Contrasting Dynamics of Littoral and Riparian Reed Stands within a Wetland Complex of Lake Cerknica DOI Creative Commons

Nik Ojdanič,

Igor Zelnik,

Matej Holcar

et al.

Plants, Journal Year: 2023, Volume and Issue: 12(5), P. 1006 - 1006

Published: Feb. 22, 2023

This contribution discusses the use of field measurements and remotely sensed data in an exploration effects environmental parameters on riparian littoral stands common reed (Phragmites australis) intermittent wetland Slovenia. For this purpose, we created a normalized difference vegetation index (NDVI) time series extending from 2017 to 2021. Data were collected fitted unimodal growth model, which determined three different stages relating reed's growth. The consisted above-ground biomass harvested at end season. Maximal NDVI values peak growing season exhibited no useful relationship with Intense long-lasting floods, especially during period intense culm growth, hindered production reeds, while dry periods temperatures helpful before began. Summer droughts little effect. Water level fluctuations exerted greater effect reeds site due more pronounced extremes. In contrast, constant moderate conditions benefited productivity reed. These results can prove for decision making regarding management lake Cerknica.

Language: Английский

Toward a better understanding of coastal salt marsh mapping: A case from China using dual-temporal images DOI
Chuanpeng Zhao,

Mingming Jia,

Zongming Wang

et al.

Remote Sensing of Environment, Journal Year: 2023, Volume and Issue: 295, P. 113664 - 113664

Published: June 15, 2023

Language: Английский

Citations

45
Cross-scale mapping of above-ground biomass and shrub dominance by integrating UAV and satellite data in temperate grassland DOI
Ang Chen, Cong Xu, Min Zhang

et al.

Remote Sensing of Environment, Journal Year: 2024, Volume and Issue: 304, P. 114024 - 114024

Published: Feb. 7, 2024

Language: Английский

Citations

22
Development of forest aboveground biomass estimation, its problems and future solutions: A review DOI Creative Commons
Taiyong Ma,

Chao Zhang,

Liping Ji

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 159, P. 111653 - 111653

Published: Feb. 1, 2024

Forest aboveground biomass (AGB) is crucial as it serves a fundamental indicator of the productivity, biodiversity, and carbon storage forest ecosystems. This paper presents targeted literature review advancements in AGB estimation methods. We conducted an extensive published using Web Science, ResearchGate, Semantic Scholar, Google Scholar. Our findings highlight importance accurate studies terrestrial cycle, ecosystem management, climate change. Moreover, contributes valuable ecological knowledge supports effective natural resource management. Unfortunately, during data collection process for estimation, we have identified two critical yet often overlooked issues: (1) reliability manual survey accuracy, (2) impact overlap between ground plots remote sensing pixels on estimation. Drawing existing technologies analysis, propose potentially solution to address these challenges. In conclusion, mapping parameters, such AGB, will remain priority forestry research foreseeable future. To ensure practical applicability findings, our future efforts focus understanding accuracy determining optimal pixels.

Language: Английский

Citations

17
Aboveground biomass retrieval of wetland vegetation at the species level using UAV hyperspectral imagery and machine learning DOI Creative Commons

Wei Zhuo,

Wu Nan, Runhe Shi

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112365 - 112365

Published: July 13, 2024

Language: Английский

Citations

10
The impact of environmental variables on reed stands of the intermittent Lake Cerknica, Slovenia: 40 years of change DOI Creative Commons

Nik Ojdanič,

Alenka Gaberščik, Igor Zelnik

et al.

Ecological Indicators, Journal Year: 2025, Volume and Issue: 170, P. 113101 - 113101

Published: Jan. 1, 2025

Language: Английский

Citations

1
Towards carbon neutrality: Enhancing CO2 sequestration by plants to reduce carbon footprint DOI
Dawid Skrzypczak,

Katarzyna Gorazda,

Katarzyna Mikula

et al.

The Science of The Total Environment, Journal Year: 2025, Volume and Issue: 966, P. 178763 - 178763

Published: Feb. 1, 2025

Language: Английский

Citations

1
Monitoring of chlorophyll-a and suspended sediment concentrations in optically complex inland rivers using multisource remote sensing measurements DOI Creative Commons
Yi Xiao, Jiahao Chen,

Yue Xu

et al.

Ecological Indicators, Journal Year: 2023, Volume and Issue: 155, P. 111041 - 111041

Published: Oct. 9, 2023

In recent decades, phytoplankton proliferation and sediment input to rivers (especially urban rivers) have become more dramatic under the compound pressure of climate change human activities. Given generally narrow width current high spatial resolution satellites, which are limited by band settings, bandwidth, signal-to-noise ratio, UAVs with their exceptional spatiotemporal can be used as a useful tool for river environmental monitoring inversion uncertainty assessment. this study, UAV-based hyperspectral (X20P) multispectral (P4M) images, along Sentinel-2 MultiSpectral Instrument (MSI), Landsat-8 Operational Land Imager (OLI) Landsat-9 OLI2 data, were assess in retrieving chlorophyll-a (Chla) suspended (SS) concentrations rivers. Chla SS models based on UAV satellite data constructed using stepwise multiple regression typical retrieval algorithms, respectively, performance was focus our research. The results demonstrated that concentration inversion, each sensor performed follows: X20P > P4M Landsat9 MSI Landsat8 OLI, OLI. addition, retrievals analyzed assistance model. Results showed bandwidths finely tuned settings essential inversion. algorithm, NDCI, is only effective certain bands (band 1 from 684 724 nm 2 660 680 nm). It also noted lack some key (e.g., red-edge 700–710 nm), severely limiting practical application relation Chla. However, specific variances different relatively small impact example, correlation between R/B (a algorithm) ranged 0.68 0.77. monitoring, other hand, necessitates higher than monitoring. accuracy decreased markedly when images resampled 10 m 30 resolution. it not crucial original (RMSE<30cm = 6.28 mg/L) (RMSE10m 5.85 (RMSE30m 4.08 while increased. Our highlighted various options future SS, exploiting synergy satellites achieve precise observations at greater temporal scales, will benefit aquatic environment management protection.

