Könyv Landscape Pattern Analysis for Assessing Ecosystem Condition Glen D. Johnson

Landscape Pattern Analysis for Assessing Ecosystem Condition

Nyelv: Angol
Kötés: Puha kötésű
Elérhetőség: Beszállítói készleten
Küldés 5-8 napon belül
57 690 Ft
This book presents a new method for assessing spatial pattern in raster land cover maps based on sat...

Információk a könyvről

Nyelv
Angol
Kötés
Könyv - Puha kötésű
Kiadva
2010
oldal
130
EAN
9781441942494
ISBN
1441942491
Enbook ID
01422754
Súly
237
Méretek
155 x 235 x 9

Teljes leírás

This book presents a new method for assessing spatial pattern in raster land cover maps based on satellite imagery in a way that incorporates multiple pixel resolutions. This is combined with more conventional single-resolution measurements of spatial pattern and simple non-spatial land cover proportions to assess predictability of both surface water quality and ecological integrity within watersheds of the state of Pennsylvania (USA).As we begin the 21st century, one of our greatest challenges is the preservation and remediation of ecosystem integrity. This requires monitoring and assessment over large geographic areas, repeatedly over time, and therefore cannot be practically fulfilled by field measurements alone. Remotely sensed imagery therefore plays a crucial role by its ability to monitor large spatially continuous areas. This technology increasingly provides extensive spatial-temporal data; however, the challenge is to extract meaningful environmental information from such extensive data.§Landscape Pattern Analysis for Assessing Ecosystem Condition presents a new method for assessing spatial pattern in raster land cover maps based on satellite imagery in a way that incorporates multiple pixel resolutions. This is combined with more conventional single-resolution measurements of spatial pattern and simple non-spatial land cover proportions to assess predictability of both surface water quality and ecological integrity within watersheds of the state of Pennsylvania (USA). The efficiency of remote sensing for rapidly assessing large areas is realized through the ability to explain much of the variability of field observations that took several years and many people to obtain.

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