Results 231 to 240 of about 17,569,314 (273)

A multi-decadal assessment dataset of soil organic matter in the Sanjiang Plain black soil region (1984-2023). [PDF]

Sci Data
Zhang Y, Liu H, Luo C.
europepmc   +1 more source

Research on the spatiotemporal evolution characteristics of NDVI in Shendong mining area based on GEE long-time series remote sensing images. [PDF]

Sci Rep
Wu Z, Wang F, Fang J.
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Assessing the spatiotemporal shifting of the Arpa river using remote sensing, GIS, and ARIMA for river morphology prediction. [PDF]

Sci Rep
Soni P, Patel RK, Patel K, Singh P, Thakur SS, Kaushik S.   +5 more
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Mangrove Phenology From Scale, Data and Species Perspectives. [PDF]

Ecol Evol
Wang Y, Liu Q, Zhu Y, Wen W, Yang S, Gong M.   +5 more
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Spatiotemporal evolution and driving mechanisms of ecological quality in shanxi province based on XGBoost-SHAP. [PDF]

Sci Rep
Yuan Y, Zhang Z, Hu S, Zhang K, Yang S.
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Activity-Weighted Assessment and Environmental Drivers of Compound Ozone-Heat Exposure Risk in Urban Outdoor Exercise Spaces. [PDF]

Toxics
Su R, Yao Z, Zhang S, Zhang K, Du P, Yao L.   +5 more
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Random Forest Detection of charcoal driven vegetation loss in Ghana's Afram Plains. [PDF]

Sci Rep
Arko T, Mensah A, Obani P, Denton F, Adomako J.   +4 more
europepmc   +1 more source

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Monitoring cropland abandonment with Landsat time series

Remote Sensing of Environment, 2020
Cropland abandonment is a widespread land-use change, but it is difficult to monitor with remote sensing because it is often spatially dispersed, easily confused with spectrally similar land-use classes such as grasslands and fallow fields, and because post-agricultural succession can take different forms in different biomes. Due to these difficulties,
Yin, He, Brandão Jr, Amintas, Buchner, Johanna, Helmers, David, Iuliano, Benjamin G., Kimambo, Niwaeli, Lewińska, Katarzyna E., Razenkova, Elena, Rizayeva, Afag, Rogova, Natalia, Spawn, Seth A., Xie, Yanhua, Radeloff, Volker C.   +12 more
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Characterization of land disturbances based on Landsat time series

2022
We developed a new Object-based Disturbance Agent Classification Approach (ODACA) to characterize land disturbance agents based on Landsat time series. Seven major disturbance agents were characterized, including harvest, mechanical, stress, debris, hydrology, and fire. We first created the land disturbance map by using a modified COntinuous monitoring
Shi Qiu, Zhe Zhu, Xiucheng Yang
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A new MODIS-Landsat fusion method to reconstruct Landsat NDVI time-series data

2021
<p>The Normalized Difference Vegetation Index (NDVI) data provided by the satellite Landsat have rich historical archive data with a spatial resolution of 30 m. However, the Landsat NDVI time-series data are quite discontinuous due to its 16-day revisit cycle, cloud contamination and some other factors.
Xiaofang Ling, Ruyin Cao
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