the method of accurately retrieving forest canopy height from ATLAS data and improve retrieval accuracy by incorporating a high-precision digital terrain model (DTM) and a data-filtering strategy. The results show that using the proposed method, the retrieval accuracy of forest canopy height in mountainous regions with dense forest cover and complex terrain conditions can be considerably improved.
Article
Computer Science, Information Systems
Mariane Souza Reis, Luciano Vieira Dutra, Maria Isabel Sobral Escada, Sidnei Joao Siqueira Sant'anna