Language: Английский

Citations

19
UAV and Satellite Synergies for Mapping Grassland Aboveground Biomass in Hulunbuir Meadow Steppe DOI Creative Commons
Zhu Xiao-hua, Xinyu Chen, Lingling Ma

et al.

Plants, Journal Year: 2024, Volume and Issue: 13(7), P. 1006 - 1006

Published: March 31, 2024

Aboveground biomass (AGB) is an important indicator of the grassland ecosystem. It can be used to evaluate productivity and carbon stock. Satellite remote sensing technology useful for monitoring dynamic changes in AGB across a wide range grasslands. However, due scale mismatch between satellite observations ground surveys, significant uncertainties biases exist mapping from data. This also common problem low- medium-resolution modeling that has not been effectively solved. The rapid development uncrewed aerial vehicle (UAV) offers way solve this problem. In study, we developed method with UAV synergies estimating filled gap observation surveys successfully mapped Hulunbuir meadow steppe northeast Inner Mongolia, China. First, based on hyperspectral data survey data, UAV-based was estimated using combination typical vegetation indices (VIs) leaf area index (LAI), structural parameter. Then, aggregated as satellite-scale sample set model satellite-based estimation. At same time, spatial information incorporated into LAI inversion process minimize bias Finally, entire experimental analyzed. results show following: (1) random forest (RF) had best performance compared simple regression (SR), partial least squares (PLSR) back-propagation neural network (BPNN) estimation, R2 0.80 RMSE 76.03 g/m2. (2) Grassland estimation through introducing achieved higher accuracy. For improved by average 10% reduced 9%. increased 0.70 0.75 decreased 78.24 g/m2 72.36 (3) Based map, accuracy significantly improved. 0.57 0.75, 99.38 suggests UAVs bridge field measurements providing sufficient training dataset

Language: Английский

Citations

8
A Novel Vegetation Index Approach Using Sentinel-2 Data and Random Forest Algorithm for Estimating Forest Stock Volume in the Helan Mountains, Ningxia, China DOI Creative Commons
Taiyong Ma,

Yang Hu,

Jie Wang

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(7), P. 1853 - 1853

Published: March 30, 2023

Forest stock volume (FSV) is a major indicator of forest ecosystem health and it also plays an important part in understanding the worldwide carbon cycle. A precise comprehension distribution patterns variations FSV crucial assessment sequestration potential optimization management programs sink. In this study, novel vegetation index based on Sentinel-2 data for modeling with random (RF) algorithm Helan Mountains, China has been developed. Among all other variables correlation coefficient r = 0.778, (NDVIRE) developed red-edge bands was most significant. Meanwhile, model that combined indices (bands + VIs-based model, BVBM) performed best training phase (R2 0.93, RMSE 10.82 m3ha−1) testing 0.60, 27.05 m3ha−1). Using Mountains first mapped accuracy 80.46% obtained. The RF thus effective method to assess FSV. addition, can provide new estimate areas, especially sequestration.

Language: Английский

Citations

16
Analysis of the Spatiotemporal Characteristics and Influencing Factors of the NDVI Based on the GEE Cloud Platform and Landsat Images DOI Creative Commons
Zhisong Liu,

Yankun Chen,

Chao Chen

et al.

Remote Sensing, Journal Year: 2023, Volume and Issue: 15(20), P. 4980 - 4980

Published: Oct. 16, 2023

Vegetation is an important type of land cover. Long-term, large-scale, and high-precision vegetation monitoring great significance for ecological environment investigation regional sustainable development in protected areas. This paper develops a long-term remote sensing method by calculating the normalized difference index (NDVI) based on Google Earth Engine (GEE) cloud platform Landsat satellite images. First, images GEE, spatiotemporal distribution map NDVI accurately drawn. Subsequently, classified, time trend analysis conducted mean graphs, transition matrices, etc. Then, combined with Moran’s I, high/low clusters, other methods, spatial pattern characteristics are analyzed. Finally, climate factors, terrain anthropologic factors considered comprehensively. An affecting evolution performed. Taking Zhoushan Island, China, as example, experiment conducted, results reveal that (1) average exhibits decreasing from 1985 to 2022, 0.53 0.46 2022. (2) Regarding transitions, high areas (0.6–1) exhibit most substantial shift toward moderately values (0.4–0.6), covering area 83.10 km2. (3) There obvious agglomeration phenomenon Island. The high-high clusters significant hot spots predominantly concentrated island’s interior regions, while low-low cold mainly situated along coastal (4) DEM, slope, temperature have greater influence among single 2015. differences between DEM precipitation, slope aspect population, gross domestic product (GDP). temperature, population three sets strong interaction. study provides data support scientific management resources Island island region.

Language: Английский

Citations

16