Geospatial Insights for Assessing Agricultural Drought Hazards of Rabi Season in Assam DOI

V. Senpakapriya,

Jonali Goswami,

Debashree Battacharjee

et al.

Journal of the Indian Society of Remote Sensing, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 11, 2025

Language: Английский

Assessing terrestrial water storage variations in Afghanistan using GRACE and FLDAS-Central Asia data DOI Creative Commons
Son K., Fazlullah Akhtar, Benjamin D. Goffin

et al.

Journal of Hydrology Regional Studies, Journal Year: 2024, Volume and Issue: 55, P. 101906 - 101906

Published: July 30, 2024

Afghanistan, Central Asia. In this study, we evaluated the terrestrial water storage dynamics in Afghanistan and its five major river basins using anomalies (TWSA) from three Gravity Recovery Climate Experiment (GRACE) mascons observations JPL, CSR, GSFC processing centers, Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System – Asia (FLDAS-CA) simulation. Since 2008, due to intense prolonged drought conditions groundwater overexploitation, TWS has been decreasing at an alarming rate. The average slopes of TWSA trend for GRACE period (2003–2016) products range between − 3.6 4.8 mm/year. decrease is further exacerbated during GRACE-FO (2019–2022), ranging 20.4 30 Because heavily relied on country but human-induced change (i.e., extraction) not simulated FLDAS-CA, a significant difference could be observed FLDAS-CA results, especially following after each severe event (e.g., 2018) when substantial extraction occurred. assimilation into framework will undoubtedly have positive impact decision-makers local stakeholders preparing mitigating impacts overexploitation

Language: Английский

Citations

24

Remote Sensing Indices for Spatial Monitoring of Agricultural Drought in South Asian Countries DOI Creative Commons
Muhammad Shahzaman,

Weijun Zhu,

Muhammad Bilal

et al.

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(11), P. 2059 - 2059

Published: May 23, 2021

Drought is an intricate atmospheric phenomenon with the greatest impacts on food security and agriculture in South Asia. Timely appropriate forecasting of drought vital reducing its negative impacts. This study intended to explore performance evaporative stress index (ESI), vegetation health (VHI), enhanced (EVI), standardized anomaly (SAI) based satellite remote sensing data from 2002–2019 for agricultural assessment Afghanistan, Pakistan, India, Bangladesh. The spatial maps were generated against each index, which indicated a severe during year 2002, compared other years. results showed that southeast region north, northwest, southwest regions India Afghanistan significantly affected by drought. However, Bangladesh faced substantial northeast northwest (2002). longest period seven months was observed followed Pakistan six months, while, only three perceived correlation between indices climate variables such as soil moisture has remained significant drought-initiating variable. Furthermore, this confirmed (ESI) good indicator, being quick greater sensitivity, thus advantageous VHI, EVI, SAI indices.

Language: Английский

Citations

88

Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries DOI Creative Commons
Muhammad Shahzaman,

Weijun Zhu,

Irfan Ullah

et al.

Remote Sensing, Journal Year: 2021, Volume and Issue: 13(16), P. 3294 - 3294

Published: Aug. 20, 2021

The substantial reliance of South Asia (SA) to rain-based agriculture makes the region susceptible food scarcity due droughts. Previously, most research on SA has emphasized meteorological aspects with little consideration agrarian drought impressions. insufficient amount in situ precipitation data across also hindered thorough investigation sector. In recent times, models, satellite remote sensing, and reanalysis products have increased data. Hence, soil moisture, precipitation, terrestrial water storage (TWS), vegetation condition index (VCI) been employed illustrate droughts from 1982 2019 using a standardized index/anomaly approach. Besides, relationships these towards crop production are evaluated annual national barley, maize, rice, wheat by computing yield anomaly (YAI). Our findings indicate that MERRA-2, CPC, FLDAS (soil moisture), GPCC, CHIRPS (precipitation) alike constant over entire four regions (northwest, southwest, northeast, southeast). On other hand, GLDAS ERA5 remain poor when compared moisture identified conditions one (northwest) three (northeast). Likewise, TWS such as MERRA-2 GRACE (2002–2014) followed patterns presented divergent inconsistent patterns. Furthermore, remained less responsive (northeast) (southeast) only. Based data, FLDAS, performed fairly well indicated stronger more significant associations (0.80 0.96) others. Thus, current outcomes imperative for gauging deficient region, they provide substitutes agricultural monitoring.

