Remote Sensing Sensors and Recent Techniques in Desertification and Land Degradation Mapping––A Review

Dharumarajan, S.; S., Veeramani; Suputhra, Amar; Parmar, Manish; Kalaiselvi, B.; Lalitha, M.; Vasundhara, R.; Hegde, Rajendra; Rajawat, A. S.

doi:10.1007/978-3-030-85682-3_32

Cited by 3 publications

(1 citation statement)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Environments are being polluted and losing their normal functioning. Due to global warming, sea levels are rising, deforestation is increasing, and soil fertility and water quality are decreasing (Dharumarajan et al 2022, Whitehead et al 2009). Water quality has decreased due to the increasing salinity caused by rising sea water levels (Rakib et al 2020).…”

Section: Introductionmentioning

confidence: 99%

Growth performance of broilers and prevalence of different diseases vary with environmental variation

Ahmed¹,

Siddiqui

Das

et al. 2022

Preprint

View full text Add to dashboard Cite

Broiler meat is known for its nutritional value, availability, and low price. Although, broilers are more sensitive to environmental conditions and need a specific environment for optimum production. However, global warming and natural disasters are important obstacles to broiler production. Therefore, we conducted this study to reveal the broiler production status throughout the year in a subtropical region. In our study, we selected the years 2019, 2020, and 2022. The study area included Noakhali and Lakshimpur, located in the southern part of Bangladesh. We selected 10 smallholder broiler farms following specific conditions and collected information at the end of each month for analysis. The body weight of broilers was significantly lower in July than in other months. However, the mortality was significantly lower in July than in other months of the year. Nonetheless, the prevalence of viral disease was higher in the winter season (January, February, and December). Although, the metabolic disease prevalence was higher in October, a high prevalence of bacterial disease was found in April. These results suggest that high temperatures decrease broiler production while broilers are more susceptible to viral disease in the winter season.

show abstract

Section: Introductionmentioning

confidence: 99%

Growth performance of broilers and prevalence of different diseases vary with environmental variation

Ahmed¹,

Siddiqui

Das

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

Land Degradation and Desertification

Badapalli,

Kottala,

Pujari

2023

Advances in Geographical and Environmental Sciences

View full text Add to dashboard Cite

is a full professor of rural land-use planning in protected area bionetworks. He obtained his undergraduate degree from the University of Dar es Salaam in 1991. He did his MSc at ITC in the Netherlands in 1995 and his PhD at Greenwich University in the United Kingdom in 2006. For more than three decades, Professor Kaswamila has worked as an Agricultural Research Officer at Mlingano Agricultural Research Institute and a Don at Mweka Wildlife College and later at the University of Dodoma. Professor Kaswamila has published widely in areas of land-use planning, land management, agriculture, poverty and livelihood, biodiversity conservation, and community conservation. He is currently a Professot at the College of Humanities and Social Sciences Research

show abstract

Evaluation of Soil Rocky Desertification in Karst Region Based on Deep Belief Network

Meng

2023

Ecological Chemistry and Engineering S

View full text Add to dashboard Cite

Dynamic features from remote sensing photos may be successfully extracted using deep learning and symmetric network structure, which can then be used to direct them to carry out accurate classification. The DBN model can more effectively extract features from photos since it uses unsupervised learning. It can be reduced to the many symmetric Restricted Boltmann Machines (RBM) training problem. In this paper, a soil rocky desertification (RD) assessment model based on a deep belief network (DBN) is created in light of the complicated influencing aspects of Karst RD risk assessment encompassing several geographical elements. The model builds upon the conventional RBM framework and incorporates the influence layer of related elements as an auxiliary requirement for retrieving Geographic Information System (GIS) score data. Then, in order to forecast the level of soil rocky desertification, it learns the features of many elements. The experimental results show that the proposed model proposed in this paper has better prediction performance and faster convergence speed, and its classification results for different degrees of RD are more consistent with the actual risk assessment results.

show abstract

Remote Sensing Sensors and Recent Techniques in Desertification and Land Degradation Mapping––A Review

Cited by 3 publications

References 46 publications

Growth performance of broilers and prevalence of different diseases vary with environmental variation

Growth performance of broilers and prevalence of different diseases vary with environmental variation

Land Degradation and Desertification

Evaluation of Soil Rocky Desertification in Karst Region Based on Deep Belief Network

Contact Info

Product

Resources

About