scholarly journals A Regional Drought Monitoring and Outlook System for South Asia

2021 ◽  
pp. 59-78
Author(s):  
Faisal Mueen Qamer ◽  
Mir A. Matin ◽  
Ben Zaitchik ◽  
Kiran Shakya ◽  
Yi Fan ◽  
...  
Keyword(s):  
South Asia ◽  
Land Surface ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Observation Data ◽  
Surface Models ◽  
Regional Drought ◽  
Drought Indicators ◽  
Earth Observation Data ◽  
Operational Service

AbstractThe Regional Drought Monitoring and Outlook System (RDMOS) is an operational service which produces reliable drought indicators for the south Asia region with a specific focus on Afghanistan, Bangladesh, Nepal, and Pakistan. The system incorporates climatic models with suitable Earth observation data and land surface models to produce drought indices—precipitation, temperature, soil moisture, evapotranspiration—and vegetation conditions at 10-day intervals for near realtime monitoring of droughts. The RDMOS also provides seasonal outlooks at four-month intervals to support drought management and preparedness processes.

scholarly journals Quantifying Tree Cover Loss in Urban Forests within Nairobi City Metropolitan Area from Earth Observation Data

2020 ◽  
Vol 3 (1) ◽  
pp. 78
Author(s):  
Francis Oloo ◽  
Godwin Murithi ◽  
Charlynne Jepkosgei
Keyword(s):  
Land Cover ◽  
Metropolitan Area ◽  
Land Surface ◽  
Urban Forest ◽  
Urban Forests ◽  
Earth Observation ◽  
Tree Cover ◽  
Observation Data ◽  
Vegetation Health ◽  
Earth Observation Data

Urban forests contribute significantly to the ecological integrity of urban areas and the quality of life of urban dwellers through air quality control, energy conservation, improving urban hydrology, and regulation of land surface temperatures (LST). However, urban forests are under threat due to human activities, natural calamities, and bioinvasion continually decimating forest cover. Few studies have used fine-scaled Earth observation data to understand the dynamics of tree cover loss in urban forests and the sustainability of such forests in the face of increasing urban population. The aim of this work was to quantify the spatial and temporal changes in urban forest characteristics and to assess the potential drivers of such changes. We used data on tree cover, normalized difference vegetation index (NDVI), and land cover change to quantify tree cover loss and changes in vegetation health in urban forests within the Nairobi metropolitan area in Kenya. We also used land cover data to visualize the potential link between tree cover loss and changes in land use characteristics. From approximately 6600 hectares (ha) of forest land, 720 ha have been lost between 2000 and 2019, representing about 11% loss in 20 years. In six of the urban forests, the trend of loss was positive, indicating a continuing disturbance of urban forests around Nairobi. Conversely, there was a negative trend in the annual mean NDVI values for each of the forests, indicating a potential deterioration of the vegetation health in the forests. A preliminary, visual inspection of high-resolution imagery in sample areas of tree cover loss showed that the main drivers of loss are the conversion of forest lands to residential areas and farmlands, implementation of big infrastructure projects that pass through the forests, and extraction of timber and other resources to support urban developments. The outcome of this study reveals the value of Earth observation data in monitoring urban forest resources.

scholarly journals On the utility of land surface models for agricultural drought monitoring

2012 ◽  
Vol 16 (9) ◽  
pp. 3451-3460 ◽  
Author(s):  
W. T. Crow ◽  
S. V. Kumar ◽  
J. D. Bolten
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Cross Correlation ◽  
Root Zone ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Global Evaluation ◽  
Land Surface Models ◽  
Surface Models

Abstract. The lagged rank cross-correlation between model-derived root-zone soil moisture estimates and remotely sensed vegetation indices (VI) is examined between January 2000 and December 2010 to quantify the skill of various soil moisture models for agricultural drought monitoring. Examined modeling strategies range from a simple antecedent precipitation index to the application of modern land surface models (LSMs) based on complex water and energy balance formulations. A quasi-global evaluation of lagged VI/soil moisture cross-correlation suggests, when globally averaged across the entire annual cycle, soil moisture estimates obtained from complex LSMs provide little added skill (< 5% in relative terms) in anticipating variations in vegetation condition relative to a simplified water accounting procedure based solely on observed precipitation. However, larger amounts of added skill (5–15% in relative terms) can be identified when focusing exclusively on the extra-tropical growing season and/or utilizing soil moisture values acquired by averaging across a multi-model ensemble.

scholarly journals Using Long-Term Earth Observation Data to Reveal the Factors Contributing to the Early 2020 Desert Locust Upsurge and the Resulting Vegetation Loss

2021 ◽  
Vol 13 (4) ◽  
pp. 680
Author(s):  
Lei Wang ◽  
Wen Zhuo ◽  
Zhifang Pei ◽  
Xingyuan Tong ◽  
Wei Han ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arabian Peninsula ◽  
Vegetation Coverage ◽  
Observation Data ◽  
Desert Locust ◽  
Meteorological Observations ◽  
Earth Observation Data ◽  
Vegetation Loss

