Article
Environmental Sciences
Lei Cui, Mei Sun, Ziti Jiao, Jongmin Park, Muge Agca, Hu Zhang, Long He, Yiqun Dai, Yadong Dong, Xiaoning Zhang, Yi Lian, Lei Chen, Kaiguang Zhao
Summary: In this study, the effectiveness of using multi-angle optical reflectance measurements, specifically those from the MODIS instrument, for estimating forest aboveground biomass (AGB) was examined. The results showed that multi-angle reflectances, particularly in the NIR band, were sensitive to forest AGB after accounting for complex terrain and pixel heterogeneity. The accuracy of the estimates also varied with the acquisition dates or season of the MODIS images. Overall, the study suggested that incorporating multi-angle reflectances in optical remote sensing can improve the estimation of forest AGB.
Article
Environmental Sciences
Shuai Zhang, Tamlin M. Pavelsky, Christopher D. Arp, Xiao Yang
Summary: A remote sensing-derived lake ice phenology database covering all lakes in Alaska from 2000 to 2019 was constructed to analyze the trends of earlier breakup and later freezeup of lake ice in the region. The dataset showed significant trends towards earlier or later ice breakup and freezeup for various lakes, with most significant trends observed in lakes north of the Brooks Range. This dataset contributes to the understanding of interactions between lake processes and climate change, supporting research on biogeochemical, limnological, and ecological regimes in Alaska and pan-Arctic regions.
ENVIRONMENTAL RESEARCH LETTERS
(2021)
Article
Environmental Sciences
Xiaoyan Wang, Chao Han, Zhiqi Ouyang, Siyong Chen, Hui Guo, Jian Wang, Xiaohua Hao
Summary: This study investigates cloud-snow confusion in MODIS snow cover products and proposes a temporal-sequence cloud-snow-distinguishing algorithm. The algorithm distinguishes cloud and snow by comparing the NDSI variance, effectively reducing cloud mask errors and correctly identifying ice clouds that may have been misclassified as snow.
Article
Environmental Sciences
Jieying Ma, Shuanggen Jin, Jian Li, Yang He, Wei Shang
Summary: The study proposed a multi-source remote sensing-based approach for monitoring Harmful algal blooms (HABs) in Chaohu Lake, China, achieving high temporal and spatial resolution observations. By utilizing different spectral indices algorithms, HABs were successfully extracted and misidentification of mixed pixels was avoided. The results revealed the seasonal outbreaks of HABs, the driving forces behind their growth, and the significant impact of wind on their surface variation.
Review
Environmental Sciences
Yidan Si, Qifeng Lu, Xingying Zhang, Xiuqing Hu, Fu Wang, Lei Li, Songyan Gu
Summary: This paper introduces the common technique of using satellite observation data to retrieve atmospheric pollution parameters and summarizes the new developments in detecting aerosol parameters with multi-angle and/or polarized remote sensing observation instruments. The research status of aerosol characteristics in recent years is discussed from the perspective of airborne, space-borne, and ground-based detections, introducing the advancements in data set accuracy evaluation, inversion algorithm improvement, and product application.
ATMOSPHERIC ENVIRONMENT
(2021)
Article
Environmental Sciences
Md Ataullah Raza Khan, Shaktiman Singh, Pratima Pandey, Anshuman Bhardwaj, Sheikh Nawaz Ali, Vasudha Chaturvedi, Prashant Kumar Champati Ray
Summary: This study quantified the distribution of permafrost in the Western Himalaya using multisource satellite datasets, revealing a large portion of barren land and majority of the area with a mean annual air temperature below 1 degree Celsius. The research also showed high interannual variability in permafrost distribution and a significant decrease in permafrost cover from 2002 to 2020.
Article
Environmental Sciences
Hongtao Cao, Dongqin You, Dabin Ji, Xingfa Gu, Jianguang Wen, Jianjun Wu, Yong Li, Yongqiang Cao, Tiejun Cui, Hu Zhang
Summary: This study presents a method for bidirectional reflectivity measurement of ground-based objects using unmanned aerial vehicles (UAVs). It utilizes a polygonal flight path and photogrammetry's principle of aerial triangulation to obtain accurate observation angles and geometric structure. Three BRDF models were compared and evaluated, with the RPV model showing the best inversion performance. These methods and findings are of great importance for studying the reflection properties of ground-based objects.
