Cutting the Greenness Index into 12 Monthly Slices: How Intra-Annual NDVI Dynamics Help Decipher Drought Responses in Mixed Forest Tree Species DOI Creative Commons
Andrea Cecilia Acosta-Hernández, Marin Pompa-García, José Alexis Martínez-Rivas

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 389 - 389

Published: Jan. 18, 2024

We studied the correspondence between historical series of tree-ring width (TRW) and normalized difference vegetation index (NDVI, i.e., greenness index) values acquired monthly over an entire year by unmanned aerial vehicles. Dendrochronological techniques revealed differentiated responses species seasonality. Pinus engelmannii Carrière Juniperus deppeana Steudel were affected warm temperatures (TMAX) during winter prior to growth benefited from precipitation (PP) seasons spring period. The standardized precipitation–evapotranspiration (SPEI) confirmed high sensitivity P. drought (r = 0.7 SPEI). Quercus grisea Liebm. presented a positive association with PP at beginning end its season. Monthly NDVI data individual tree level in three (NDVI ~0.37–0.48) statistically temporal differences. Q. showed drastic decrease dry season 0.1) that had no impact on same period, according climate-TRW relationship. conclude relationship is plausible crown radial growth, although more extended windows should be explored. Differences susceptibility found among would presumably have implications for composition these forests under scenarios.

Language: Английский

Impacts of change in multiple cropping index of rice on hydrological components and grain production in the Zishui River Basin, Southern China DOI Creative Commons

Chengcheng Yuan,

Xinlin Li, Yufeng Wu

et al.

Agricultural Water Management, Journal Year: 2025, Volume and Issue: 316, P. 109572 - 109572

Published: May 23, 2025

Language: Английский

Citations

0
Remote sensing vegetation Indices-Driven models for sugarcane evapotranspiration estimation in the semiarid Ethiopian Rift Valley DOI
Gezahegn Weldu Woldemariam, Berhan Gessesse Awoke, Raian Vargas Maretto

et al.

ISPRS Journal of Photogrammetry and Remote Sensing, Journal Year: 2024, Volume and Issue: 215, P. 136 - 156

Published: July 8, 2024

Language: Английский

Citations

3
Near surface camera informed agricultural land monitoring for climate smart agriculture DOI Creative Commons
Le Yu, Zhenrong Du,

Xiyu Li

et al.

Climate smart agriculture., Journal Year: 2024, Volume and Issue: 1(1), P. 100008 - 100008

Published: July 8, 2024

Continuous and accurate monitoring of agricultural landscapes is crucial for understanding crop phenology responding to climatic anthropogenic changes. However, the widely used optical satellite remote sensing limited by revisit cycles weather conditions, leading gaps in monitoring. To address these limitations, we designed deployed a Near Surface Camera (NSCam) Network across China, explored its application land achieving climate-smart agriculture (CSA). By analyzing image data captured NSCam Network, can accurately assess long-term or abrupt According preliminary results, integrating with imagery greatly enhances temporal details accuracy monitoring, aiding managers making informed decisions. The impacts abnormal conditions human activities on land, which are not imagery, be complemented incorporating our Network. successful implementation this method underscores potential broader CSA, promoting resilient sustainable practices.

Language: Английский

Citations

3
Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review DOI Creative Commons
Mateo Gašparović, Ivan Pilaš, Dorijan Radočaj

et al.

Applied Sciences, Journal Year: 2024, Volume and Issue: 14(24), P. 12020 - 12020

Published: Dec. 22, 2024

Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, forest agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the advancement of LSP research, enabling global continuous monitoring vegetation cycles. This review provides brief overview key EO satellite missions, including advanced very-high resolution radiometer (AVHRR), moderate imaging spectroradiometer (MODIS), Landsat program, which an important capturing dynamics at various spatial temporal scales. Recent advancements machine learning techniques further enhanced prediction capabilities, offering promising approaches short-term cropland suitability assessment. Data cubes, organize multidimensional data, provide innovative framework enhancing analyses by integrating diverse data sources simplifying access processing. highlights potential satellite-based monitoring, models, cube infrastructure advancing research insights into current trends, challenges, future directions.

Language: Английский

Citations

3
Cutting the Greenness Index into 12 Monthly Slices: How Intra-Annual NDVI Dynamics Help Decipher Drought Responses in Mixed Forest Tree Species DOI Creative Commons
Andrea Cecilia Acosta-Hernández, Marin Pompa-García, José Alexis Martínez-Rivas

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 389 - 389

Published: Jan. 18, 2024

We studied the correspondence between historical series of tree-ring width (TRW) and normalized difference vegetation index (NDVI, i.e., greenness index) values acquired monthly over an entire year by unmanned aerial vehicles. Dendrochronological techniques revealed differentiated responses species seasonality. Pinus engelmannii Carrière Juniperus deppeana Steudel were affected warm temperatures (TMAX) during winter prior to growth benefited from precipitation (PP) seasons spring period. The standardized precipitation–evapotranspiration (SPEI) confirmed high sensitivity P. drought (r = 0.7 SPEI). Quercus grisea Liebm. presented a positive association with PP at beginning end its season. Monthly NDVI data individual tree level in three (NDVI ~0.37–0.48) statistically temporal differences. Q. showed drastic decrease dry season 0.1) that had no impact on same period, according climate-TRW relationship. conclude relationship is plausible crown radial growth, although more extended windows should be explored. Differences susceptibility found among would presumably have implications for composition these forests under scenarios.

Language: Английский

Citations

2