Massive desert locust swarms have been threatening and devouring natural vegetation and agricultural crops in East Africa and West Asia since 2019, and the event developed into a rare and globally concerning locust upsurge in early 2020. The breeding, maturation, concentration and migration of locusts rely on appropriate environmental factors, mainly precipitation, temperature, vegetation coverage and land-surface soil moisture. Remotely sensed images and long-term meteorological observations across the desert locust invasion area were analyzed to explore the complex drivers, vegetation losses and growing trends during the locust upsurge in this study. The results revealed that (1) the intense precipitation events in the Arabian Peninsula during 2018 provided suitable soil moisture and lush vegetation, thus promoting locust breeding, multiplication and gregarization; (2) the regions affected by the heavy rainfall in 2019 shifted from the Arabian Peninsula to West Asia and Northeast Africa, thus driving the vast locust swarms migrating into those regions and causing enormous vegetation loss; (3) the soil moisture and NDVI anomalies corresponded well with the locust swarm movements; and (4) there was a low chance the eastwardly migrating locust swarms would fly into the Indochina Peninsula and Southwest China.

Earth observation data for assessing biodiversity conservation priorities in South Asia

2018 ◽  
Vol 28 (8-9) ◽  
pp. 2197-2219 ◽  
Author(s):  
C. Sudhakar Reddy ◽  
V. S. Faseela ◽  
Anjaly Unnikrishnan ◽  
C. S. Jha
Keyword(s):  
South Asia ◽  
Biodiversity Conservation ◽  
Earth Observation ◽  
Conservation Priorities ◽  
Observation Data ◽  
Earth Observation Data

Regional Drought Monitoring for Managing Water Security in South Asia

2021 ◽  
pp. 465-481
Author(s):  
Giriraj Amarnath ◽  
Surajit Ghosh ◽  
Niranga Alahacoon ◽  
Toru Nakada ◽  
K. V. Rao ◽  
...  
Keyword(s):  
South Asia ◽  
Water Security ◽  
Drought Monitoring ◽  
Regional Drought

Evaluation of Model-Based Soil Moisture Drought Monitoring over Three Key Regions in China

2018 ◽  
Vol 57 (9) ◽  
pp. 1989-2004 ◽  
Author(s):  
Yiping Li ◽  
Yaohui Li ◽  
Xing Yuan ◽  
Liang Zhang ◽  
Sha Sha
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Northern China ◽  
Drought Monitoring ◽  
Drought Indices ◽  
China Meteorological Administration ◽  
Objective Monitoring ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Land Exchange

AbstractLand surface models (LSMs) have been widely used to provide objective monitoring of soil moisture during drought, but large uncertainties exist because of the different parameterizations in LSMs. This study aims to evaluate the ability to monitor soil moisture drought over three key regions in China by using the Noah LSM from the Global Land Data Assimilation System, version 2 (GLDASv2), and the Community Atmosphere Biosphere Land Exchange (CABLE) model that is currently used at the China Meteorological Administration. The modeled soil moisture drought indices were verified against the standardized precipitation evapotranspiration index (SPEI), which served as a reference drought indicator over northern China (NC), northwestern China (NWC), and southwestern China (SWC) from 1961 to 2010. The results show that the precipitation forcing data that drive both LSMs have high accuracy when compared with local observational data. GLDASv2/Noah outperforms CABLE in capturing soil moisture anomalies and variability, especially in SWC, but both show good correlations with the 3-month SPEI (SPEI3) in NC, NWC, and SWC. The autumn drought of 2002 and spring drought of 2010 were selected for the comparison of the modeled drought categories with the SPEI3 drought category, where GLDASv2/Noah performed slightly better than CABLE. This work demonstrates that the choice of LSM is crucial for monitoring soil moisture drought and that the GLDASv2/Noah LSM can be a good candidate for the development of a new operational drought-monitoring system in China.

Overview of Application of Remote Sensing on Drought Monitoring in Inner Mongolia

2014 ◽  
Vol 955-959 ◽  
pp. 3735-3739
Author(s):  
Yin Tai Na
Keyword(s):  
Remote Sensing ◽  
Inner Mongolia ◽  
Research Work ◽  
Drought Monitoring ◽  
Drought Indices ◽  
Technology Application ◽  
Remote Sensing Technology ◽  
Stage Of Development ◽  
Sensing Technology ◽  
Regional Drought

Inner Mongolia is one of the most typical and severe dry provinces, drought is it’s main meteorological disasters. Remote sensing monitoring becomes irreplaceable effective means in the regional drought monitoring and drought mechanism research with the advantages of macro, rapid, objective, dynamic and real time. Inner Mongolia region is vast and flat, so suitable for carrying out the regional drought monitoring research with remote sensing technology. Application of meteorological drought indices and historical documents for drought monitoring and study is relatively more. However application of remote sensing technology for drought monitoring in Inner Mongolia is at the beginning stage of development. Further study and exploration is urgently needed. In this paper research work of application of remote sensing approach in drought monitoring in Inner Mongolia is summarized and existing problems are pointed out. Finally give some suggestions for the application of remote sensing technology in the drought monitoring in Inner Mongolia.

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