Article
Environmental Sciences
Yuan Yao, Yee Leung, Tung Fung, Zhenfeng Shao, Jie Lu, Deyu Meng, Hanchi Ying, Yu Zhou
Summary: This paper analyzes the differences between traditional remote sensing data and continuous multi-angle remote sensing (CMARS) data, highlighting the advantages of using CMARS data for classification. Real-life experiments show the superiority of CMARS data over traditional data in classification, with an increase in overall accuracy of up to about 9%. The research also explores the advantages and disadvantages of utilizing CMARS data directly and the potential for better utilization through the extraction of key features characterizing spectral reflectance variations.
Article
Plant Sciences
Hai-Yan Zhang, Meng-Ran Liu, Zi-Heng Feng, Li Song, Xiao Li, Wan-Dai Liu, Chen-Yang Wang, Wei Feng
Summary: The study utilized multi-angle remote sensing technology to monitor the water use efficiency of winter wheat, finding that backward observation angles were better than forward angles. A new water efficiency index (WEI) was developed, which showed greater sensitivity to changes in WUE compared to common spectral parameters.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Environmental Sciences
Hu Zhang, Mengzhuo Zhao, Ziti Jiao, Yi Lian, Lei Chen, Lei Cui, Xiaoning Zhang, Yan Liu, Yadong Dong, Da Qian, Yiting Wang, Juan Li, Tiejun Cui
Summary: This study proposed an approach to extracting a priori BRDF (F) from the MODIS BRDF/albedo product, demonstrating high consistency between F-based shortwave albedo and the MODIS albedo product in most cases. The improvement of LCT and NDVI based on F is significant for tiles containing large areas of vegetation and barren ground.
Article
Environmental Sciences
Mark Chopping, Zhuosen Wang, Crystal Schaaf, Michael A. Bull, Rocio R. Duchesne
Summary: The study utilized NASA Jet Propulsion Laboratory Multi-angle Imaging Spectro-Radiometer (MISR) data to accurately map aboveground biomass density in forests of the southwestern United States. The results showed that MISR estimates reliably captured ABG compared to radar and lidar-derived estimates, confirming the consistency of the results.
REMOTE SENSING OF ENVIRONMENT
(2022)
Article
Ecology
Yelu Zeng, Dalei Hao, Taejin Park, Peng Zhu, Alfredo Huete, Ranga Myneni, Yuri Knyazikhin, Jianbo Qi, Ramakrishna R. Nemani, Fa Li, Jianxi Huang, Yongyuan Gao, Baoguo Li, Fujiang Ji, Philipp Koehler, Christian Frankenberg, Joseph A. Berry, Min Chen
Summary: Vegetation greenness, measured by spectral vegetation indices, can be affected by shadows cast by complex forest structures, leading to lower greenness measures. Understanding the impact of shadows is important for interpreting remote sensing data accurately.
NATURE ECOLOGY & EVOLUTION
(2023)
Article
Remote Sensing
Fadi Kizel, Yulia Vidro
Summary: This study investigates the influence of spectral mixture on the correction of the Bidirectional Reflectance Distribution Function (BRDF) effect and proposes an unmixing-based model to improve the correction accuracy. Experimental results demonstrate that the proposed model outperforms the traditional method in reducing the BRDF effect.
INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
(2023)
Article
Environmental Sciences
Junyu Gao, Maoguo Gong, Xuelong Li
Summary: In this paper, we propose a method named SwinCounter for object counting in remote sensing. The method addresses the issue of imbalanced object labels by introducing a Balanced MSE Loss and captures multi-scale information accurately using the attention mechanism. Experiments on the RSOC dataset demonstrate the competitiveness and superiority of the proposed method.