Language: Английский

Citations

87

Decadal Urban Land Use/Land Cover Changes and Its Impact on Surface Runoff Potential for the Dhaka City and Surroundings Using Remote Sensing DOI Creative Commons
M Moniruzzaman, Praveen K. Thakur, Pramod Kumar

et al.

Remote Sensing, Journal Year: 2020, Volume and Issue: 13(1), P. 83 - 83

Published: Dec. 29, 2020

Rapid urban growth processes give rise to impervious surfaces and are regarded as the primary cause of flooding or waterlogging in areas. The high rate urbanization has caused many parts Dhaka city. Therefore, study is undertaken quantify changes land use/land cover (LULC) runoff extent based on Natural Resources Conservation Service (NRCS) Curve Number (CN) during 1978–2018. five-decadal LULC been analyzed using three-generation Landsat time-series data considering six different classes, namely agriculture, built-up, wetland, open land, green spaces, water bodies for years 1978, 1988, 1998, 2007, 2018. Significant area from 1978–2018 observed 13.1%, 4.8%, 7.8% reduction agricultural bodies, respectively, a 22.1% increase built-up estimated. Within city, 14.6%, 16.0%, 12.3% radical 41.9% reckoned. decadal assessment carried out NRCS-CN method, an extreme rainfall event 341 mm/day (13 September 2004). catchment under very category 159.5 km2 (1978) 318.3 (2018), whereas, setting dynamic increased 74.24 (24.44%) 174.23 (57.36%) 1978 2018, and, mostly, potential areas correspond dense surfaces.

Language: Английский

Citations

83

GCI30: a global dataset of 30 m cropping intensity using multisource remote sensing imagery DOI Creative Commons
Miao Zhang,

Bingfang Wu,

Hongwei Zeng

et al.

Earth system science data, Journal Year: 2021, Volume and Issue: 13(10), P. 4799 - 4817

Published: Oct. 21, 2021

Abstract. The global distribution of cropping intensity (CI) is essential to our understanding agricultural land use management on Earth. Optical remote sensing has revolutionized ability map CI over large areas in a repeated and cost-efficient manner. Previous studies have mainly focused investigating the spatiotemporal patterns ranging from regions entire globe with coarse-resolution data, which are inadequate for characterizing farming practices within heterogeneous landscapes. To fill this knowledge gap, study, we utilized multiple satellite data develop global, spatially continuous dataset at 30 m resolution (GCI30). Accuracy assessments indicated that GCI30 exhibited high agreement visually interpreted validation samples situ observations PhenoCam network. We carried out both statistical spatial comparisons six existing estimates. Based GCI30, estimated average annual during 2016–2018 was 1.05, close mean (1.09) median (1.07) values estimates, although temporal coverage vary significantly among products. A comparison two satellite-based surface phenology products further suggested not only capable capturing overall pattern but also provided many details. single primary system Earth, accounting 81.57 % (12.28×106 km2) world's cropland extent. Multiple-cropping systems, other hand, were commonly observed South America Asia. found variations across countries agroecological zones, reflecting joint control natural anthropogenic drivers regulating practices. As first global-coverage, fine-resolution product, expected gap promoting sustainable agriculture by depicting worldwide diversity intensity. available Harvard Dataverse: https://doi.org/10.7910/DVN/86M4PO (Zhang et al., 2020).

Language: Английский

Citations

72

Mobile Internet Technology Adoption for Sustainable Agriculture: Evidence from Wheat Farmers DOI Creative Commons
Nawab Khan, Ram L. Ray, Hazem S. Kassem

et al.

Applied Sciences, Journal Year: 2022, Volume and Issue: 12(10), P. 4902 - 4902

Published: May 12, 2022

Mobile internet technology (MIT) is considered a significant advancement in information and communication (ICT), due to its crucial impact on the financial system social life. In addition, it an essential overcome digital divide between urban rural areas. terms of agricultural advancement, MIT can play key role data collection implementation smart technologies. The main objectives this study were (i) investigate adoption use sustainable agriculture development among selected wheat farmers Pakistan (ii) examine factors influencing adoption. This 628 from four districts Khyber Pakhtunkhwa Province (KPK), Pakistan, for sampling. used bivariate probit method sampling farmers. analysis farmer’s showed age, farm size, location, knowledge about Internet (IT) are strongly correlated with development. Results average, 65% have mobile devices supporting these technologies, 55% environments. Since extant research production sparse, helps advance adoption-based studies. These outcomes may draw attention decision-makers dealing IT infrastructure equipment who support adopting MIT.

