4.3 Article

Detecting semi-arid forest decline using time series of Landsat data

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Multidisciplinary Sciences

Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh

Ashim C. Das et al.

Summary: Drought in the north-western region of Bangladesh, a dry and arid area, has not received sufficient attention and mitigation efforts. This study assessed the drought condition using earth observation techniques and found that deforestation and expansion of settlement and agricultural land have led to the reduction of forests and water bodies. The decrease in vegetation indices and increase in land surface temperature indicate a drought-induced shock to the vegetation. The findings have practical implications for agriculture, forests, water development, and economic zone planning.

HELIYON (2023)

Article Environmental Sciences

A 30 m global map of elevation with forests and buildings removed

Laurence Hawker et al.

Summary: This article introduces a method that uses machine learning to remove buildings and forests from the Copernicus Digital Elevation Model, generating a more accurate global map of elevation. By training the algorithm with unique reference elevation data from 12 countries, the method significantly reduces vertical errors in built-up areas and forests. The resulting elevation map is more accurate than existing global elevation maps.

ENVIRONMENTAL RESEARCH LETTERS (2022)

Article Biodiversity Conservation

Sequential droughts: A silent trigger of boreal forest mortality

Martina Sanchez-Pinillos et al.

Summary: The study found that frequent low-intensity droughts have a stronger impact on forest mortality than the intensity of a single drought. These dry conditions exacerbate the effects of stand characteristics and environmental conditions on forest mortality, especially for forests dominated by shade-tolerant conifers.

GLOBAL CHANGE BIOLOGY (2022)

Review Environmental Sciences

Remote sensing for monitoring tropical dryland forests: a review of current research, knowledge gaps and future directions for Southern Africa

Ruusa M. David et al.

Summary: This study analyzes and synthesizes peer-reviewed research publications on remote sensing of dryland forests in Southern Africa from 1997 to 2020. It finds that remote sensing technologies are helpful in assessing and monitoring forest ecosystems in the region. However, challenges still remain. The study hopes to stimulate discussion and promote the use of new remote sensing tools and data for monitoring dryland forests.

ENVIRONMENTAL RESEARCH COMMUNICATIONS (2022)

Article Multidisciplinary Sciences

A Sentinel-2 derived dataset of forest disturbances occurred in Italy between 2017 and 2020

Saverio Francini et al.

Summary: This study introduces a spatially explicit dataset of forest disturbances in Italy from 2017 to 2020, using Sentinel-2 satellite data for assessing greenhouse gas balance and forest sustainability. The dataset can be utilized to estimate areas of different forest disturbances and minimize errors in assessment.

DATA IN BRIEF (2022)

Article Environmental Sciences

Disentangling Soil, Shade, and Tree Canopy Contributions to Mixed Satellite Vegetation Indices in a Sparse Dry Forest

Huanhuan Wang et al.

Summary: This study uses unmanned aerial vehicle (UAV) to obtain high-resolution multispectral images and estimates the fraction and reflectance of different surface components. The study also finds a mismatch between satellite data and tower-based data and develops a method to resolve the mismatch.

REMOTE SENSING (2022)

Article Environmental Sciences

Dynamic Monitoring of Environmental Quality in the Loess Plateau from 2000 to 2020 Using the Google Earth Engine Platform and the Remote Sensing Ecological Index

Jing Zhang et al.

Summary: This study used remote sensing technology and data analysis methods to investigate the spatio-temporal changes in environmental quality in the Loess Plateau from 2000 to 2020 and the factors affecting it. The results showed an overall improvement in environmental quality in the region, but with spatial variations. Greenness, heat, wetness, dryness, and land use types were identified as prominent factors. These findings provide important references for local environmental protection and regional planning.

REMOTE SENSING (2022)

Article Green & Sustainable Science & Technology

The Importance of Adding Short-Wave Infrared Bands for Forest Disturbance Monitoring in the Subtropical Region

Xi Li et al.