Article
Environmental Sciences
Mohammad Reza Goodarzi, Maryam Sabaghzadeh, Majid Niazkar
Summary: This study examined the impact of snowmelt on flooding and found that the contribution of snowmelt is more significant than rainfall in stream flows, especially in high-altitude areas.
Article
Multidisciplinary Sciences
Eduardo Eiji Maeda, Temesgen Alemayehu Abera, Mika Siljander, Luiz E. O. C. Aragao, Yhasmin Mendes de Moura, Janne Heiskanen
Summary: Deforestation in the Amazon rainforest has diverse and dynamic impacts on local climates, with large-scale commodity agriculture causing reductions in convective rainfall and increases in land surface temperature. Alternative agricultural practices and forest restoration are urgently needed to mitigate these effects.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Environmental Sciences
Zhipeng Tang, Giuseppe Amatulli, Petri K. E. Pellikka, Janne Heiskanen
Summary: The number of Landsat time-series applications has increased due to its long history and high spatial resolution, however, gaps in observations have limited its development. A new method, STIMDR, has been proposed to fill gaps and has shown robust and accurate performance in experiments.
Article
Forestry
Titta Majasalmi, Miina Rautiainen
Summary: A new approach was developed to calibrate phenological events in boreal forests using satellite and surface temperature data. Results showed that using standard phenometrics directly on satellite data may lead to biases in all species groups.
ANNALS OF FOREST SCIENCE
(2022)
Article
Geography, Physical
Hengwei Zhao, Yanfei Zhong, Xinyu Wang, Xin Hu, Chang Luo, Mark Boitt, Rami Piiroinen, Liangpei Zhang, Janne Heiskanen, Petri Pellikka
Summary: This study proposes a deep positive and unlabeled learning based OCC framework for identifying invasive tree species in the Taita Hills of southern Kenya. The framework achieves significant improvement in detection accuracy by fully utilizing massive unlabeled data.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Ecology
Jussi Juola, Aarne Hovi, Miina Rautiainen
Summary: The woody material of forest canopies affects the interpretation of remotely sensed data. This study developed a novel measurement setup and used a mobile hyperspectral camera to measure the stem bark reflectance spectra of ten tree species. The results showed that there was similarity in the visible region, but large interspecific variation in the near-infrared region.
ECOLOGY AND EVOLUTION
(2022)
Article
Environmental Sciences
Maria Yli-Heikkila, Samantha Wittke, Markku Luotamo, Eetu Puttonen, Mika Sulkava, Petri Pellikka, Janne Heiskanen, Arto Klami
Summary: One of the key principles of food security is to ensure the proper functioning of global food markets. This study proposes a method for large-scale crop yield estimations using satellite image time series, and demonstrates that a deep learning-based temporal convolutional network outperforms traditional machine learning methods and national crop forecasts in accuracy. The study also shows that mean-aggregated regional predictions with histogram-based features calculated from farm-level observations perform better than other tested approaches.
Article
Agronomy
Petri R. Forsstrom, Aarne Hovi, Jussi Juola, Miina Rautiainen
Summary: The study investigates the relationship between light availability at forest floor and its spectral reflectance properties and fractional cover across boreal and temperate Europe. The results show that tree canopy structure is linked to the vegetation composition and spectral reflectance properties of forest floor, and these relationships differ between forest biomes.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Letter
Multidisciplinary Sciences
Jan Pisek, Oliver Sonnentag, Torben R. R. Christensen
Article
Ecology
Sini-Selina Salko, Jussi Juola, Iuliia Burdun, Harri Vasander, Miina Rautiainen
Summary: The study highlights the importance of using spectral data in the shortwave infrared region (1100-2500 nm) for remote sensing applications, especially in monitoring the changes in wetland conditions.
ECOLOGY AND EVOLUTION
(2023)
Article
Forestry
Edward Amara, Hari Adhikari, James M. Mwamodenyi, Petri K. E. Pellikka, Janne Heiskanen
Summary: In the Taita Hills in Kenya, large trees and specific tree species play an important role in aboveground biomass (AGB), with riverine forests, montane forests, and mixed forests having the greatest contribution. Different land cover types also have characteristic tree species that contribute to AGB.