Language: Английский

Citations

52

Comprehensive Assessment of Drought Susceptibility Using Predictive Modeling, Climate Change Projections, and Land Use Dynamics for Sustainable Management DOI Creative Commons
Jinping Liu, Mingzhe Li, Renzhi Li

et al.

Land, Journal Year: 2025, Volume and Issue: 14(2), P. 337 - 337

Published: Feb. 7, 2025

This study assessed the drought susceptibility in Golestan Province, Northeastern Iran, using land use change modeling and climate projections from CMIP6 framework, under three Shared Socioeconomic Pathways (SSP1-2.6, SSP2-4.5, SSP5-8.5) for 2030–2050. The development of current (2022) future maps was based on agrometeorological sample points 14 environmental factors—such as use, precipitation, mean temperature, soil moisture, remote sensing-driven vegetation indices—used inputs into a machine learning model, maximum entropy. model showed very robust predictive capacity, with AUCs training test data 0.929 0.910, thus certifying model’s reliability. analysis identified major hotspots Gomishan Aqqala, where 66.12% 36.12% their areas, respectively, exhibited “very high” susceptibility. Projections SSP scenarios, particularly SSP5-8.5, indicate that risk will be most severe Maraveh Tappeh, 72.09% area exhibits risk. results revealed Province is at crossroads. Rising temperatures, exceeding 35 °C summer, combined declining rainfall, intensify agricultural hydrological droughts. These aggravated risks are compounded transitions rangelands to bare land, mostly Aqqala Gomishan, besides urban expansion Bandar-e Torkman Bandar Gaz, all which face less groundwater recharge increased surface runoff. Golestan’s vulnerability has both local regional impacts, its affecting neighboring communities ecosystems. Trade, migration, ecological stresses linked water resources may emerge critical challenges, requiring collaboration mitigation. Targeted interventions prioritizing sustainable practices, cooperation, collaborative strategies essential address mitigate these cascading safeguard vulnerable communities.

Language: Английский

Citations

1

Spatio-temporal analysis of precipitation pattern and trend using standardized precipitation index and Mann–Kendall test in coastal Andhra Pradesh DOI
Mirza Razi Imam Baig,

Shahfahad,

Mohd Waseem Naikoo

et al.

Modeling Earth Systems and Environment, Journal Year: 2021, Volume and Issue: 8(2), P. 2733 - 2752

Published: Aug. 22, 2021

Language: Английский

Citations

44

End-to-End Detail-Enhanced Dehazing Network for Remote Sensing Images DOI Creative Commons
Weida Dong, Chunyan Wang,

Hao Sun

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(2), P. 225 - 225

Published: Jan. 6, 2024

Space probes are always obstructed by floating objects in the atmosphere (clouds, haze, rain, etc.) during imaging, resulting loss of a significant amount detailed information remote sensing images and severely reducing quality images. To address problem images, we propose an end-to-end detail enhancement network to directly remove haze restore image, improve image. In order enhance designed multi-scale unit stepped attention unit, respectively. The former extracts from integrates global local information, constrains image details. latter uses mechanism adaptively process uneven distribution three dimensions: deep, middle shallow. It focuses on effective such as high frequency further addition, embed parallel normalization module dehazing performance robustness network. Experimental results SateHaze1k HRSD datasets demonstrate that our method effectively handles obscured various levels restores outperforms current state-of-the-art removal methods.

Language: Английский

Citations

7

Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis DOI Creative Commons
Jie Lu, Tianling Qin, Denghua Yan

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(4), P. 630 - 630

Published: Feb. 8, 2024

The vegetation and ecosystem in the source region of Yangtze River Yellow (SRYY) are fragile. Affected by climate change, extreme droughts frequent permafrost degradation is serious this area. It very important to quantify drought–vegetation interaction area under influence climate–permafrost coupling. In study, based on saturated vapor pressure deficit (VPD) soil moisture (SM) that characterize atmospheric drought, as well Normalized Differential Vegetation Index (NDVI) solar-induced fluorescence (SIF) greenness function, evolution regional productivity drought were systematically identified. On basis, technical advantages causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) applied distinguish response VPD SM. Furthermore, study delves into mechanisms NDVI SIF considering different types areas. findings indicated low SM high limiting factors for growth. positive negative effects accounted 47.88% 52.12% total area, respectively. Shrubs most sensitive SM, speed grassland was faster than forest land. impact SRYY stronger VPD, effect frozen more obvious. average 0.21 0.41, respectively, which twice those whole dominated changes 62.87% (76.60%) research results can provide scientific basis theoretical support assessment adaptation permafrost, vegetation, change reference ecological protection regions.

Language: Английский

Citations

7