Summary: Forest disturbance, such as harvest and fire, can lead to significant carbon emissions from soil to the atmosphere. Monitoring forest disturbance at a high spatial resolution is crucial for soil carbon modeling. This study evaluates the impact of including short-wave infrared (SWIR) bands in forest disturbance monitoring and demonstrates the importance of these bands for accurate detection. The results highlight the need to consider satellite data with at least one SWIR band to improve soil carbon modeling.

SUSTAINABILITY (2022)

Article Remote Sensing

Mapping fractional woody cover in an extensive semi-arid woodland area at different spatial grains with Sentinel-2 and very high-resolution data

Elham Shafeian et al.

Summary: Woody canopy cover is crucial for understanding vegetation health, carbon accumulation, and land-atmosphere exchange processes. Remote sensing data combined with machine learning algorithms can provide accurate estimates of woody cover over large areas, as demonstrated in the Zagros Mountains region. The approach shows stable performance with 40 m spatial grain models, which can potentially be applied to other arid and semi-arid regions for improving global woody cover products.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2021)

Article Geosciences, Multidisciplinary

Topographic patterns of forest decline as detected from tree rings and NDVI

Zhou Wang et al.

Summary: The study shows that topographic factors, especially elevation, indirectly influence the vulnerability of sites to forest decline, which can be used to predict spatial decline risks.

CATENA (2021)

Article Environmental Sciences

Using spectral indices as early warning signals of forest dieback: The case of drought-prone Pinus pinaster forests

Daniel Moreno-Fernandez et al.

Summary: Combining fieldwork and remote sensing, this study explored the links between forest dieback and land surface phenological and trend variables. The results showed that forest dieback was mainly associated with the trend component of the spectral indices series, while phenological metrics were not related to forest dieback.

SCIENCE OF THE TOTAL ENVIRONMENT (2021)

Article Environmental Sciences

Disturbance detection in landsat time series is influenced by tree mortality agent and severity, not by prior disturbance

Kyle C. Rodman et al.

Summary: Landsat time series (LTS) and change detection algorithms are useful for monitoring global change impacts on Earth's ecosystems, but accuracy can be influenced by factors such as initial forest density and disturbance severity. LTS algorithms are robust in areas with multiple disturbance events, which is important for future mapping efforts utilizing Landsat data.

REMOTE SENSING OF ENVIRONMENT (2021)

Article Multidisciplinary Sciences

A unified vegetation index for quantifying the terrestrial biosphere

Gustau Camps-Valls et al.

Summary: This study generalized commonly used vegetation indices by exploiting higher-order relations between spectral channels, resulting in increased sensitivity to vegetation physiological and biophysical parameters. The nonlinear NDVI consistently improved accuracy in monitoring key parameters, suggesting potential for more precise measurements of terrestrial carbon dynamics.

SCIENCE ADVANCES (2021)

Article Environmental Sciences

Detecting Forest Degradation in the Three-North Forest Shelterbelt in China from Multi-Scale Satellite Images

Tao Yu et al.

Summary: This study developed a quick and applicable approach to monitor forest degradation in the Three-North Forest Shelterbelt in China, showing that multi-scale remote sensing data have great potential in detecting regional forest degradation.

REMOTE SENSING (2021)

Article Geography

ZONING OF AREAS WITH SUSCEPTIBILITY TO OAK DECLINE IN WESTERN IRAN

Mohadeseh Ghanbari Motlagh et al.

Summary: Zagros forests play a crucial role in soil and water conservation in western Iran, but oak forests in Ilam province have been significantly affected. By using fuzzy logic method, it was found that over 77% of oak forests in the province are highly susceptible to decline, highlighting the urgent need for protection plans. The fuzzy method proposed in this study can be a fast and efficient approach for preparing similar maps for other regions.

QUAESTIONES GEOGRAPHICAE (2021)

Article Forestry

Detection of high potential areas of persian oak forests decline in Zagros, Iran, using topsis method

Mohammad Javad Moradi et al.

