Jun 17, 2022

Public workspaceGeocarto International manuscript data V.2

DOI
dx.doi.org/10.17504/protocols.io.5jyl89j77v2w/v2
  • 1Tembotov Institute of Ecology of Mountain Territories of Russian Academy of Science, Nalchik, Russia
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DOI: dx.doi.org/10.17504/protocols.io.5jyl89j77v2w/v2
Document Citation: Pshegusov R.H., Chadaeva V.A. 2022. Geocarto International manuscript data. protocols.io https://dx.doi.org/10.17504/protocols.io.5jyl89j77v2w/v2Version created by Pshegusov R.H.
License: This is an open access document distributed under the terms of the Creative Commons Attribution License,  which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Created: June 17, 2022
Last Modified: June 17, 2022
Document Integer ID: 64792
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Abstract
This paper presents an approach to studying rangeland degradation by integrating remote sensing data, geographic information systems, and ecological niche theory. The document provides information about the source data used in writing the manuscript.
Identification of degradation factors in mountain semiarid rangelands usingremote sensing data integrated into spatial distribution modelling and ecological niche theory

R code:
"Digression_stady_work.R"
https://www.protocols.io/file/gq32bnyuf.r?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWSNCI5SNCPTWTQQ%2F20220223%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220223T193146Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=2786b68684724485e72facd35467f206c44a5eab24f8eea3586ccf1004a52163

"interactive map digression stady.R"
https://www.protocols.io/file/gq5tbnyuf.r?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWSNCI5SNCPTWTQQ%2F20220223%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220223T193146Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=a4e0568f14554f487147a64ff8a74b6a7092c0e91180d369d7eeee7557b175db

working file:
sample
https://www.protocols.io/file/gq5xbnyuf.rar?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWSNCI5SNCPTWTQQ%2F20220223%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220223T193652Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=422c5f83ff3d3424d1d5ef302d923986d9c9db66f2d2c6631f31a95efa268cdc
digression stage shapefile, calculated by predictive maps
https://www.protocols.io/file/gq5wbnyuf.rar?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWSNCI5SNCPTWTQQ%2F20220223%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220223T193652Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=92a3b0c61e62bf8165ba2a84339240e62a332ef05298f88f50fca9ca6497eeb7

NOTE: predictor layers too large to be deposited, can be sent upon request.