Article
Agronomy
Daniel Schraik, Di Wang, Aarne Hovi, Miina Rautiainen
Summary: In this study, a method was developed to measure the clumping index (CI) of forest stands using terrestrial lidar data. Measurements of CI and STARf were conducted on 38 forest stands in Finland, Estonia, and Czechia to study their natural range and relationships with other forest variables and Landsat 8 OLI surface reflectance. It was found that CI was closely correlated with surface reflectance in conifer forests.
AGRICULTURAL AND FOREST METEOROLOGY
(2023)
Article
Ecology
Iris Johanna Aalto, Eduardo Eiji Maeda, Janne Heiskanen, Eljas Kullervo Aalto, Petri Kauko Emil Pellikka
Summary: Climate change has harmful effects on fragile ecosystems and food security, but trees can play a crucial role in mitigating these impacts. This study examines the influence of canopy cover on microclimate in a modified landscape, showing that increasing canopy cover reduces temperatures and highlights the importance of preserving tree cover in warmer conditions.
Article
Computer Science, Information Systems
Temesgen Alemayehu Abera, Ilja Vuorinne, Martha Munyao, Petri K. E. Pellikka, Janne Heiskanen
Summary: Taita Taveta County, known for its biodiversity, has been mapped using satellite observations and machine learning algorithms. The land cover map produced has an overall accuracy of 81% and provides valuable information for land use planning, conservation management, and research.
Article
Forestry
Daniel Schraik, Aarne Hovi, Miina Rautiainen
Summary: Terrestrial laser scanning provides a unique opportunity to study forest canopy structure, but estimating leaf area density is biased by the physical dimensions of laser beams. Research found that conifer foliage had a lower average per-pulse cover fraction than broadleaved foliage, indicating an increased number of partial hits in conifer foliage.
Article
Multidisciplinary Sciences
Aarne Hovi, Petri R. Forsstrom, Giulia Ghielmetti, Michael E. Schaepman, Miina Rautiainen
Summary: This article presents a dataset of multiangular scattering properties of small trees in visible, near-infrared, and shortwave-infrared wavelengths, along with supporting auxiliary data. The data, collected from three common European tree species, are valuable for modeling the shortwave reflectance characteristics of small trees and potentially forests, and can benefit climate modeling and remote sensing data interpretation.
Article
Environmental Sciences
Ruonan Chen, Liangyun Liu, Xinjie Liu, Zhunqiao Liu, Lianhong Gu, Uwe Rascher
Summary: This study presents methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Daniel L. Goldberg, Madankui Tao, Gaige Hunter Kerr, Siqi Ma, Daniel Q. Tong, Arlene M. Fiore, Angela F. Dickens, Zachariah E. Adelman, Susan C. Anenberg
Summary: A novel method is applied in this study to directly use satellite data to evaluate the spatial patterns of urban NOx emissions inventories. The results show that the 108 spatial surrogates used by NEMO are generally appropriate, but there may be underestimation in areas with dense intermodal facilities and overestimation in wealthy communities.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Zhuoyue Hu, Xiaoyan Li, Liyuan Li, Xiaofeng Su, Lin Yang, Yong Zhang, Xingjian Hu, Chun Lin, Yujun Tang, Jian Hao, Xiaojin Sun, Fansheng Chen
Summary: This paper proposes a whisk-broom imaging method using a long-linear-array detector and high-precision scanning mirror to achieve high-resolution and wide-swath thermal infrared data. The method has been implemented in the SDGs satellite and has shown promising test results.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Dandan Wang, Leiqiu Hu, James A. Voogt, Yunhao Chen, Ji Zhou, Gaijing Chang, Jinling Quan, Wenfeng Zhan, Zhizhong Kang
Summary: This study evaluates different schemes for determining model coefficients to quantify and correct the anisotropic impact from remote sensing LST for urban applications. The schemes have consistent results and accurately estimate parameter values, facilitating the broadening of parametric models.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jamie Tolan, Hung - Yang, Benjamin Nosarzewski, Guillaume Couairon, Huy V. Vo, John Brandt, Justine Spore, Sayantan Majumdar, Daniel Haziza, Janaki Vamaraju, Theo Moutakanni, Piotr Bojanowski, Tracy Johns, Brian White, Tobias Tiecke, Camille Couprie