Summary: Using GIS technique and multi-criteria evaluation methods, this study identified high-risk areas of Oak decline potential in two selected stands in Ilam Province, Iran. Factors such as rainfall, pests, and diseases were found to have the greatest impact on Oak forest decline.
Article Environmental Sciences

Continuous monitoring of land disturbance based on Landsat time series

Zhe Zhu et al.

REMOTE SENSING OF ENVIRONMENT (2020)

Article Multidisciplinary Sciences

Excess forest mortality is consistently linked to drought across Europe

Cornelius Senf et al.

NATURE COMMUNICATIONS (2020)

Article Environmental Sciences

Comparison of Landsat-8 and Sentinel-2 Data for Estimation of Leaf Area Index in Temperate Forests

Lorenz Hans Meyer et al.

REMOTE SENSING (2019)

Article Plant Sciences

Early-Warning Signals of Individual Tree Mortality Based on Annual Radial Growth

Maxime Cailleret et al.

FRONTIERS IN PLANT SCIENCE (2019)

Article Environmental Sciences

Linking Remote Sensing and Dendrochronology to Quantify Climate-Induced Shifts in High-Elevation Forests Over Space and Time

A. Correa-Diaz et al.

JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES (2019)

Article Engineering, Multidisciplinary

THE USE OF VARI, GLI, AND VIGREEN FORMULAS IN DETECTING VEGETATION IN AERIAL IMAGES

Lim Soon Eng et al.

INTERNATIONAL JOURNAL OF TECHNOLOGY (2019)

Article Remote Sensing

Estimating tree species diversity in the savannah using NDVI and woody canopy cover

Sabelo Madonsela et al.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION (2018)

Article Geography, Physical

Mapping fractional woody cover in semi-arid savannahs using multi-seasonal composites from Landsat data

Thomas P. Higginbottom et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2018)

Article Environmental Sciences

Optimisation of Savannah Land Cover Characterisation with Optical and SAR Data

Elias Symeonakis et al.

REMOTE SENSING (2018)

Review Forestry

Forest Degradation: When Is a Forest Degraded?

Angelica Vasquez-Grandon et al.

FORESTS (2018)

Review Geography, Physical

Random forest in remote sensing: A review of applications and future directions

Mariana Belgiu et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2016)

Article Geography, Physical

Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia

Loic Paul Dutrieux et al.

ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING (2015)

Review Plant Sciences

Tree mortality from drought, insects, and their interactions in a changing climate

William R. L. Anderegg et al.

NEW PHYTOLOGIST (2015)

Article Environmental Sciences

Detecting forest disturbance in the Pacific Northwest from MODIS time series using temporal segmentation

Damien Sulla-Menashe et al.

REMOTE SENSING OF ENVIRONMENT (2014)

Article Environmental Sciences

Continuous change detection and classification of land cover using all available Landsat data

Zhe Zhu et al.

REMOTE SENSING OF ENVIRONMENT (2014)

Article Plant Sciences

Deforestation and precipitation patterns in the arid Chaco forests of central Argentina

L. E. Hoyos et al.

APPLIED VEGETATION SCIENCE (2013)

Article Environmental Sciences

Phenological change detection while accounting for abrupt and gradual trends in satellite image time series

Jan Verbesselt et al.

REMOTE SENSING OF ENVIRONMENT (2010)

Article Geosciences, Multidisciplinary

Evaluation of MODIS NDVI and NDWI for vegetation drought monitoring using Oklahoma Mesonet soil moisture data

Yingxin Gu et al.

GEOPHYSICAL RESEARCH LETTERS (2008)

Article Geosciences, Multidisciplinary

Remote estimation of canopy chlorophyll content in crops -: art. no. L08403

AA Gitelson et al.

GEOPHYSICAL RESEARCH LETTERS (2005)

Article Environmental Sciences

Novel algorithms for remote estimation of vegetation fraction

AA Gitelson et al.

REMOTE SENSING OF ENVIRONMENT (2002)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)