Summary: Vegetation structure mapping is crucial for understanding the global carbon cycle and monitoring nature-based approaches to climate adaptation and mitigation. This study presents the first high-resolution canopy height maps for California and Sao Paulo, achieved through the use of very high resolution satellite imagery and aerial lidar data. The maps provide valuable tools for forest structure assessment and land use monitoring.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Regina Eckert, Steffen Mauceri, David R. Thompson, Jay E. Fahlen, Philip G. Brodrick
Summary: In this paper, a mathematical framework is proposed to improve the retrieval of surface reflectance and atmospheric parameters by leveraging the expected spatial smoothness of the atmosphere. Experimental results show that this framework can reduce the surface reflectance retrieval error and surface-related biases.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Chongya Jiang, Kaiyu Guan, Yizhi Huang, Maxwell Jong
Summary: This study presents the Field Rover method, which uses vehicle-mounted cameras to collect ground truth data on crop harvesting status. The machine learning approach and remote sensing technology are employed to upscale the results to a regional scale. The accuracy of the remote sensing method in predicting crop harvesting dates is validated through comparison with satellite data.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Oksana V. Lunina, Anton A. Gladkov, Alexey V. Bochalgin
Summary: In this study, an unmanned aerial vehicle (UAV) was used to detect and map surface discontinuities with displacements of a few centimeters, indicating the presence of initial geological deformations. The study found that sediments of alluvial fans are susceptible to various tectonic and exogenous deformational processes, and the interpretation of ultra-high resolution UAV images can help recognize low-amplitude brittle deformations at an early stage. UAV surveys are critical for discerning neotectonic activity and its related hazards over short observation periods.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Feng Zhao, Weiwei Ma, Jun Zhao, Yiqing Guo, Mateen Tariq, Juan Li
Summary: This study presents a data-driven approach to reconstruct the terrestrial SIF spectrum using measurements from the TROPOMI instrument on Sentinel-5 precursor mission. The reconstructed SIF spectrum shows improved spatiotemporal distributions and demonstrates consistency with other datasets, indicating its potential for better understanding of the ecosystem function.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Stephen Stehman, John E. Wagner
Summary: This article investigates optimal sample allocation in stratified random sampling for estimation of accuracy and proportion of area in applications where the target class is rare. The study finds that precision of estimated accuracy has a stronger impact on sample allocation than estimation of proportion of area, and the trade-offs among these estimates become more pronounced as the target class becomes rarer. The results provide quantitative evidence to guide sample allocation decisions in specific applications.
REMOTE SENSING OF ENVIRONMENT
(2024)
Article
Environmental Sciences
Jingyao Zheng, Tianjie Zhao, Haishen Lu, Defu Zou, Nemesio Rodriguez-Fernandez, Arnaud Mialon, Philippe Richaume, Jianshe Xiao, Jun Ma, Lei Fan, Peilin Song, Yonghua Zhu, Rui Li, Panpan Yao, Qingqing Yang, Shaojie Du, Zhen Wang, Zhiqing Peng, Yuyang Xiong, Zanpin Xing, Lin Zhao, Yann Kerr, Jiancheng Shi
Summary: Soil moisture and freeze/thaw (F/T) play a crucial role in water and heat exchanges at the land-atmosphere interface. This study reports the establishment of a wireless sensor network for soil moisture and temperature over the permafrost region of Tibetan Plateau. Satellite-based surface soil moisture (SSM) and F/T products were evaluated using ground-based measurements. The results show the reliability of L-band passive microwave SSM and F/T products, while existing F/T products display earlier freezing and later thawing, leading to unsatisfactory accuracy.
REMOTE SENSING OF ENVIRONMENT
(2024)
